Kalman Exponential SuperTrendThe Kalman Exponential SuperTrend is a new, smoother & superior version of the famous "SuperTrend". Using Kalman smoothing, a concept from the EMA (Exponential Moving Average), this script leverages the best out of each and combines it into a single indicator.
How does it work?
First, we need to calculate the Kalman smoothed source. This is a kind of complex calculation, so you need to study it if you want to know how it works precisely. It smooths the source of the SuperTrend, which helps us smooth the SuperTrend.
Then, we calculate "a" where:
n = user defined ATR length
a = 2/(n+1)
Now we calculate the ATR over "n" period. Classical calculation, nothing changed here.
Now we calculate the SuperTrend using the Kalman smoothed source & ATR where:
kalman = kalman smoothed source
ATR = Average True Range
m = Factor chosen by user.
Upper Band = kalman + ATR * m
Lower Band = kalman - ATR * m
Now we just smooth it a bit further using the "a" and a concept from the EMA.
u1 = Upper Band a bar ago
l1 = Lower Band a bar ago
u = Upper Band
l = Lower Band
Upper = u1 * (1-a) + u * a
Lower = l1 * (1-a) + u * a
When the classical (not Kalman) source crosses above the Upper, it indicates an uptrend. When it crosses below the Lower, it indicates a downtrend.
Methodology & Concepts
When I took a look at the classical SuperTrend => It was just far too slow, and if I made it faster it was noisy as hell. So I decided I would try to make up for it.
I tried the gaussian, bilateral filter, but then I tried kalman and that worked the best, so I added it. Now it was still too noisy and unconsistent, so I revisited my knowledge of concepts and picked the one from the EMA, and it kinda solved it.
In the core of the indicator, all it does is combine them in a really simple way, but if you go more deeply you see how it fits the puzzlé really well.
It is not about trying out random things´=> but about seeking what it is missing and trying to lessen its bad side.
That is the entire point of this indicator => Offer a unique approach to the SuperTrend type, that lessen the bad sides of it.
I also added different plotting types, this is so everyone can find their favorite
Enjoy Gs!
Moving Averages
EMA 9 + VWAP Bands Crossover With Buy Sell SignalsEMA 9 + VWAP Bands Crossover With Buy Sell Signals
EMA/SMA Band with Buy sellThe EMA Band Indicator is a technical analysis tool that smooths market data using Exponential Moving Averages (EMA).
It displays adaptive upper and lower bands around price to help visualize trend direction and market momentum.
The color of the band changes with EMA slope, allowing users to easily recognize when the trend is strengthening or weakening.
This visual approach helps traders observe price behavior around dynamic support and resistance zones.
It is designed for trend analysis and momentum visualization only — not as a buy or sell signal generator.
EdgeBox: MA DistanceEdgeBox: MA Distance adds a clean HUD showing the percentage distance from the current close to your selected moving averages (default: SMA 100/150/200/250). Values are positive when MAs are above price and negative when below. Also includes ATR% (volatility) and RSI(14). Fully customizable: corner position, font sizes, and text/background colors. A fast context panel for trend and volatility at a glance.
Grok's xAI Signal (GXS) Indicator for BTC V6Grok's xAI Signal (GXS) Indicator: A Simple Guide
Imagine trying to decide if Bitcoin is a "buy," "sell," or "wait" without staring at 10 different charts. The GXS Indicator does that for you—it's like a smart dashboard for BTC traders, overlaying signals right on your price chart. It boils down complex market clues into one easy score (from -1 "super bearish" to +1 "super bullish") and flashes green/red arrows or shaded zones when action's needed. No fancy math overload; just clear visuals like tiny triangles for trades, colored clouds for trends, and a bottom "mood bar" (green=up vibe, red=down, gray=meh).
At its core, GXS mixes three big-picture checks:
Price Momentum (50% weight): Quick scans of RSI (overbought/oversold vibes), MACD (speed of ups/downs), EMAs (is price riding the trend wave?), and Bollinger Bands (is the market squeezing for a breakout?). This catches short-term "hot or not" energy.
Network Health (30% weight): A simple "NVT" hack using trading volume vs. price to spot if BTC feels undervalued (buy hint) or overhyped (sell warning). It's like checking if the crowd's too excited or chill.
Trend Strength (20% weight): ADX filter ensures signals only fire in "trending" markets (not choppy sideways noise), plus a MACD boost for extra momentum nudge.
Why this approach? BTC's wild—pure price charts give false alarms in flat times, while ignoring volume/network ignores the "why" behind moves. GXS blends old-school TA (reliable for patterns) with on-chain smarts (crypto-specific "under the hood" data) and a trend gate (skips 70% of bad trades). It's conservative: Signals need the score to cross ±0.08 and a strong trend, reducing noise for swing/position traders. Result? Fewer emotional guesses, more "wait for confirmation" patience—perfect for volatile assets like BTC where hype kills.
Quick Tips to Tweak for Better Results
Start with defaults, then experiment on historical charts (backtest via TradingView's strategy tester if pairing with one):
Fewer False Signals: Bump thresholds to ±0.15 (buy/sell)—trades only on stronger conviction, cutting whipsaws by 20-30% in choppy markets. Or raise ADX thresh to 28 for "only big trends."
Faster/Slower Response: Shorten EMAs (e.g., 5/21) or RSI (10) for quicker scalps; lengthen (12/50) for swing holds. Test on 4H/daily BTC.
Volume Sensitivity: If NVT flips too often, extend its length to 20—smooths on-chain noise in bull runs.
Visual Polish: Crank cloud opacity to 80% for subtler fills; toggle off EMAs if they clutter. Enable table for score breakdowns during live trades.
Risk Tip: Always pair with stops (e.g., 2-3% below signals). On BTC, tweak in bull markets (looser thresh) vs. bears (tighter).
In short, GXS is your BTC "sixth sense"—balanced, not black-box. Tweak small, track win rate, and let trends lead. Happy trading!
Hull Suite Strategy with Time FilterThis script is a Hull Moving Average–based trend system designed to visualize market direction and filter signals during specific trading hours.
It features:
Dual HMA bands for smoother trend detection
Color changes based on slope to highlight momentum
Optional time filter for signal control within session hours
Compact buy/sell signal markers
You can adjust HMA lengths, time filters, and visual options from the settings panel.
This script is intended for educational and analytical purposes only — not financial advice.
Adaptive Trend OscillatorAdaptive Trend Oscillator (ATO) — Publishing Description and User Guide
Purpose
The Adaptive Trend Oscillator (ATO) is a research and decision‑support indicator designed to help traders assess momentum, trend stability, and changing volatility conditions within a single, unified panel. It provides a configurable signal line, optional confidence bands, adaptive zones, and contextual Bollinger Band cues. ATO is intended for educational and analytical use on TradingView charts and does not execute trades or make investment recommendations.
Methodology (High‑Level Overview)
ATO integrates several well‑known concepts into a cohesive framework while avoiding proprietary implementation details:
- Core Oscillator: A smoothed momentum line derived from standard price‑based calculations (e.g., RSI) with confidence‑aware coloring to reflect relative stability and recent behavior.
- Signal Candle Visualization: A Heikin‑Ashi style signal candle, computed from the oscillator series, helps users visually interpret direction, strength, and transitions. Smoothing controls reduce jitter in the open component to improve readability.
- Volatility Regime Detection: Rolling dispersion and average comparisons classify conditions into Low/Medium/High volatility regimes. This regime context informs confidence scoring and adaptive visualization.
- Adaptive Zones: Overbought/Oversold zones adjust to market conditions using observed distribution and lookback windows, offering dynamic boundaries that can better reflect regime changes compared with fixed thresholds.
- Bollinger Context: Bands applied to the oscillator series provide cues about contraction (squeeze), expansion (divergence), and convergence. Optional fills highlight changing states while remaining purely informational.
- Confidence Bands: Optional envelopes around the oscillator estimate uncertainty ranges derived from recent behavior and regime context. These bands are visual aids, not predictions.
- Performance Mode: An optional toggle that simplifies visuals (thinner lines, reduced fills, disabling inner layers) to improve responsiveness on devices or layouts where rendering cost matters. Calculations remain unchanged.
Inputs and Configuration (Summary)
ATO organizes settings for clarity and quick start:
- Quick Start & Display Toggles: Show/hide key elements such as adaptive zones, confidence bands, and Bollinger fills; enable Performance Mode for faster rendering.
- Core Signal Tuning: Adjust smoothing for the signal candle open, choose theme, and set lookback parameters used in the underlying oscillator and contextual measures.
- Visualization Layers: Confidence bands, inner/outer envelopes, and color themes can be enabled or disabled as needed.
Intended Use and Application
- ATO is most effective as a complementary tool. Use it alongside price action, volume, risk management rules, and broader market context.
- Signals should be validated with multiple factors (support/resistance, higher‑timeframe bias, and instrument characteristics). Parameter tuning is recommended for different assets and timeframes.
- The indicator does not generate trade orders. Any buy/sell interpretations are at the user’s discretion and should be independently evaluated.
Limitations and Risks
- No Guarantees: The indicator cannot predict future prices. Visual cues reflect historical and current data only.
- Lag and Whipsaws: Smoothing improves stability but introduces lag. During range‑bound or choppy conditions, oscillators may experience false starts or rapid flips.
- Data Quality and Availability: Calculations rely on TradingView‑provided data, which may include delays or revisions depending on the data source and subscription.
- User Configuration: Improper or aggressive settings may reduce effectiveness. Always backtest and forward‑test configurations before use.
Required Disclosures and Regulatory Statements
- Educational Use Only: ATO is provided for informational and educational purposes. It does not constitute investment advice, solicitation, or a recommendation to buy or sell any security or derivative.
- No Advisor Relationship: The publisher is not acting as a broker, dealer, investment advisor, or fiduciary. Users are solely responsible for decisions made using the indicator.
- Past Performance: Past performance, whether shown in charts or inferred from historical signals, does not guarantee future results.
- Risk of Loss: Trading and investing involve substantial risk. You can lose more than your initial capital. Consider your financial situation, risk tolerance, and seek advice from a qualified, licensed professional where appropriate.
- Jurisdictional Compliance: Users must comply with all applicable laws and regulations in their jurisdiction and with TradingView’s Terms of Use and House Rules.
Attribution and Code Notes
- ATO relies on standard Pine Script constructs and common analytical concepts (e.g., RSI, Bollinger Band‑style dispersion, Heikin‑Ashi visualization). No external data sources are accessed.
- Calculations and visual layers are original work tailored for research utility. Specific implementation details are intentionally summarized to respect intellectual property and maintain clarity.
Publishing‑Friendly Content Guidelines
- No exaggerated claims, guarantees, or sensational language are used. Descriptions focus on functionality, method, and limitations.
- The indicator is positioned as a tool for research and decision support, not as a promise of profit or certainty.
Getting Started (Suggested Workflow)
1) Add ATO to your chart and choose a theme suitable for your background (Light/Dark).
2) Enable/disable visualization layers (Adaptive Zones, Confidence Bands, Bollinger Fill) to match your preference.
3) Adjust signal smoothing and lookback parameters to fit your instrument and timeframe; conservative settings generally produce steadier signals.
4) Optional: Turn on Performance Mode if you use multiple panels or need faster UI responsiveness; this simplifies visuals while preserving calculations.
5) Validate signals with price structure, volume context, and higher‑timeframe bias before making any decision.
Support and Contact
- For questions or feedback, please use TradingView direct messages to the publisher’s account: .
- Personal financial advice is not provided. Support is limited to general usage guidance and technical questions about the indicator.
Final Reminder
ATO is a tool for analysis, not a guarantee of outcomes. Always manage risk, perform independent research, and remember that past performance does not guarantee future results.
SC_Reversal Confirmation 30 minutes by Claude (Version 1)📉 When to Use
Use this setup when the stock is in a downtrend and a bullish reversal is anticipated.
🔍 Recommended Usage This model is designed for pullback phases, where the asset is declining and a reversal is expected. It helps filter out weak signals and waits for technical confirmation before triggering an entry.
✅ Entry Signal Green triangles appear only when all reversal conditions are fully met. Entry may occur slightly after the bottom, but with a reduced likelihood of false signals.
📊 Suggested Settings Apply on a 30-minute chart using a 100-period Exponential Moving Average (EMA) based on close. Recommended for Cobalt Chart 0.
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Rainbow Moving Averages (v5 safe)Rainbow Moving Averages — plots multiple moving averages of different lengths in a rainbow colour scheme to visualise market trend strength and direction. The spread and alignment of the lines help identify trend changes and momentum shifts.
Institutional DMAs (50/100/200) – with AlertsTitle
D1 DMAs (50/100/200) – Alerts for Trend & Trend Stoppers
Summary
Plots the 50/100/200-day moving averages (DMAs) strictly from the Daily (D1) timeframe and projects them onto any chart timeframe. Comes with a focused alert engine for price↔DMA crosses and DMA↔DMA crosses (Golden/Death Cross). Designed to identify trend direction, potential regime shifts, and “trend stoppers” (dynamic S/R).
What it does
– Computes the 50/100/200 DMAs on D1 only (no matter your chart timeframe)
– Alerts for:
1. Price crossing D1 50/100/200 DMAs
2. DMA crossovers between 50/100/200 (D1-confirmed Golden/Death Cross)
– Optional “close-only” confirmation to reduce noise on price↔DMA alerts
Why DMAs (and why D1)?
DMAs (Daily SMAs) are widely tracked by institutional players—banks, hedge funds, CTAs, pensions—as trend filters and dynamic support/resistance.
– 50 DMA: short-term momentum bias
– 100 DMA: medium-term trend anchor/mean
– 200 DMA: long-term regime line (above = bullish, below = bearish)
Crossover events (e.g., 50>200 Golden Cross, 50<200 Death Cross) are often read as regime changes. D1 confirmation aligns with how institutions evaluate trends and filters intraday noise.
How it helps your trading
– Trend detection: Price above 200 DMA with 50>100>200 = healthy uptrend stacking
– Trend stoppers: Strong reactions at 100/200 DMA often precede pullbacks, pauses, or reversals
– Intraday timing: See D1 levels on lower TFs to plan entries/exits at “big picture” lines
Alerts (selection)
– Price crosses ABOVE/BELOW D1 50 DMA
– Price crosses ABOVE/BELOW D1 100 DMA
– Price crosses ABOVE/BELOW D1 200 DMA
– D1 50 crosses ABOVE/BELOW D1 100
– D1 50 crosses ABOVE/BELOW D1 200
– D1 100 crosses ABOVE/BELOW D1 200
Note: DMA↔DMA alerts are confirmed on the Daily close (fewer false signals).
How to set alerts
1. Add the indicator to your chart
2. Click “Alert” → “+”
3. Condition = this indicator → choose the desired alert line (e.g., “Price crosses ABOVE D1 200 DMA”)
4. Customize message/webhook if needed → Create
Settings
– Colors: 50 = Yellow, 100 = Green, 200 = Red (editable)
– Line width
– “Only alert on bar close” for price↔DMA (recommended for robustness)
– Enable/disable price-cross alerts
– Enable/disable DMA-cross alerts (D1-confirmed)
Best practices
– Trend follow: Favor longs when price is above the 200 DMA; favor shorts below
– Pullback entries: Watch 50/100 DMAs for reactions; add structure/volume confluence
– Regime filter: Use Golden/Death Cross alerts as a high-level bias, refine entries on lower TF signals
Technical notes
– Uses lookahead_off (no future leak)
– DMA cross logic computed and confirmed on D1
– Price↔DMA logic runs on your active timeframe with optional close confirmation
Keywords
DMA, Daily SMA, 50 100 200 MA, Golden Cross, Death Cross, Trend Filter, Dynamic Support Resistance, Institutional Levels, Regime Change, Alert Signals, Intraday with Daily Bias, Hedge Funds, Banks
EMA 10/50 Multi-Pair Scanner (LANRE²)This script is an EMA 10/50 multi-pair scanner that:
Monitors multiple symbols (pairs or indices).
Scans multiple timeframes (M1, M5, H1, etc.).
Detects when the 10 EMA crosses above/below the 50 EMA.
Displays a dashboard showing the current trend ("BUY", "SELL", or "⚠ NEAR CROSS").
Optionally sends alerts when new crosses or near-cross events occur.
Plots EMA lines and buy/sell markers on your current chart.
EMA HeatmapEMA Heatmap — Indicator Description
The EMA Order Heatmap is a visual trend-structure tool designed to show whether the market is currently trending bullish, trending bearish, or moving through a neutral consolidation phase. It evaluates the alignment of multiple exponential moving averages (EMAs) at three different structural layers: short-term daily, medium-term daily, and weekly macro trend. This creates a quick and intuitive picture of how well price movement is organized across timeframes.
Each layer of the heatmap is scored from bearish to bullish based on how the EMAs are stacked relative to each other. When EMAs are in a fully bullish configuration, the row displays a bright green or lime color. Fully bearish alignment is shown in red. Yellow tones appear when the EMAs are mixed or compressing, indicating uncertainty, trend exhaustion, or a change in market character. The three rows combined offer a concise view of whether strength or weakness is isolated to one timeframe or broad across the market.
This indicator is best used as a trend filter before making trading decisions. Traders may find more consistent setups when the majority of the heatmap supports the direction of their trade. Green-dominant conditions suggest a trending bullish environment where long trades can be favored. Red-dominant conditions indicate bearish momentum and stronger potential for short opportunities. When yellow becomes more prominent, the market may be transitioning, ranging, or gearing up for a breakout, making timing more challenging and risk higher.
• Helps quickly identify directional bias
• Highlights when trends strengthen, weaken, or turn
• Provides insight into whether momentum is supported by higher timeframes
• Encourages traders to avoid fighting market structure
It is important to recognize the limitations. EMAs are lagging indicators, so the heatmap may confirm a trend after the initial move is underway, especially during fast reversals. In sideways or low-volume environments, the structure can shift frequently, reducing clarity. This tool does not generate entry or exit signals on its own and should be paired with price action, momentum studies, or support and resistance analysis for precise trade execution.
The EMA Order Heatmap offers a clean and reliable way to stay aligned with the broader market environment and avoid lower-quality trades in indecisive conditions. It supports more disciplined decision-making by helping traders focus on setups that match the prevailing structural trend.
Nosreme v6 - Kulture MetricsNosreme v6 — Kulture Metrics
The evolution of Klarity.
Nosreme brings refined volume intelligence and conviction-based trade mapping to the Kulture Metrics framework.
It only triggers when trend structure and real participation align — filtering false breakouts and fake volume.
Core Elements
• Simple Moving Average (SMA) defines trend bias
• Volume SMA filter validates momentum participation
• ATR-based dynamic risk levels project targets & stops
• Visual “BUY/SELL (Nosreme)” markers at confirmed triggers
• Background shading for directional bias (green = bullish, red = bearish)
Usage
Add to chart, any asset or timeframe (ideal: 15 min – 4 h).
Set alerts “Once per bar close” on Nosreme BUY or Nosreme SELL.
Tune ATR Multiplier / R:R ratio to match volatility profile.
Kulture Metrics • Detroit × Atlanta • Billions Mindset • © 2025
Precision. Discipline. Nosreme.
MMT AI IndicatorOverview
The MMT AI INDICATOR is an advanced technical indicator used to predict trends in price movements by utilizing a combination of traditional AI techniques, and the Momentum Model.
The Beginning MasterThe Beginning Master
Description:
The Beginning Master is a structured micro-futures scalping strategy engineered for small accounts, particularly those trading micro futures such as M2K (Micro Russell 2000), MNQ (Micro Nasdaq), or MES (Micro E-mini S&P 500).
It combines multiple layers of trend, momentum, and volatility logic to identify short-term directional opportunities while maintaining strict capital protection.
The system evaluates:
Trend bias using a dual-moving-average framework that reacts to shifts in short-term momentum.
Momentum strength and confirmation through adaptive readings of directional movement and relative-strength behavior to avoid low-energy markets.
Volatility awareness, adjusting stops and targets based on real-time range analysis so each trade risks only a small, consistent fraction of equity.
Session filters, restricting activity to high-liquidity U.S. hours for more stable fills.
Capital management tools, including a daily loss limit and a unique “profit floor” safeguard that locks gains once a target profit is reached, preventing drawdown from giving back realized profit.
The strategy is optimized for:
Micro-futures traders starting with modest capital (~$100)
Any micro futures instrument (M2K, MNQ, MES, etc.)
Fast execution via automated trade platforms (e.g., TradersPost)
Consistent, repeatable setups rather than prediction
Default settings:
Initial capital: $100
Daily loss cap: $15
Profit-floor protection: $25
Position size: 1 contract
Realistic commission and tick size from exchange data
⚠️ Disclaimer:
This publication is for educational and research purposes only.
It is not financial advice or a solicitation to trade.
Performance results are hypothetical and do not guarantee future returns.
Ehlers Ultrasmooth Filter (USF)# USF: Ultrasmooth Filter
## Overview and Purpose
The Ultrasmooth Filter (USF) is an advanced signal processing tool that represents the pinnacle of noise reduction technology for financial time series. Developed by John Ehlers, this filter implements a complex algorithm that provides exceptional smoothing capabilities while minimizing the lag typically associated with heavy filtering. USF builds upon the Super Smooth Filter (SSF) with enhanced noise suppression characteristics, making it particularly valuable for identifying clear trends in extremely noisy market conditions where even traditional smoothing techniques struggle to produce clean signals.
## Core Concepts
* **Maximum noise suppression:** Provides the highest level of noise reduction among Ehlers' filter designs
* **Optimized coefficient structure:** Uses carefully designed mathematical relationships to achieve superior filtering performance
* **Market application:** Particularly effective for long-term trend identification and minimizing false signals in highly volatile market conditions
The core innovation of USF is its second-order filter structure with optimized coefficients that create an exceptionally smooth frequency response. By careful mathematical design, USF achieves near-optimal noise suppression characteristics while minimizing the lag and waveform distortion that typically accompany such heavy filtering. This makes it especially valuable for identifying major market trends amid significant short-term volatility.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Length | 20 | Controls the cutoff period | Increase for smoother signals, decrease for more responsiveness |
| Source | close | Price data used for calculation | Consider using hlc3 for a more balanced price representation |
**Pro Tip:** USF is ideal for defining major market trends - try using it with a length of 40-60 on daily charts to identify dominant market direction and ignoring shorter-term noise completely.
## Calculation and Mathematical Foundation
**Simplified explanation:**
The Ultrasmooth Filter creates an extremely clean price representation by combining current and past price data with previous filter outputs using precisely calculated mathematical relationships. This creates a highly effective "averaging" process that removes virtually all market noise while still maintaining the essential trend information.
**Technical formula:**
USF = (1-c1)X + (2c1-c2)X₁ - (c1+c3)X₂ + c2×USF₁ + c3×USF₂
Where coefficients are calculated as:
- a1 = exp(-1.414π/length)
- b1 = 2a1 × cos(1.414 × 180/length)
- c1 = (1 + c2 - c3)/4
- c2 = b1
- c3 = -a1²
> 🔍 **Technical Note:** The filter combines both feed-forward (X terms) and feedback (USF terms) components in a second-order structure, creating a response with exceptional roll-off characteristics and minimal passband ripple.
## Interpretation Details
The Ultrasmooth Filter can be used in various trading strategies:
* **Major trend identification:** The direction of USF indicates the dominant market trend with minimal noise interference
* **Signal generation:** Crossovers between price and USF generate high-reliability trade signals with minimal false positives
* **Support/resistance levels:** USF can act as strong dynamic support during uptrends and resistance during downtrends
* **Market regime identification:** The slope of USF helps identify whether markets are in trending or consolidation phases
* **Multiple timeframe analysis:** Using USF across different chart timeframes creates a cohesive picture of nested trend structures
## Limitations and Considerations
* **Significant lag:** The extreme smoothing comes with increased lag compared to lighter filters
* **Initialization period:** Requires more bars than simpler filters to stabilize at the start of data
* **Less suitable for short-term trading:** Generally too slow-responding for short-term strategies
* **Parameter sensitivity:** Performance depends on appropriate length selection for the timeframe
* **Complementary tools:** Best used alongside faster-responding indicators for timing signals
## References
* Ehlers, J.F. "Cycle Analytics for Traders," Wiley, 2013
* Ehlers, J.F. "Rocket Science for Traders," Wiley, 2001
Fishnet Squeeze [Osprey]🟠 Overview
The SMA Fishnet with Squeeze indicator combines a multi-timeframe moving average ribbon system with an advanced squeeze detection algorithm to help traders identify both trend direction and potential breakout opportunities.
🟠 How to Use This Indicator
- Squeeze Breakout Trading
When the indicator signals a squeeze (yellow diamond marker and highlighted background), prepare for a potential breakout in either direction
- Support and Resistance Identification
The twelve SMA levels act as dynamic support and resistance zones. Price often bounces or pauses at these levels, especially at the convergence of multiple SMAs.
Squeeze Settings
- **Enable/Disable**: Toggle squeeze detection on or off
- **Lookback Period**: Adjust the historical comparison window (20-200 bars)
- **Percentile Threshold**: Set sensitivity for squeeze detection (1-20%)
- **Minimum Duration**: Define how many bars must confirm a squeeze (1-10)
- **Visual Customization**: Modify squeeze marker colors to suit your preferences
‼️ Test different values for Lookback Period ! Lower lookback period = more frequent squeeze marks. I suggest using 31 or 100.
🟠 The Fishnet Structure
The indicator employs twelve SMAs ranging from ultra-short-term (3-period) to long-term (200-period), creating a "fishnet" pattern on your chart. This graduated approach provides a comprehensive view of price action across multiple timeframes simultaneously:
🟠 Advanced Squeeze Detection Algorithm
The squeeze detection component identifies periods when all twelve SMAs converge into an unusually tight range, indicating market indecision and potential energy buildup. The algorithm uses several sophisticated filters:
1. ATR-Normalized Range Calculation: The indicator normalizes the SMA range using Average True Range (ATR) to ensure consistent squeeze detection across different volatility environments and price levels.
2. Historical Percentile Analysis: Compares the current normalized range against a customizable lookback period (default: 31 bars) to identify when SMAs are in the bottom percentile of historical tightness.
3. Statistical Validation: Uses z-score analysis to confirm that the current range is significantly below the mean, filtering out false signals.
4. Duration Confirmation: Requires the squeeze condition to persist for a minimum number of consecutive bars (default: 3) to validate genuine compression.
5. Local Minimum Verification: Confirms that the current squeeze represents the tightest point in recent history (20-bar window).
BB LONG 2BX & FVB StrategyThis Strategy is optimized for the 2h timeframe. Happy Charting and you're welcome!
**BB LONG 2BX & FVB Strategy – Simple Text Guide**
---
### **What It Does**
A **long-only trading strategy** that:
- Enters on **strong upward momentum**
- Adds a second position when the trend gets stronger
- Takes profits in parts at **smart price levels**
- Exits fully if the trend weakens or reverses
---
### **Main Tools Used**
| Tool | Simple Meaning |
|------|----------------|
| **B-Xtrender (Oscillator)** | Measures speed of price move. Above 0 = bullish, below 0 = bearish |
| **Weekly & Monthly Timeframes** | Checks if higher timeframes agree with the trade |
| **Red ATR Line** | A moving stop-loss that follows price up |
| **Fair Value Bands (1x, 2x, 3x)** | Profit targets that adjust to market volatility |
---
### **When It Enters a Trade (Long)**
**First Entry:**
- Weekly momentum is **rising**
- Monthly momentum is **positive or increasing**
- No current position
**Second Entry (Pyramiding):**
- Already in trade
- Price breaks **above the Red ATR line** → add same size again
(Max 2 total entries)
---
### **When It Takes Profit (Scaling Out)**
| Level | Action |
|-------|--------|
| **1x Band** | Sell **50%** when price pulls back from this level |
| **2x Band** | Sell **50%** when price pulls back from this level |
| **3x Band** | **Exit everything** when price pulls back from this level |
> You can hit 1x and 2x **multiple times** – it will keep taking 50% each time
---
### **When It Exits Fully (Closes Everything)**
1. Price **closes below Red ATR line**
2. Weekly momentum shows **2 red bars in a row, both falling**
3. Weekly momentum **crosses below zero** AND price is below Red ATR
4. Weekly momentum **drops sharply** (more than 25 points in one bar)
> After full exit, it **won’t re-enter** unless price comes back below 2x band
---
### **Alerts You Get**
Every time price **touches** a profit band, you get an alert:
- “Price touched 1x band from below”
- “Price touched 1x band from above”
- Same for **2x** and **3x**
> One alert per touch, per bar
---
### **On the Chart – What You See**
- **Histogram bars (weekly momentum)**
Lime = up, Red = down
**Yellow highlight** = warning (exit soon)
- **Red broken line** = stop-loss level
- **Blue line** = fair middle price
- **Orange, Purple, Pink lines** = 1x, 2x, 3x profit targets
---
### **Best Used On**
- Daily or 4-hour charts
- Strong trending assets (like Bitcoin, Tesla, S&P 500)
---
### **Quick Rules Summary**
| Do This | When |
|--------|------|
| **Enter** | Weekly up + monthly support |
| **Add more** | Price breaks above Red line |
| **Take 50% profit** | Price pulls back from 1x or 2x |
| **Exit all** | Red line break, weak momentum, or 3x hit |
---
**Simple Idea:**
**Ride strong trends, add when confirmed, take profits in chunks, cut losses fast.**
Reactive Curvature Smoother Moving Average IndicatorSummary in one paragraph
RCS MA is a reactive curvature smoother for any liquid instrument on intraday through swing timeframes. It helps you act only when context strengthens by adapting its window length with a normalized path energy score and by smoothing with robust residual weights over a quadratic fit, then optionally blending a capped one step forecast. Add it to a clean chart and watch the single colored line. Shapes can shift while a bar forms and settle on close. For conservative use, judge on bar close.
Scope and intent
• Markets: major FX pairs, index futures, large cap equities, liquid crypto
• Timeframes: one minute to daily
• Purpose: reduce lag in trends while resisting chop and outliers
• Limits: indicator only, no orders
Originality and usefulness
• Novelty: adaptive window selection by minimizing normalized path energy with directionality bias, plus Huber weighted residuals and curvature aware penalty, finished with a mintick capped forecast blend
• Failure modes addressed: whipsaws from fixed length MAs and outlier spikes that pull means
• Testable: Inputs expose all components and optional diagnostics show chosen length, directionality, and energy
• Portable yardstick: forecast cap uses mintick to stay symbol aware
Method overview in plain language
Base measures
• Range span of the tested window and a path energy defined as the sum of squared price increments, normalized by span
Components
Adaptive window chooser: scans L between Min and Max using an energy over trend score and picks the lowest score
Robust smoother: fits a quadratic to the last L bars, computes residuals, applies Huber weights and an exponential residual penalty scaled down when curvature is high
Forecast blend: projects one step ahead from the quadratic, caps displacement by a multiple of mintick, blends by user weight
Fusion rule
• Final line equals robust mean plus optional capped forecast blend
Signal rule
• Visual bias only: color turns lime when close is above the line, red otherwise
What you will see on the chart
• One colored line that tightens in trends and relaxes in chop
• Optional debug overlays for core value, chosen L, directionality, and energy
• Optional last bar label with L, directionality, and energy
• Reminder: drawings can move intrabar and settle on close
Inputs with guidance
Setup
• Source: price series to smooth
Logic
• Min window l_min. Typical 5 to 21. Higher increases stability, adds lag
• Max window l_max. Typical 40 to 128. Higher reduces noise, adds lag ceiling
• Length step grid_step. Typical 1 to 8. Smaller is finer and heavier
• Trend bias trend_bias. Typical 0.50 to 0.80. Higher favors trend persistence
• Residual penalty lambda_base. Typical 0.8 to 2.0. Higher downweights large residuals more
• Huber threshold huber_k. Typical 1.5 to 3.0. Higher admits more outliers
• Curvature guard curv_guard. Typical 0.3 to 1.0. Higher reduces influence when curve is tight
• Forecast blend lead_blend. 0 disables. Typical 0.10 to 0.40
• Forecast cap lead_limit. Typical 1 to 5 minticks
• Show chosen L and metrics show_debug. Diagnostics toggle
Optional: enable diagnostics to see length, direction, and energy
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while bars are open and settle on close
• Use on standard candles for analysis and combine with your own risk process
Honest limitations and failure modes
• Very quiet regimes can reduce energy contrast, length selection may hover near the bounds
• Gap heavy symbols can disrupt quadratic fit on the window edges
• Excessive forecast blend may look anticipatory; use low values and the cap
Directional EMA - For Loop | Lyro RSDirectional EMA - For Loop | Lyro RS
Introduction
This indicator combines multi-type moving averages, loop-based momentum scoring, and divergence detection for adaptive trend and reversal analysis.
Key Features:
Multiple Moving Average Selection System: Choose from 16 different MA types - HMA, ALMA and JMA etc. To match your style best.
For Loop Based Scoring: Uses a From / To system to calculate cumulative buying/selling pressure across recent price action.
Signal Threshold: Long / Short threshold levels to control the sensitivity for different market conditions.
Divergence Detection: Regular bullish / bearish with clear labels for potential reversal points.
Clean Visuals: Multiple color themes with table and color based indicator line for easy reading.
How It Works:
Core Calculation: The indicator first creates a directional signal by comparing price to your selected moving average, normalized for current volatility.
Loop Analysis: This signal feeds into a for-loop that scores recent price history, generating a cumulative momentum value.
Signal Generation:
Bullish signals trigger when the score crosses above the Upper Threshold
Bearish signals trigger when the score crosses below the Lower Threshold
Divergence Alerts: Automatically detects when price makes new highs/lows that aren't confirmed by the oscillator.
Practical Use:
Trend Identification: The color-coded oscillator and signal table help confirm trend direction.
Reversal Warning: Divergence labels highlight potential trend exhaustion points for careful watch.
Customization:
Adjust MA type and length for sensitivity tuning
Modify loop parameters (From/To) to change analysis depth
Fine-tune threshold levels for signal frequency
Enable/disable divergence detection as needed
⚠️ Disclaimer
This tool is for technical analysis education only. It does not guarantee results or constitute financial advice. Always use proper risk management and combine with other analysis methods. Past performance doesn't predict future results.
vagab0nd AlgoCombination of simple and exponential moving averages, SuperIchi cloud by LuxAlgo (love that group!), and a conglomeration of various indicators I've compiled over the years to try to spot tops and bottoms.
My custom indicator will highlight the background either green or orange/red and will show small yellow, or larger white arrows to indicate potential tops and bottoms. It is oscillator based so it can often show a strong signal for a top or bottom where price can rebound from, but will often retest or even stop loss run the previous signal area while not showing another signal. This indicates an underlying divergence that can potentially be taken advantage of.
Magnus Bestest 2This indicator is a sophisticated version of my Magnus Bestest signature move only as this script is highly advanced and has a huge amount of lines of code and structures so I had to create a new separate indicator for it. It signals only when there is a very nice liquidity and broken pivot points, confirming a truly nice trade opportunity.
My main indicator named Magnus Bestest is still working great and has all the other signals and alerts.
DISCLAIMER: I'm not a financial adviser and this is not a financial advise, just for educational purposed. Remember, most traders lose money.
Trading Toolkit - Comprehensive AnalysisTrading Toolkit – Comprehensive Analysis
A unified trading analysis toolkit with four sections:
📊 Company Info
Fundamentals, market cap, sector, and earnings countdown.
📅 Performance
Date‑range analysis with key metrics.
🎯 Market Sentiment
CNN‑style Fear & Greed Index (7 components) + 150‑SMA positioning.
🛡️ Risk Levels
ATR/MAD‑based stop‑loss and take‑profit calculations.
Key Features
CNN‑style Fear & Greed approximation using:
Momentum: S&P 500 vs 125‑DMA
Price Strength: NYSE 52‑week highs vs lows
Market Breadth: McClellan Volume Summation (Up/Down volume)
Put/Call Ratio: 5‑day average (inverted)
Volatility: VIX vs 50‑DMA (inverted)
Safe‑Haven Demand: 20‑day SPY–IEF return spread
Junk‑Bond Demand: HY vs IG credit spread (inverted)
Normalization: z‑score → percentile (0–100) with ±3 clipping.
CNN‑aligned thresholds:
Extreme Fear: 0–24 | Fear: 25–44 | Neutral: 45–54 | Greed: 55–74 | Extreme Greed: 75+.
Risk tools: ATR & MAD volatility measures with configurable multipliers.
Flexible layout: vertical or side‑by‑side columns.
Data Sources
S&P 500: CBOE:SPX or AMEX:SPY
NYSE: INDEX:HIGN, INDEX:LOWN, USI:UVOL, USI:DVOL
Options: USI:PCC (Total PCR), fallback INDEX:CPCS (Equity PCR)
Volatility: CBOE:VIX
Treasuries: NASDAQ:IEF
Credit Spreads: FRED:BAMLH0A0HYM2, FRED:BAMLC0A0CM
Risk Management
ATR risk bands: 🟢 ≤3%, 🟡 3–6%, ⚪ 6–10%, 🟠 10–15%, 🔴 >15%
MAD‑based stop‑loss and take‑profit calculations.
Author: Daniel Dahan
(AI Generated, Merged & enhanced version with CNN‑style Fear & Greed)
