DECODE Global Liquidity IndexDECODE Global Liquidity Index 🌊
The DECODE Global Liquidity Index is a powerful tool designed to track and aggregate global liquidity by combining data from the world's 13 largest economies. It offers a comprehensive view of financial liquidity, providing crucial insights into the underlying currents that can influence asset prices and market trends.
The economies covered are: United States, China, European Union, Japan, India, United Kingdom, Brazil, Canada, Russia, South Korea, Australia, Mexico, and Indonesia. The European Union accounts for major individual economies within the EU like Germany, France, Italy, Spain, Netherlands, Poland, etc.
Key Features:
1. Customizable Liquidity Sources
Include Global M2: You can opt to include the M2 money supply from the 13 listed economies. M2 is a broad measure of money supply that includes cash, checking deposits, savings deposits, money market securities, mutual funds, and other time deposits. (Note: Australia uses M3 as its primary measure, which is included when M2 is selected for Australia).
Include Central Bank Balance Sheets (CBBS): Alternatively, or in addition, you can include the total assets held by the central banks of these economies. Central bank balance sheets expand or contract based on monetary policy operations like quantitative easing (QE) or tightening (QT).
Combined View: If you select both M2 and CBBS, and data is available for both, the indicator will display an average of the two aggregated values. If only one source type is selected, or if data for one type is unavailable despite both being selected, the indicator will display the single available and selected component. This provides flexibility in how you define and analyze global liquidity.
2. Lead/Lag Analysis (Forward Projection):
Lead Offset (Days): This feature allows you to project the liquidity index forward by a specified number of days.
Why it's useful: Global liquidity changes can often be a leading indicator for various asset classes, particularly those sensitive to risk appetite, like Bitcoin or growth stocks. These assets might lag shifts in liquidity. By applying a lead (e.g., 90 days), you can shift the liquidity data forward on your chart to more easily visualize potential correlations and identify if current asset price movements might be responding to past changes in liquidity.
3. Rate of Change (RoC) Oscillator:
Year-over-Year % View: Instead of viewing aggregate liquidity, you can switch to a Year-over-Year (YoY%) Rate of Change (ROC) oscillator.
Why it's useful:
Momentum Identification: The ROC highlights the speed and direction of liquidity changes. Positive values indicate liquidity is increasing compared to a year ago, while negative values show it's decreasing.
Turning Points: Oscillators make it easier to spot potential accelerations, decelerations, or reversals in liquidity trends. A cross above the zero line can signal strengthening liquidity momentum, while a cross below can signal weakening momentum.
Cycle Analysis: It helps in assessing the cyclical nature of liquidity provision and its potential impact on market cycles.
This indicator aims to provide a clear, customizable, and insightful measure of global liquidity to aid traders and investors in their market analysis.
Forecasting
Momentum Fusion v1Momentum Fusion v1
Overview
Momentum Fusion v1 (MFusion) is a multi-oscillator indicator that combines several components to analyze market momentum and trend strength. It incorporates modified versions of classic indicators such as PVI (Positive Volume Index), NVI (Negative Volume Index), MFI (Money Flow Index), RSI, Stochastic, and Bollinger Bands Oscillator. The indicator displays a histogram that changes color based on momentum strength and includes "FUSION🔥" signal labels when extreme values are reached.
Indicator Settings
Parameters:
EMA Length – Smoothing period for the moving average (default: 255).
Smoothing Period – Internal calculation smoothing parameter (default: 15).
BB Multiplier – Standard deviation multiplier for Bollinger Bands (default: 2.0).
Show verde / marron / media lines – Toggles the display of auxiliary lines.
Show FUSION🔥 label – Enables/disables signal labels.
Indicator Components
1. PVI (Positive Volume Index)
Formula:
pvi := volume > volume ? nz(pvi ) + (close - close ) / close * sval : nz(pvi )
Description:
PVI increases when volume rises compared to the previous bar and accounts for price percentage change. The stronger the price movement with increasing volume, the higher the PVI value.
2. NVI (Negative Volume Index)
Formula:
nvi := volume < volume ? nz(nvi ) + (close - close ) / close * sval : nz(nvi )
Description:
NVI tracks price movements during declining volume. If the price rises on low volume, it may indicate a "stealth" trend.
3. Money Flow Index (MFI)
Formula:
100 - 100 / (1 + up / dn)
Description:
An oscillator measuring money flow strength. Values above 80 suggest overbought conditions, while values below 20 indicate oversold conditions.
4. Stochastic Oscillator
Formula:
k = 100 * (close - lowest(low, length)) / (highest(high, length) - lowest(low, length))
Description:
A classic stochastic oscillator showing price position relative to the selected period's range.
5. Bollinger Bands Oscillator
Formula:
(tprice - BB midline) / (upper BB - lower BB) * 100
Description:
Indicates the price position relative to Bollinger Bands in percentage terms.
Key Lines & Histogram
1. Verde (Green Line)
Calculation:
verde = marron + oscp (normalized PVI)
Interpretation:
Higher values indicate stronger bullish momentum. A FUSION🔥 signal appears when the value reaches 750+.
2. Marron (Brown Line)
Calculation:
marron = (RSI + MFI + Bollinger Osc + Stochastic / 3) / 2
Interpretation:
A composite oscillator combining multiple indicators. Higher values suggest overbought conditions.
3. Media (Red Line)
Calculation:
media = EMA of marron with smoothing period
Interpretation:
Acts as a signal line for trend confirmation.
4. Histogram
Calculation:
histo = verde - marron
Colors:
Bright green (>100) – Strong bullish momentum.
Light green (>0) – Moderate bullish momentum.
Orange (<0) – Bearish momentum.
Red (<-100) – Strong bearish momentum.
Signals & Alerts
1. FUSION🔥 (Strong Momentum)
Condition:
verde >= 750
Visualization:
A "FUSION🔥" label appears below the chart.
Alert:
Can be set to trigger notifications when the condition is met.
2. Background Aura
Condition:
verde > 850
Visualization:
The chart background turns teal, indicating extreme momentum.
Usage Recommendations
FUSION🔥 Signal – Can be used as a long entry point when confirmed by other indicators.
Histogram:
1. Green bars – Potential long entry.
2. Red/orange bars – Potential short entry.
3. Media & Marron Crossover – Can serve as an additional trend filter.
4. Suitable for a 5-15 minute time frame
Conclusion
Momentum Fusion v1 is a powerful tool for momentum analysis, combining multiple indicators into a unified system. It is suitable for:
Trend traders (catching strong movements).
Scalpers (identifying short-term impulses).
Swing traders (filtering entry points).
The indicator features customizable settings and visual signals, making it adaptable to various trading styles.
Candle/RSI BUY SELLWhy Use Candlesticks?
They help traders visualize price action
Used in technical analysis and price pattern recognition (e.g., Doji, Engulfing, Hammer)
Assist in determining entry and exit points
Why Traders Use RSI:
To identify potential reversal zones
To confirm trend strength
To detect divergences between price and momentum
Why Combine Candlestick Patterns with RSI?
Using Candlestick patterns together with the Relative Strength Index (RSI) enhances trading decisions by combining price action and momentum analysis.
Conclusion:
Combining RSI with Candlestick patterns allows traders to:
Confirm potential reversals
Filter false signals
Improve entry and exit timing
Make more confident and accurate decisions
How It Works:
RSI Calculation
Custom RSI is calculated manually using Wilder's smoothing technique.
MA or BB Option
User can select whether to apply a smoothing MA or Bollinger Bands to RSI (useful for visual enhancements or custom strategies).
Buy/Sell Logic
check for:
Buy when the current candle is bullish (open <= close) and the previous candle was bearish (open >= close ), AND RSI is ≥ 50.
Sell when current candle is bearish and previous was bullish, AND RSI is ≤ 50.
Plot Buy/Sell Labels
Final Verdict
code is:
Valid (no syntax errors)
Useful (combines candlestick confirmation + RSI strength)
Extendable (can add divergence, alerts, etc.)
This Timeframe 5 min : XAU
MTF - Quantum Fibonacci ATR/ADR Levels & Targets V_2.0# Quantum Fibonacci Wave Mechanics v2.0 Release Notes
## 🚀 New Features
- Added multi-timeframe alert system for buy/sell signals
- Implemented dynamic label management with price values
- New mid-level trigger option for additional signals
- New EMA trigger option for confirmation signals
- Signal bar highlighting option
- Customizable line widths for all levels
## 🎨 Visual Improvements
- Completely redesigned label system (left-aligned with offsets)
- More intuitive input organization
- Better color customization options
## ⚙️ Technical Upgrades
- Upgraded to Pine Script v6
- Reduced repainting with stricter confirmation checks
- Optimized performance with proper variable initialization
## ⚠️ Note for Existing Users
- Some color parameters have been renamed
- Label positioning has changed (now with configurable offset)
- Review new mid-level trigger option in strategy settings
## 🐛 Bug Fixes
- Fixed potential repainting issues in signal generation
- Improved label cleanup between periods
- More robust security function implementation
## ⚠️ Caution for Mid-Level & EMA Signals
- Mid-Level Reversals may trigger premature entries in ranging markets.
- EMA crossovers can lag; confirm with price action.
CAFX Liquidity Pro V1CAFX Liquidity Pro Indicator
Precision Engineered for Smart Profit-Taking
The CAFX Liquidity Pro Indicator is a powerful trading tool designed to help traders pinpoint high-probability liquidity zones, making it ideal for setting accurate and strategic take profit levels. By identifying where institutional interest is likely to reside, this indicator highlights the areas where price is most likely to react, reverse, or pause—giving you the edge in locking in profits before the market shifts.
Whether you're scalping, day trading, or swing trading, the CAFX Liquidity Pro provides clear visual cues that simplify your decision-making process and enhance your trade management. With a focus on precision and reliability, it helps you avoid emotional exits and instead base your take profits on real market behavior and liquidity dynamics.
Use CAFX Liquidity Pro to stay one step ahead—because knowing where to exit is just as important as knowing when to enter.
EMA5/21 + VWAP + MACD HistogramScript Summary: EMA + VWAP + MACD + RSI Strategy
Objective: Combine multiple technical indicators to identify market entry and exit opportunities, aiming to increase signal accuracy.
Indicators Used:
EMAs (Exponential Moving Averages): Periods of 5 (short-term) and 21 (long-term) to identify trend crossovers.
VWAP (Volume Weighted Average Price): Serves as a reference to determine if the price is in a fair value zone.
MACD (Moving Average Convergence Divergence): Standard settings of 12, 26, and 9 to detect momentum changes.
RSI (Relative Strength Index): Period of 14 to identify overbought or oversold conditions.
Entry Rules:
Buy (Long): 5-period EMA crosses above the 21-period EMA, price is above VWAP, MACD crosses above the signal line, and RSI is above 40.
Sell (Short): 5-period EMA crosses below the 21-period EMA, price is below VWAP, MACD crosses below the signal line, and RSI is below 60.
Exit Rules:
For long positions: When the 5-period EMA crosses below the 21-period EMA or MACD crosses below the signal line.
For short positions: When the 5-period EMA crosses above the 21-period EMA or MACD crosses above the signal line.
Visual Alerts:
Buy and sell signals are highlighted on the chart with green (buy) and red (sell) arrows below or above the corresponding candles.
Indicator Plotting:
The 5 and 21-period EMAs, as well as the VWAP, are plotted on the chart to facilitate the visualization of market conditions.
This script is a versatile tool for traders seeking to combine multiple technical indicators into a single strategy. It can be used across various timeframes and assets, allowing adjustments according to the trader's profile and market characteristics.
Juliano Einhardt Ulguim, Brazil, 05/27/2025.
Trucker Doug Master Indicator for Making Money📈 Trucker Doug Master Indicator for Making Money™
This all-in-one indicator was built for speed, clarity, and dominance — designed by a trader, for traders who hate fluff and want to get paid.
🔥 What It Does:
TP/SL/R:R Overlay: Automatically plots entry, stop-loss, and 5 take-profit levels (including a "TP LAMBO" target) based on your custom ATR multiplier and risk percentage. Each TP level includes its R:R ratio, so you can instantly see if the trade is worth it.
Live Volume Analysis: Displays Relative Volume (RVOL) as a percentage, with color-coded states (red = weak, black = neutral, yellow = increasing, green = explosive). Also shows average volume for context.
ATR Value: Dynamically calculated and displayed so you always know your volatility baseline.
MACD & RSI Values: Shown in the overlay box for a quick read — no extra indicators cluttering your chart.
EMA/SMA Lines: Clean, adjustable moving averages (default: EMA 5, EMA 9, SMA 50) plotted directly on the chart.
Fuse Visual Explainer™: Marks EMA 5 crossing EMA 9 (colored dot) and EMA 5 crossing SMA 50 (black X) directly where they intersect. Helps you visually confirm momentum or momentum reversals in real time.
⚙️ Fully Customizable in Settings:
Toggle on/off: TP lines, the volume/ATR table, EMA/SMA lines, RSI/MACD display, Fuse visuals.
Adjust:
TP multipliers (TP1–TP4, Lambo)
Stop-loss offset %
ATR period
Volume average period
Line colors for each TP level, SL, entry, and even the R:R label
Table text size and position
TP/SL line length (how far it stretches left/right)
💡 Why It’s Awesome:
No more layering 5 indicators. No more eyeballing risk-to-reward. No more guessing if volume is legit. This is a precision tool for real traders.
Built for those who are tired of chart noise and want everything that matters — clean, calculated, and completely in your control.
Parabolic-Fibonacci MA ForecastThis indicator displays a series of projected price levels based on Fibonacci moving averages. For each selected Fibonacci period, it calculates a simple moving average (SMA) and mirrors the distance from the current price to that SMA in the opposite direction, creating a vertical forecast distance. These forecast distances are drawn forward into the future using geometric spacing (squared increments: 1², 2², 3², etc.), creating a fan-like or polyline visual structure.
Users can choose between three display modes:
Fan: Lines drawn from the current price to projected values at increasing intervals
Polyline: Forecast points connected to form a jagged projection path
Both: Displays both fan and polyline structures simultaneously
Options are provided to adjust the number of Fibonacci lines (up to 12), line width, and colors for lines above/below price or up/down slope.
This tool can help visualize directional price tendencies using multiple SMA-based forecasts in a spatially meaningful layout.
Linear Regression ForecastDescription:
This indicator computes a series of simple linear regressions anchored at the current bar, using look-back windows from 2 bars up to the user-defined maximum. Each regression line is projected forward by the same number of bars as its look-back, producing a family of forecast endpoints. These endpoints are then connected into a continuous polyline: ascending segments are drawn in green, and descending segments in red.
Inputs:
maxLength – Maximum number of bars to include in the longest regression (minimum 2)
priceSource – Price series used for regression (for example, close, open, high, low)
lineWidth – Width of each line segment
Calculation:
For each window size N (from 2 to maxLength):
• Compute least-squares slope and intercept over the N most recent bars (with bar 0 = current bar, bar 1 = one bar ago, etc.).
• Project the regression line to bar_index + N to obtain the forecast price.
Collected forecast points are sorted by projection horizon and then joined:
• First segment: current bar’s price → first forecast point
• Subsequent segments: each forecast point → next forecast point
Segment colors reflect slope direction: green for non-negative, red for negative.
Usage:
Apply this overlay to any price chart. Adjust maxLength to control the depth and reach of the forecast fan. Observe how shorter windows produce nearer-term, more reactive projections, while longer windows yield smoother, more conservative forecasts. Use the colored segments to gauge the overall bias of the fan at each step.
Limitations:
This tool is for informational and educational purposes only. It relies on linear regression assumptions and past price behavior; it does not guarantee future performance. Users should combine it with other technical or fundamental analyses and risk management practices.
TP/SL Overlay with Volume/ATR TableThis is a Take Profit and Stop Loss indicator that plots the TP/SL levels, along with the Risk/Reward ratios on the chart similar to an auto fib overlay. These levels are ATR based and are dynamic, based on the current price. It also includes heads-up display that shows the Relative Volume, ATR and several TP levels. All settings and configurations are editable from the settings menu, as well. I created this to make it easier to estimate TP levels without having to pull up a calculator or the "Long" tool that TradingView provides. Hope you like it!
Range Progress TrackerRANGE PROGRESS TRACKER(RPT)
PURPOSE
This indicator helps traders visually and statistically understand how much of the typical price range (measured by ATR) has already been covered in the current period (Daily, Weekly, or Monthly). It includes key features to assist in trend exhaustion analysis, reversal spotting, and smart alerting.
CORE LOGIC
The indicator calculates the current range of the selected time frame (e.g., Daily), which is:
Current Range = High - Low
This is then compared to the ATR (Average True Range) of the same time frame, which represents the average price movement range over a defined period (default is 14).
The comparison is expressed as a percentage, calculated with this formula:
Range % = (Current Range / ATR) × 100
This percentage shows how much of the “average expected move” has already occurred.
WHY IT MATTERS
When the current range approaches or exceeds 100% of ATR, it means the price has already moved as much as it typically does in a full session.
This indicates a lower probability of continuing the trend with a new high or low, especially when the price is already near the session's high or low.
This setup can signal:
A possible consolidation phase
A reversal in trend
The market entering a corrective phase
SMART ALERTS
The indicator can alert you when:
A new high is made after the range percentage exceeds your set threshold.
A new low is made after the range percentage exceeds your set threshold.
You can adjust the Range % Alert Threshold in the settings to tailor it to your trading style.
Tangent Extrapolation ForecastTangent Extrapolation Forecast
This indicator visually projects price direction by drawing a smoothed sequence of tangent lines based on recent price movements. For each bar in a user-defined lookback window, it calculates the slope over a smoothing period and extends the projected price forward. The resulting polyline forecast connect the endpoints of the extrapolations, and is color-coded to reflect directional changes: green for upward moves, red for downward, and gray for flat segments. This tool can assist traders in visualizing short-term momentum and potential trend continuity without introducing artificial future gaps.
Inputs:
Bars to Use: Number of historical bars used in the forecast.
Slope Smoothing Window: The number of bars used to calculate slope for projection.
Source: Price input for calculations (default is close).
This indicator does not generate buy/sell signals. It is intended as a visual aid to support discretionary analysis.
H2-25 cuts (bp)This custom TradingView indicator tracks and visualizes the implied pricing of Federal Reserve rate cuts in the market, specifically for the second half of 2025. It does so by comparing the price differences between two specific Fed funds futures contracts: one for June 2025 and one for December 2025. These contracts are traded on the Chicago Board of Trade (CBOT) and are a widely-used market gauge of the expected path of U.S. interest rates.
The indicator calculates the difference between the implied rates for June and December 2025, and then multiplies the result by 100 to express it in basis points (bps). Each 0.01 change in the spread corresponds to a 1-basis point change in expectations for future rate cuts. A positive value indicates that the market is pricing in a higher likelihood of one or more rate cuts in 2025, while a negative value suggests that the market expects the Fed to hold rates steady or even raise them.
The plot represents the difference in implied rate cuts (in basis points) between the two contracts:
June 2025 (ZQM2025): A contract representing the implied Fed funds rate for June 2025.
December 2025 (ZQZ2025): A contract representing the implied Fed funds rate for December 2025.
Stochastic RSI with Alerts# Stochastic RSI with Alerts - User Manual
## 1. Overview
This enhanced Stochastic RSI indicator identifies overbought/oversold conditions with visual signals and customizable alerts. It features:
- Dual-line Stoch RSI (K & D)
- Threshold-based buy/sell signals
- Configurable alert system
- Customizable parameters
## 2. Installation
1. Open TradingView chart
2. Open Pine Editor (📈 icon at bottom)
3. Copy/paste the full code
4. Click "Add to Chart"
## 3. Input Parameters
### 3.1 Core Settings
| Parameter | Default | Description |
|-----------|---------|-------------|
| K | 3 | Smoothing period for %K line |
| D | 3 | Smoothing period for %D line |
| RSI Length | 14 | RSI calculation period |
| Stochastic Length | 14 | Lookback period for Stoch calculation |
| RSI Source | Close | Price source for RSI calculation |
### 3.2 Signal Thresholds
| Parameter | Default | Description |
|-----------|---------|-------------|
| Upper Limit | 80 | Sell signal threshold (overbought) |
| Lower Limit | 20 | Buy signal threshold (oversold) |
### 3.3 Alert Settings
| Parameter | Default | Description |
|-----------|---------|-------------|
| Enable Buy Alerts | True | Toggle buy notifications |
| Enable Sell Alerts | True | Toggle sell notifications |
| Custom Alert Message | Empty | Additional text for alerts |
## 4. Signal Logic
### 4.1 Buy Signal (Green ▲)
Triggers when:
\text{%K crossover %D} \quad AND \quad (\text{%K ≤ Lower Limit} \quad OR \quad \text{%D ≤ Lower Limit})
### 4.2 Sell Signal (Red ▼)
Triggers when:
\text{%K crossunder %D} \quad AND \quad (\text{%K ≥ Upper Limit} \quad OR \quad \text{%D ≥ Upper Limit})
## 5. Alert System
### 5.1 Auto-Generated Alerts
The script automatically creates these alert conditions:
- **Buy Signal Alert**: Triggers on valid buy signals
- **Sell Signal Alert**: Triggers on valid sell signals
Alert messages include:
- Signal type (Buy/Sell)
- Current %K and %D values
- Custom message (if configured)
### 5.2 Alert Configuration
**Method 1: Script-Generated Alerts**
1. Hover over any signal marker
2. Click the 🔔 icon
3. Select trigger conditions:
- "Buy Signal Alert"
- "Sell Signal Alert"
**Method 2: Manual Setup**
1. Open Alert creation window
2. Condition: Select "Stoch RSI Alerts"
3. Choose:
- "Buy Signal Alert" for long entries
- "Sell Signal Alert" for exits/shorts
## 6. Customization Tips
### 6.1 Threshold Adjustment
// For day trading (tighter ranges)
upperLimit = 75
lowerLimit = 25
// For swing trading (wider ranges)
upperLimit = 85
lowerLimit = 15
### 6.2 Visual Modifications
Change signal markers via:
- `style=` : Try `shape.labelup`, `shape.flag`, etc.
- `color=` : Use hex codes (#FF00FF) or named colors
- `size=` : `size.tiny` to `size.huge`
## 7. Recommended Use Cases
1. **Mean Reversion Strategies**: Pair with support/resistance levels
2. **Trend Confirmation**: Filter with 200EMA direction
3. **Divergence Trading**: Compare with price action
## 8. Limitations
- Works best in ranging markets
- Combine with volume analysis for confirmation
- Not recommended as standalone strategy
---
This documentation follows technical writing best practices with:
- Clear parameter tables
- Mathematical signal logic
- Visual hierarchy
- Practical examples
- Usage recommendations
HTF ReversalsHTF Reversals — Big Turtle Soup & Relief Patterns
A multi-timeframe reversal indicator based on the logic of how pivots form and how true reversals begin. Designed for traders who want to catch high-probability turning points on higher timeframes, with visual clarity and actionable signals.
“Reversals don’t start from nowhere — they begin with a failed expansion and a reclaim of a prior range. This script helps you spot those moments, before the crowd.”
How It Works
Detects High Timeframe (HTF) “CR” Candles:
The script scans for large-bodied candles (“CR” candles) on higher timeframes (Monthly, Weekly, 3-Day). These candles often mark the end of a trend expansion and the start of a potential reversal zone.
Looks for “Inside” Candles:
After a CR candle, the script waits for a smaller “inside” candle, which signals a pause or failed continuation. The relationship between the CR and inside candle is key for identifying a possible reversal setup.
Engulfing Confirmation (Optional):
If the inside candle doesn’t immediately trigger a reversal, the script can wait for an engulfing move in the opposite direction, confirming the failed expansion and increasing the probability of a reversal.
Entry & Target Calculation:
For each valid setup, the script calculates a retracement entry (using Fibonacci levels like 0.382 or 0.618) and a logical target (usually the CR candle’s high or low).
Visuals: Lines & Boxes:
Each signal is marked with a horizontal line (entry) and a colored box extending from the HTF close to the entry price, visually highlighting the reversal zone for the same duration as the signal’s expected play-out.
Dashboard & Alerts:
A dashboard table summarizes the latest signals for each timeframe. Custom alerts notify you of new setups in real time.
Why It Works
Pivot Logic:
Reversals often start when a strong expansion candle (pivot) is followed by a failed attempt to continue in the same direction. This script codifies that logic, looking for the “pause” after the expansion and the first sign of a reclaim.
Multi-Timeframe Edge:
By focusing on higher timeframes, the indicator filters out noise and highlights only the most significant reversal opportunities.
Objective, Repeatable Rules:
All conditions are clearly defined and repeatable, removing subjectivity from reversal trading.
Visual Clarity:
The combination of lines and boxes makes it easy to see where reversals are likely to start and where your risk/reward lies.
How to Use
Add the indicator to your chart and select your preferred timeframes (Monthly, Weekly, 3-Day).
Watch for new signals on the dashboard or via alerts.
Use the entry line and box as your trade zone; the target is also displayed.
Combine with your own confluence (price action, volume, etc.) for best results.
This indicator is best used as a framework for understanding where high-probability reversals are likely to occur, not as a standalone buy/sell tool. Always use proper risk management.
Risk Calculator PRO — manual lot size + auto lot-suggestionWhy risk management?
90 % of traders blow up because they size positions emotionally. This tool forces Risk-First Thinking: choose the amount you’re willing to lose, and the script reverse-engineers everything else.
Key features
1. Manual or Market Entry – click “Use current price” or type a custom entry.
2. Setup-based ₹-Risk – four presets (A/B/C/D). Edit to your workflow.
3. Lot-Size Input + Auto Lot Suggestion – you tell the contract size ⇒ script tells you how many lots.
4. Auto-SL (optional) – tick to push stop-loss to exactly 1-lot risk.
5. Instant Targets – 1 : 2, 1 : 3, 1 : 4, 1 : 5 plotted and alert-ready.
6. P&L Preview – table shows potential profit at each R-multiple plus real ₹ at SL.
7. Margin Column – enter per-lot margin once; script totals it for any size.
8. Clean Table UI – dark/light friendly; updates every 5 bars.
9. Alert Pack – SL, each target, plus copy-paste journal line on the chart.
How to use
1. Add to chart > “Format”.
2. Type the lot size for the symbol (e.g., 1250 for Natural Gas, 1 for cash equity).
3. Pick Side (Buy / Sell) & Setup grade.
4. ✅ If you want the script to place SL for you, tick Auto-SL (risk = 1 lot).
5. Otherwise type your own Stop-loss.
6. Read the table:
• Suggested lots = how many to trade so risk ≤ setup ₹.
• Risk (currency) = real money lost if SL hits.
7. Set TradingView alerts on the built-in conditions (T1_2, SL_hit, etc.) if you’d like push / email.
8. Copy the orange CSV label to Excel / Sheets for journalling.
Best practices
• Never raise risk to “fit” a trade. Lower size instead.
• Review win-rate vs. R multiple monthly; adjust setups A–D accordingly.
• Test Auto-SL in replay before going live.
Disclaimer
This script is educational. Past performance ≠ future results. The author isn’t responsible for trading losses.
DXY Monthly Return (+3M Lead)This indicator calculates the rolling monthly return (based on 21 trading days) for the U.S. Dollar Index (DXY), applying a +3-month forward shift (lead) to the series.
It is designed to help visualize the leading effect of USD strength or weakness on other macro-sensitive assets — particularly Bitcoin and crypto markets, which often react to changes in global dollar liquidity with a lag of approximately 10 weeks.
Note: This script does not invert the values directly. To match the inverted Y-axis visual used by Steno Research — where negative USD returns are displayed at the top — simply right-click the Y-axis in the chart panel and select “Invert Scale.”
💡 Use this tool for macro trend analysis, early crypto signal generation, or studying inverse correlations between USD and risk assets.
Source logic: Steno Research, Bloomberg, Macrobond.
Taylor Series ForecastThis indicator projects future price movement using a second-order Taylor Series expansion, calculated from a smoothed price (EMA). It models price momentum and acceleration to generate a forward-looking trajectory.
Forecast points are plotted continuously as connected line segments extending into the future. Each segment is color-coded based on slope:
Green indicates an upward slope (bullish forecast).
Red indicates a downward slope (bearish forecast).
The forecast adapts to current market conditions and updates dynamically with each new bar. Useful for visualizing potential future price paths and identifying directional bias based on recent price action.
Inputs:
Max Forecast Horizon: How many bars into the future the forecast extends.
EMA Smoothing Length: The smoothing applied to price before calculating derivatives.
This tool is experimental and should be used in conjunction with other analysis methods. It does not guarantee future price performance.
UT Bot + Hull MA Confirmed Signal DelayOverview
This indicator is designed to detect high-probability reversal entry signals by combining "UT Bot Alerts" (UT Bot Alerts script adapted from QuantNomad - Originally developed by Yo_adriiiiaan and idea of original code for "UT Bot Alerts" from HPotter ) with confirmation from a Hull Moving Average (HMA) Developed by Alan Hull . It focuses on capturing momentum shifts that often precede trend reversals, helping traders identify potential entry points while filtering out false signals.
🔍 How It Works
This strategy operates in two stages:
1. UT Bot Momentum Trigger
The foundation of this script is the "UT Bot Alerts" , which uses an ATR-based trailing stop to detect momentum changes. Specifically:
The script calculates a dynamic stop level based on the Average True Range (ATR) multiplied by a user-defined sensitivity factor (Key Value).
When price closes above this trailing stop and the short-term EMA crosses above the stop, a potential buy setup is triggered.
Conversely, when price closes below the trailing stop and the short-term EMA crosses below, a potential sell setup is triggered.
These UT Bot alerts are designed to identify the initial shift in market direction, acting as the first filter in the signal process.
2. Hull MA Confirmation
To reduce noise and false triggers from the UT Bot alone, this script delays the entry signal until price confirms the move by crossing the Hull Moving Average (or its variants: HMA, THMA, EHMA) in the same direction as the UT Bot trigger:
A Buy Signal is generated only when:
A UT Bot Buy condition is active, and
The price closes above the Hull MA.
Or, if a UT Bot Buy condition was recently triggered but price hadn’t yet crossed above the Hull MA, a delayed buy is signaled when price finally breaks above it.
A Sell Signal is generated only when:
A UT Bot Sell condition is active, and
The price closes below the Hull MA.
Similarly, a delayed sell signal can occur if price breaks below the Hull MA shortly after a UT Bot Sell trigger.
This dual-confirmation process helps traders avoid premature entries and improves the reliability of reversal signals.
📈 Best Use Cases
Reversal Trading: This strategy is particularly well-suited for catching early trend reversals rather than trend continuations. It excels at identifying momentum pivots that occur after pullbacks or exhaustion moves.
Heikin Ashi Charts Recommended: The script offers a Heikin Ashi mode for smoothing out noise and enhancing visual clarity. Using Heikin Ashi candles can further reduce whipsaws and highlight cleaner shifts in trend direction.
MACD Alignment: For best results, trade in the direction of the MACD trend or use it as a filter to avoid counter-trend trades.
⚠️ Important Notes
Entry Signals Only: This indicator only plots entry points (Buy and Sell signals). It does not define exit strategies, so users should manage trades manually using trailing stops, profit targets, or other exit indicators.
No Signal = No Confirmation: You may see a UT Bot trigger without a corresponding Buy/Sell signal. This means the price did not confirm the move by crossing the Hull MA, and therefore the setup was considered too weak or incomplete.
⚙️ Customization
UT Bot Sensitivity: Adjust the “Key Value” and “ATR Period” to make the UT Bot more or less reactive to price action.
Use Heikin Ashi: Toggle between standard candles or Heikin Ashi in the indicator settings for a smoother trading experience.
The HMA length may also be modified in the indicator settings from its standard 55 length to increase or decrease the sensitivity of signal.
This strategy is best used by traders looking for a structured, logic-based way to enter early into reversals with added confirmation to reduce risk. By combining two independent systems—momentum detection (UT Bot) and trend confirmation (Hull MA)—it aims to provide high-confidence entries without overwhelming complexity.
Let the indicator guide your entries—you manage the exits.
Examples of use:
Futures:
Stock:
Crypto:
As shown in the snapshots this strategy, like most, works the best when price action has a sizeable ATR and works the least when price is choppy. Therefore it is always best to use this system when price is coming off known support or resistance levels and when it is seen to respect short term EMA's like the 9 or 15.
My personal preference to use this system is for day trading on a 3 or 5 minute chart. But it is valid for all timeframes and simply marks a high probability for a new trend to form.
Sources:
Quant Nomad - www.tradingview.com
Yo_adriiiiaan - www.tradingview.com
HPotter - www.tradingview.com
Hull Moving Average - alanhull.com
JPMorgan G7 Volatility IndexThe JPMorgan G7 Volatility Index: Scientific Analysis and Professional Applications
Introduction
The JPMorgan G7 Volatility Index (G7VOL) represents a sophisticated metric for monitoring currency market volatility across major developed economies. This indicator functions as an approximation of JPMorgan's proprietary volatility indices, providing traders and investors with a normalized measurement of cross-currency volatility conditions (Clark, 2019).
Theoretical Foundation
Currency volatility is fundamentally defined as "the statistical measure of the dispersion of returns for a given security or market index" (Hull, 2018, p.127). In the context of G7 currencies, this volatility measurement becomes particularly significant due to the economic importance of these nations, which collectively represent more than 50% of global nominal GDP (IMF, 2022).
According to Menkhoff et al. (2012, p.685), "currency volatility serves as a global risk factor that affects expected returns across different asset classes." This finding underscores the importance of monitoring G7 currency volatility as a proxy for global financial conditions.
Methodology
The G7VOL indicator employs a multi-step calculation process:
Individual volatility calculation for seven major currency pairs using standard deviation normalized by price (Lo, 2002)
- Weighted-average combination of these volatilities to form a composite index
- Normalization against historical bands to create a standardized scale
- Visual representation through dynamic coloring that reflects current market conditions
The mathematical foundation follows the volatility calculation methodology proposed by Bollerslev et al. (2018):
Volatility = σ(returns) / price × 100
Where σ represents standard deviation calculated over a specified timeframe, typically 20 periods as recommended by the Bank for International Settlements (BIS, 2020).
Professional Applications
Professional traders and institutional investors employ the G7VOL indicator in several key ways:
1. Risk Management Signaling
According to research by Adrian and Brunnermeier (2016), elevated currency volatility often precedes broader market stress. When the G7VOL breaches its high volatility threshold (typically 1.5 times the 100-period average), portfolio managers frequently reduce risk exposure across asset classes. As noted by Borio (2019, p.17), "currency volatility spikes have historically preceded equity market corrections by 2-7 trading days."
2. Counter-Cyclical Investment Strategy
Low G7 volatility periods (readings below the lower band) tend to coincide with what Shin (2017) describes as "risk-on" environments. Professional investors often use these signals to increase allocations to higher-beta assets and emerging markets. Campbell et al. (2021) found that G7 volatility in the lowest quintile historically preceded emerging market outperformance by an average of 3.7% over subsequent quarters.
3. Regime Identification
The normalized volatility framework enables identification of distinct market regimes:
- Readings above 1.0: Crisis/high volatility regime
- Readings between -0.5 and 0.5: Normal volatility regime
- Readings below -1.0: Unusually calm markets
According to Rey (2015), these regimes have significant implications for global monetary policy transmission mechanisms and cross-border capital flows.
Interpretation and Trading Applications
G7 currency volatility serves as a barometer for global financial conditions due to these currencies' centrality in international trade and reserve status. As noted by Gagnon and Ihrig (2021, p.423), "G7 currency volatility captures both trade-related uncertainty and broader financial market risk appetites."
Professional traders apply this indicator in multiple contexts:
- Leading indicator: Research from the Federal Reserve Board (Powell, 2020) suggests G7 volatility often leads VIX movements by 1-3 days, providing advance warning of broader market volatility.
- Correlation shifts: During periods of elevated G7 volatility, cross-asset correlations typically increase what Brunnermeier and Pedersen (2009) term "correlation breakdown during stress periods." This phenomenon informs portfolio diversification strategies.
- Carry trade timing: Currency carry strategies perform best during low volatility regimes as documented by Lustig et al. (2011). The G7VOL indicator provides objective thresholds for initiating or exiting such positions.
References
Adrian, T. and Brunnermeier, M.K. (2016) 'CoVaR', American Economic Review, 106(7), pp.1705-1741.
Bank for International Settlements (2020) Monitoring Volatility in Foreign Exchange Markets. BIS Quarterly Review, December 2020.
Bollerslev, T., Patton, A.J. and Quaedvlieg, R. (2018) 'Modeling and forecasting (un)reliable realized volatilities', Journal of Econometrics, 204(1), pp.112-130.
Borio, C. (2019) 'Monetary policy in the grip of a pincer movement', BIS Working Papers, No. 706.
Brunnermeier, M.K. and Pedersen, L.H. (2009) 'Market liquidity and funding liquidity', Review of Financial Studies, 22(6), pp.2201-2238.
Campbell, J.Y., Sunderam, A. and Viceira, L.M. (2021) 'Inflation Bets or Deflation Hedges? The Changing Risks of Nominal Bonds', Critical Finance Review, 10(2), pp.303-336.
Clark, J. (2019) 'Currency Volatility and Macro Fundamentals', JPMorgan Global FX Research Quarterly, Fall 2019.
Gagnon, J.E. and Ihrig, J. (2021) 'What drives foreign exchange markets?', International Finance, 24(3), pp.414-428.
Hull, J.C. (2018) Options, Futures, and Other Derivatives. 10th edn. London: Pearson.
International Monetary Fund (2022) World Economic Outlook Database. Washington, DC: IMF.
Lo, A.W. (2002) 'The statistics of Sharpe ratios', Financial Analysts Journal, 58(4), pp.36-52.
Lustig, H., Roussanov, N. and Verdelhan, A. (2011) 'Common risk factors in currency markets', Review of Financial Studies, 24(11), pp.3731-3777.
Menkhoff, L., Sarno, L., Schmeling, M. and Schrimpf, A. (2012) 'Carry trades and global foreign exchange volatility', Journal of Finance, 67(2), pp.681-718.
Powell, J. (2020) Monetary Policy and Price Stability. Speech at Jackson Hole Economic Symposium, August 27, 2020.
Rey, H. (2015) 'Dilemma not trilemma: The global financial cycle and monetary policy independence', NBER Working Paper No. 21162.
Shin, H.S. (2017) 'The bank/capital markets nexus goes global', Bank for International Settlements Speech, January 15, 2017.
Cointegration Heatmap & Spread Table [EdgeTerminal]The Cointegration Heatmap is a powerful visual and quantitative tool designed to uncover deep, statistically meaningful relationships between assets.
Unlike traditional indicators that react to price movement, this tool analyzes the underlying statistical relationship between two time series and tracks when they diverge from their long-term equilibrium — offering actionable signals for mean-reversion trades .
What Is Cointegration?
Most traders are familiar with correlation, which measures how two assets move together in the short term. But correlation is shallow — it doesn’t imply a stable or predictable relationship over time.
Cointegration, however, is a deeper statistical concept: Two assets are cointegrated if a linear combination of their prices or returns is stationary , even if the individual series themselves are non-stationary.
Cointegration is a foundational concept in time series analysis, widely used by hedge funds, proprietary trading firms, and quantitative researchers. This indicator brings that institutional-grade concept into an easy-to-use and fully visual TradingView indicator.
This tool helps answer key questions like:
“Which stocks tend to move in sync over the long term?”
“When are two assets diverging beyond statistical norms?”
“Is now the right time to short one and long the other?”
Using a combination of regression analysis, residual modeling, and Z-score evaluation, this indicator surfaces opportunities where price relationships are stretched and likely to snap back — making it ideal for building low-risk, high-probability trade setups.
In simple terms:
Cointegrated assets drift apart temporarily, but always come back together over time. This behavior is the foundation of successful pairs trading.
How the Indicator Works
Cointegration Heatmap indicator works across any market supported on TradingView — from stocks and ETFs to cryptocurrencies and forex pairs.
You enter your list of symbols, choose a timeframe, and the indicator updates every bar with live cointegration scores, spread signals, and trade-ready insights.
Indicator Settings:
Symbol list: a customizable list of symbols separated by commas
Returns timeframe: time frame selection for return sampling (Weekly or Monthly)
Max periods: max periods to limit the data to a certain time and to control indicator performance
This indicator accomplishes three major goals in one streamlined package:
Identifies stable long-term relationships (cointegration) between assets, using a heatmap visualization.
Tracks the spread — the difference between actual prices and the predicted linear relationship — between each pair.
Generates trade signals based on Z-score deviations from the mean spread, helping traders know when a pair is statistically overextended and likely to mean revert.
The math:
Returns are calculated using spread tickers to ensure alignment in time and adjust for dividends, splits, and other inconsistencies.
For each unique pair of symbols, we perform a linear regression
Yt=α+βXt+ε
Then we compute the residuals (errors from the regression):
Spreadt=Yt−(α+βXt)
Calculate the standard deviation of the spread over a moving window (default: 100 samples) and finally, define the Cointegration Score:
S=1/Standard Deviation of Residuals
This means, the lower the deviation, the tighter the relationship, so higher scores indicate stronger cointegration.
Always remember that cointegration can break down so monitor the asset over time and over multiple different timeframes before making a decision.
How to use the indicator
The heatmap table:
The indicator displays 2 very important tables, one in the middle and one on the right side. After entering your symbols, the first table to pay attention to is the middle heatmap table.
Any assets with a cointegration value of 25% is something to pay attention to and have a strong and stable relationship. Anything below is weak and not tradable.
Additionally, the 40% level is another important line to cross. Assets that have a cointegration score of over 40% will most likely have an extremely strong relationship.
Think about it this way, the higher the percentage, the tighter and more statistically reliable the relationship is.
The spread table:
After finding a good asset pair using heatmap, locate the same pair in the spread table (right side).
Here’s what you’ll see on the table:
Spread: Current difference between the two symbols based on the regression fit
Mean: Historical average of that spread
Z-score: How far current spread is from the mean in standard deviations
Signal: Trade suggestion: Short, Long, or Neutral
Since you’re expecting mean reversion, the idea is that the spread will return to the average. You want to take a trade when the z-score is either over +2 or below -2 and exit when z-score returns to near 0.
You will usually see the trade suggestion on the spread chart but you can make your own decision based on your risk level.
Keep in mind that the Z-score for each pair refers to how off the first asset is from the mean compared to the second one, so for example if you see STOCKA vs STOCKB with a Z-score of -1.55, we are regressing STOCKB (Y) on STOCKA (X).
In this case, STOCKB is the quoted asset and STOCKA is the base asset.
In this case, this means that STOCKB is much lower than expected relative to STOCKA, so the trade would be a long position on stock B and short position on stock A.
Seasonality DOW CombinedOverall Purpose
This script analyzes historical daily returns based on two specific criteria:
Month of the year (January through December)
Day of the week (Sunday through Saturday)
It summarizes and visually displays the average historical performance of the selected asset by these criteria over multiple years.
Step-by-Step Breakdown
1. Initial Settings:
Defines minimum year (i_year_start) from which data analysis will start.
Ensures the user is using a daily timeframe, otherwise prompts an error.
Sets basic display preferences like text size and color schemes.
2. Data Collection and Variables:
Initializes matrices to store and aggregate returns data:
month_data_ and month_agg_: store monthly performance.
dow_data_ and dow_agg_: store day-of-week performance.
COUNT tracks total number of occurrences, and COUNT_POSITIVE tracks positive-return occurrences.
3. Return Calculation:
Calculates daily percentage change (chg_pct_) in price:
chg_pct_ = close / close - 1
Ensures it captures this data only for the specified years (year >= i_year_start).
4. Monthly Performance Calculation:
Each daily return is grouped by month:
matrix.set updates total returns per month.
The script tracks:
Monthly cumulative returns
Number of occurrences (how many days recorded per month)
Positive occurrences (days with positive returns)
5. Day-of-Week Performance Calculation:
Similarly, daily returns are also grouped by day-of-the-week (Sunday to Saturday):
Daily return values are summed per weekday.
The script tracks:
Cumulative returns per weekday
Number of occurrences per weekday
Positive occurrences per weekday
6. Visual Display (Tables):
The script creates two visual tables:
Left Table: Monthly Performance.
Right Table: Day-of-the-Week Performance.
For each table, it shows:
Yearly data for each month/day.
Summaries at the bottom:
SUM row: Shows total accumulated returns over all selected years for each month/day.
+ive row: Shows percentage (%) of times the month/day had positive returns, along with a tooltip displaying positive occurrences vs total occurrences.
Cells are color-coded:
Green for positive returns.
Red for negative returns.
Gray for neutral/no change.
7. Interpreting the Tables:
Monthly Table (left side):
Helps identify seasonal patterns (e.g., historically bullish/bearish months).
Day-of-Week Table (right side):
Helps detect recurring weekday patterns (e.g., historically bullish Mondays or bearish Fridays).
Practical Use:
Traders use this to:
Identify patterns based on historical data.
Inform trading strategies, e.g., avoiding historically bearish days/months or leveraging historically bullish periods.
Example Interpretation:
If the table shows consistently green (positive) for March and April, historically the asset tends to perform well during spring. Similarly, if the "Friday" column is often red, historically Fridays are bearish for this asset.
VOL & AVG OverlayCustom Session Volume Versus Average Volume
Description:
This indicator will create an overlay on your chart that will show you the following information:
Custom Session Volume
Average For Selected Session
Percentage Comparison
Options:
Set Custom Time Frame For Calculations
Set Custom Time Frame For Average Comparison
Set Custom Time Zone
Enable / Disable Each Value
Change Text Color
Change Background Color
Change Table location
Example:
Set indicator to 30 period average. Set custom time frame to 9:30am to 10:30am Eastern/New York.
When the time frame for the calculation is closed , the indicator will provide a comparison of the current days volume compared to the average of 30 previous days for that same time frame and display it as a percentage in the table.
In this example you could compare how the first hour of the trading day compares to the previous 30 day's average, aiding in evaluating the potential volume for the remainder of the day.
Notes:
Times must be entered in 24 hour format. (1pm = 13:00 etc.)
This indicator is for Intra-day time frames, not > Day.
If you prefer data in this format as opposed to a plotted line, check out my other indicator: ADR & ATR Overlay
