Mythical EMAs + Dynamic VWAP BandThis indicator titled "Mythical EMAs + Dynamic VWAP Band." It overlays several volatility-adjusted Exponential Moving Averages (EMAs) on the chart, along with a Volume Weighted Average Price (VWAP) line and a dynamic band around it.
Additionally, it uses background coloring (clouds) to visualize bullish or bearish trends, with intensity modulated by the price's position relative to the VWAP.
The EMAs are themed with mythical names (e.g., Hermes for the 9-period EMA), but this is just stylistic flavoring and doesn't affect functionality.
I'll break it down section by section, explaining what each part does, how it works, and its purpose in the context of technical analysis. This indicator is designed for traders to identify trends, momentum, and price fairness relative to volume-weighted averages, with volatility adjustments to make the EMAs more responsive in volatile markets.
### 1. **Volatility Calculation (ATR)**
```pine
atrLength = 14
volatility = ta.atr(atrLength)
```
- **What it does**: Calculates the Average True Range (ATR) over 14 periods (a common default). ATR measures market volatility by averaging the true range (the greatest of: high-low, |high-previous close|, |low-previous close|).
- **Purpose**: This volatility value is used later to dynamically adjust the EMAs, making them more sensitive in high-volatility conditions (e.g., during market swings) and smoother in low-volatility periods. It helps the indicator adapt to changing market environments rather than using static EMAs.
### 2. **Custom Mythical EMA Function**
```pine
mythical_ema(src, length, base_alpha, vol_factor) =>
alpha = (2 / (length + 1)) * base_alpha * (1 + vol_factor * (volatility / src))
ema = 0.0
ema := na(ema ) ? src : alpha * src + (1 - alpha) * ema
ema
```
- **What it does**: Defines a custom function to compute a modified EMA.
- It starts with the standard EMA smoothing factor formula: `2 / (length + 1)`.
- Multiplies it by a `base_alpha` (a user-defined multiplier to tweak responsiveness).
- Adjusts further for volatility: Adds a term `(1 + vol_factor * (volatility / src))`, where `vol_factor` scales the impact, and `volatility / src` normalizes ATR relative to the source price (making it scale-invariant).
- The EMA is then calculated recursively: If the previous EMA is NA (e.g., at the start), it uses the current source value; otherwise, it weights the current source by `alpha` and the prior EMA by `(1 - alpha)`.
- **Purpose**: This creates "adaptive" EMAs that react faster in volatile markets (higher alpha when volatility is high relative to price) without overreacting in calm periods. It's an enhancement over standard EMAs, which use fixed alphas and can lag in choppy conditions. The mythical theme is just naming—functionally, it's a volatility-weighted EMA.
### 3. **Calculating the EMAs**
```pine
ema9 = mythical_ema(close, 9, 1.2, 0.5) // Hermes - quick & nimble
ema20 = mythical_ema(close, 20, 1.0, 0.3) // Apollo - short-term foresight
ema50 = mythical_ema(close, 50, 0.9, 0.2) // Athena - wise strategist
ema100 = mythical_ema(close, 100, 0.8, 0.1) // Zeus - powerful oversight
ema200 = mythical_ema(close, 200, 0.7, 0.05) // Kronos - long-term patience
```
- **What it does**: Applies the custom EMA function to the close price with varying lengths (9, 20, 50, 100, 200 periods), base alphas (decreasing from 1.2 to 0.7 for longer periods to make shorter ones more responsive), and volatility factors (decreasing from 0.5 to 0.05 to reduce volatility influence on longer-term EMAs).
- **Purpose**: These form a multi-timeframe EMA ribbon:
- Shorter EMAs (e.g., 9 and 20) capture short-term momentum.
- Longer ones (e.g., 200) show long-term trends.
- Crossovers (e.g., short EMA crossing above long EMA) can signal buy/sell opportunities. The volatility adjustment makes them "mythical" by adding dynamism, potentially improving signal quality in real markets.
### 4. **VWAP Calculation**
```pine
vwap_val = ta.vwap(close) // VWAP based on close price
```
- **What it does**: Computes the Volume Weighted Average Price (VWAP) using the built-in `ta.vwap` function, anchored to the close price. VWAP is the average price weighted by volume over the session (resets daily by default in Pine Script).
- **Purpose**: VWAP acts as a benchmark for "fair value." Prices above VWAP suggest bullishness (buyers in control), below indicate bearishness (sellers dominant). It's commonly used by institutional traders to assess entry/exit points.
### 5. **Plotting EMAs and VWAP**
```pine
plot(ema9, color=color.fuchsia, title='EMA 9 (Hermes)')
plot(ema20, color=color.red, title='EMA 20 (Apollo)')
plot(ema50, color=color.orange, title='EMA 50 (Athena)')
plot(ema100, color=color.aqua, title='EMA 100 (Zeus)')
plot(ema200, color=color.blue, title='EMA 200 (Kronos)')
plot(vwap_val, color=color.yellow, linewidth=2, title='VWAP')
```
- **What it does**: Overlays the EMAs and VWAP on the chart with distinct colors and titles for easy identification in TradingView's legend.
- **Purpose**: Visualizes the EMA ribbon and VWAP line. Traders can watch for EMA alignments (e.g., all sloping up for uptrend) or price interactions with VWAP.
### 6. **Dynamic VWAP Band**
```pine
band_pct = 0.005
vwap_upper = vwap_val * (1 + band_pct)
vwap_lower = vwap_val * (1 - band_pct)
p1 = plot(vwap_upper, color=color.new(color.yellow, 0), title="VWAP Upper Band")
p2 = plot(vwap_lower, color=color.new(color.yellow, 0), title="VWAP Lower Band")
fill_color = close >= vwap_val ? color.new(color.green, 80) : color.new(color.red, 80)
fill(p1, p2, color=fill_color, title="Dynamic VWAP Band")
```
- **What it does**: Creates a band ±0.5% around the VWAP.
- Plots the upper/lower bands with full transparency (color opacity 0, so lines are invisible).
- Fills the area between them dynamically: Semi-transparent green (opacity 80) if close ≥ VWAP (bullish bias), red if below (bearish bias).
- **Purpose**: Highlights deviations from VWAP visually. The color change provides an at-a-glance sentiment indicator—green for "above fair value" (potential strength), red for "below" (potential weakness). The narrow band (0.5%) focuses on short-term fairness, and the fill makes it easier to spot than just the line.
### 7. **Trend Clouds with VWAP Interaction**
```pine
bullish = ema9 > ema20 and ema20 > ema50
bearish = ema9 < ema20 and ema20 < ema50
bullish_above_vwap = bullish and close > vwap_val
bullish_below_vwap = bullish and close <= vwap_val
bearish_below_vwap = bearish and close < vwap_val
bearish_above_vwap = bearish and close >= vwap_val
bgcolor(bullish_above_vwap ? color.new(color.green, 50) : na, title="Bullish Above VWAP")
bgcolor(bullish_below_vwap ? color.new(color.green, 80) : na, title="Bullish Below VWAP")
bgcolor(bearish_below_vwap ? color.new(color.red, 50) : na, title="Bearish Below VWAP")
bgcolor(bearish_above_vwap ? color.new(color.red, 80) : na, title="Bearish Above VWAP")
```
- **What it does**: Defines trend conditions based on EMA alignments:
- Bullish: Shorter EMAs stacked above longer ones (9 > 20 > 50, indicating upward momentum).
- Bearish: The opposite (downward momentum).
- Sub-conditions combine with VWAP: E.g., bullish_above_vwap is true only if bullish and price > VWAP.
- Applies background colors (bgcolor) to the entire chart pane:
- Strong bullish (above VWAP): Green with opacity 50 (less transparent, more intense).
- Weak bullish (below VWAP): Green with opacity 80 (more transparent, less intense).
- Strong bearish (below VWAP): Red with opacity 50.
- Weak bearish (above VWAP): Red with opacity 80.
- If no condition matches, no color (na).
- **Purpose**: Creates "clouds" for trend visualization, enhanced by VWAP context. This helps traders confirm trends—e.g., a strong bullish cloud (darker green) suggests a high-conviction uptrend when price is above VWAP. The varying opacity differentiates signal strength: Darker for aligned conditions (trend + VWAP agreement), lighter for misaligned (potential weakening or reversal).
### Overall Indicator Usage and Limitations
- **How to use it**: Add this to a TradingView chart (e.g., stocks, crypto, forex). Look for EMA crossovers, price bouncing off EMAs/VWAP, or cloud color changes as signals. Bullish clouds with price above VWAP might signal buys; bearish below for sells.
- **Strengths**: Combines momentum (EMAs), volume (VWAP), and volatility adaptation for a multi-layered view. Dynamic colors make it intuitive.
- **Limitations**:
- EMAs lag in ranging markets; volatility adjustment helps but doesn't eliminate whipsaws.
- VWAP resets daily (standard behavior), so it's best for intraday/session trading.
- No alerts or inputs for customization (e.g., changeable lengths)—it's hardcoded.
- Performance depends on the asset/timeframe; backtest before using.
- **License**: Mozilla Public License 2.0, so it's open-source and modifiable.
Cari dalam skrip untuk "bear"
ICT PDA - Gold & BTC (QuickScalp Bias/FVG/OB/OTE + Alerts)What this script does
This indicator implements a complete ICT Price Delivery Algorithm (PDA) workflow tailored for XAUUSD and BTCUSD. It combines HTF bias, OTE zones, Fair Value Gaps, Order Blocks, micro-BOS confirmation, and liquidity references into a single, cohesive tool with early and final alerts. The script is not a mashup for cosmetic plotting; each component feeds the next decision step.
Why this is original/useful
Symbol-aware impulse filter: A dynamic displacement threshold kTune adapts to Gold/BTC volatility (body/ATR vs. per-symbol factor), reducing noise on fast markets without hiding signals.
Scalping preset: “Quick Clean” mode limits drawings to the most recent bars and keeps only the latest FVG/OB zones for a clear chart.
Three display modes: Full, Clean, and Signals-Only to match analysis vs. execution.
Actionable alerts: Early heads-up when price enters OTE in the HTF bias direction, and Final alerts once mitigation + micro-break confirm the setup.
How it works (high-level logic)
HTF Bias: Uses request.security() on a user-selected timeframe (e.g., 240m) and EMA filter. Bias = close above/below HTF EMA.
Dealing Range & OTE: Recent swing high/low (pivot length configurable) define the range; OTE (62–79%) boxes are drawn contextually for up/down ranges.
Displacement: A candle’s body/ATR must exceed kTune and break short-term structure (displacement up/down).
FVG: 3-bar imbalance (bull: low > high ; bear: high < low ). Latest gaps are tracked and extended.
Order Blocks: Last opposite candle prior to a qualifying displacement that breaks recent highs/lows; zones are drawn and extended.
Entry & Alerts:
Long: Bullish bias + price inside buy-OTE + mitigation of a bullish FVG or OB + micro BOS up → “PDA Long (Final)”.
Short: Bearish bias + price inside sell-OTE + mitigation of a bearish FVG or OB + micro BOS down → “PDA Short (Final)”.
Early Alerts: Trigger as soon as price enters OTE in the direction of the active bias.
Inputs & controls (key ones)
Bias (HTF): timeframe minutes, EMA length.
Structure: ATR length, Impulse Threshold (Body/ATR), swing pivot length, OB look-back.
OTE/FVG/OB/LP toggles: show/hide components.
Auto-Tune: per-symbol factors for Gold/BTC + manual tweak.
Display/Performance: View Mode, keep-N latest FVG/OB, limit drawings to last N bars.
Recommended usage (scalping)
Timeframes: Execute on M1–M5 with HTF bias from 120–240m.
Defaults (starting point): ATR=14, Impulse Threshold≈1.6; Gold factor≈1.05, BTC factor≈0.90; Keep FVG/OB=2; last 200–300 bars; View Mode=Clean.
Workflow: Wait for OTE in bias direction → see mitigation (FVG/OB) → confirm with micro BOS → manage risk to nearest liquidity (prev-day H/L or recent swing).
Alerts available
“PDA Early Long/Short”
“PDA Long (Final)” / “PDA Short (Final)”
Attach alerts on “Any alert() function call” or the listed conditions.
Chart & screenshots
Please include symbol and timeframe on screenshots. The on-chart HUD shows the script name and state to help reviewers understand context.
Limitations / notes
This is a discretionary framework. Signals can cluster during news or extreme volatility; use your own risk management. No guarantee of profitability.
Changelog (brief)
v1.2 QuickScalp: added Quick Clean preset, safer array handling, symbol-aware impulse tuning, display modes.
------------------------------
ملخص عربي:
المؤشر يطبق تسلسل PDA عملي للذهب والبتكوين: تحيز من فريم أعلى، مناطق OTE، فجوات FVG، بلوكات أوامر OB، وتأكيد micro-BOS، مع تنبيهات مبكرة ونهائية. تمت إضافة وضع “Quick Clean” لتقليل العناصر على الشارت وحساسية إزاحة تتكيّف مع الأصل. للاستخدام كسكالب: نفّذ على M1–M5 مع تحيز 120–240 دقيقة، وابدأ من الإعدادات المقترحة بالأعلى. هذا إطار سلوكي وليس توصية مالية.
Reversal Probability Meter PRO [optimized for Xau/Usd m5]🎯 Reversal Probability Meter PRO
A powerful multi-factor reversal probability detector that calculates the likelihood of bullish or bearish reversals using RSI, EMA bias, ATR spikes, candle patterns, volume spikes, and higher timeframe (HTF) trend alignment.
🧩 MAIN FEATURES
1. Reversal Probability (Bullish & Bearish)
Displays two key metrics:
Bull % — probability of bullish reversal
Bear % — probability of bearish reversal
These are computed using RSI, EMAs, ATR, demand/supply zones, candle confirmations, and volume spikes.
📊 Interpretation:
Bull % > 70% → Buying pressure building up
Bull % > 85% → Strong bullish reversal confirmed
Bear % > 70% → Selling pressure building up
Bear % > 85% → Strong bearish reversal confirmed
2. Alert Probability Threshold
Adjustable via alertThreshold (default = 85%).
Alerts trigger only when probability ≥ threshold, and confirmed by zone + volume spike + candle pattern.
🔔 Alerts Available:
✅ Bullish Smart Reversal
🔻 Bearish Smart Reversal
To activate: Right-click chart → “Add alert” → choose the alert condition from the indicator.
3. Demand / Supply Zone Detection
The script determines the price position within the last zoneLook (default 30) bars:
🟢 DEMAND → Lower 35% of range (potential bounce zone)
🔴 SUPPLY → Upper 35% of range (potential rejection zone)
⚪ MID → Neutral area
📘 Purpose: Validates reversals based on context:
Bullish only valid in Demand zones
Bearish only valid in Supply zones
4. Higher Timeframe (HTF) Trend Alignment
Reads EMA bias from a higher timeframe (default = 15m) for trend confirmation.
Reversals against HTF trend are automatically weighted down prevents false countertrend signals.
📈 Example:
M5 chart under M15 downtrend → Bullish probability is reduced.
5. Candle Confirmation Patterns
Two key price action confirmations:
Bullish: Engulfing or Pin Bar
Bearish: Engulfing or Pin Bar
A valid reversal requires both a candle confirmation and a volume spike.
6. Volume & ATR Spike Filters
Volume Spike: volume > SMA(20) × 1.3
ATR Spike: ATR > SMA(ATR, 50) × volMult
🎯 Ensures that only strong market moves with real energy are considered valid reversals.
7. Reversal Momentum Histogram
A color-gradient oscillator showing the momentum difference:
Green = bullish dominance
Red = bearish dominance
Flat near 0 = neutral
Controlled by showOscillator toggle.
8. Smart Info Panel
A compact dashboard displayed on the top-right with 4 rows:
Row Info Description
1 Bull % Bullish reversal probability
2 Bear % Bearish reversal probability
3 Zone Market context (DEMAND / SUPPLY / MID)
4 Signal Strength Current signal intensity (probability %)
Dynamic Colors:
90% → Bright (strong signal)
75–90% → Yellow/Orange (medium)
<75% → Gray (weak)
9. Sensitivity Mode
Fine-tunes indicator reactivity:
🟥 Aggressive: Detects reversals early (more signals, less accurate)
🟨 Normal: Balanced, default mode
🟩 Conservative: Filters only strongest reversals (fewer but more reliable)
10. Custom Color Options
Customize bullish and bearish colors via bullBaseColor and bearBaseColor inputs for your preferred chart theme.
⚙️ HOW TO USE
Add to Chart
→ Paste the script into Pine Editor → “Add to chart”.
Select Timeframe
→ Best for M5–M30 (scalping/intraday).
→ H1–H4 for swing trading.
Monitor the Info Panel:
Bull % ≥ 85% + Zone = Demand → Strong bullish reversal signal
Bear % ≥ 85% + Zone = Supply → Strong bearish reversal signal
Watch the Histogram:
Rising green bars = bullish momentum gaining
Deep red bars = bearish momentum gaining
Enable Alerts:
Right-click chart → “Add alert”
Choose Bullish Smart Reversal or Bearish Smart Reversal
🧠 TRADING TIPS
Use Conservative mode for noisy lower timeframes (M5–M15).
Use Aggressive mode for higher timeframes (H1–H4).
Combine with manual support/resistance or zone boxes for precision entries. Personally i use Order Block.
Best reversal setups occur when all align:
Bull % > 85%
Zone = DEMAND
Volume spike present
Candle = Bullish engulfing
HTF trend supportive
Dynamic Equity Allocation Model"Cash is Trash"? Not Always. Here's Why Science Beats Guesswork.
Every retail trader knows the frustration: you draw support and resistance lines, you spot patterns, you follow market gurus on social media—and still, when the next bear market hits, your portfolio bleeds red. Meanwhile, institutional investors seem to navigate market turbulence with ease, preserving capital when markets crash and participating when they rally. What's their secret?
The answer isn't insider information or access to exotic derivatives. It's systematic, scientifically validated decision-making. While most retail traders rely on subjective chart analysis and emotional reactions, professional portfolio managers use quantitative models that remove emotion from the equation and process multiple streams of market information simultaneously.
This document presents exactly such a system—not a proprietary black box available only to hedge funds, but a fully transparent, academically grounded framework that any serious investor can understand and apply. The Dynamic Equity Allocation Model (DEAM) synthesizes decades of financial research from Nobel laureates and leading academics into a practical tool for tactical asset allocation.
Stop drawing colorful lines on your chart and start thinking like a quant. This isn't about predicting where the market goes next week—it's about systematically adjusting your risk exposure based on what the data actually tells you. When valuations scream danger, when volatility spikes, when credit markets freeze, when multiple warning signals align—that's when cash isn't trash. That's when cash saves your portfolio.
The irony of "cash is trash" rhetoric is that it ignores timing. Yes, being 100% cash for decades would be disastrous. But being 100% equities through every crisis is equally foolish. The sophisticated approach is dynamic: aggressive when conditions favor risk-taking, defensive when they don't. This model shows you how to make that decision systematically, not emotionally.
Whether you're managing your own retirement portfolio or seeking to understand how institutional allocation strategies work, this comprehensive analysis provides the theoretical foundation, mathematical implementation, and practical guidance to elevate your investment approach from amateur to professional.
The choice is yours: keep hoping your chart patterns work out, or start using the same quantitative methods that professionals rely on. The tools are here. The research is cited. The methodology is explained. All you need to do is read, understand, and apply.
The Dynamic Equity Allocation Model (DEAM) is a quantitative framework for systematic allocation between equities and cash, grounded in modern portfolio theory and empirical market research. The model integrates five scientifically validated dimensions of market analysis—market regime, risk metrics, valuation, sentiment, and macroeconomic conditions—to generate dynamic allocation recommendations ranging from 0% to 100% equity exposure. This work documents the theoretical foundations, mathematical implementation, and practical application of this multi-factor approach.
1. Introduction and Theoretical Background
1.1 The Limitations of Static Portfolio Allocation
Traditional portfolio theory, as formulated by Markowitz (1952) in his seminal work "Portfolio Selection," assumes an optimal static allocation where investors distribute their wealth across asset classes according to their risk aversion. This approach rests on the assumption that returns and risks remain constant over time. However, empirical research demonstrates that this assumption does not hold in reality. Fama and French (1989) showed that expected returns vary over time and correlate with macroeconomic variables such as the spread between long-term and short-term interest rates. Campbell and Shiller (1988) demonstrated that the price-earnings ratio possesses predictive power for future stock returns, providing a foundation for dynamic allocation strategies.
The academic literature on tactical asset allocation has evolved considerably over recent decades. Ilmanen (2011) argues in "Expected Returns" that investors can improve their risk-adjusted returns by considering valuation levels, business cycles, and market sentiment. The Dynamic Equity Allocation Model presented here builds on this research tradition and operationalizes these insights into a practically applicable allocation framework.
1.2 Multi-Factor Approaches in Asset Allocation
Modern financial research has shown that different factors capture distinct aspects of market dynamics and together provide a more robust picture of market conditions than individual indicators. Ross (1976) developed the Arbitrage Pricing Theory, a model that employs multiple factors to explain security returns. Following this multi-factor philosophy, DEAM integrates five complementary analytical dimensions, each tapping different information sources and collectively enabling comprehensive market understanding.
2. Data Foundation and Data Quality
2.1 Data Sources Used
The model draws its data exclusively from publicly available market data via the TradingView platform. This transparency and accessibility is a significant advantage over proprietary models that rely on non-public data. The data foundation encompasses several categories of market information, each capturing specific aspects of market dynamics.
First, price data for the S&P 500 Index is obtained through the SPDR S&P 500 ETF (ticker: SPY). The use of a highly liquid ETF instead of the index itself has practical reasons, as ETF data is available in real-time and reflects actual tradability. In addition to closing prices, high, low, and volume data are captured, which are required for calculating advanced volatility measures.
Fundamental corporate metrics are retrieved via TradingView's Financial Data API. These include earnings per share, price-to-earnings ratio, return on equity, debt-to-equity ratio, dividend yield, and share buyback yield. Cochrane (2011) emphasizes in "Presidential Address: Discount Rates" the central importance of valuation metrics for forecasting future returns, making these fundamental data a cornerstone of the model.
Volatility indicators are represented by the CBOE Volatility Index (VIX) and related metrics. The VIX, often referred to as the market's "fear gauge," measures the implied volatility of S&P 500 index options and serves as a proxy for market participants' risk perception. Whaley (2000) describes in "The Investor Fear Gauge" the construction and interpretation of the VIX and its use as a sentiment indicator.
Macroeconomic data includes yield curve information through US Treasury bonds of various maturities and credit risk premiums through the spread between high-yield bonds and risk-free government bonds. These variables capture the macroeconomic conditions and financing conditions relevant for equity valuation. Estrella and Hardouvelis (1991) showed that the shape of the yield curve has predictive power for future economic activity, justifying the inclusion of these data.
2.2 Handling Missing Data
A practical problem when working with financial data is dealing with missing or unavailable values. The model implements a fallback system where a plausible historical average value is stored for each fundamental metric. When current data is unavailable for a specific point in time, this fallback value is used. This approach ensures that the model remains functional even during temporary data outages and avoids systematic biases from missing data. The use of average values as fallback is conservative, as it generates neither overly optimistic nor pessimistic signals.
3. Component 1: Market Regime Detection
3.1 The Concept of Market Regimes
The idea that financial markets exist in different "regimes" or states that differ in their statistical properties has a long tradition in financial science. Hamilton (1989) developed regime-switching models that allow distinguishing between different market states with different return and volatility characteristics. The practical application of this theory consists of identifying the current market state and adjusting portfolio allocation accordingly.
DEAM classifies market regimes using a scoring system that considers three main dimensions: trend strength, volatility level, and drawdown depth. This multidimensional view is more robust than focusing on individual indicators, as it captures various facets of market dynamics. Classification occurs into six distinct regimes: Strong Bull, Bull Market, Neutral, Correction, Bear Market, and Crisis.
3.2 Trend Analysis Through Moving Averages
Moving averages are among the oldest and most widely used technical indicators and have also received attention in academic literature. Brock, Lakonishok, and LeBaron (1992) examined in "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns" the profitability of trading rules based on moving averages and found evidence for their predictive power, although later studies questioned the robustness of these results when considering transaction costs.
The model calculates three moving averages with different time windows: a 20-day average (approximately one trading month), a 50-day average (approximately one quarter), and a 200-day average (approximately one trading year). The relationship of the current price to these averages and the relationship of the averages to each other provide information about trend strength and direction. When the price trades above all three averages and the short-term average is above the long-term, this indicates an established uptrend. The model assigns points based on these constellations, with longer-term trends weighted more heavily as they are considered more persistent.
3.3 Volatility Regimes
Volatility, understood as the standard deviation of returns, is a central concept of financial theory and serves as the primary risk measure. However, research has shown that volatility is not constant but changes over time and occurs in clusters—a phenomenon first documented by Mandelbrot (1963) and later formalized through ARCH and GARCH models (Engle, 1982; Bollerslev, 1986).
DEAM calculates volatility not only through the classic method of return standard deviation but also uses more advanced estimators such as the Parkinson estimator and the Garman-Klass estimator. These methods utilize intraday information (high and low prices) and are more efficient than simple close-to-close volatility estimators. The Parkinson estimator (Parkinson, 1980) uses the range between high and low of a trading day and is based on the recognition that this information reveals more about true volatility than just the closing price difference. The Garman-Klass estimator (Garman and Klass, 1980) extends this approach by additionally considering opening and closing prices.
The calculated volatility is annualized by multiplying it by the square root of 252 (the average number of trading days per year), enabling standardized comparability. The model compares current volatility with the VIX, the implied volatility from option prices. A low VIX (below 15) signals market comfort and increases the regime score, while a high VIX (above 35) indicates market stress and reduces the score. This interpretation follows the empirical observation that elevated volatility is typically associated with falling markets (Schwert, 1989).
3.4 Drawdown Analysis
A drawdown refers to the percentage decline from the highest point (peak) to the lowest point (trough) during a specific period. This metric is psychologically significant for investors as it represents the maximum loss experienced. Calmar (1991) developed the Calmar Ratio, which relates return to maximum drawdown, underscoring the practical relevance of this metric.
The model calculates current drawdown as the percentage distance from the highest price of the last 252 trading days (one year). A drawdown below 3% is considered negligible and maximally increases the regime score. As drawdown increases, the score decreases progressively, with drawdowns above 20% classified as severe and indicating a crisis or bear market regime. These thresholds are empirically motivated by historical market cycles, in which corrections typically encompassed 5-10% drawdowns, bear markets 20-30%, and crises over 30%.
3.5 Regime Classification
Final regime classification occurs through aggregation of scores from trend (40% weight), volatility (30%), and drawdown (30%). The higher weighting of trend reflects the empirical observation that trend-following strategies have historically delivered robust results (Moskowitz, Ooi, and Pedersen, 2012). A total score above 80 signals a strong bull market with established uptrend, low volatility, and minimal losses. At a score below 10, a crisis situation exists requiring defensive positioning. The six regime categories enable a differentiated allocation strategy that not only distinguishes binarily between bullish and bearish but allows gradual gradations.
4. Component 2: Risk-Based Allocation
4.1 Volatility Targeting as Risk Management Approach
The concept of volatility targeting is based on the idea that investors should maximize not returns but risk-adjusted returns. Sharpe (1966, 1994) defined with the Sharpe Ratio the fundamental concept of return per unit of risk, measured as volatility. Volatility targeting goes a step further and adjusts portfolio allocation to achieve constant target volatility. This means that in times of low market volatility, equity allocation is increased, and in times of high volatility, it is reduced.
Moreira and Muir (2017) showed in "Volatility-Managed Portfolios" that strategies that adjust their exposure based on volatility forecasts achieve higher Sharpe Ratios than passive buy-and-hold strategies. DEAM implements this principle by defining a target portfolio volatility (default 12% annualized) and adjusting equity allocation to achieve it. The mathematical foundation is simple: if market volatility is 20% and target volatility is 12%, equity allocation should be 60% (12/20 = 0.6), with the remaining 40% held in cash with zero volatility.
4.2 Market Volatility Calculation
Estimating current market volatility is central to the risk-based allocation approach. The model uses several volatility estimators in parallel and selects the higher value between traditional close-to-close volatility and the Parkinson estimator. This conservative choice ensures the model does not underestimate true volatility, which could lead to excessive risk exposure.
Traditional volatility calculation uses logarithmic returns, as these have mathematically advantageous properties (additive linkage over multiple periods). The logarithmic return is calculated as ln(P_t / P_{t-1}), where P_t is the price at time t. The standard deviation of these returns over a rolling 20-trading-day window is then multiplied by √252 to obtain annualized volatility. This annualization is based on the assumption of independently identically distributed returns, which is an idealization but widely accepted in practice.
The Parkinson estimator uses additional information from the trading range (High minus Low) of each day. The formula is: σ_P = (1/√(4ln2)) × √(1/n × Σln²(H_i/L_i)) × √252, where H_i and L_i are high and low prices. Under ideal conditions, this estimator is approximately five times more efficient than the close-to-close estimator (Parkinson, 1980), as it uses more information per observation.
4.3 Drawdown-Based Position Size Adjustment
In addition to volatility targeting, the model implements drawdown-based risk control. The logic is that deep market declines often signal further losses and therefore justify exposure reduction. This behavior corresponds with the concept of path-dependent risk tolerance: investors who have already suffered losses are typically less willing to take additional risk (Kahneman and Tversky, 1979).
The model defines a maximum portfolio drawdown as a target parameter (default 15%). Since portfolio volatility and portfolio drawdown are proportional to equity allocation (assuming cash has neither volatility nor drawdown), allocation-based control is possible. For example, if the market exhibits a 25% drawdown and target portfolio drawdown is 15%, equity allocation should be at most 60% (15/25).
4.4 Dynamic Risk Adjustment
An advanced feature of DEAM is dynamic adjustment of risk-based allocation through a feedback mechanism. The model continuously estimates what actual portfolio volatility and portfolio drawdown would result at the current allocation. If risk utilization (ratio of actual to target risk) exceeds 1.0, allocation is reduced by an adjustment factor that grows exponentially with overutilization. This implements a form of dynamic feedback that avoids overexposure.
Mathematically, a risk adjustment factor r_adjust is calculated: if risk utilization u > 1, then r_adjust = exp(-0.5 × (u - 1)). This exponential function ensures that moderate overutilization is gently corrected, while strong overutilization triggers drastic reductions. The factor 0.5 in the exponent was empirically calibrated to achieve a balanced ratio between sensitivity and stability.
5. Component 3: Valuation Analysis
5.1 Theoretical Foundations of Fundamental Valuation
DEAM's valuation component is based on the fundamental premise that the intrinsic value of a security is determined by its future cash flows and that deviations between market price and intrinsic value are eventually corrected. Graham and Dodd (1934) established in "Security Analysis" the basic principles of fundamental analysis that remain relevant today. Translated into modern portfolio context, this means that markets with high valuation metrics (high price-earnings ratios) should have lower expected returns than cheaply valued markets.
Campbell and Shiller (1988) developed the Cyclically Adjusted P/E Ratio (CAPE), which smooths earnings over a full business cycle. Their empirical analysis showed that this ratio has significant predictive power for 10-year returns. Asness, Moskowitz, and Pedersen (2013) demonstrated in "Value and Momentum Everywhere" that value effects exist not only in individual stocks but also in asset classes and markets.
5.2 Equity Risk Premium as Central Valuation Metric
The Equity Risk Premium (ERP) is defined as the expected excess return of stocks over risk-free government bonds. It is the theoretical heart of valuation analysis, as it represents the compensation investors demand for bearing equity risk. Damodaran (2012) discusses in "Equity Risk Premiums: Determinants, Estimation and Implications" various methods for ERP estimation.
DEAM calculates ERP not through a single method but combines four complementary approaches with different weights. This multi-method strategy increases estimation robustness and avoids dependence on single, potentially erroneous inputs.
The first method (35% weight) uses earnings yield, calculated as 1/P/E or directly from operating earnings data, and subtracts the 10-year Treasury yield. This method follows Fed Model logic (Yardeni, 2003), although this model has theoretical weaknesses as it does not consistently treat inflation (Asness, 2003).
The second method (30% weight) extends earnings yield by share buyback yield. Share buybacks are a form of capital return to shareholders and increase value per share. Boudoukh et al. (2007) showed in "The Total Shareholder Yield" that the sum of dividend yield and buyback yield is a better predictor of future returns than dividend yield alone.
The third method (20% weight) implements the Gordon Growth Model (Gordon, 1962), which models stock value as the sum of discounted future dividends. Under constant growth g assumption: Expected Return = Dividend Yield + g. The model estimates sustainable growth as g = ROE × (1 - Payout Ratio), where ROE is return on equity and payout ratio is the ratio of dividends to earnings. This formula follows from equity theory: unretained earnings are reinvested at ROE and generate additional earnings growth.
The fourth method (15% weight) combines total shareholder yield (Dividend + Buybacks) with implied growth derived from revenue growth. This method considers that companies with strong revenue growth should generate higher future earnings, even if current valuations do not yet fully reflect this.
The final ERP is the weighted average of these four methods. A high ERP (above 4%) signals attractive valuations and increases the valuation score to 95 out of 100 possible points. A negative ERP, where stocks have lower expected returns than bonds, results in a minimal score of 10.
5.3 Quality Adjustments to Valuation
Valuation metrics alone can be misleading if not interpreted in the context of company quality. A company with a low P/E may be cheap or fundamentally problematic. The model therefore implements quality adjustments based on growth, profitability, and capital structure.
Revenue growth above 10% annually adds 10 points to the valuation score, moderate growth above 5% adds 5 points. This adjustment reflects that growth has independent value (Modigliani and Miller, 1961, extended by later growth theory). Net margin above 15% signals pricing power and operational efficiency and increases the score by 5 points, while low margins below 8% indicate competitive pressure and subtract 5 points.
Return on equity (ROE) above 20% characterizes outstanding capital efficiency and increases the score by 5 points. Piotroski (2000) showed in "Value Investing: The Use of Historical Financial Statement Information" that fundamental quality signals such as high ROE can improve the performance of value strategies.
Capital structure is evaluated through the debt-to-equity ratio. A conservative ratio below 1.0 multiplies the valuation score by 1.2, while high leverage above 2.0 applies a multiplier of 0.8. This adjustment reflects that high debt constrains financial flexibility and can become problematic in crisis times (Korteweg, 2010).
6. Component 4: Sentiment Analysis
6.1 The Role of Sentiment in Financial Markets
Investor sentiment, defined as the collective psychological attitude of market participants, influences asset prices independently of fundamental data. Baker and Wurgler (2006, 2007) developed a sentiment index and showed that periods of high sentiment are followed by overvaluations that later correct. This insight justifies integrating a sentiment component into allocation decisions.
Sentiment is difficult to measure directly but can be proxied through market indicators. The VIX is the most widely used sentiment indicator, as it aggregates implied volatility from option prices. High VIX values reflect elevated uncertainty and risk aversion, while low values signal market comfort. Whaley (2009) refers to the VIX as the "Investor Fear Gauge" and documents its role as a contrarian indicator: extremely high values typically occur at market bottoms, while low values occur at tops.
6.2 VIX-Based Sentiment Assessment
DEAM uses statistical normalization of the VIX by calculating the Z-score: z = (VIX_current - VIX_average) / VIX_standard_deviation. The Z-score indicates how many standard deviations the current VIX is from the historical average. This approach is more robust than absolute thresholds, as it adapts to the average volatility level, which can vary over longer periods.
A Z-score below -1.5 (VIX is 1.5 standard deviations below average) signals exceptionally low risk perception and adds 40 points to the sentiment score. This may seem counterintuitive—shouldn't low fear be bullish? However, the logic follows the contrarian principle: when no one is afraid, everyone is already invested, and there is limited further upside potential (Zweig, 1973). Conversely, a Z-score above 1.5 (extreme fear) adds -40 points, reflecting market panic but simultaneously suggesting potential buying opportunities.
6.3 VIX Term Structure as Sentiment Signal
The VIX term structure provides additional sentiment information. Normally, the VIX trades in contango, meaning longer-term VIX futures have higher prices than short-term. This reflects that short-term volatility is currently known, while long-term volatility is more uncertain and carries a risk premium. The model compares the VIX with VIX9D (9-day volatility) and identifies backwardation (VIX > 1.05 × VIX9D) and steep backwardation (VIX > 1.15 × VIX9D).
Backwardation occurs when short-term implied volatility is higher than longer-term, which typically happens during market stress. Investors anticipate immediate turbulence but expect calming. Psychologically, this reflects acute fear. The model subtracts 15 points for backwardation and 30 for steep backwardation, as these constellations signal elevated risk. Simon and Wiggins (2001) analyzed the VIX futures curve and showed that backwardation is associated with market declines.
6.4 Safe-Haven Flows
During crisis times, investors flee from risky assets into safe havens: gold, US dollar, and Japanese yen. This "flight to quality" is a sentiment signal. The model calculates the performance of these assets relative to stocks over the last 20 trading days. When gold or the dollar strongly rise while stocks fall, this indicates elevated risk aversion.
The safe-haven component is calculated as the difference between safe-haven performance and stock performance. Positive values (safe havens outperform) subtract up to 20 points from the sentiment score, negative values (stocks outperform) add up to 10 points. The asymmetric treatment (larger deduction for risk-off than bonus for risk-on) reflects that risk-off movements are typically sharper and more informative than risk-on phases.
Baur and Lucey (2010) examined safe-haven properties of gold and showed that gold indeed exhibits negative correlation with stocks during extreme market movements, confirming its role as crisis protection.
7. Component 5: Macroeconomic Analysis
7.1 The Yield Curve as Economic Indicator
The yield curve, represented as yields of government bonds of various maturities, contains aggregated expectations about future interest rates, inflation, and economic growth. The slope of the yield curve has remarkable predictive power for recessions. Estrella and Mishkin (1998) showed that an inverted yield curve (short-term rates higher than long-term) predicts recessions with high reliability. This is because inverted curves reflect restrictive monetary policy: the central bank raises short-term rates to combat inflation, dampening economic activity.
DEAM calculates two spread measures: the 2-year-minus-10-year spread and the 3-month-minus-10-year spread. A steep, positive curve (spreads above 1.5% and 2% respectively) signals healthy growth expectations and generates the maximum yield curve score of 40 points. A flat curve (spreads near zero) reduces the score to 20 points. An inverted curve (negative spreads) is particularly alarming and results in only 10 points.
The choice of two different spreads increases analysis robustness. The 2-10 spread is most established in academic literature, while the 3M-10Y spread is often considered more sensitive, as the 3-month rate directly reflects current monetary policy (Ang, Piazzesi, and Wei, 2006).
7.2 Credit Conditions and Spreads
Credit spreads—the yield difference between risky corporate bonds and safe government bonds—reflect risk perception in the credit market. Gilchrist and Zakrajšek (2012) constructed an "Excess Bond Premium" that measures the component of credit spreads not explained by fundamentals and showed this is a predictor of future economic activity and stock returns.
The model approximates credit spread by comparing the yield of high-yield bond ETFs (HYG) with investment-grade bond ETFs (LQD). A narrow spread below 200 basis points signals healthy credit conditions and risk appetite, contributing 30 points to the macro score. Very wide spreads above 1000 basis points (as during the 2008 financial crisis) signal credit crunch and generate zero points.
Additionally, the model evaluates whether "flight to quality" is occurring, identified through strong performance of Treasury bonds (TLT) with simultaneous weakness in high-yield bonds. This constellation indicates elevated risk aversion and reduces the credit conditions score.
7.3 Financial Stability at Corporate Level
While the yield curve and credit spreads reflect macroeconomic conditions, financial stability evaluates the health of companies themselves. The model uses the aggregated debt-to-equity ratio and return on equity of the S&P 500 as proxies for corporate health.
A low leverage level below 0.5 combined with high ROE above 15% signals robust corporate balance sheets and generates 20 points. This combination is particularly valuable as it represents both defensive strength (low debt means crisis resistance) and offensive strength (high ROE means earnings power). High leverage above 1.5 generates only 5 points, as it implies vulnerability to interest rate increases and recessions.
Korteweg (2010) showed in "The Net Benefits to Leverage" that optimal debt maximizes firm value, but excessive debt increases distress costs. At the aggregated market level, high debt indicates fragilities that can become problematic during stress phases.
8. Component 6: Crisis Detection
8.1 The Need for Systematic Crisis Detection
Financial crises are rare but extremely impactful events that suspend normal statistical relationships. During normal market volatility, diversified portfolios and traditional risk management approaches function, but during systemic crises, seemingly independent assets suddenly correlate strongly, and losses exceed historical expectations (Longin and Solnik, 2001). This justifies a separate crisis detection mechanism that operates independently of regular allocation components.
Reinhart and Rogoff (2009) documented in "This Time Is Different: Eight Centuries of Financial Folly" recurring patterns in financial crises: extreme volatility, massive drawdowns, credit market dysfunction, and asset price collapse. DEAM operationalizes these patterns into quantifiable crisis indicators.
8.2 Multi-Signal Crisis Identification
The model uses a counter-based approach where various stress signals are identified and aggregated. This methodology is more robust than relying on a single indicator, as true crises typically occur simultaneously across multiple dimensions. A single signal may be a false alarm, but the simultaneous presence of multiple signals increases confidence.
The first indicator is a VIX above the crisis threshold (default 40), adding one point. A VIX above 60 (as in 2008 and March 2020) adds two additional points, as such extreme values are historically very rare. This tiered approach captures the intensity of volatility.
The second indicator is market drawdown. A drawdown above 15% adds one point, as corrections of this magnitude can be potential harbingers of larger crises. A drawdown above 25% adds another point, as historical bear markets typically encompass 25-40% drawdowns.
The third indicator is credit market spreads above 500 basis points, adding one point. Such wide spreads occur only during significant credit market disruptions, as in 2008 during the Lehman crisis.
The fourth indicator identifies simultaneous losses in stocks and bonds. Normally, Treasury bonds act as a hedge against equity risk (negative correlation), but when both fall simultaneously, this indicates systemic liquidity problems or inflation/stagflation fears. The model checks whether both SPY and TLT have fallen more than 10% and 5% respectively over 5 trading days, adding two points.
The fifth indicator is a volume spike combined with negative returns. Extreme trading volumes (above twice the 20-day average) with falling prices signal panic selling. This adds one point.
A crisis situation is diagnosed when at least 3 indicators trigger, a severe crisis at 5 or more indicators. These thresholds were calibrated through historical backtesting to identify true crises (2008, 2020) without generating excessive false alarms.
8.3 Crisis-Based Allocation Override
When a crisis is detected, the system overrides the normal allocation recommendation and caps equity allocation at maximum 25%. In a severe crisis, the cap is set at 10%. This drastic defensive posture follows the empirical observation that crises typically require time to develop and that early reduction can avoid substantial losses (Faber, 2007).
This override logic implements a "safety first" principle: in situations of existential danger to the portfolio, capital preservation becomes the top priority. Roy (1952) formalized this approach in "Safety First and the Holding of Assets," arguing that investors should primarily minimize ruin probability.
9. Integration and Final Allocation Calculation
9.1 Component Weighting
The final allocation recommendation emerges through weighted aggregation of the five components. The standard weighting is: Market Regime 35%, Risk Management 25%, Valuation 20%, Sentiment 15%, Macro 5%. These weights reflect both theoretical considerations and empirical backtesting results.
The highest weighting of market regime is based on evidence that trend-following and momentum strategies have delivered robust results across various asset classes and time periods (Moskowitz, Ooi, and Pedersen, 2012). Current market momentum is highly informative for the near future, although it provides no information about long-term expectations.
The substantial weighting of risk management (25%) follows from the central importance of risk control. Wealth preservation is the foundation of long-term wealth creation, and systematic risk management is demonstrably value-creating (Moreira and Muir, 2017).
The valuation component receives 20% weight, based on the long-term mean reversion of valuation metrics. While valuation has limited short-term predictive power (bull and bear markets can begin at any valuation), the long-term relationship between valuation and returns is robustly documented (Campbell and Shiller, 1988).
Sentiment (15%) and Macro (5%) receive lower weights, as these factors are subtler and harder to measure. Sentiment is valuable as a contrarian indicator at extremes but less informative in normal ranges. Macro variables such as the yield curve have strong predictive power for recessions, but the transmission from recessions to stock market performance is complex and temporally variable.
9.2 Model Type Adjustments
DEAM allows users to choose between four model types: Conservative, Balanced, Aggressive, and Adaptive. This choice modifies the final allocation through additive adjustments.
Conservative mode subtracts 10 percentage points from allocation, resulting in consistently more cautious positioning. This is suitable for risk-averse investors or those with limited investment horizons. Aggressive mode adds 10 percentage points, suitable for risk-tolerant investors with long horizons.
Adaptive mode implements procyclical adjustment based on short-term momentum: if the market has risen more than 5% in the last 20 days, 5 percentage points are added; if it has declined more than 5%, 5 points are subtracted. This logic follows the observation that short-term momentum persists (Jegadeesh and Titman, 1993), but the moderate size of adjustment avoids excessive timing bets.
Balanced mode makes no adjustment and uses raw model output. This neutral setting is suitable for investors who wish to trust model recommendations unchanged.
9.3 Smoothing and Stability
The allocation resulting from aggregation undergoes final smoothing through a simple moving average over 3 periods. This smoothing is crucial for model practicality, as it reduces frequent trading and thus transaction costs. Without smoothing, the model could fluctuate between adjacent allocations with every small input change.
The choice of 3 periods as smoothing window is a compromise between responsiveness and stability. Longer smoothing would excessively delay signals and impede response to true regime changes. Shorter or no smoothing would allow too much noise. Empirical tests showed that 3-period smoothing offers an optimal ratio between these goals.
10. Visualization and Interpretation
10.1 Main Output: Equity Allocation
DEAM's primary output is a time series from 0 to 100 representing the recommended percentage allocation to equities. This representation is intuitive: 100% means full investment in stocks (specifically: an S&P 500 ETF), 0% means complete cash position, and intermediate values correspond to mixed portfolios. A value of 60% means, for example: invest 60% of wealth in SPY, hold 40% in money market instruments or cash.
The time series is color-coded to enable quick visual interpretation. Green shades represent high allocations (above 80%, bullish), red shades low allocations (below 20%, bearish), and neutral colors middle allocations. The chart background is dynamically colored based on the signal, enhancing readability in different market phases.
10.2 Dashboard Metrics
A tabular dashboard presents key metrics compactly. This includes current allocation, cash allocation (complement), an aggregated signal (BULLISH/NEUTRAL/BEARISH), current market regime, VIX level, market drawdown, and crisis status.
Additionally, fundamental metrics are displayed: P/E Ratio, Equity Risk Premium, Return on Equity, Debt-to-Equity Ratio, and Total Shareholder Yield. This transparency allows users to understand model decisions and form their own assessments.
Component scores (Regime, Risk, Valuation, Sentiment, Macro) are also displayed, each normalized on a 0-100 scale. This shows which factors primarily drive the current recommendation. If, for example, the Risk score is very low (20) while other scores are moderate (50-60), this indicates that risk management considerations are pulling allocation down.
10.3 Component Breakdown (Optional)
Advanced users can display individual components as separate lines in the chart. This enables analysis of component dynamics: do all components move synchronously, or are there divergences? Divergences can be particularly informative. If, for example, the market regime is bullish (high score) but the valuation component is very negative, this signals an overbought market not fundamentally supported—a classic "bubble warning."
This feature is disabled by default to keep the chart clean but can be activated for deeper analysis.
10.4 Confidence Bands
The model optionally displays uncertainty bands around the main allocation line. These are calculated as ±1 standard deviation of allocation over a rolling 20-period window. Wide bands indicate high volatility of model recommendations, suggesting uncertain market conditions. Narrow bands indicate stable recommendations.
This visualization implements a concept of epistemic uncertainty—uncertainty about the model estimate itself, not just market volatility. In phases where various indicators send conflicting signals, the allocation recommendation becomes more volatile, manifesting in wider bands. Users can understand this as a warning to act more cautiously or consult alternative information sources.
11. Alert System
11.1 Allocation Alerts
DEAM implements an alert system that notifies users of significant events. Allocation alerts trigger when smoothed allocation crosses certain thresholds. An alert is generated when allocation reaches 80% (from below), signaling strong bullish conditions. Another alert triggers when allocation falls to 20%, indicating defensive positioning.
These thresholds are not arbitrary but correspond with boundaries between model regimes. An allocation of 80% roughly corresponds to a clear bull market regime, while 20% corresponds to a bear market regime. Alerts at these points are therefore informative about fundamental regime shifts.
11.2 Crisis Alerts
Separate alerts trigger upon detection of crisis and severe crisis. These alerts have highest priority as they signal large risks. A crisis alert should prompt investors to review their portfolio and potentially take defensive measures beyond the automatic model recommendation (e.g., hedging through put options, rebalancing to more defensive sectors).
11.3 Regime Change Alerts
An alert triggers upon change of market regime (e.g., from Neutral to Correction, or from Bull Market to Strong Bull). Regime changes are highly informative events that typically entail substantial allocation changes. These alerts enable investors to proactively respond to changes in market dynamics.
11.4 Risk Breach Alerts
A specialized alert triggers when actual portfolio risk utilization exceeds target parameters by 20%. This is a warning signal that the risk management system is reaching its limits, possibly because market volatility is rising faster than allocation can be reduced. In such situations, investors should consider manual interventions.
12. Practical Application and Limitations
12.1 Portfolio Implementation
DEAM generates a recommendation for allocation between equities (S&P 500) and cash. Implementation by an investor can take various forms. The most direct method is using an S&P 500 ETF (e.g., SPY, VOO) for equity allocation and a money market fund or savings account for cash allocation.
A rebalancing strategy is required to synchronize actual allocation with model recommendation. Two approaches are possible: (1) rule-based rebalancing at every 10% deviation between actual and target, or (2) time-based monthly rebalancing. Both have trade-offs between responsiveness and transaction costs. Empirical evidence (Jaconetti, Kinniry, and Zilbering, 2010) suggests rebalancing frequency has moderate impact on performance, and investors should optimize based on their transaction costs.
12.2 Adaptation to Individual Preferences
The model offers numerous adjustment parameters. Component weights can be modified if investors place more or less belief in certain factors. A fundamentally-oriented investor might increase valuation weight, while a technical trader might increase regime weight.
Risk target parameters (target volatility, max drawdown) should be adapted to individual risk tolerance. Younger investors with long investment horizons can choose higher target volatility (15-18%), while retirees may prefer lower volatility (8-10%). This adjustment systematically shifts average equity allocation.
Crisis thresholds can be adjusted based on preference for sensitivity versus specificity of crisis detection. Lower thresholds (e.g., VIX > 35 instead of 40) increase sensitivity (more crises are detected) but reduce specificity (more false alarms). Higher thresholds have the reverse effect.
12.3 Limitations and Disclaimers
DEAM is based on historical relationships between indicators and market performance. There is no guarantee these relationships will persist in the future. Structural changes in markets (e.g., through regulation, technology, or central bank policy) can break established patterns. This is the fundamental problem of induction in financial science (Taleb, 2007).
The model is optimized for US equities (S&P 500). Application to other markets (international stocks, bonds, commodities) would require recalibration. The indicators and thresholds are specific to the statistical properties of the US equity market.
The model cannot eliminate losses. Even with perfect crisis prediction, an investor following the model would lose money in bear markets—just less than a buy-and-hold investor. The goal is risk-adjusted performance improvement, not risk elimination.
Transaction costs are not modeled. In practice, spreads, commissions, and taxes reduce net returns. Frequent trading can cause substantial costs. Model smoothing helps minimize this, but users should consider their specific cost situation.
The model reacts to information; it does not anticipate it. During sudden shocks (e.g., 9/11, COVID-19 lockdowns), the model can only react after price movements, not before. This limitation is inherent to all reactive systems.
12.4 Relationship to Other Strategies
DEAM is a tactical asset allocation approach and should be viewed as a complement, not replacement, for strategic asset allocation. Brinson, Hood, and Beebower (1986) showed in their influential study "Determinants of Portfolio Performance" that strategic asset allocation (long-term policy allocation) explains the majority of portfolio performance, but this leaves room for tactical adjustments based on market timing.
The model can be combined with value and momentum strategies at the individual stock level. While DEAM controls overall market exposure, within-equity decisions can be optimized through stock-picking models. This separation between strategic (market exposure) and tactical (stock selection) levels follows classical portfolio theory.
The model does not replace diversification across asset classes. A complete portfolio should also include bonds, international stocks, real estate, and alternative investments. DEAM addresses only the US equity allocation decision within a broader portfolio.
13. Scientific Foundation and Evaluation
13.1 Theoretical Consistency
DEAM's components are based on established financial theory and empirical evidence. The market regime component follows from regime-switching models (Hamilton, 1989) and trend-following literature. The risk management component implements volatility targeting (Moreira and Muir, 2017) and modern portfolio theory (Markowitz, 1952). The valuation component is based on discounted cash flow theory and empirical value research (Campbell and Shiller, 1988; Fama and French, 1992). The sentiment component integrates behavioral finance (Baker and Wurgler, 2006). The macro component uses established business cycle indicators (Estrella and Mishkin, 1998).
This theoretical grounding distinguishes DEAM from purely data-mining-based approaches that identify patterns without causal theory. Theory-guided models have greater probability of functioning out-of-sample, as they are based on fundamental mechanisms, not random correlations (Lo and MacKinlay, 1990).
13.2 Empirical Validation
While this document does not present detailed backtest analysis, it should be noted that rigorous validation of a tactical asset allocation model should include several elements:
In-sample testing establishes whether the model functions at all in the data on which it was calibrated. Out-of-sample testing is crucial: the model should be tested in time periods not used for development. Walk-forward analysis, where the model is successively trained on rolling windows and tested in the next window, approximates real implementation.
Performance metrics should be risk-adjusted. Pure return consideration is misleading, as higher returns often only compensate for higher risk. Sharpe Ratio, Sortino Ratio, Calmar Ratio, and Maximum Drawdown are relevant metrics. Comparison with benchmarks (Buy-and-Hold S&P 500, 60/40 Stock/Bond portfolio) contextualizes performance.
Robustness checks test sensitivity to parameter variation. If the model only functions at specific parameter settings, this indicates overfitting. Robust models show consistent performance over a range of plausible parameters.
13.3 Comparison with Existing Literature
DEAM fits into the broader literature on tactical asset allocation. Faber (2007) presented a simple momentum-based timing system that goes long when the market is above its 10-month average, otherwise cash. This simple system avoided large drawdowns in bear markets. DEAM can be understood as a sophistication of this approach that integrates multiple information sources.
Ilmanen (2011) discusses various timing factors in "Expected Returns" and argues for multi-factor approaches. DEAM operationalizes this philosophy. Asness, Moskowitz, and Pedersen (2013) showed that value and momentum effects work across asset classes, justifying cross-asset application of regime and valuation signals.
Ang (2014) emphasizes in "Asset Management: A Systematic Approach to Factor Investing" the importance of systematic, rule-based approaches over discretionary decisions. DEAM is fully systematic and eliminates emotional biases that plague individual investors (overconfidence, hindsight bias, loss aversion).
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Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
Market Sentiment Trend Gauge [LevelUp]Market Sentiment Trend Gauge simplifies technical analysis by mathematically combining momentum, trend direction, volatility position, and comparison against a market benchmark, into a single trend score from -100 to +100. Displayed in a separate pane below your chart, it resolves conflicting signals from RSI, moving averages, Bollinger Bands, and market correlations, providing clear insights into trend direction, strength, and relative performance.
THE PROBLEM MARKET SENTIMENT TREND GAUGE (MSTG) SOLVES
Traditional indicators often produce conflicting signals, such as RSI showing overbought while prices rise or moving averages indicating an uptrend despite market underperformance. MSTG creates a weighted composite score to answer: "What's the overall bias for this asset?"
KEY COMPONENTS AND WEIGHTINGS
The trend score combines
▪ Momentum (25%): Normalized 14-period RSI, capped at ±100.
▪ Trend Direction (35%): 10/21-period EMA relationships,
▪ Volatility Position (20%): Price position, 20-period Bollinger Bands, capped at ±100.
▪ Market Comparison (20%): Daily performance vs. SPY benchmark, capped at ±100.
Final score = Weighted sum, smoothed with 5-period EMA.
INTERPRETING THE MSTG CHART
Trend Score Ranges and Colors
▪ Bright Green (>+30): Strong bullish; ideal for long entries.
▪ Light Green (+10 to +30): Weak bullish; cautiously favorable.
▪ Gray (-10 to +10): Neutral; avoid directional trades.
▪ Light Red (-10 to -30): Weak bearish; exercise caution.
▪ Bright Red (<-30): Strong bearish; high-risk for longs, consider shorts.
Reference Lines
▪ Zero Line (Gray): Separates bullish/bearish; crossovers signal trend changes.
▪ ±30 Lines (Dotted, Green/Red): Thresholds for strong trends.
▪ ±60 Lines (Dashed, Green/Red): Extreme strength zones (not overbought/oversold); manage risk (tighten stops, partial profits) but trends may persist.
Background Colors
▪ Green Tint (>+20): Bullish environment; favorable for longs.
▪ Red Tint (<-20): Bearish environment; caution for longs.
▪ Light Gray Tint (-20 to +20): Neutral/range-bound; wait for signals.
Extreme Readings vs. Traditional Signals
MSTG ±60 indicates maximum alignment of all factors, not reversals (unlike RSI >70/<30). Use for risk management, not automatic exits. Strong trends can sustain extremes; breakdowns occur below +30 or above -30.
INFORMATION TABLE INTERPRETATION
Trend Score Symbols
▲▲ >+30 strong bullish
▲ +10 to +30
● -10 to +10 neutral
▼ -30 to -10
▼▼ <-30 strong bearish
Colors: Green (positive), White (neutral), Red (negative).
Momentum Score
+40 to +100 strong bullish
0 to +40 moderate bullish
-40 to 0 moderate bearish
-100 to -40 strong bearish
Market vs. Stock
▪ Green: Stock outperforming market
▪ Red: Stock underperforming market
Example Interpretations:
-0.45% / +1.23% (Green): Market down, stock up = Strong relative strength
+2.10% / +1.50% (Red): Both rising, but stock lagging = Relative weakness
-1.20% / -0.80% (Green): Both falling, but stock declining less = Defensive strength
UNDERSTANDING EXTREME READINGS VS TRADITIONAL OVERBOUGHT/OVERSOLD
⚠️ Critical distinctions
Traditional Overbought/Oversold Signals:
▪ Single indicator (like RSI >70 or <30) showing momentum excess
▪ Often suggests immediate reversal or pullback expected
▪ Based on "price moved too far, too fast" concept
MSTG Extreme Readings (±60):
▪ Composite alignment of 4 different factors (momentum, trend, volatility, relative strength)
▪ Indicates maximum strength in current direction
▪ NOT a reversal signal - means "all systems extremely bullish/bearish"
Key Differences:
▪ RSI >70: "Price got ahead of itself, expect pullback"
▪ MSTG >+60: "Everything is extremely bullish right now"
▪ Strong trends can maintain extreme MSTG readings during major moves
▪ Breakdowns happen when MSTG falls below +30, not at +60
Proper Usage of Extreme Readings:
▪ Risk Management: Tighten stops, take partial profits
▪ Position Sizing: Reduce new position sizes at extremes
▪ Trend Continuation: Watch for sustained extreme readings in strong markets
▪ Exit Signals: Look for breakdown below +30, not reversal from +60
TRADING WITH MSTG
Quick Assessment
1. Check trend symbol for direction.
2. Confirm momentum strength.
3. Note relative performance color.
Examples:
▲▲ 55.2 (Green), Momentum +28.4, Outperforming: Strong buy setup.
▼ -18.6 (Red), Momentum -43.2, Underperforming: Defensive positioning.
Entry Conditions
▪ Long: stock outperforming market
- Score >+30 (bright green)
- Sustained green background
- ▲▲ symbol,
▪ Short: stock underperforming market
- Score <-30 (bright red)
- Sustained red background
- ▼▼ symbol
Avoid Trading When:
▪ Gray zone (-10 to +10).
▪ Rapid color changes or frequent zero-line crosses (choppy market).
▪ Gray background (range-bound).
Risk Management:
▪ Stop Loss: Exit on zero-line crossover against position.
▪ Take Profit: Partial at ±60 for risk control.
▪ Position Sizing: Larger when signals align; smaller in extremes or mixed conditions.
KEY ADVANTAGES
▪ Unified View: Weighted composite reduces noise and conflicts.
▪ Visual Clarity: 5-color system with gradients for rapid recognition.
▪ Market Context: Relative strength vs. SPY identifies leaders/laggards.
▪ Flexibility: Works across timeframes (1-min to weekly); customizable table.
▪ Noise Reduction: EMA smoothing minimizes false signals.
EXAMPLES
Strong Bull: Trend Score 71.9, Momentum Score 76.9
Neutral: Trend Score 0.1, Momentum Score -9.2
Strong Bear: Trend Score -51.7, Momentum Score -51.5
PERFORMANCE AND LIMITATIONS
Strengths: Trend identification, noise reduction, relative performance versus market.
Limitations: Lags at turning points, less effective in extreme volatility or non-trending markets.
Recommendations: View on multiple timeframes, combine with price action and fundamentals.
Trend Score with Dynamic Stop Loss RTH
📘 Trend Score with Dynamic Stop Loss (RTH) — Guide
🔎 Overview
This indicator tracks intraday momentum during Regular Trading Hours and flags trend flips using a cumulative TrendScore. It also draws dynamic stop-loss levels and shows a live stats table for quick decision-making and journaling.
⸻
⚙️ Core Concepts
1) TrendScore (per bar)
• +1 if the current bar makes a higher high than the previous bar (counted once per bar).
• –1 if the current bar makes a lower low than the previous bar (counted once per bar).
• If a bar takes both the prior high and low, the net contribution can cancel out within that bar.
2) Cumulative TrendScore (running total)
• The per-bar TrendScore accumulates across the session to form the cumulative TrendScore (TS).
• TS resets to 0 at session open and is cleared at session close.
• Rising TS = persistent upside pressure; falling TS = persistent downside pressure.
⸻
🔄 Flip Rules (3-point reversal of the cumulative TrendScore)
A flip occurs when the cumulative TrendScore reverses by 3 points in the opposite direction of the current trend.
• Bullish Flip
• Trigger: After a decline, the cumulative TrendScore rises by +3 from its down-leg.
• Interpretation: Bulls have taken control.
• Stop-loss: the lowest price of the prior (down) leg.
• Bearish Flip
• Trigger: After a rise, the cumulative TrendScore falls by –3 from its up-leg.
• Interpretation: Bears have taken control.
• Stop-loss: the highest price of the prior (up) leg.
Flip bars are marked with ▲ (lime) for bullish and ▼ (red) for bearish.
Note: If you prefer a different reversal distance, adjust the flip distance setting in the script’s inputs (default is 3).
⸻
📏 Stop-Loss Lines
• A dotted line is drawn at the prior leg’s extreme:
Green (below price) after a bullish flip.
Red (above price) after a bearish flip.
• Options:
Remove on touch for a clean chart.
Freeze on touch to keep a visual record for journaling.
• All stop lines are cleared at session end.
⸻
🧮 Stats Table (what you see)
• Trend: Bull / Bear / Neutral
• Bars in Trend: Count since the flip bar
• Since Flip: Current close minus flip bar close
• Since SL: Current close minus active stop level
• MFE-Maximum Favorable Excursion: Highest favorable move since flip
• MAE-Maximum Adverse Excursion: Largest adverse move since flip
Table colors reflect the current trend (green for bull, red for bear).
⸻
📊 Trading Playbook
Entries
• Aggressive: Enter immediately on a flip marker.
• Conservative: Wait for a small pullback that doesn’t violate the stop.
Stops
• Place the stop at the script’s flip stop-loss line (the prior leg extreme).
Exits
Choose one style and stick with it:
• Stop-only: Exit when the stop is hit.
• Time-based: Flatten at session close.
• Targets: Scale/close at 1R, 2R.
• Trailing: Trail behind minor swings once MFE > 1R.
Ultimately Exit choice is your own edge, so you must decide for yourself.
💡 Best Practices
• Skip the first few bars after the open (gap noise).
• Use regular candles (Heikin-Ashi will distort highs/lows).
• If you want fewer flips, increase the flip distance (e.g., 4 or 5). For more
responsiveness, use 2. Otherwise, increase your time frame to 5m, 10m, 15m.
• Keep SL lines frozen (not auto-removed) if you’re journaling.
Sniper-2025 Sniper-2025 Indicator Explanation
Overview
The Sniper-2025 indicator is a versatile technical analysis tool designed for TradingView, combining a Hyper Wave oscillator, Smart Money Flow analysis, divergence detection, reversal signals, confluence visualization, and a machine learning-based k-Nearest Neighbors (k-NN) prediction model. It provides traders with actionable buy and sell signals, trend insights, and confluence indicators to enhance decision-making across various trading strategies. The indicator is highly customizable, allowing users to adjust sensitivity, colors, and display options to suit their preferences.
Key Features
1. Hyper Wave Oscillator: A normalized oscillator based on price data, smoothed with either a Simple Moving Average (SMA) or Exponential Moving Average (EMA), highlighting momentum and potential reversal points.
2. Smart Money Flow: Tracks bullish and bearish money flow using a smoothed Money Flow Index (MFI), providing insights into market strength and direction.
3. Divergence Detection: Identifies bullish and bearish divergences between price and the oscillator, with optional labels displaying price levels.
4. Reversal Signals: Detects major and minor reversal conditions based on volume, oscillator values, and RSI, visualized as triangles and circles on the chart.
5. Confluence Meter and Areas: Visualizes alignment between the oscillator and MFI, indicating bullish or bearish confluence with customizable colors and shaded areas.
6. Signal and Divergence Labels: Displays labels for key oscillator levels (e.g., Z-Buy, Z-V-Sell) and money flow conditions (e.g., C-Buy, T-Sell) with customizable visibility and sizes.
7. Trend and Control Table: Shows the current trend (Bullish/Bearish) and control (Bull/Bear) in a customizable table positioned on the chart.
8. k-NN Prediction: Uses a k-Nearest Neighbors algorithm to predict price movement direction based on RSI indicators, with adjustable prediction sensitivity.
9. Gradient Fills and Alerts: Visualizes overbought and oversold zones with gradient fills and provides alert conditions for key crossovers and crossunders.
How It Works
- Hyper Wave Oscillator: The oscillator is calculated by normalizing the close price relative to the highest, lowest, and average prices over a user-defined length (default: 15). It is smoothed using SMA or EMA (default: SMA, length 3) to generate a signal line. Crossovers and crossunders of the oscillator and signal line are plotted as circles, indicating potential buy or sell signals.
- Smart Money Flow: The MFI is calculated over a user-defined length (default: 10) and smoothed (default: 6). It tracks bullish (positive) or bearish (negative) money flow, with colors changing based on direction (blue for bullish, red for bearish). The indicator compares current MFI to its historical average to identify strong trends.
- Divergence Detection: The script identifies divergences by comparing oscillator peaks/troughs with price highs/lows. Bullish divergences (price makes lower lows, oscillator does not) and bearish divergences (price makes higher highs, oscillator does not) are plotted as lines, with optional labels showing the divergence type and price.
- Reversal Signals: Major reversals are detected when volume exceeds a threshold (based on a 7-period SMA and reversal factor, default: 4) and the oscillator exceeds ±4. Minor reversals consider RSI (±20) and oscillator crossovers. Signals are plotted as triangles (major) or circles (minor), with blue for bullish and red for bearish.
- Confluence Meter and Areas: The confluence meter, displayed on the right, shows alignment between the oscillator and MFI using a gradient from red (bearish) to blue (bullish). Shaded areas at ±55 highlight strong bullish or bearish confluence when both indicators align.
- Signal and Divergence Labels: Labels are plotted on the candlestick chart when the oscillator crosses key levels (±20, ±40) or when money flow conditions are met (e.g., MFI crossing 0 or ±20/±40). Users can toggle label visibility and adjust sizes (Small, Normal, Large, Huge).
- Trend and Control Table: A table displays the trend (based on oscillator SMA) and control (based on MFI direction), with customizable position (default: Top Right), text color, and background color. Sensitivity for trend and control calculations can be adjusted.
- k-NN Prediction: The k-NN algorithm predicts price movement direction by comparing current RSI values (5-period and 20-period WMAs) to historical data. The number of neighbors (default: 200) and trend length (default: 20) control prediction sensitivity. A green line shows the prediction, with gradient fills indicating overbought (lime) and oversold (red) zones.
- Gradient Fills and Alerts: Gradient fills highlight the prediction's position relative to overbought/oversold zones, calculated using a 2000-period lookback and standard deviation. Alerts are triggered for crossovers/crossunders of the prediction line with its WMA, overbought/oversold levels, or the zero line.
Usage Instructions
1. Add the Sniper-2025 indicator to your TradingView chart.
2. Interpret signals:
- Z-Buy/Z-V-Buy (green labels): Potential buy signals when the oscillator crosses below -20/-40.
- Z-Sell/Z-V-Sell (red labels): Potential sell signals when the oscillator crosses above 20/40.
- C-Buy/C-Sell (green/red labels): Money flow shifts to bullish/bearish when MFI crosses 0.
- T-Buy/T-Sell (green/red labels): Money flow crosses ±20, indicating stronger trends.
- T-V-Buy/T-V-Sell (green/red labels): Money flow crosses ±40, indicating very strong trends.
- Divergence Labels: Green (D-Bullish) or red (D-Bearish) labels indicate potential reversals.
- Reversal Signals: Blue triangles/circles for bullish reversals, red for bearish.
- Confluence Meter: Blue (bullish) or red (bearish) gradient indicates alignment strength.
- Table: Check "Trend" and "Control" for market direction (🟩/🟥 for trend, 🟢/🔴 for control).
- k-NN Prediction: Green line above 0 suggests bullish momentum; below 0 suggests bearish. Watch for crossovers with the WMA or overbought/oversold zones.
3. Set alerts for crossovers/crossunders of the prediction line, oscillator, or MFI to automate trading signals.
Customization Options
- Hyper Wave: Adjust Main Length (mL, default: 15) for oscillator sensitivity, Signal Type (sT, SMA/EMA), and Signal Length (sLHW, default: 3). Customize colors and transparency.
- Smart Money Flow: Set Money Flow Length (mfL, default: 10) and Smooth (mfS, default: 6) for MFI sensitivity. Choose bullish/bearish colors.
- Divergence: Modify Divergence Sensibility (dvT, default: 20) for short-term (lower) or long-term (higher) divergences. Toggle visibility and price display on labels.
- Reversal: Adjust Reversal Factor (rsF, default: 4) for signal strength (higher = fewer, stronger signals). Set colors for bullish/bearish signals.
- Confluence: Toggle Confluence Meter (sCNF) and Areas (sCNB), and customize colors.
- Labels: Enable/disable specific signal labels (e.g., showZBuy, showHSell) and adjust Label Size (default: Normal).
- Table: Toggle Trend and Control display, adjust sensitivities, and set position and colors.
- k-NN Prediction: Adjust Prediction Data (numNeighbors, default: 200) for sensitivity and Trend Length (momentumWindow, default: 20) for responsiveness.
Conclusion
The Sniper-2025 indicator is a powerful tool for traders seeking a comprehensive analysis of price momentum, money flow, divergences, reversals, and predictive signals. Its customizable settings and clear visualizations make it suitable for both novice and experienced traders. Use the indicator to identify high-probability trading opportunities, monitor market trends, and refine strategies with its machine learning-driven predictions.
Kio IQ [TradingIQ]Introducing: “Kio IQ ”
Kio IQ is an all-in-one trading indicator that brings momentum, trend strength, multi-timeframe analysis, trend divergences, pullbacks, early trend shift signals, and trend exhaustion signals together in one clear view.
🔶 The Philosophy of Kio IQ
Markets move in trends—and capturing them reliably is the key to consistency in trading. Without a tool to see the bigger picture, it’s easy to mistake a pullback for a breakout, a fakeout for the real deal, or random market noise as a meaningful price move.
Kio IQ cuts through that random market noise—scanning multiple timeframes, analyzing short, medium, and long-term momentum, and telling you on the spot whether a move is strong, weak, a trap, or simply a small move within a larger trend.
With Kio IQ, price action reveals its next move.
You’ll instantly see:
Which way it’s pushing — up, down, or stuck in the middle.
How hard it’s pushing — from fading weakness to full-blown strength.
When the gears are shifting — early warnings, explosive moves, smart pullbacks, or signs it’s running out of steam.
🔶 Why This Matters
Markets move in phases—sometimes they’re powering in one direction, sometimes they’re slowing down, and sometimes they’re reversing.
Knowing which phase you’re in can help you:
Avoid chasing a move that’s about to run out of steam.
Jump on a move when it’s just getting started.
Spot pullbacks inside a bigger trend (good for entries).
See when different timeframes are all pointing the same way.
🔶 What Kio IQ Shows You
Simple color-coded phases: “Strong Up,” “Up,” “Weak Up,” “Weak Down,” “Down,” “Strong Down.”
Clear visual signals
Full Shift: Strong momentum in one direction.
Half Shift: Momentum is building but not full power yet.
Pullback Shift: A small move against the trend that may be ending.
Early Scout / Lookout: First hints of a possible shift.
Exhaustion: Momentum is very stretched and may slow down.
Divergences: When price moves one way but momentum moves the opposite way—often a warning of a change.
Multi-Timeframe Table: See the trend strength for multiple timeframes (5m, current, 30m, 4h, 1D, and optional 1W/1M) all in one place.
Trend Strength %: A single number that tells you how strong the trend is across all timeframes.
Optional meters: A “momentum bar” and “trend strength gauge” for quick checks.
🔶 How It Works Behind the Scenes
Kio IQ measures price movement in different “speeds”:
Slow view: Big picture trend.
Medium view: The main engine for detecting the current phase.
Fast view: Catches recent changes in momentum.
Super-fast view: Finds tiny pullbacks inside the bigger move.
It compares these views to decide whether the market is strong up, weak up, weak down, strong down, or in between. Then it blends data from multiple timeframes so you see the whole picture, not just the current chart.
🔶 What You’ll See on the Chart
🔷 Full Shift Oscillator (FSO)
The image above highlights the Full Shift Oscillator (FSO).
The FSO is the cornerstone of Kio IQ, delivering mid-term momentum analysis. Using a proprietary formula, it captures momentum on a smooth, balanced scale — responsive enough to avoid lag, yet stable enough to prevent excessive noise or false signals.
The Key Upside Level for the FSO is +20, while the Key Downside Level is -20.
The image above shows the FSO above +20 and below -20, and the corresponding price movement.
FSML above +20 confirms sustained upside momentum — the market is being driven by consistent, broad-based buying pressure, not just a price spike.
FSML below -20 confirms sustained downside momentum — sellers are firmly in control across the market.
We do not chase the first sudden price move. Entries are only considered when the market demonstrates persistence, not impulse.
🔷 Half Shift Oscillator (HSO)
The image above highlights the Half Shift Oscillator (HSO).
The HSO is the FSO’s wingman — faster, more reactive, and designed to catch the earliest signs of strength, weakness, or momentum shifts.
While HSO reacts first, it is not a standalone confirmation of a major momentum change or trade-worthy strength.
Using the same proprietary formula as the FSO but scaled down, the HSO delivers smooth, balanced short-term momentum analysis. It is more responsive than the FSO, serving as the scout that spots potential setups before the main signal confirms.
The Key Upside Level for the FSO is +4, while the Key Downside Level is -4.
🔷 PlayBook Strategy: Shift Sync
Shift Sync is a momentum alignment play that triggers when short-term and mid-term momentum lock into the same direction, signaling strong directional control.
🔹 UpShift Sync – Bullish Alignment
HSO > +4 – Short-term momentum is firmly bullish.
FSO > +20 – Mid-term momentum confirms the bullish bias.
When both thresholds are met, buyers are in control and price is primed for continuation higher.
🔹 DownShift Sync – Bearish Alignment
HSO < -4 – Short-term momentum is firmly bearish.
FSO < -20 – Mid-term momentum confirms the bearish bias.
When both thresholds are met, sellers dominate and price is primed for continuation lower.
Execution:
Look for an entry opportunity in the direction of the alignment when conditions are met.
Avoid choppy conditions where alignment is frequently lost.
Why It Works
Think of the market as a tug-of-war between traders on different timeframes. Short-term traders (captured by the HSO) are quick movers — scalpers, intraday players, and algos hunting immediate edge. Mid-term traders (captured by the FSO) are swing traders, funds, and institutions who move slower but carry more weight.
Most of the time, these groups pull in opposite directions, creating chop and fakeouts. But when they suddenly lean the same way, the rope gets yanked hard in one direction. That’s when momentum has the highest chance to drive price further with minimal resistance.
Shift Sync works because it isolates those rare moments when multiple market “tribes” agree on direction — and when they do, price doesn’t just move, it flies.
Best Market Conditions
Shift Sync works best when the higher timeframe trend (daily, weekly, or monthly) is moving in the same direction as the alignment. This higher timeframe confluence increases follow-through potential and reduces the likelihood of false moves.
The image above shows an example of an UpShift Sync signal where the momentum table shows that the 1D momentum is bullish.
The image above shows bonus confluence, where the 1M and 1W momentum are also bullish.
The image above shows an example of a DownShift Sync signal where the momentum table shows that the 1D momentum is bearish. Bonus confluence also exists, where the 1W and 1M chart are also bearish.
Common Mistakes
Chasing late signals – Avoid entering if the Shift Sync trigger has been active for a long time. Instead, wait for a Shift Sync Pullback to look for opportunities to join in the direction of the trend.
Ignoring higher timeframe bias – Taking Shift Sync setups against the daily, weekly, or monthly trend reduces follow-through potential and increases the risk of a failed move.
🔷 Micro Shift Oscillator (MSO)
The image above highlights the Micro Shift Oscillator (MSO)
The MSO is the finishing touch to the FSO and HSO — the fastest and most reactive of the three. It’s built to spot pullback opportunities when the FSO and HSO are aligned, helping traders join strong price moves at the right time.
The MSO may reveal the earliest signs of a momentum shift, but that’s not its primary role. Its purpose is to identify retracement and pullback opportunities within the overarching trend, allowing traders to join the move while momentum remains intact.
🔷 Playbook Strategy: Shift Sync Pullback
Key Levels:
MSO Upside Trigger: +3
MSO Downside Trigger: -3
🔹 UpShift Pullback
Momentum Confirmation:
FSO > +20 – Mid-term momentum is strongly bullish.
HSO > +4 – Short-term momentum confirms alignment with the FSO.
Pullback Trigger:
MSO ≤ -3 – Signals a short-term retracement within the ongoing bullish trend and marks the earliest re-entry opportunity.
Entry Zone:
The blue arrow on the top chart shows where momentum remains intact while price pulls back into a zone primed for a move higher.
Setup Validity: Both FSO and HSO must remain above their bullish thresholds during the pullback.
Invalid Example:
If either the FSO or HSO drop below their bullish thresholds, momentum alignment breaks. No trade is taken.
🔹 DownShift Pullback
Momentum Confirmation:
FSO < -20 – Mid-term momentum is strongly bearish.
HSO < -4 – Short-term momentum aligns with the FSO, confirming seller dominance.
Pullback Trigger:
MSO ≥ +3 – Indicates a short-term retracement against the bearish trend, pointing to possible short-entry opportunities.
Entry Zone:
The purple arrow on the top chart marks valid pullback conditions — all three oscillators meet their bearish thresholds, and price is positioned to continue lower.
Setup Validity: Both FSO and HSO must remain below their bearish thresholds during the pullback.
Invalid Example:
If either oscillator rises above the bearish threshold, momentum alignment is lost and the MSO signal is ignored.
Why It Works
Even in strong trends, price rarely moves in a straight line. Supply and demand dynamics naturally create retracements as traders take profits, bet on reversals, or hedge positions.
While many momentum traders fear these pullbacks, they’re often the fuel for the next leg of the move — offering a “second chance” to join the trend at a more favorable price.
The Shift Sync Pullback pinpoints moments when both short-term (HSO) and mid-term (FSO) momentum remain firmly aligned, even as price moves temporarily against the trend. This alignment suggests the retracement is a pause, not a reversal.
By entering during a controlled pullback, traders often secure better entries, tighter stops, and stronger follow-through potential when the trend resumes.
Best Market Conditions:
Works best when the higher timeframe (daily, weekly, or monthly) is trending in the same direction as the pullback setup.
Consistent momentum is ideal — avoid erratic, news-driven chop.
Following a recent breakout (Gate Breaker setup) when momentum is still fresh.
Common Mistakes
Ignoring threshold breaks – Entering when either HSO or FSO dips through their momentum threshold often leads to taking trades in weakening trends.
Trading against higher timeframe bias – A pullback against the daily or weekly trend is more likely to fail; use higher timeframe confluence as a filter.
🔷 Macro Shift Oscillator (MaSO)
The chart above shows the MaSO in isolation.
While the MaSO is not part of any active Kio IQ playbook strategies, it delivers the clearest view of the prevailing macro trend.
MaSO > 0 – Macro trend is bullish. Readings above +4 signal extreme bullish conditions.
MaSO < 0 – Macro trend is bearish. Readings below -4 signal extreme bearish conditions.
Use the MaSO for context, not entries — it frames the environment in which all other signals occur
🔷 Shift Gates – Kio IQ Momentum Barriers
The image above shows UpShift Gates.
UpShift Gates mark the highest price reached during periods when the FSO is above +20 — moments when mid-term momentum is firmly bullish and buyers are in control.
UpShift Gates are upside breakout levels — key swing highs formed before a pullback during periods of strong bullish momentum. When price reclaims an UpShift Gate with momentum confirmation, it signals a potential continuation of the uptrend.
The image above shows DownShift Gates.
DownShift Gates Mark The Lowest Price Reached During Periods When The FSO Is Below -20 — Moments When Mid-Term Momentum Is Firmly Bearish And Sellers Are In Control.
DownShift Gates are downside breakout levels — key swing lows formed before an upside pullback during periods of strong bearish momentum. When price reclaims a DownShift Gate with momentum confirmation, it signals a potential continuation of the downtrend.
🔷 Playbook Strategy: Gate Breakers
Core Rule:
Long signal when price decisively closes beyond an UpGate (for longs) or DownGate (for shorts). The breakout must show commitment — no wick-only tests.
🔹 UpGate Breaker (UpGate)
Trigger: Price closes above the UpShift Gate level.
Bonus Confluence: MaSO > 0 at the moment of the break — confirms that the macro trend bias is in favor of the breakout.
Invalidation: Avoid taking the signal if the gate level forms part of a DownShift Rift (bearish divergence) — this signals underlying weakness despite the break.
The chart above shows valid UpGate Breakers.
The chart above shows an invalidated UpGate Breaker setup.
🔹 DownGate Breaker (DownGate)
Trigger: Price closes below the DownShift Gate level.
Bonus Confluence: MaSO < 0 at the moment of the break — confirms that the macro trend bias is in favor of the breakdown.
Invalidation: Avoid taking the trade if the gate level forms part of an UpShift Rift (bullish divergence) — this signals underlying strength despite the break.
The chart above shows a valid DownGate Breaker.
Why It Works
Key swing levels like Shift Gates attract a high concentration of resting orders — stop losses from traders caught on the wrong side and breakout orders from momentum traders waiting for confirmation.
When price decisively clears a gate with a strong close, these orders trigger in quick succession, creating a burst of directional momentum.
Adding the MaSO filter ensures you’re breaking gates with the prevailing macro bias, improving the odds that the move will continue rather than stall.
The divergence-based invalidation rule (Rift filter) prevents entries when underlying momentum is moving in the opposite direction, helping avoid “fake breakouts” that trap traders.
Best Market Conditions:
Works best in markets with clear trend structure and visible Shift Gates (not during chop).
Strongest when higher timeframe (1D, 1W, 1M) momentum aligns with the breakout direction.
MaSO > 0 for bullish breakouts, MaSO < 0 for bearish breakouts
Most reliable after a period of consolidation near the gate, where pressure builds before the break.
Common Mistakes
Trading wick-only tests – A breakout without a decisive candle close beyond the gate often fails.
Ignoring MaSO bias – Taking a break in the opposite macro direction greatly reduces follow-through odds.
Skipping the Rift filter – Entering when the gate forms part of a divergence setup exposes you to higher reversal risk.
Chasing extended moves – If price is already far beyond the gate by the time you see it, risk/reward is poor; wait for the next setup or a retest.
🔷 Shift Rifts - Kio IQ Divergences
This chart shows an UpShift Rift — a bullish divergence where price action and momentum part ways, signaling a potential trend reversal or acceleration.
Setup:
Price Action: Price is marking lower lows, indicating short-term weakness.
FSO Reading: The Full Shift Oscillator (FSO) is marking higher lows over the same period, showing underlying momentum strengthening despite falling prices.
The rift between price and the FSO suggests selling pressure is losing force while buyers quietly regain control.
When confirmed by broader trend alignment in Kio IQ’s multi-timeframe momentum table, the UpShift Rift becomes a setup for a bullish move.
This chart shows a DownShift Rift — a bearish divergence where price action and momentum split, signaling a potential downside reversal.
Setup:
Price Action: Price is marking higher highs, suggesting continued strength on the surface.
FSO Reading: The Full Shift Oscillator (FSO) is marking lower highs over the same period, revealing weakening momentum beneath the price advance.
The rift between price and momentum signals that buying pressure is fading, even as price makes new highs. This disconnect often precedes a momentum shift in favor of sellers.
When aligned with multi-timeframe bearish signals in Kio IQ’s momentum table, the DownShift Rift becomes a strong setup for downside continuation or reversal.
🔷 Playbook Strategy: Rift Reversal
The Rift Reversal is a divergence-based reversal play that signals when momentum is fading and an trend reversal is likely. It’s designed to catch early turning points before the broader market catches on.
Trader’s Note:
This strategy is not intended for beginners — it requires confidence in reading divergence and trusting momentum shifts even when price action still appears weak. Best suited for traders experienced in managing reversals, as entries often occur before the broader market confirms the move.
🔹 UpRift Reversal
Core Setup:
Price Action – Forms a lower low.
Momentum Rift – The FSO forms a higher low, signaling bullish divergence and weakening selling pressure.
Trigger:
A confirmed UpRift Reversal signal is printed when:
Bullish Divergence is detected — price makes a new low, but the oscillator fails to confirm.
Momentum begins turning up from the divergence low (marked on chart as ⇝)
The image above shows a valid UpRift Reversal play.
🔹 DownRift Reversal
Core Setup:
Price Action – Forms a higher high.
Momentum Rift – The FSO forms a lower high, signaling bearish divergence and weakening buying pressure.
Trigger
A confirmed DownRift Reversal signal is printed when:
Bearish Divergence is detected — price makes a new high, but the oscillator fails to confirm.
Momentum begins turning down from the divergence high (marked on chart as ⇝).
Why It Works
Shift Rifts work because momentum often fades before a price reverses.
Price is the final scoreboard — it reflects what has already happened. Momentum, on the other hand, is a leading indicator of pressure. When the FSO begins to move in the opposite direction of price, it signals that the dominant side in the market is losing steam, even if the scoreboard hasn’t flipped yet.
In an UpShift Rift, sellers keep pushing price lower, but each push has less force — buyers are quietly building pressure under the surface.
In a DownShift Rift, buyers keep marking new highs, but they’re spending more effort for less result — sellers are starting to take control.
These disconnects happen because large participants often scale into or out of positions gradually, creating momentum shifts before price reflects it. Shift Rifts capture those turning points early.
Best Market Conditions:
Best in markets that have been trending strongly but are starting to show signs of exhaustion.
Works well after a prolonged move into key support/resistance, where large players may take profits or reverse positions.
Higher win potential when the Rift aligns with higher timeframe momentum bias in Kio IQ’s multi-timeframe table.
Common Mistakes
Forcing Rifts in choppy markets – In sideways chop, small oscillations can look like divergences but lack conviction.
Ignoring multi-timeframe bias – Trading an UpShift Rift when higher timeframes are strongly bearish (or vice versa) reduces follow-through odds.
Entering too early – Divergences can extend before reversing; wait for momentum to confirm a turn (⇝) before making a trading decision.
Confusing normal pullbacks with Rifts – Not every dip in momentum is a divergence; the Rift requires a clear and opposing trend between price and FSO.
🔷 Shift Count – Momentum Stage Tracker
Purpose:
Shift Count measures how far a bullish or bearish push has progressed, from its first spark to potential exhaustion.
It tracks momentum in defined steps so traders can instantly gauge whether a move is just starting, picking up steam, fully extended, or at risk of reversing.
How It Works
Bullish Momentum:
Start (1–2) → New momentum emerging, early entry window.
Acceleration (3–4) → Momentum in full swing, best for holding or adding to a position.
Extreme Bullish Momentum / Final Stages (5) → Watch for signs of reversal or take partial profits.
Exhaust – Can only occur after 5 is reached, signaling that the rally may be losing steam.
Bearish Momentum:
Start (-1 to -2) → New selling pressure emerging.
Acceleration (-3 to -4) → Bear trend accelerating.
Extreme Bearish Momentum / Final Stages (-5) → Watch for reversal or scale out.
Exhaust – Can only occur after -5 is reached, signaling that the sell-off may be running out of force.
The chart above shows a full 5-UpShift count.
The chart above shows a full 5-DownShift count.
Why It’s Useful
Markets often move in momentum “steps” before reversing or taking a breather.
Shift Count makes these steps visible, helping traders:
Spot the early stages of a potential move.
Identify when a move is picking up steam.
Identify when a move is mature and vulnerable to reversal.
Combine with other Kio IQ strategies for better-timed entries and exits.
Why This Works
It’s visually obvious where you are in the momentum cycle without overthinking.
You can build rules like:
Only enter in Start phase when higher timeframe agrees.
Manage positions aggressively once in Acceleration phase.
Be ready to exit or fade in Exhaust phase.
Best Market Conditions
Trending markets where pullbacks are shallow.
Works best when combined with Shift Sync Pullback or Gate Breaker triggers to confirm timing.
Higher timeframe direction confluence.
Common Mistakes
Treating Exhaust as always a reversal — sometimes strong markets push past 5/-5 multiple times.
Ignoring higher timeframe bias — a “Start” on a 1-minute chart against a strong daily trend is much riskier.
🔷 Playbook Strategy: Exhaust Flip
Core idea: When Shift Count reaches 5 (or -5) and then prints Exhaust, momentum has likely climaxed, whether temporarily or leading to a full reversal. We take the first qualified signal against the prior move.
Trader’s Note:
This strategy is not intended for beginners — it requires confidence in trusting momentum shifts even when price action still appears strong. Best suited for traders experienced in managing reversals, as entries often occur before the broader market confirms the move.
🔹 UpExhaust Flip (fade a bullish run)
Setup:
Shift Count hits 5, then an Exhaust print occurs.
Invalidation
The local high is broken to the upside.
The chart above explains the UpExhaust Flip strategy in greater detail.
🔹 DownExhaust Flip (fade a bearish run)
Setup:
Shift Count hits -5, then an Exhaust print occurs.
Invalidation
The local low is broken to the downside.
The chart above explains the DownExhaust Flip strategy in greater detail.
Bonus Confluence (optional, not required)
Rift assist: An UpShift Rift (for longs) or DownShift Rift (for shorts) near Exhaust strengthens the flip.
MaSO context: Neutral or opposite-leaning MaSO helps. Avoid flips straight against a strong MaSO bias unless you have a structure break.
Why It Works
Exhaust marks climax behavior: the prior side has pushed hard, then failed to extend after meeting significant pushback. Liquidity gets thin at the edges; aggressive profit-taking meets early contrarians. A small confirmation (micro structure break or HSO turn) is often enough to flip the tape for a snapback.
Best Market Conditions
After extended, one-sided runs (multiple Shift Count steps without meaningful pullbacks).
Near Shift Gates or obvious swing extremes where trapped orders cluster.
When higher-timeframe momentum is neutral or softening (you’re fading the last thrust of a decisive move, not a fresh trend).
Common Mistakes
Fading too early: Taking the trade at 5 without waiting for the Exhaust.
Fading freight trains: Fighting a fresh Shift Sync in the same direction right after Exhaust (often just a pause).
No structure reference: Entering without a clear micro swing to anchor risk.
🔷 MTF Shift Table
The MTF Shift Table table provides a compact, multi-timeframe view of market momentum shifts. Each cell represents the current shift count within a given timeframe, while the classification label indicates whether momentum is strong, weak, or normal.
The chart above further outlines the MTF Shift Table.
Why It Works
Markets rarely move in a perfectly linear fashion — momentum develops, stalls, and transitions at different speeds across different timeframes. This table allows you to:
See momentum alignment at a glance – If multiple higher and lower timeframes show a sustained shift count in the same direction, the move has greater structural support.
Spot divergences early – A shorter timeframe reversing against a longer-term sustained count can warn of potential pullbacks or trend exhaustion before price confirms.
Identify “momentum stacking” opportunities – When shift counts escalate across timeframes in sequence, it often signals a stronger and more durable move.
Avoid false enthusiasm – A single timeframe spike without agreement from other periods may be noise rather than genuine momentum.
The Trend Score provides a concise, at-a-glance evaluation of an asset’s directional strength across multiple timeframes. It distills complex momentum and Shift data into a single, easy-to-read metric, allowing traders to quickly determine whether the prevailing conditions favor bullish or bearish continuation. The Trend Scale scales from -100 to 100.
How to Use It in Practice
Trend Confirmation – Confirm that your intended trade direction is backed by multiple timeframes maintaining consistent momentum.
Risk Timing – Reduce position size or take partial profits when lower timeframes begin shifting against the dominant momentum classification.
Multi-timeframe Confluence – Combine with other system signals (e.g., FSO, HSO) for higher-probability entries.
This table effectively turns a complex multi-timeframe read into a single, glanceable heatmap of momentum structure, enabling quicker and more confident decision-making.
The MTF Shift Table is the confluence backbone of every playbook strategy for Kio IQ.
🔷 Momentum Meter
The Momentum Meter is a composite gauge built from three of Kio IQ’s core momentum engines:
HSO – Short-term momentum scout
FSO – Mid-term momentum backbone
MaSO – Macro trend context
By combining these three readings, the meter provides the most strict and lagging momentum classification in Kio IQ.
It only flips direction when a composite score of all three oscillators reach defined thresholds, filtering out short-lived counter-moves and false starts.
Why It Works
Many momentum tools flip too quickly — reacting to short-lived spikes that don’t represent real directional commitment. The Momentum Meter avoids this by requiring alignment across short, mid, and macro momentum engines before it shifts bias.
This triple-confirmation rule filters out noise, catching only those moments when traders of all speeds — scalpers, swing traders, and long-term participants — are leaning in the same direction. When that happens, price movement tends to be more sustained and less prone to immediate reversal.
In other words, the Momentum Meter doesn’t just tell you “momentum looks good” — it tells you momentum looks good to everyone who matters, across all horizons.
How It Works
Blue = All three engines align bullish.
Pink = All three engines align bearish.
The meter ignores smaller pullbacks or temporary oscillations that might flip the faster indicators — it waits for total alignment before changing state.
Because of this strict confirmation requirement, the Momentum Meter reacts slower but delivers higher-conviction shifts.
How to Interpret Readings
Blue (Bullish Alignment):
Sustained buying pressure across short, mid, and macro views. Often marks the “full confirmation” stage of a move.
Pink (Bearish Alignment):
Sustained selling pressure across all views. Confirms sellers are in control.
Practical Uses
Trend Followers – Use as a “stay-in” confirmation once a position is already open.
Swing Traders – Great for filtering out low-conviction setups; if the Momentum Meter disagrees with your intended direction, conditions aren’t fully aligned.
Confluence and Direction Filter – The Momentum Meter can be used as a form of confluence i.e. blue = longs only, pink = shorts only.
Limitations
Will always turn after the faster oscillators (HSO/MSO). This is intentional.
Works best in trending markets — in choppy conditions it may lag shifts significantly.
Should be used as a bias filter, not a standalone entry signal.
🔷 Trend Strength Meter
The Trend Strength Meter is a compact visual gauge that scores the current trend’s strength on a scale from -5 to +5:
+5 = Extremely strong bullish trend
0 = Neutral, no clear trend
-5 = Extremely strong bearish trend
This is an optional tool in Kio IQ — designed for quick reference rather than as a primary trading trigger.
Why it works
Single-indicator trend reads can be misleading — they might look strong on one metric while quietly weakening on another. The Trend Strength Meter solves this by blending multiple inputs (momentum alignment, structure persistence, and multi-timeframe data) into one composite score.
This matters because trend health isn’t just about direction — it’s about persistence. A +5 or -5 score means the market is not only trending but holding that trend with structural support across multiple timeframes.
By tracking both direction and staying power, the Trend Strength Meter flags when a move is at risk of fading before price action fully confirms it — giving you a head start on adjusting your position or taking profits.
How It Works
The Trend Strength Meter evaluates multiple market inputs — including momentum alignment, price structure, and persistence — to assign a numeric value representing how firmly the current move is holding.
The scoring logic:
Positive values indicate bullish conditions.
Negative values indicate bearish conditions.
Higher magnitude (closer to ±5) = stronger conviction in that direction.
Values near zero suggest the market is in a transition or range.
How to Interpret Readings
+4 to +5 (Strong Up) – Trend is well-established, often with multi-timeframe agreement.
+1 to +3 (Up) – Bullish bias present, but not at maximum conviction.
0 (Neutral) – No dominant trend; could be consolidation or pre-shift phase.
-1 to -3 (Down) – Bearish bias present but moderate.
-4 to -5 (Strong Down) – Trend is firmly bearish, with consistent downside momentum.
Why It Works
A single timeframe or momentum reading can give a false sense of trend health.
The Trend Strength Meter aggregates multiple layers of market data into one simplified score, making it easy to see whether a move has the underlying support to continue — or whether it’s more likely to stall.
Because the score considers both direction and persistence, it can flag when a move is losing strength even before price structure fully shifts.
🔷 Kio IQ – Supplemental Playbook Strategies
These phases are part of the Kio IQ Playbook—situational tools that can help you anticipate potential momentum changes.
While they can be useful for planning and tactical adjustments, they are not primary trade triggers and should be treated as early, lower-conviction cues.
🔹 1. Scouting Phase (Light Early Cue)
Purpose: Provide the earliest possible hint that momentum may be shifting.
Upshift Trigger: FSO crosses above the 0 line.
Downshift Trigger: FSO crosses below the 0 line.
Why It Works
The 0 line in the Full Shift Oscillator (FSO) acts as a neutral momentum boundary.
When the FSO moves above 0, it suggests that medium-term momentum has shifted to bullish territory.
When it moves below 0, it suggests that medium-term momentum has shifted to bearish territory.
This crossover is often the first measurable sign of a momentum reversal or acceleration, well before slower indicators confirm it.
Think of it as "momentum poking its head above water"—you’re spotting the change before it becomes obvious on price alone.
Best Use
Works best when confirmed later by Lookout Phase or other primary Kio IQ signals.
Ideal for scouting in anticipation of potential opportunities.
Helpful when monitoring multiple assets and you want a quick filter for shifts worth watching.
Can act as a trade trigger when the MTF Shift Table shows confluence (i.e., UpShift Scouting Signal + Bullish MTF Table + High Trend Strength Score).
Common Mistakes
Acting on Scouting Phase signals against the MTF Shift Table as a stand-alone trade trigger. Without higher timeframe alignment or additional confirmation, many Scouting Phase crossovers can fade quickly or reverse, leading to premature entries.
Ignoring market context
A bullish Scouting Phase in a strong downtrend can easily fail.
Always check higher timeframe trend alignment.
Overreacting to noise: On lower timeframes, small fluctuations can create false scouting signals.
Best Practices
Filter with trend: Only act on Scouting Phases that align with the dominant higher timeframe trend.
Watch volatility: In low-volatility conditions, false scouting triggers are more likely.
🔹 2. Lookout Phase (Early Momentum Alert)
Purpose:
The Lookout Phase signals an early alert that momentum is potentially strengthening in a given direction. It’s more meaningful than the Scouting Phase, but still considered a preliminary cue.
Triggers:
Upshift: FSO crosses above the HSO.
Downshift: FSO crosses below the HSO.
Why It Works:
The Lookout Phase is designed to identify moments when mid-term momentum (FSO) overtakes short-term momentum (HSO). Since the FSO is smoother and reacts more gradually, its crossover of the faster-reacting HSO can indicate a shift from short-lived fluctuations to a more sustained directional move.
This makes it a valuable early read on momentum transitions—especially when supported by higher-timeframe context.
Best Practices:
Always check the MTF Shift Table for higher-timeframe alignment before acting on a Lookout Phase signal.
Look for confluence with the Momentum Meter
Treat Lookout Phase entries as probing positions—small, exploratory trades that can be scaled into if follow-through develops.
Common Mistakes:
Treating Lookout Phase signals as a definitive trade trigger without context
Entering solely on a Lookout Phase crossover, without considering the MTF Shift Table or broader market structure, can result in chasing short-lived momentum bursts that fail to follow through.
Ignoring prevailing higher-timeframe momentum
Trading a Lookout Phase signal that is counter to the dominant trend or higher-timeframe bias increases the risk of whipsaws and false moves.
🔶 Summary
Kio IQ is an all-in-one trading indicator that combines momentum, trend strength, multi-timeframe analysis, divergences, pullbacks, and exhaustion alerts into a clear, structured view. It helps traders cut through market noise by showing whether a move is strong, weak, a trap, or simply part of a larger trend. With tools like the Full Shift Oscillator, Multi-Timeframe Shift Table, Shift Gates, and Rift Divergences, Kio IQ simplifies complex market behavior into easy-to-read signals. It’s designed to help traders spot early shifts, align with momentum, and recognize when trends are building or losing steam—all in one place.
Skrip berbayar
Wickless Tap Signals Wickless Tap Signals — TradingView Indicator (v6)
A precision signal-only tool that marks BUY/SELL events when price “retests” the base of a very strong impulse candle (no wick on the retest side) in the direction of trend.
What it does (in plain English)
Finds powerful impulse candles:
Bull case: a green candle with no lower wick (its open ≈ low).
Bear case: a red candle with no upper wick (its open ≈ high).
Confirms trend with an EMA filter:
Only looks for bullish bases while price is above the EMA.
Only looks for bearish bases while price is below the EMA.
Waits for the retest (“tap”):
Later, if price revisits the base of that wickless candle
Bullish: taps the candle’s low/open → BUY signal
Bearish: taps the candle’s high/open → SELL signal
Optional level “consumption” so each base can trigger one signal, not many.
The idea: a wickless impulse often marks strong initiative order flow. The first retest of that base frequently acts as a springboard (bull) or ceiling (bear).
Exact rules (formal)
Let tick = syminfo.mintick, tol = tapTicks * tick.
Trend filter
inUp = close > EMA(lenEMA)
inDn = close < EMA(lenEMA)
Wickless impulse candles (confirmed on bar close)
Bullish wickless: close > open and abs(low - open) ≤ tol
Bearish wickless: close < open and abs(high - open) ≤ tol
When such a candle closes with trend alignment:
Store bullTapLevel = low (for bull case) and its bar index.
Store bearTapLevel = high (for bear case) and its bar index.
Signals (must happen on a later bar than the origin)
BUY: low ≤ bullTapLevel + tol and inUp and bar_index > bullBarIdx
SELL: high ≥ bearTapLevel - tol and inDn and bar_index > bearBarIdx
One-shot option
If enabled, once a signal fires, the stored level is cleared so it won’t trigger again.
Inputs (Settings)
Trend EMA Length (lenEMA): Default 200.
Use 50–100 for intraday, 200 for swing/position.
Tap Tolerance (ticks) (tapTicks): Default 1.
Helps account for tiny feed discrepancies. Set 0 for strict equality.
One Signal per Level (oneShot): Default ON.
If OFF, multiple taps can create multiple signals.
Plot Tap Levels (plotLevels): Draws horizontal lines at active bases.
Show Pattern Labels (showLabels): Marks the origin wickless candles.
Plots & Visuals
EMA trend line for context.
Tap Levels:
Green line at bullish base (origin candle’s low/open).
Red line at bearish base (origin candle’s high/open).
Signals:
BUY: triangle-up below the bar on the tap.
SELL: triangle-down above the bar on the tap.
Labels (optional):
Marks the original wickless impulse candle that created each level.
Alerts
Two alert conditions are built in:
“BUY Signal” — fires when a bullish tap occurs.
“SELL Signal” — fires when a bearish tap occurs.
How to set:
Add the indicator to your chart.
Click Alerts (⏰) → Condition = this indicator.
Choose BUY Signal or SELL Signal.
Set your alert frequency and delivery method.
Recommended usage
Timeframes: Works on any; start with 5–15m intraday, or 1H–1D for swing.
Markets: Equities, futures, FX, crypto. For thin/illiquid assets, consider a slightly larger Tap Tolerance.
Confluence ideas (optional, but helpful):
Higher-timeframe trend agreeing with your chart timeframe.
Volume surge on the origin wickless candle.
S/R, order blocks, or SMC structures near the tap level.
Avoid major news moments when slippage is high.
No-repaint behavior
Origin patterns are detected only on bar close (barstate.isconfirmed), so bases are created with confirmed data.
Signals come after the origin bar, on subsequent taps.
There is no lookahead; lines and shapes reflect information known at the time.
(As with all real-time indicators, an intrabar tap can trigger an alert during the live bar; the signal then remains if that condition held at bar close.)
Known limitations & design choices
Single active level per side: The script tracks only the most recent bullish base and most recent bearish base.
Want a queue of multiple simultaneous bases? That’s possible with arrays; ask and we’ll extend it.
Heikin Ashi / non-standard candles: Wick definitions change; for consistent behavior use regular OHLC candles.
Gaps: On large gaps, taps can occur instantly at the open. Consider one-shot ON to avoid rapid repeats.
This is an indicator, not a strategy: It does not place trades or compute PnL. For backtesting, we can convert it into a strategy with SL/TP logic (ATR or structure-based).
Practical tips
Tap Tolerance:
If you miss obvious taps by a hair, increase to 1–2 ticks.
For FX/crypto with tiny ticks, even 0 or 1 is often enough.
EMA length:
Shorten for faster signals; lengthen for cleaner trend selection.
Risk management (manual suggestion):
For BUY signals, consider a stop slightly below the tap level (or ATR-based).
For SELL signals, consider a stop slightly above the tap level.
Scale out or trail using structure or ATR.
Quick checklist
✅ Price above EMA → watch for a green no-lower-wick candle → store its low → BUY on tap.
✅ Price below EMA → watch for a red no-upper-wick candle → store its high → SELL on tap.
✅ Use Tap Tolerance to avoid missing precise touches by one tick.
✅ Consider One Signal per Level to keep trades uncluttered.
FAQ
Q: Why did I not get a signal even though price touched the level?
A: Check Tap Tolerance (maybe too strict), trend alignment at the tap bar, and that the tap happened after the origin candle. Also confirm you’re on regular candles.
Q: Can I see multiple bases at once?
A: This version tracks the latest bull and bear bases. We can extend to arrays to keep N recent bases per side.
Q: Will it repaint?
A: No. Bases form on confirmed closes, and signals only on later bars.
Q: Can I backtest it?
A: This is a study. Ask for the strategy variant and we’ll add entries, exits, SL/TP, and stats.
📱 EMA Stability Mobile + Pulse BG + Alerts (edegrano)User Manual: 📱 EMA Stability Mobile + Pulse BG + Alerts
Overview
This indicator monitors the stability of the market trend by analyzing the relative positions and gaps between the 50, 100, and 200 EMAs (Exponential Moving Averages) on a user-defined higher timeframe. It detects when the EMAs align bullishly or bearishly with a minimum gap tolerance and provides visual signals, background pulses, and alerts when such stable conditions start.
Key Features
Uses 3 EMAs (50, 100, 200) from a selectable timeframe.
Checks if EMAs are aligned in a stable bullish or bearish order with configurable minimum percentage gaps.
Confirms that price is not touching the EMA50 (to avoid instability).
Displays arrow, text status ("Bull", "Bear", or "Unst" for unstable).
Shows a strength score representing the average EMA gap relative to tolerance.
Pulses the chart background green or red when stability starts.
Sends alerts when a new bullish or bearish stability condition begins.
Displays a table summary at the top center of the chart.
Inputs
Parameter Description Default Value
EMA TF Timeframe to fetch EMA values from. "15" (15 min)
Min Gap (%) Minimum % gap required between EMAs for stability. 0.1%
Background Opacity Opacity level (0-100) for the pulse background color. 85
How It Works
The indicator fetches EMA50, EMA100, and EMA200 values from the chosen timeframe.
It calculates the percentage gap between EMA50 & EMA100 and EMA100 & EMA200.
It checks if:
For bullish stability: EMA50 > EMA100 by at least the tolerance and EMA100 > EMA200 by at least tolerance, AND current candle’s low is above EMA50.
For bearish stability: EMA50 < EMA100 by at least the tolerance and EMA100 < EMA200 by at least tolerance, AND current candle’s high is below EMA50.
When a stable bullish or bearish condition starts (i.e., it was not stable the previous bar), it triggers a pulse on the background and sends an alert.
The strength score reflects how strong the EMA gaps are relative to the minimum gap set.
A table displays key info: stability arrow, status, strength percentage, and gap percentages.
Visuals on Chart
Arrow:
▲ = Bullish Stability
▼ = Bearish Stability
• = Unstable (no stability detected)
Status Text: "Bull", "Bear", or "Unst"
Background Pulse: Green for bullish stability start, red for bearish stability start (fades based on opacity setting).
Table at top center shows:
EMA stability arrow and status
Strength score (%)
Percentage gaps between EMAs 50-100 and 100-200
Alerts
The indicator sends alerts when a new stable bullish or bearish trend begins.
Alert messages include:
📈 Bullish Stability detected on ( )
📉 Bearish Stability detected on ( )
Alerts are triggered only once per bar close on the condition's start.
Recommended Usage Tips
Adjust EMA TF to your preferred higher timeframe for trend confirmation.
Set Min Gap (%) depending on how strict you want the gap between EMAs for stability (smaller gap = more sensitive).
Use Background Opacity to make pulses subtle or prominent according to your preference.
Combine this indicator with price action or other tools for entry/exit timing.
Use alerts to be notified instantly when stable trends form.
Nifty50 Swing Trading Super Indicator# 🚀 Nifty50 Swing Trading Super Indicator - Complete Guide
**Created by:** Gaurav
**Date:** August 8, 2025
**Version:** 1.0 - Optimized for Indian Markets
---
## 📋 Table of Contents
1. (#quick-start-guide)
2. (#indicator-overview)
3. (#installation-instructions)
4. (#parameter-settings)
5. (#signal-interpretation)
6. (#trading-strategy)
7. (#risk-management)
8. (#optimization-tips)
9. (#troubleshooting)
---
## 🎯 Quick Start Guide
### What You Get
✅ **2 Complete Pine Script Indicators:**
- `swing_trading_super_indicator.pine` - Universal version for all markets
- `nifty_optimized_super_indicator.pine` - Specifically optimized for Nifty50 & Indian stocks
✅ **Key Features:**
- Multi-component signal confirmation system
- Optimized for daily and 3-hour timeframes
- Built-in risk management with dynamic stops and targets
- Real-time signal strength monitoring
- Gap analysis for Indian market characteristics
### Immediate Setup
1. Copy the Pine Script code from `nifty_optimized_super_indicator.pine`
2. Paste into TradingView Pine Editor
3. Add to chart on daily or 3-hour timeframe
4. Look for 🚀BUY and 🔻SELL signals
5. Use the information table for signal confirmation
---
## 🔍 Indicator Overview
### Core Components Integration
**🎯 Range Filter (35% Weight)**
- Primary trend identification using adaptive volatility filtering
- Optimized sampling period: 21 bars for Indian market volatility
- Enhanced range multiplier: 3.0 to handle market gaps
- Provides trend direction and strength measurement
**⚡ PMAX (30% Weight)**
- Volatility-adjusted trend confirmation using ATR-based calculations
- Dynamic multiplier adjustment based on market volatility
- 14-period ATR with 2.5 multiplier for swing trading sensitivity
- Offers trailing stop functionality
**🏗️ Support/Resistance (20% Weight)**
- Dynamic level identification using pivot point analysis
- Tighter channel width (3%) for precise Indian market levels
- Enhanced strength calculation with historical interaction weighting
- Provides entry/exit timing and breakout signals
**📊 EMA Alignment (15% Weight)**
- Multi-timeframe moving average confirmation
- Key EMAs: 9, 21, 50, 200 (popular in Indian markets)
- Hierarchical alignment scoring for trend strength
- Additional trend validation layer
### Advanced Features
**🌅 Gap Analysis**
- Automatic detection of significant price gaps (>2%)
- Gap strength measurement and impact on signals
- Specific optimization for Indian market overnight gaps
- Visual gap markers on chart
**⏰ Multi-Timeframe Integration**
- Higher timeframe bias from daily/weekly data
- Configurable daily bias weight (default 70%)
- 3-hour confirmation for precise entry timing
- Prevents counter-trend trades against major timeframe
**🛡️ Risk Management**
- Dynamic stop-loss calculation using multiple methods
- Automatic profit target identification
- Position sizing guidance based on signal strength
- Anti-whipsaw logic to prevent false signals
---
## 📥 Installation Instructions
### Step 1: Access TradingView
1. Open TradingView.com
2. Navigate to Pine Editor (bottom panel)
3. Create a new indicator
### Step 2: Copy the Code
**For Nifty50 & Indian Stocks (Recommended):**
```pinescript
// Copy entire content from nifty_optimized_super_indicator.pine
```
**For Universal Use:**
```pinescript
// Copy entire content from swing_trading_super_indicator.pine
```
### Step 3: Configure and Apply
1. Click "Add to Chart"
2. Select daily or 3-hour timeframe
3. Adjust parameters if needed (defaults are optimized)
4. Enable alerts for signal notifications
### Step 4: Verify Installation
- Check that all components are visible
- Confirm information table appears in top-right
- Test with known trending stocks for signal validation
---
## ⚙️ Parameter Settings
### 🎯 Range Filter Settings
```
Sampling Period: 21 (optimized for Indian market volatility)
Range Multiplier: 3.0 (handles overnight gaps effectively)
Source: Close (most reliable for swing trading)
```
### ⚡ PMAX Settings
```
ATR Length: 14 (standard for daily/3H timeframes)
ATR Multiplier: 2.5 (balanced for swing trading sensitivity)
Moving Average Type: EMA (responsive to price changes)
MA Length: 14 (matches ATR period for consistency)
```
### 🏗️ Support/Resistance Settings
```
Pivot Period: 8 (shorter for Indian market dynamics)
Channel Width: 3% (tighter for precise levels)
Minimum Strength: 3 (higher quality levels only)
Maximum Levels: 4 (focus on strongest levels)
Lookback Period: 150 (sufficient historical data)
```
### 🚀 Super Indicator Settings
```
Signal Sensitivity: 0.65 (balanced for swing trading)
Trend Strength Requirement: 0.75 (high quality signals)
Gap Threshold: 2.0% (significant gap detection)
Daily Bias Weight: 0.7 (strong higher timeframe influence)
```
### 🎨 Display Options
```
Show Range Filter: ✅ (trend visualization)
Show PMAX: ✅ (trailing stops)
Show S/R Levels: ✅ (key price levels)
Show Key EMAs: ✅ (trend confirmation)
Show Signals: ✅ (buy/sell alerts)
Show Trend Background: ✅ (visual trend state)
Show Gap Markers: ✅ (gap identification)
```
---
## 📊 Signal Interpretation
### 🚀 BUY Signals
**Requirements for BUY Signal:**
- Price above Range Filter with upward trend
- PMAX showing bullish direction (MA > PMAX line)
- Support/resistance breakout or favorable positioning
- EMA alignment supporting upward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
**Signal Strength Indicators:**
- **90-100%:** Extremely strong - Maximum position size
- **80-89%:** Very strong - Large position size
- **75-79%:** Strong - Standard position size
- **65-74%:** Moderate - Reduced position size
- **<65%:** Weak - Wait for better opportunity
### 🔻 SELL Signals
**Requirements for SELL Signal:**
- Price below Range Filter with downward trend
- PMAX showing bearish direction (MA < PMAX line)
- Resistance breakdown or unfavorable positioning
- EMA alignment supporting downward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
### ⚖️ NEUTRAL Signals
**Characteristics:**
- Conflicting signals between components
- Low overall signal strength (<65%)
- Range-bound market conditions
- Wait for clearer directional bias
### 📈 Information Table Guide
**Component Status:**
- **BULL/BEAR:** Current signal direction
- **Strength %:** Component contribution strength
- **Status:** Additional context (STRONG/WEAK/ACTIVE/etc.)
**Overall Signal:**
- **🚀 STRONG BUY:** All systems aligned bullish
- **🔻 STRONG SELL:** All systems aligned bearish
- **⚖️ NEUTRAL:** Mixed or weak signals
---
## 💼 Trading Strategy
### Daily Timeframe Strategy
**Setup:**
1. Apply indicator to daily chart of Nifty50 or Indian stocks
2. Wait for 🚀BUY or 🔻SELL signal with >75% strength
3. Confirm higher timeframe bias alignment
4. Check for significant support/resistance levels
**Entry:**
- Enter on signal bar close or next bar open
- Use 3-hour chart for precise entry timing
- Avoid entries during major news events
- Consider gap analysis for overnight positions
**Position Sizing:**
- **>90% Strength:** 3-4% of portfolio
- **80-89% Strength:** 2-3% of portfolio
- **75-79% Strength:** 1-2% of portfolio
- **<75% Strength:** Avoid or minimal size
### 3-Hour Timeframe Strategy
**Setup:**
1. Confirm daily timeframe bias first
2. Apply indicator to 3-hour chart
3. Look for signals aligned with daily trend
4. Use for entry/exit timing optimization
**Entry Refinement:**
- Wait for 3H signal confirmation
- Enter on pullbacks to key levels
- Use tighter stops for better risk/reward
- Monitor intraday support/resistance
### Risk Management Rules
**Stop Loss Placement:**
1. **Primary:** Use indicator's dynamic stop level
2. **Secondary:** Below/above nearest support/resistance
3. **Maximum:** 2-3% of portfolio per trade
4. **Trailing:** Move stops with PMAX line
**Profit Taking:**
1. **Target 1:** First resistance/support level (50% position)
2. **Target 2:** Second resistance/support level (30% position)
3. **Runner:** Trail remaining 20% with PMAX
**Position Management:**
- Review positions at daily close
- Adjust stops based on new signals
- Exit if trend changes to opposite direction
- Reduce size during high volatility periods
---
## 🎯 Optimization Tips
### For Nifty50 Trading
- Use daily timeframe for primary signals
- Monitor sector rotation impact
- Consider index futures for better liquidity
- Watch for RBI policy and global cues impact
### For Individual Stocks
- Verify stock follows Nifty correlation
- Check sector-specific news and events
- Ensure adequate liquidity for position size
- Monitor earnings calendar for volatility
### Market Condition Adaptations
**Trending Markets:**
- Increase position sizes for strong signals
- Use wider stops to avoid whipsaws
- Focus on trend continuation signals
- Reduce counter-trend trading
**Range-Bound Markets:**
- Reduce position sizes
- Use tighter stops and quicker profits
- Focus on support/resistance bounces
- Increase signal strength requirements
**High Volatility Periods:**
- Reduce overall exposure
- Use smaller position sizes
- Increase stop-loss distances
- Wait for clearer signals
### Performance Monitoring
- Track win rate and average profit/loss
- Monitor signal quality over time
- Adjust parameters based on market changes
- Keep trading journal for pattern recognition
---
## 🔧 Troubleshooting
### Common Issues
**Q: Signals appear too frequently**
A: Increase "Trend Strength Requirement" to 0.8-0.9
**Q: Missing obvious trends**
A: Decrease "Signal Sensitivity" to 0.5-0.6
**Q: Too many false signals**
A: Enable "3H Confirmation" and increase strength requirements
**Q: Indicator not loading**
A: Check Pine Script version compatibility (requires v5)
### Parameter Adjustments
**For More Sensitive Signals:**
- Decrease Signal Sensitivity to 0.5-0.6
- Decrease Trend Strength Requirement to 0.6-0.7
- Increase Range Filter multiplier to 3.5-4.0
**For More Conservative Signals:**
- Increase Signal Sensitivity to 0.7-0.8
- Increase Trend Strength Requirement to 0.8-0.9
- Enable all confirmation features
### Performance Issues
- Reduce lookback periods if chart loads slowly
- Disable some visual elements for better performance
- Use on liquid stocks/indices for best results
---
## 📞 Support & Updates
This super indicator combines the best of Range Filter, PMAX, and Support/Resistance analysis specifically optimized for Indian market swing trading. The multi-component approach significantly improves signal quality while the built-in risk management features help protect capital.
**Remember:** No indicator is 100% accurate. Always combine with proper risk management, market analysis, and your trading experience for best results.
**Happy Trading! 🚀**
Mig Trade Model - Kill Zones
Key features:
Liquidity Hunt Detection: Spots aggressive moves that "hunt" stops beyond recent swing highs/lows.
Consolidation Filter: Requires 1-3 small-range candles after a hunt before confirming with a strong candle.
Bias Application: Uses daily open/close to auto-detect bias or allows manual override.
Kill Zone Restriction: Limits signals to London (default: 7-10 AM UTC) and NY (default: 12-3 PM UTC) sessions for better relevance in active markets.
This strategy is inspired by smart money concepts (SMC) and ICT (Inner Circle Trader) methodologies, aiming to capture venom-like "stings" in price action where liquidity is grabbed before reversals.
How It Works
ATR Calculation: Uses a user-defined ATR length (default: 14) to measure volatility, which scales candle body and range thresholds.
Bias Determination:
Auto: Compares daily close to open (bullish if close > open).
Manual: User selects "Bullish" or "Bearish."
Strong Candles:
Bullish: Green candle with body > 2x ATR (configurable).
Bearish: Red candle with body > 2x ATR.
Small Range Candles:
Candles where high-low < 0.5x ATR (configurable).
Liquidity Hunt:
Bullish Hunt: Strong bearish candle making a new low below the past swing low (default: 10 bars).
Bearish Hunt: Strong bullish candle making a new high above the past swing high.
Signal Generation:
After a hunt, counts 1-3 small-range candles.
Confirms with a strong candle in the opposite direction (e.g., strong bullish after bearish hunt).
Resets if >3 small candles or an opposing strong candle appears.
Kill Zone Filter:
Checks if the current bar's time (in UTC) falls within London or NY Kill Zones.
Only allows final "Buy" (bullish entry) or "Sell" (bearish entry) if bias matches and in Kill Zone.
Plots:
Yellow circle (below): Bullish liquidity hunt.
Orange circle (above): Bearish liquidity hunt.
Blue diamond (below): Raw bullish signal.
Purple diamond (above): Raw bearish signal.
Green triangle up ("Buy"): Filtered bullish entry.
Red triangle down ("Sell"): Filtered bearish entry.
Inputs
Bias: "Auto" (default), "Bullish", or "Bearish" – Controls signal direction based on daily trend.
ATR Length: 14 (default) – Period for ATR calculation.
Swing Length for Liquidity Hunt: 10 (default) – Bars to look back for swing highs/lows.
Strong Candle Body Multiplier (x ATR): 2.0 (default) – Threshold for strong candle bodies.
Small Range Multiplier (x ATR): 0.5 (default) – Threshold for small-range candles.
London Kill Zone Start/End Hour (UTC): 7/10 (default) – Customize London session hours.
NY Kill Zone Start/End Hour (UTC): 12/15 (default) – Customize New York session hours.
Usage Tips
Timeframe: Best on lower timeframes (e.g., 5-15 min) for intraday trading, especially forex pairs like EURUSD or GBPUSD.
Timezone Adjustment: Inputs are in UTC. If your chart is in a different timezone (e.g., EST = UTC-5), adjust hours accordingly (e.g., London: 2-5 AM EST → 7-10 UTC).
Risk Management: Use with stop-loss (e.g., beyond the hunt low/high) and take-profit based on ATR multiples. Not financial advice—backtest thoroughly.
Customization: Tweak multipliers for different assets; higher for volatile cryptos, lower for stocks.
Limitations: Relies on historical data; may generate false signals in ranging markets. Combine with other indicators like volume or support/resistance.
This indicator is for educational purposes. Always use discretion and proper risk management in live trading. If you find it useful, feel free to share feedback or suggestions!
LTPI Global Liquidity | JeffreyTimmermansLong-Term Probability Indicator (LTPI)
The "Long-Term Probability Indicator (LTPI)" on a generic liquidity ticker is a custom-built analytical tool designed to evaluate market conditions over a long-term horizon, with a strong focus on global liquidity trends. By combining six carefully selected input signals into a single probability score, this indicator helps traders and analysts identify prevailing long-term market states: Bullish, Bearish, or Neutral.
Where short-term systems/timeframes react quickly to price fluctuations, LTPI smooths out noise and focuses on the bigger picture, allowing for informed strategic decision-making rather than short-term speculation.
Key Features
Multi-Input Aggregation:
Uses six independent inputs, each based on long-term liquidity and macro-related data, to generate a composite market probability score.
Long-Term Focus:
Prioritizes medium-to-long-term trends, ignoring smaller fluctuations that often mislead traders in volatile markets.
Simplified Market States:
Classifies the global market into three primary states:
Bullish: Favorable liquidity and conditions for long-term risk-taking.
Bearish: Tightening liquidity and conditions that require caution.
Neutral: Transitional phases or uncertain conditions.
Background Coloring:
Visual cues on the chart help identify which regime is active at a glance.
Global Liquidity Perspective:
Designed for use on a generic liquidity ticker, based on M2 money supply, to track macroeconomic liquidity flows and risk appetite.
Dashboard Display:
A compact on-screen table summarizes all six inputs, their states, and the resulting LTPI score.
Dynamic Alerts:
Real-time alerts signal when the LTPI shifts from one regime to another.
Inputs & Settings
LTPI Inputs:
Input Sources (6): Each input is a carefully chosen trend following indicator.
Weighting: Each input contributes equally to the final score.
Score Calculation:
Bullish = +1
Bearish = -1
Neutral = 0
Color Settings:
Strong Bullish: Bright Green
Weak Bullish: Light Green
Neutral: Gray/Orange
Weak Bearish: Light Red
Strong Bearish: Bright Red
(Colors can be customized.)
Calculation Process
Collect Data:
Six long-term inputs are evaluated at each bar.
Scoring:
Each input’s state contributes +1 (bullish), -1 (bearish), or around 0 (neutral).
Aggregate Probability:
The LTPI Score is calculated as the sum of all six scores divided by 6, resulting in a value between -1 and +1.
Market Classification:
Score > 0.1: Bullish regime
Score < -0.1: Bearish regime
-0.1 ≤ Score ≤ 0.1: Neutral
Background Coloring:
Background colors are applied to highlight the current regime.
How to Use LTPI
Strategic Positioning:
Bullish: Favor holding or adding to long-term positions.
Bearish: Reduce risk, protect capital.
Neutral: Wait for confirmation before making significant moves.
Confirmation Tool:
LTPI works best when combined with shorter-term indicators like MTPI or trend-following tools to confirm alignment across multiple timeframes.
Dynamic Alerts:
Bullish Regime Entry: When the LTPI Score crosses above 0.1.
Bearish Regime Entry: When the LTPI Score crosses below -0.1.
Neutral Zone: When the score moves back between -0.1 and 0.1.
These alerts help identify significant macro-driven shifts in market conditions.
Conclusion
The Long-Term Probability Indicator (LTPI) is an advanced, liquidity-focused tool for identifying macro-driven market phases. By consolidating six inputs into a single probability score and presenting the results visually, LTPI helps long-term investors and analysts stay aligned with global liquidity trends and avoid being distracted by short-term volatility.
MTPI TOTAL / BTC | JeffreyTimmermansMedium-Term Probability Indicator (MTPI)
The "Medium-Term Probability Indicator (MTPI)" is a multi-factor model designed to evaluate the medium-term state of a market. By aggregating signals from 20 underlying inputs, it generates a composite score that classifies the market as Bullish, Bearish, or Neutral. This helps traders understand the prevailing market regime and adapt strategies accordingly.
Key Features
Multi-Input Scoring: Combines up to 20 individual inputs (indicators, conditions, or models) into a single probability-based score.
Composite Market State: Translates raw input signals into three states: Bullish, Bearish, or Neutral.
Dynamic Background Coloring: Uses color-coded background shading to visually separate bullish, bearish, and neutral phases.
MTPI Score: Calculates a final numeric score (ranging from -1 to +1) to quantify the market’s directional bias.
Dashboard Display: Shows all input signals, their individual states, and the aggregated MTPI score at a glance.
Medium-Term Focus: Helps identify prevailing conditions that last from several weeks to several months.
Inputs & Settings
MTPI Settings:
Input Signals (1 to 20): Default: Predefined conditions. Each input evaluates the market from a unique perspective (trend, momentum, volatility, etc.).
Composite Score Calculation: Default weighting is equal across all inputs.
Color Settings:
Bullish: Bright green background
Neutral: Gray/orange background
Bearish: Bright red background
These colors can be customized as desired.
Calculation Process
Signal Aggregation:
Each input generates a state:
1 to 0.1 = Bullish
0.1 to -0.1 = Neutral
-0.1 to -1 = Bearish
Scoring:
The MTPI aggregates these values and calculates an average score.
Classification:
Bullish: Score > 0
Bearish: Score < 0
Neutral: Score ≈ 0
Visualization:
Background Coloring: Highlights the dominant phase on the chart.
Dashboard: Displays individual input states, the total MTPI score, and the resulting classification.
How to Use the MTPI
Identifying Market Regimes:
Bullish: Majority of inputs align positively. Favor long positions or trend-following strategies.
Bearish: Majority of inputs align negatively. Favor short positions or defensive strategies.
Neutral: Mixed signals. Caution or range-bound strategies may be preferable.
Transition Detection:
Changes in background color or the MTPI dashboard (score flipping from positive to negative, or vice versa) indicate potential regime shifts.
Dynamic Dashboard:
Score: Displays the net sum of all input signals (normalized).
State: Provides the classification (Bullish, Bearish, Neutral).
Trend: Visual cues for each input showing the current contribution to the MTPI.
Conclusion
The Medium-Term Probability Indicator (MTPI) consolidates multiple signals into a single, intuitive visualization that helps traders quickly assess the medium-term market environment. Its combination of a multi-input dashboard, composite scoring, and background coloring makes it a powerful decision-support tool.
This script is developed by Jeffrey Timmermans and is designed to complement other analysis methods.
CBC Flip with Volume [Pt]█ CBC Flip with Volume
A price-action based indicator that detects real-time control flips between bulls and bears, enhanced with volume filtering and Pine Screener compatibility.
This tool tracks when the market shifts from bear control to bull control or vice versa, using candle structure and volume behavior. It highlights key reversal points, filters low-conviction moves, and provides two screener-ready outputs for directional monitoring.
█ What It Detects
This script identifies when control flips between buyers and sellers on a candle-by-candle basis. A flip is confirmed only when both price structure and volume meet strict criteria. The indicator uses an internal state to track who is in control and updates when a flip occurs.
█ Flip Conditions
Bull Flip
• Previous bar was under bear control
• Current candle closes above the previous high
• Candle is bullish (close is above open)
• Volume is greater than the previous bar
Bear Flip
• Previous bar was under bull control
• Current candle closes below the previous low
• Candle is bearish (close is below open)
• Volume is greater than the previous bar
When a flip occurs, the indicator updates the control state and records the open price of the flip candle.
█ Strong Flip Detection
A flip is considered strong when volume is also greater than the average volume over a set number of candles (default is 50). Strong flips are visually emphasized using larger markers and darker background shading. This helps filter out moves that lack follow-through volume.
█ Visual Elements on Chart
• Bull Flip (Normal): Small teal triangle below the candle
• Bull Flip (Strong): Larger green triangle below the candle
• Bear Flip (Normal): Small salmon triangle above the candle
• Bear Flip (Strong): Larger red triangle above the candle
• Background Color:
– Green shades for bull flips
– Red shades for bear flips
– Darker color when flip is strong
These visual elements appear only on the candle where a flip is detected. No markers are shown on continuation candles.
█ Inputs
• Volume MA Lookback : Sets the moving average length used for determining whether volume is high enough for a strong flip (default: 50)
█ Alerts
• Bull Flip – Notifies when bulls take control
• Bear Flip – Notifies when bears take control
Alerts are triggered at candle close.
█ Pine Screener Support
This script includes two output columns for TradingView’s Pine Screener:
• Bull in Control (% gain) : Shows the percentage gain from the bull flip’s open to the current close. Resets to 0 when bulls lose control.
• Bear in Control (% gain) : Shows the percentage drop from the bear flip’s open to the current close (as a positive number). Resets to 0 when bears lose control.
These outputs allow you to filter for active moves. For example:
• Bull in Control (% gain) > 2.0 to find strong uptrends
• Bear in Control (% gain) > 1.5 to find sharp breakdowns
█ Use Cases
• Confirm breakouts using volume-backed flips
• Spot short-term reversals at key zones
• Filter out low-volume chop
• Combine screener results with trend or volatility filters
• Build entries around control flips and follow-through strength
Inspired by MapleStax’s original CBC method.
Overheat Oscillator with DivergenceIndicator Description
The Overheat Oscillator with Divergence is an advanced technical indicator designed for the TradingView platform, assisting traders in identifying potential market reversal points by analyzing price momentum and volume, as well as detecting divergences. The indicator combines trend strength assessment with signal smoothing to provide clear indications of market overheat or oversold conditions. An optional divergence detection feature allows for the identification of discrepancies between price movement and the oscillator's value, which may signal upcoming trend changes.
The indicator is displayed in a separate panel below the price chart and offers visual cues through a color gradient, horizontal reference lines, and a dynamic market sentiment table. Users can customize numerous parameters, such as calculation periods, sentiment thresholds, line colors, and visualization styles, making the indicator a versatile tool for various trading strategies.
How the Indicator Works
The indicator is based on the following key components:
Oscillator Calculations
The indicator analyzes price candles, assigning a score based on their nature. A bullish candle (when the closing price is higher than the opening price) receives a score of +1.0, while a bearish candle (when the closing price is lower than the opening price) receives a score of -1.0. This scoring reflects the strength of price movement over a given period.
The score is modified by a volume multiplier (default: 2.0) if the candle's volume exceeds the volume's simple moving average (SMA, default: calculated over 20 candles). This ensures that candles with higher volume have a greater impact on the oscillator's value, better capturing significant market movements driven by increased trading activity. For example, a bullish candle with high volume may receive a score of +2.0 instead of +1.0, amplifying the bullish signal.
The scores are summed over a specified number of candles (default: 20), normalized to a 0–100 range, and then smoothed using a simple moving average (SMA, default: 5 periods) to reduce noise and improve signal clarity.
Color Gradient
The oscillator's values are visualized using a color gradient that changes based on the oscillator's level:
Green: Market cooldown (values below the Gradient Min threshold).
Yellow: Neutral sentiment (values between Gradient Min and Gradient Yellow).
Orange: Elevated activity (values between Gradient Yellow and Gradient Orange).
Red: Market overheat (values above Gradient Orange).
The color gradient is applied as the background in the oscillator panel, facilitating quick assessment of market sentiment.
Reference Levels
The indicator displays customizable horizontal lines for key thresholds (e.g., Overheat Threshold, Oversold Threshold, Gradient Min, Yellow, Orange, Max). These lines are visible only at the height of the last few oscillator candles, preventing chart clutter and helping users focus on current values.
Users can also define three custom horizontal lines with selectable styles (solid, dotted, dashed) and colors. These lines serve as auxiliary tools, e.g., for marking personal support/resistance levels, but do not affect the oscillator's signals or background colors.
Market Sentiment
The indicator displays sentiment labels in a table located in the top-right corner of the panel, dynamically updating based on the oscillator's value:
Cooled: Values below Gradient Yellow (default: 35).
Neutral: Values between Gradient Yellow and Gradient Orange (default: 60).
Excited: Values between Gradient Orange and Overheat Threshold (default: 70).
Overheated: Values above Overheat Threshold (default: 70).
The Overheat Threshold and Oversold Threshold are critical for displaying the "Overheated" and "Cooled" labels in the sentiment table, enabling users to quickly identify extreme market conditions. The labels update when key thresholds are crossed, and their colors match the oscillator's gradient.
Divergence Detection
The indicator offers optional detection of regular bullish and bearish divergences:
Bullish Divergence: Occurs when the price forms a lower low, but the oscillator forms a higher low, suggesting a weakening downtrend.
Bearish Divergence: Occurs when the price forms a higher high, but the oscillator forms a lower high, suggesting a weakening uptrend.
Divergences are marked on the chart with labels ("Bull" for bullish, "Bear" for bearish) and lines indicating pivot points. They are calculated with a delay equal to the Lookback Right setting (default: 5 candles), meaning signals appear after pivot confirmation in the specified lookback period. The indicator also generates alerts for users when a divergence is detected.
Indicator Settings
Main Settings (SETTINGS)
Period Length: Specifies the number of candles used for oscillator calculations (default: 20).
Volume SMA Period: The period for the volume's simple moving average (default: 20).
Volume Multiplier: Multiplier applied to candle scores when volume exceeds the average (default: 2.0).
SMA Length: The period for smoothing the oscillator with a simple moving average (default: 5).
Thresholds (THRESHOLDS)
Overheat Threshold: Level indicating market overheat (default: 70). This value determines when the sentiment table displays the "Overheated" label, signaling a potential peak in an uptrend.
Oversold Threshold: Level indicating market cooldown (default: 30). This value determines when the sentiment table displays the "Cooled" label, signaling a potential bottom in a downtrend.
Gradient Min (Green): Lower threshold for the green gradient (default: 20).
Gradient Yellow Threshold: Threshold for the yellow gradient (default: 35).
Gradient Orange Threshold: Threshold for the orange gradient (default: 60).
Gradient Max (Red): Upper threshold for the red gradient (default: 70).
Visualization (VISUALIZATION)
Signal Line Color: Color of the oscillator line (default: dark red, RGB(5, 0, 0)).
Show Reference Lines: Enables/disables the display of threshold lines (default: enabled).
Divergence Settings (DIVERGENCE SETTINGS)
Calculate Divergence: Enables/disables divergence detection (default: disabled).
Lookback Right: Number of candles back for pivot analysis (default: 5).
Lookback Left: Number of candles to the left for pivot analysis (default: 5).
Line Style (STYLE)
Custom Line 1, 2, 3 Value: Levels for custom horizontal lines (default: 70, 50, 30).
Custom Line 1, 2, 3 Color: Colors for custom lines (default: black, RGB(0, 0, 0)).
Custom Line 1, 2, 3 Style: Line styles (solid, dotted, dashed; default: dashed, dotted, dashed).
How to Use the Indicator
Adding to the Chart
Add the indicator to your TradingView chart by searching for "Overheat Oscillator with Divergence."
Configure the settings according to your trading strategy.
Signal Interpretation
Overheated: Values above the Overheat Threshold (default: 70) in the sentiment table may indicate a potential uptrend peak.
Cooled: Values below the Oversold Threshold (default: 30) in the sentiment table may suggest a potential downtrend bottom.
Divergences:
Bullish: Look for "Bull" labels on the chart, indicating potential upward reversals (calculated with a Lookback Right delay).
Bearish: Look for "Bear" labels, indicating potential downward reversals (calculated with a Lookback Right delay).
Customization
Experiment with settings such as period length, volume multiplier, or gradient thresholds to tailor the indicator to your trading style (e.g., scalping, medium-term trading).
Usage Examples
Scalping: Set a shorter period (e.g., Period Length = 10, SMA Length = 3) and monitor rapid sentiment changes and divergences on lower timeframes (e.g., 5-minute charts).
Medium-Term Trading: Use default settings or increase Period Length (e.g., 30) and SMA Length (e.g., 7) for more stable signals on hourly or daily charts.
Reversal Detection: Enable divergence detection and observe "Bull" or "Bear" labels in conjunction with overheat/cooled levels in the sentiment table.
Notes
The indicator performs best when used in conjunction with other technical analysis tools, such as support/resistance lines, moving averages, or Fibonacci levels.
Divergences may serve as early signals but do not always guarantee immediate trend reversals—confirmation with other indicators is recommended.
Test different settings on historical data to find the optimal configuration for your chosen market and timeframe.
OI Analysis (Smoothed + Pivots + OI Divergence)Description
OI Pivot & Divergence Explorer is a multi-tool indicator for TradingView that blends Open Interest (OI) analysis with price action pivots and OI–price divergences. It helps you:
Visualize OI Trends: A thick, semi-transparent “glow” line shows smoothed OI changes, with a crisp center line for exact values.
Shade Momentum Scenarios: Background highlights flip between four market states—High Conviction, Squeeze, Bear Pressure, Liquidation—based on the confluence of price direction and OI spikes.
Detect Pivot Levels: Internally computes classic pivots on the OI series to mark potential turning points.
Spot OI-Price Divergences: Draws both regular and hidden bullish/bearish divergences between price pivots and corresponding OI pivots, connecting them with colored lines and labeling high-probability reversal setups.
Custom Alerts: Triggers alert conditions for each divergence type, so you can get notified of potentially actionable setups in real time.
Logic & Features
Inputs
Pivot Lookback (default 5): Number of bars on each side to qualify a pivot in both price and OI.
OI Change Smoothing (default 3) & OI Average Length (default 20): Control smoothing of raw OI delta and define the average band for threshold comparisons.
OI Change Threshold (%) (default 0.2%): Minimum relative OI change required to flag a “big” move.
Show OI Divergences (toggle on/off): Enable or disable drawing divergence lines and labels.
Scenario Shading
Computes raw OI delta → smoothed OI delta → compares against average OI.
Combines with price direction (up/down) to classify four states:
↑Price + ↑OI → High Conviction (green)
↑Price + ↓OI → Squeeze (orange)
↓Price + ↑OI → Bear Pressure (red)
↓Price + ↓OI → Liquidation (blue)
Shades the chart background only when the state flips.
Pivot Markers
Finds pivots on the OI series using the same lookback as price pivots.
(Pivot labels are removed from the visible pane; pivots now serve divergence logic.)
OI-Price Divergences
Regular Bullish: Price makes a lower low while OI makes a higher low.
Hidden Bullish: Price makes a higher low while OI makes a lower low.
Regular Bearish: Price makes a higher high while OI makes a lower high.
Hidden Bearish: Price makes a lower high while OI makes a higher high.
Connects each pivot pair with a thin line:
Regular uses dark navy
Hidden uses a lighter blue
Labels each divergence (“Bull Div,” “H Bull Div,” etc.) above or below the OI line for clarity.
How to Use
Add to Chart:
Open Pine Editor → paste the script → Save → “Add to Chart.”
Configure Inputs:
Adjust Pivot Lookback to match your timeframe: shorter (3–5) for intraday, longer (8–12) for daily/weekly.
Tweak OI Change Threshold to filter out noise or capture more subtle OI shifts.
Interpretation:
Background Color: Quick read on whether OI is reinforcing or diverging from price.
Divergence Lines: Look for regular divergences as early reversal signals; hidden divergences often indicate trend continuation or strong pullback entry points.
Alerts: Set up custom alerts on “Regular Bullish OI Divergence,” etc., to get popup/messages/notifications.
Best Practices:
Combine with your favorite price-based indicators (e.g. RSI, VWAP) for confluence.
Validate divergence signals against higher-timeframe pivots to avoid false breakouts.
Use in trending markets for continuation trades (hidden divergences) and in range markets for reversal setups (regular divergences).
Advanced MACD Pro (WhiteStone_Ibrahim) - T3 Themed✨ Advanced MACD Pro (WhiteStone_Ibrahim) - T3 Themed ✨
Take your MACD analysis to the next level with the Advanced MACD Pro - T3 Themed indicator by WhiteStone_Ibrahim! This isn't just another MACD; it's a comprehensive toolkit packed with advanced features, unique T3 integration, and extensive customization options to provide deeper market insights.
Whether you're a seasoned trader or just starting, this indicator offers a versatile and powerful way to analyze momentum, identify trends, and spot potential reversals.
Key Features:
Core MACD Functionality:
Classic MACD Line: Calculated from customizable Fast and Slow EMAs using your chosen source (Close, Open, HLC3, etc.).
Standard Signal Line: EMA of the MACD line, with adjustable length.
Dynamic MACD Line Coloring: Automatically changes color based on whether it's above or below the zero line (positive/negative).
Zero Line: Clearly plotted for reference.
Enhanced MACD Histogram:
Sophisticated Color Coding: The histogram isn't just positive or negative. It intelligently colors based on momentum strength and direction:
Strong Bullish: MACD above signal, histogram increasing.
Weakening Bullish: MACD above signal, histogram decreasing.
Strong Bearish: MACD below signal, histogram decreasing.
Weakening Bearish: MACD below signal, histogram increasing.
Neutral: Default color for other conditions.
Optional Histogram Smoothing: Smooth out the histogram noise using one of five different moving average types: SMA, EMA, WMA, RMA, or the advanced T3 (Tilson T3). Customize smoothing length and T3 vFactor.
🌟 Unique T3 Integration (T3 Themed):
Extra T3 Signal Line (on MACD): An additional, fast-reacting T3 moving average calculated directly from the MACD line. This provides an alternative and often quicker signal.
Customizable T3 length and vFactor.
Dynamic Coloring: The T3 Signal Line changes color (bullish/bearish) based on its crossover with the MACD line, offering clear visual cues.
T3 is also available as a smoothing option for the main histogram (see above).
🔍 Disagreement & Divergence Detection:
Bar/Price Disagreement Markers:
Highlights instances where the price bar's direction (e.g., a bullish candle) contradicts the current MACD momentum (e.g., MACD below its signal line).
Visual markers (circles) appear above/below bars to draw attention to these potential early warnings or confirmations.
Histogram Color Change on Disagreement: Optionally, the histogram can adopt distinct alternative colors during these bar/price disagreements for even clearer visual alerts.
Classic Bullish & Bearish Divergence Detection:
Automatically identifies regular divergences between price action (Higher Highs/Lower Lows) and the MACD line (Lower Highs/Higher Lows).
Customizable pivot lookback periods (left and right bars) for divergence sensitivity.
Plots clear "Bull" and "Bear" labels on the price chart where divergences occur.
🎨 Extensive Customization & Visuals:
Multiple Color Themes: Choose from pre-set themes like 'Dark Mode', 'Light Mode', 'Neon Night', or use 'Default (Current Settings)' to fine-tune every color yourself.
Granular Control (Default Theme): Individually customize colors and thickness for:
MACD Line (positive/negative)
Standard Signal Line
Extra T3 Signal Line (bullish/bearish)
Histogram (all four momentum states + neutral)
Disagreement Markers & Histogram Alt Colors
Divergence Lines/Labels
Zero Line
Toggle Visibility: Easily show or hide the Standard Signal Line and the Extra T3 Signal Line as needed.
🔔 Comprehensive Alert System:
Stay informed of key market events with a wide array of configurable alerts:
MACD Line / Standard Signal Line Crossover
Histogram / Zero Line Crossover
MACD Line / Zero Line Crossover
Bullish Divergence Detected
Bearish Divergence Detected
Bar/Price Disagreement (Bullish & Bearish)
MACD Line / Extra T3 Signal Line Crossover
Each alert can be individually enabled or disabled.
The Advanced MACD Pro - T3 Themed indicator is designed to be your go-to tool for momentum analysis. Its rich feature set empowers you to tailor it to your specific trading style and gain a more nuanced understanding of market dynamics.
Add it to your charts today and experience the difference!
(Developed by WhiteStone_Ibrahim)
PCA Regime & Conviction IndexThis indicator diagnoses the underlying character and conviction of the market's current behavior, going far beyond simple price direction.
Instead of just asking "Is the market going up or down?", this tool answers the more critical question: "How is the market moving right now?"
To do this, it provides two key pieces of information:
1. It Identifies the Current Market Phase.
The indicator classifies the market's behavior into one of four distinct phases, which are displayed as a clear background color and an explicit text label:
Quiet Bull: A steady, healthy, low-volatility uptrend.
Volatile Bull: An explosive, energetic, or potentially exhaustive uptrend.
Quiet Bear: A slow, grinding, low-volatility downtrend or "bleed."
Volatile Bear: A sharp, high-energy, or panic-driven downtrend.
This tells you the fundamental personality of the market at a glance.
2. It Measures the Conviction of That Phase.
Alongside identifying the phase, the indicator plots a "Conviction Index"—a clear gold line oscillating between 0 and 100. This index measures the strength and clarity of the current market phase.
A high conviction level (e.g., above 75) means the current phase is strong, stable, and decisive.
A low conviction level (e.g., below 25) means the phase is weak, uncertain, and lacks energy.
The Ultimate Benefit:
By understanding both what the market is doing (the phase) and how strongly it's doing it (the conviction), a trader can make more intelligent decisions. It helps you adapt your strategy in real-time by providing a clear framework to:
Confidently pursue trends when the market is in a high-conviction "Quiet Bull" or "Quiet Bear" phase.
Exercise caution and manage risk during high-conviction "Volatile" phases.
Avoid whipsaws and frustration by recognizing when the market has low conviction and is likely to be choppy and unpredictable, regardless of the phase.
Visual ProwessVisual Prowess: Ultimate Visual of Price Action Indicator
Overview
Visual Prowess is a Pine Script indicator that integrates Trend, Momentum, Strength/Weakness, Money Flow, and Volatility into a single, intuitive interface. Scaled from 0 to 100, it provides traders with clear bullish (>50) and bearish (<50) zones. Visual Prowess is made up of several data components which will be explained below. All these components have custom thresholds that lead to Green Dot Buy Signals and Red Dot sell signals. Designed for multi-timeframe analysis, it helps traders anticipate market moves with precision seeing behind the scenes of price action.
The fundamental inputs of price action are made up of different variables -- the components of Trend Strength, Volatility, Momentum, Money Flow/Volume and Overbought/Oversold. These are very important inputs market makers use. From what I've learned in my trading journey (always still learning), this is the data I value most important. This is why I combined all these components into one indicator.....to be an ultimate visual—this extrapolation of different pieces of data is the Visual Prowess.
What It Does
Visual Prowess combines five key market factors into a unified score (0-100) to assess market conditions by examining the price action like an x-ray aka Visual Prowess:
• Trend Direction & Strength (Green and Red Wave) : Identifies bullish (green clouds) or bearish (red clouds) trend. This data is designed to illustrate the trend by the color, and its strength by the height (score).
How it is Calculated = Data is derived from price action-- comparing the current and previous price highs and lows to measure the strength of upward (+) or downward (-) price movements, smoothed over a period and expressed as a percentage of the price range.
• Momentum (Blue and White Wave): Tracks price acceleration via a custom momentum oscillator, displayed as blue (positive) or white (negative) waves.
How it is Calculated = Data is calculated by subtracting a longer-term exponential moving average from a shorter-term exponential moving average to measure momentum and trend direction. Momentum strength is measured by height on 0-100 score, and color dictates the trend-- Blue up, White down.
• Strength Index (Purple Line): Measures overbought/oversold conditions with a normalized index, derived from price deviation.
How it is Calculated = Strength Index is calculated by comparing the average of price gains to the average of price losses over a specified period, expressed as a value between 0 and 100 to measure momentum and identify overbought or oversold conditions.
• Money Flow: Monitors capital inflows and outflows using a modified Money Flow Index, shown as green (buying) or red (selling) circles.
How it is Calculated = The Money Flow is calculated by using price and volume data to measure buying and selling pressure, comparing positive and negative money flow over a specified period to produce a value between 0 and 100, indicating overbought or oversold conditions and more importantly where the money is moving, + or -.
• Volatility: Gauges market volatility, marked by colored crosses (blue for low, red for high). Blue illustrates low volatility which is key for big moves either + or -; red to illustrate when price action is extremely overheated either + or -.
How it is Calculated = The volatility is calculated by the creator of the BBWP The_Caretaker. This excellent work is calculated using the width of the iconic indicator the Bollinger Bands (the difference between the upper and lower bands divided by the middle band (the moving average), expressed as a percentage to show how volatile the price is relative to its recent average.
Originality
Unlike traditional multi-indicator dashboards, Visual Prowess uses a combination of specific open-source indicators which I believe to be the most important inputs in price action-- trend, momentum, strength, money flow, and volatility into an all-in-one visual ratioed on a 0-100 scale. This unique synthesis of data reduces noise, prioritizes signal alignment, and a look behind the scenes of price action to see deeper into the movement – This combination of indicators has custom thresholds, when these components in alignment with each other hit certain parameters; it leads to key custom price action signals -- Green Dot Buy and Red Dot Sell signals.
There is also a bonus indicator….. a Yellow Triangle. When you see this, it is rare and strong. It only prints when strength index reaches extreme lows at the same time volatility reaches extreme highs…. It then waits to print the yellow triangle upon a third condition= which is price action is back in bullish/positive zone. This Yellow triangle is meant to be strong reversals of Macro Trend lows.
How to Use the Visual Prowess Components:
• Add to Chart: Apply Visual Prowess to any timeframe (recommended: higher timeframes 12H, 1D, 2D, 3D for optimal signals).
• Interpret Zones: Values >50 indicate bullish conditions (green background); <50 signal bearish conditions (red background).
Wait for Green Dot Buy signal for buys and Red Dot Sell signals for sells. One can read each component individually to gauge the price action and predict before the buy signal prints; all of those components merged together is what leads to the buy and sell signals. The story of what’s to come can be seen at lower timeframes before the higher timeframes print, that is a key way to gauge projections of bull or bear prints to come.
HOW TO READ EACH DATA COMPONENT
TREND CLOUDS: Green/red clouds show trend direction; vivid colors tied to number/ score on the 0-100 scale indicate strength of the trend.
Bull Conditions
Green cloud illustrates the trend is bullish. The height is correlated to the trend’s strength—this height is also aligned with colors, more transparent green is weak, then it gets more opaque being medium strength, and the most vibrant is the strongest. How to ride the bull condition is by seeing this transformation of trend get from weak to strong, until it tops out and the wave points down losing strength which alludes to the bear condition.
Bear Conditions
Vice versa with the bear condition. Different shades of red tie into the strength of the bear trend. How to read when things are about to get bearish, is by seeing bull trend shift levels of strength (Example- medium to weak). This transition of bull strength getting weaker is the start, once it gets to weak bear it has commenced until bearish strength tops out before it begins to get weaker leading to the next bull phase.
MOMENTUM WAVES: Blue waves above 50 suggest bullish momentum; white waves below 50 warn of bearish shifts.
Bull Conditions
Good to look at flips of white wave to blue in bearish zones to see the tide turning= guaranteed bullish when safely gets above and holds above 50 zone.
Bear Conditions
Vice versa for Bearish side of this momentum wave being blue wave turning white in bullish zone aiming down to break below 50 zone to confirm bearish descent.
STRENGTH INDEX: Values >80 indicate overbought; <20 suggest oversold. Look for “Bull” or “Bear” labels for divergences.
Bull Conditions
Above 50 level is key, so seeing price action break from below 50 to above 50 is strong buy condition until it gets overbought.
Bear Conditions
Once conditions are too overbought and falling making lower lows (especially when price action is climbing or staying sideways) it is indicating strength is getting weaker. When this indicator fights 50 level and breaks down below 50 level bearish conditions are coming until it gets to an oversold level.
MONEYFLOW: Green circles signal buying pressure; red circles indicate selling.
Bull Conditions
Green circles show money flow is positive so that’s a good sign of upward price action to come, and again above 50 level is bullish conditions
Bear Conditions
Red circles show money flow is negative so that’s a bad sign of price action to come, pointing down and breaking below 50 level is no good. It can have corrections in bullish scenario keep in mind seeing red doesn’t mean trend is over z9could be in higher low scenario).
VOLATILITY: Blue crosses (<25% volatility) suggest breakout potential; red crosses (>75%) warn of overheated markets.
Bull Conditions
This is a very important indication. Big volatile moves can move either direction + or -. When all other components look positive/bullish and this is signalling blue crosses it means a big move is coming and will most likely be in the upward direction –If all other components align/lean bullish.
Another bullish scenario is when price action is down large and red crosses are forming. This indicates that the downward move is overheated (red x’s are rare). This extremely oversold condition can be great buying opportunities when volatility is hot printing red x’s.
Bear Conditions
When all other components look negative/bearish and this is signalling blue crosses it means a big move is coming and will most likely be in the downward direction –If all other components align/lean bearish.
Another bearish scenario is when price action is up large and red crosses are forming. This indicates that the upward move is overheated (red x’s are rare). This extremely overbought condition can be great selling opportunities when volatility is hot printing red x’s.
*****All these components in alignment of hitting each pertaining important threshold--is what prints the green dot and sell signals to trade by. It is not black and white; each component has a sweet spot fine tuned to be triggered through analysis of what is happening individually to each component and how it is reacting to the price action data.
EXAMPLE= Taking a look at the screenshot (Perfect Scenario)
Bullish Examination
- Taking a look at the 2-D timeframe on BTC
x>50
x= all components traveling to the bullish zone. Blue wave, Strength Index with bullish divergence accumulation, Money Flow Positive with Green Trend Wave starting, with teal low volatility cross→→→ leads to Green Dot Buy Signal print…. And the big rise speaks for itself with price action and the big mountain wave of the Green Trend Wave.
This rise leads to
↓↓↓↓
Bearish Examination
Strength Index gets really high at 80 scale, Red X’s showing extremely heated Volatility, Money Flow turning red and sloping down, Trend Wave peaking starting to roll over, Blue Momentum Wave transitioning to white, bearish divergence of price action related to Strength Index→→→ leads to Red Dot Sell Signal print… and the flush speaks for itself when all components fall below 50 level with Trend wave turning red
All this is forecasted in the data, showing weakness before weakness and showing strength before strength. It works because every single piece of important elements in data of price action is incorporated in this all-in-one indicator…. Which leads to the reasoning of me calling this indicator the Visual Prowess, for its unprecedent sharpness of visual observation.
****This is a passion script incorporating every piece of data I value important when reading a chart — to see current perspective of a chart and to help foresee future projection of direction Up or Down. Any community feedback is greatly appreciated. Ongoing work will be done on this script as new thoughts and fine tuning will continuously be done for infinity, as this is my personal go to model for data on the markets.
MMPD @MaxMaserati 2.0The MMPD @MaxMaserati 2.0 is a powerful TradingView indicator (Pine Script v6) designed to reveal institutional price action when paired with MMM 2.0 and MMPB 2.0 as part of the Max Maserati Method (MMM) System. It analyzes momentum across multiple timeframes, helping you understand whether the market is overbought (premium) or oversold (discount). With vibrant candle colors, a consistency table, momentum dots, and renamed lines for clarity, it provides an intuitive way to read market dynamics.
Key Features
Multi-Timeframe Analysis: Evaluates six user-defined timeframes to ensure signal consistency.
Candle Classifications: Colors candles to reflect momentum and institutional activity (e.g., Strong Bullish, Bearish Reversal).
Consistency Table: Displays candle types and market conditions across timeframes with a summary bias.
Momentum Dots: Visual dots indicate alignment strength across momentum, balance, and trend direction.
Premium/Discount Zones: Highlights overbought (red fill) and oversold (green fill) areas.
Renamed Lines: Clear labels like "Momentum Line," "Balance Line," and "Trend Direction Line" for better usability.
Input Parameters
Timeframe Settings: Six timeframes (htf1 to htf6, default: 45s, 1m, 5m, 15m, 60m, daily) for multi-timeframe analysis.
Display Settings:
Use Closed Candle Data: Default true, ensures reliability by using closed candles.
Show Momentum Line: Default true, displays the momentum indicator.
Show Balance Line: Default true, shows the market’s directional balance.
Show Trend Direction Line: Default false, optional trend slope.
Trend Direction Length: Default 10, range 3-50, adjusts trend slope sensitivity.
Show Premium/Discount Fill: Default true, highlights overbought/oversold zones.
Visual Settings: Customize colors (e.g., Bullish Color, Bearish Color) and candle opacity (default 20, range 0-100).
Threshold Settings:
Percentage Threshold: Default 60%, sets minimum strength for bullish/bearish classifications.
Premium Threshold: Default 65, defines overbought zone.
Discount Threshold: Default 35, defines oversold zone.
Core Components
1. Candle Types
MMPD classifies candles based on price action, syncing with MMM 2.0’s structure and MMPB 2.0’s blocks:
Strong Bullish: Institutional buying, often at MMPB eBreaks.
Bullish Resumption: Buyers continuing after a pause, tied to MMM’s C3/C4.
Bullish Reversal: Buyers flipping bearish moves, great at MMPB discount zones.
Weak Bullish: Mild bullishness, confirm with MMM’s PO4.
Bullish Pullback: Buyers resting, a setup for MMM’s resumption.
Strong Bearish: Heavy selling, often at MMPB premium eBlocks.
Bearish Resumption: Sellers pushing on, aligned with MMM’s bearish PO4.
Bearish Reversal: Sellers dominating, great at MMPB premium zones.
Weak Bearish: Soft selling, check MMM’s MC2.
Bearish Pullback: Sellers pausing, potential MMPB short entries.
Neutral: No clear direction, use MMM’s structure.
Trap: Warning of a fake-out, cross-check with MMM.
HVC Bullish: Explosive up-move, align with MMM’s C4.
HVC Bearish: Sharp drop, confirm with MMPB’s bearish blocks.
2. Candle Colors
Colors enhance readability, tying to MMM and MMPB:
Bright Green: Strong Bullish/Resumption—big buying.
Cyan: Bullish Reversal—buyers flipping bearish moves.
Green: Weak Bullish/standard bullish close.
Light Green: Bullish Pullback—buyers pausing.
Magenta: Strong Bearish/Resumption—big selling.
Bright Red: Bearish Reversal—sellers taking over.
Red: Weak Bearish/standard bearish close.
Light Red: Bearish Pullback—sellers resting.
Teal: HVC Bullish—high-energy surge.
Dark Red: HVC Bearish—sharp drop.
Orange: Trap—potential fake-out.
Gray: Neutral—no clear bias.
3. Market Conditions
MMPD flags pricing levels:
Extreme Premium (>90): Overbought, likely reversal.
Premium (65-90): Pricey, cautious longs.
Neutral (35-65): Balanced market.
Discount (10-35): Bargain, buying opportunity.
Extreme Discount (<10): Deeply undervalued.
4. Consistency Table
A top-right table summarizes:
Timeframes: Your six chosen timeframes.
MMPD Type: Candle type, colored to match.
MMPD Level: Premium/discount/neutral, with red/green backgrounds.
Summary: Bias (Bullish, Bearish, Premium, Discount) and action (Cheap, Expensive, Neutral).
5. Visual Elements
Momentum Line: Tracks momentum, colored per candle type
Balance Line: Green (bullish) or magenta (bearish), shows market direction.
Trend Direction Line: Optional, green up, magenta down.
Momentum Dots: Green (bullish) or magenta (bearish) circles:
3 dots (Normal, at 0/100): Strong alignment of momentum, balance, and trend.
2 dots (Small, at 1/99): Moderate alignment.
1 dot (Tiny, at 2/98): Weak alignment.
Premium/Discount Fills: Red (>65), green (<35).
Candles: Custom candles, colored to reflect momentum.
How to Use It
Setup: Add to TradingView with MMM 2.0 and MMPB 2.0. Set timeframes (e.g., 45s to daily), tweak thresholds, and enable visuals.
Read the Table: Look for alignment (5+ timeframes Bullish/Discount or Bearish/Premium).
Summary guides bias and action
Interpret Candles: Bright Green/Cyan for bullish setups, Magenta/Bright Red for bearish, Orange for traps.
Use Dots: Three green dots signal strong bullish alignment; three magenta dots signal bearish alignment.
Combine with MMM/MMPB: MMM for structure, MMPB for entries—MMPD confirms momentum and pricing.
Why It’s Special
Institutional Insight: Spots big-player moves with MMM and MMPB.
Clear Visuals: Dots and renamed lines make momentum easy to read.
Versatile: Works for scalping or swings, across markets.
Protective: Trap signals and premium/discount zones keep you sharp.
Notes
Lag: Uses closed candles by default—pair with MMM for real-time.
Best in Trends: Shines in moving markets, less clear in chop.
Learning Curve: Takes time to sync with MMM and MMPB.
Customize: Adjust inputs for your market.
Final Thought
“Analyze, wait, repeat.” MMPD @MaxMaserati 2.0, with MMM 2.0 and MMPB 2.0, helps you master price action. It’s your guide to seeing the market like the pros.
Built on the Max Maserati Method for educational and trading purposes.
Precision Trend Shot | JeffreyTimmermansPrecision Trend Shot
The "Precision Trend Shot" Indicator is an advanced technical tool designed to provide a dynamic and adaptive view of market trends. By combining three core components—RSI Oscillator, LSMA ATR, and Adaptable Trend—this indicator delivers precise signals that help traders identify market direction, volatility, and potential trend reversals. The calculated total score, derived from these components, provides a clear, actionable view of market conditions.
Key Features
Multi-Component Analysis: Integrates three key indicators (RSI, LSMA ATR, and Adaptable Trend) for a comprehensive view of market trends.
Dynamic Trend Classification: Categorizes market states as "Bullish" or "Bearish", based on a combined score.
Standard Deviation Bands: Displays standard deviation bands around the score line for enhanced volatility visualization.
Gradient Background Coloring: Visually highlights market phases with gradient colors, aiding quick interpretation.
Customizable Visuals: Offers extensive settings for coloring, background gradients, and signal visibility.
Real-Time Alerts: Generates alerts for significant trend changes or transitions between market states.
Inputs & Settings
RSI Settings:
RSI Source: Default: Close price. Defines the data source for RSI calculation.
RSI Length: Default: 10. Sets the period for calculating RSI.
LSMA ATR Settings:
LSMA Source: Default: Close price. Defines the data source for LSMA calculation.
LSMA Length: Default: 21. Sets the period for calculating the Least Squares Moving Average.
ATR Length: Default: 12. Sets the period for calculating the Average True Range.
Adaptable Trend Settings:
Trend Length: Default: 5. Sets the period for calculating the trend.
Smoothing Length: Default: 5. Controls the smoothing of trend volatility.
Sensitivity: Default: 1.5. Adjusts the sensitivity of trend bands.
Standard Deviation Settings:
Enable Standard Deviation Bands: Default: True. Toggles the display of standard deviation bands.
Standard Deviation Length: Default: 20. Sets the period for standard deviation calculation.
Standard Deviation Multiplier: Default: 2.0. Adjusts the width of the bands.
Smoothing Length: Default: 5. Controls the smoothing of standard deviation bands.
Visual Settings:
Enable Candle Coloring: Default: True. Colors candles based on market state (Bullish or Bearish).
Enable Background Gradient: Default: True. Applies gradient coloring to the background based on trend direction.
Score Line Colors: Customize colors for bullish or bearish score lines.
Calculation Process
RSI Calculation:
Computes the Relative Strength Index (RSI) of the selected source data.
Signals bullish (RSI > 50) or bearish (RSI < 50) conditions.
LSMA ATR Calculation:
Computes LSMA for trend direction and ATR for volatility measurement.
Generates buy and sell signals based on crossover and crossunder of ATR bands.
Adaptable Trend Calculation:
Calculates dynamic trend levels using EMA and standard deviation bands.
Classifies trend states as Bullish or Bearish.
Combined Signal Calculation:
Averages the signals from RSI, LSMA ATR, and Adaptable Trend to generate a total score.
Classifies the market as "Bullish" or "Bearish" based on this score.
Standard Deviation Bands:
Plots standard deviation bands around the combined signal for enhanced volatility analysis.
Gradient Background Coloring:
Colors the chart background based on the identified market state (Bullish or Bearish).
How to Use the Precision Trend Shot Indicator
Identifying Market States:
Bullish Market: Total score > 0, gradient background green.
Bearish Market: Total score < 0, gradient background red.
Confirming Signals:
Use RSI and LSMA ATR signals for early indications.
Use Trend Recon for confirming longer-term trend direction.
Visualizing Volatility:
Standard deviation bands highlight potential reversal zones.
Dynamic Alerts
The Precision Trend Shot Indicator includes a robust alert system for real-time market transitions:
Bullish to Bearish: Market shifts from a bullish to bearish trend.
Bearish to Bullish: Market shifts from a bearish to bullish trend.
Conclusion
The Precision Trend Shot Indicator is an advanced, versatile tool for identifying market trends, visualizing volatility, and generating actionable signals. With customizable settings, dynamic alerts, and clear visual representation, it is an essential addition to any trader’s toolkit.
-Jeffrey
