JXMJXRS - Anchor Bias ToolThe Anchor Bias Tool is a precision-based market structure tool designed to help traders visually quantify bias from any significant market event. Rather than relying on subjective trendlines or reactive signals, this tool lets you define a specific candle. Typically tied to a news event, breakout, or key swing point and then monitor how price behaves from that point forward.
You set an anchor candle using a specific date and time (UTC). The tool draws a horizontal anchor line at the closing price of that candle, calculates real-time price deviation from that level as a percentage, and then identifies whether price is in a bullish, bearish, or neutral zone based on how far it has moved from the anchor. This creates a clear, objective method for assessing whether the market is following through on an event or fading it.
Anchor Time (UTC) -
Define the exact candle you want to anchor from typically a reaction to a news event, breakout, or structural shift. All bias calculations begin from this candle’s closing price.
Bias Threshold (%) -
Sets how far price must move away from the anchor to be considered a valid directional bias. For example, 2.0% means price must be at least 2% above or below the anchor to enter bullish or bearish territory.
Show Bias Zones -
Toggles visual background shading on the chart. Green represents bullish bias, red for bearish. Helping you quickly identify where the market stands relative to the anchor.
Show Bias Labels -
Enables or disables the live label showing current bias (Bullish, Bearish, or Neutral) along with the real-time % deviation from the anchor level
Volatilità
Signalgo XSignalgo X
Signalgo X is a sophisticated indicator crafted for traders who demand a disciplined, multi-layered approach to market analysis and trade management. This overview will help you understand its capabilities, logic, and how it can elevate your trading.
Core Concept
Signalgo X is built to:
Scan multiple timeframes simultaneously for price, volume, and volatility patterns.
Filter out unreliable signals during periods of market hype or manipulation.
Automate trade management with dynamic take-profit (TP), stop-loss (SL), and trailing logic.
Deliver actionable, visual signals and alerts for timely, confident decisions.
Inputs & Controls
Preset System Parameters:
News Sensitivity: Determines how responsive the indicator is to price moves.
Hype Filter Strength: Sets how aggressively the system avoids volatile, manipulated, or news-driven periods.
User-Configurable:
Show TP/SL Logic: Turn on/off the display of take-profit and stop-loss levels directly on your chart.
How Signalgo X Works
1. Multi-Timeframe Market Analysis
Signalgo X continuously monitors:
Closing price
Trading volume
Volatility (ATR)
across six distinct timeframes, from 1 hour to 3 months. This layered approach ensures that signals are validated by both short-term momentum and long-term trends.
2. Price, Volume, and Volatility Synthesis
Price Change: The system tracks percentage changes over each timeframe to gauge momentum.
Volume Ratio: By comparing current volume to a moving average, it detects unusual spikes that may signal institutional activity or manipulation.
Volatility: Measures the intensity of price movements relative to average ranges, helping to identify breakout or exhaustion scenarios.
3. Proprietary Anti-Hype Filter
A unique scoring mechanism evaluates:
Volume spikes without corresponding price action
Sudden jumps in volatility
Conflicting signals across timeframes
Social hype proxies (e.g., sharp moves on low volume)
If the market is deemed “hyped,” all trading signals are suppressed and a clear warning is shown, keeping you out of unpredictable conditions.
4. Signal Classification & Mapping
Significant Moves: Only price actions that exceed a sensitivity threshold and are confirmed by volume/volatility are considered.
Bullish/Bearish Signals: Generated for each timeframe.
Signal Strength: Categorized as regular, or strong based on multi-timeframe agreement.
Entry & Exit Strategy
Entry Logic
Long (Buy) Entry: Triggered when bullish signals are detected (of any strength) and no hype is present.
Short (Sell) Entry: Triggered when bearish signals are detected and no hype is present.
Exit & Trade Management
Stop Loss (SL): Placed at a calculated distance from entry, adapting to recent volatility.
Take Profits (TP1, TP2, TP3): Three profit targets, each at a greater reward multiple.
Trailing Stop: After the first take-profit is hit, the stop-loss moves to breakeven and a trailing stop is activated to protect further gains.
Event Tracking: The indicator visually marks when each TP or SL is hit, providing real-time feedback.
Chart Plots: All relevant SL, TP, and trailing stop levels are clearly marked for both long and short trades.
Labels: Entry, exit, and signal strength events are color-coded and visually prominent.
Alerts: Built-in alert conditions allow you to set up TradingView notifications for strong/regular buy/sell signals and hype warnings.
Trading Strategy Application
Multi-Timeframe Confirmation: Only strong signals confirmed by several timeframes are acted upon, reducing false positives.
Volume & Volatility Awareness: The indicator avoids low-quality, “fakeout” signals by requiring confirmation from both price and volume/volatility.
Hype Avoidance: Keeps you out of the market during news-driven or manipulated periods, helping to protect your capital.
Automated Discipline: The TP/SL logic enforces a rules-based exit strategy, helping you lock in profits and limit losses without emotional interference.
Who Should Use Signalgo X?
Signalgo X is ideal for traders who want:
Systematic, high-confidence signals
Automated and disciplined trade management
Protection against unpredictable market events
Clear, actionable visuals and alerts
ATR > VXN Alert (5m)ATR > VXN Volatility Divergence Indicator
This custom TradingView indicator monitors real-time volatility divergence between realized volatility (via Average True Range, ATR) and implied volatility (via the CBOE NASDAQ Volatility Index, VXN). It is inspired by the GJR-GARCH (Glosten-Jagannathan-Runkle Generalized Autoregressive Conditional Heteroskedasticity) model, which captures asymmetric volatility dynamics—particularly how markets respond more sharply to negative shocks than to positive ones.
Core Logic:
Chart on NQ (5 minute timeframe)
ATR (5-min) reflects realized intraday volatility of the Nasdaq 100 futures (NQ).
VXN (5-min, delayed) represents forward-looking implied volatility.
The indicator highlights regime shifts in volatility:
ATR < VXN: Volatility compression → potential energy building up (market coiling).
ATR > VXN: Volatility expansion → real movement exceeds expectations → potential breakout zone.
Visuals & Alerts:
Background turns green when ATR crosses above VXN, signaling a bullish expansion regime.
Background turns red when ATR drops below VXN, signaling compression or risk-off environment.
Custom alerts trigger on volatility regime shifts for breakout traders.
Application (Manual GJR-GARCH Strategy):
Similar to how the GJR-GARCH model captures volatility clustering and asymmetry, this indicator identifies when actual price volatility (ATR) begins to spike beyond implied forecasts (VXN), often after periods of contraction—mirroring a conditional variance shock in the GARCH framework.
Traders can align with directional bias using technical confluence (order flow, structure breaks, liquidity zones) once expansion is confirmed.
Fundig Rate OI# 🚀 Bitcoin Funding Rate + Open Interest Indicator - PineScript v6
## 📋 Summary
I've developed a **Bitcoin-specific** indicator that combines **Funding Rate** with **normalized Open Interest** for advanced futures analysis. After months of testing exclusively on BTC, the results have been excellent for identifying reversal points and confirming trends.
---
## 🎯 Why Bitcoin Only?
**Technical reasons:**
- BTC has the highest volume and liquidity in futures
- More consistent and reliable data
- Less manipulation than altcoins
- More stable correlation between FR and OI
**Problem it solves:**
- Traditional indicators only show one metric
- Difficult to correlate FR with BTC market volume/interest
- Lack of normalization makes OI hard to interpret
- Need for a tool specific to the king of cryptos
**Solution:**
✅ **Dynamic Funding Rate** optimized for BTC
✅ **Normalized Open Interest** (3 different methods)
✅ **Binance BTCUSDTPERP data** exclusively
✅ **Alert system** calibrated for BTC volatility
✅ **Real-time info table**
---
## 🔧 Technical Features
### Main Configurations:
- **Fixed symbol:** BTCUSDTPERP (Binance)
- **Lower timeframe:** 1m, 5m, 15m for precise calculations
- **OI normalization methods:**
- Min-Max (0-1 range)
- RSI (momentum-based)
- Z-Score (statistical distribution)
- **Optimized lookback:** 100 bars (ideal for BTC)
- **Alert system:** Thresholds calibrated for BTC
### Data Sources:
🔸 **Premium Index:** BINANCE:BTCUSDT_PREMIUM
🔸 **Open Interest:** BINANCE:BTCUSDTPERP_OI
🔸 **Timeframes:** From 1m to Daily
🔸 **Precision:** 4 decimals for FR
---
## 📊 How to Interpret Bitcoin Signals
### Funding Rate (Histogram):
- **FR > 0.1%:** BTC longs paying high → Possible short
- **FR < -0.1%:** BTC shorts paying high → Possible long
- **FR extreme (>0.5%):** High probability of BTC reversal
- **FR neutral (±0.05%):** Balanced market
### Open Interest (Blue line):
- **OI > 0.8 + high FR:** Many BTC longs trapped → Bearish
- **OI < 0.2 + low FR:** Short capitulation → Bullish
- **OI divergence:** BTC trend weakening
### Bitcoin-Specific Combinations:
1. **FR > 0.3% + OI > 0.85:** Imminent bearish reversal
2. **FR < -0.2% + OI < 0.15:** Probable bullish reversal
3. **FR oscillating + OI growing:** Accumulation before move
---
## 💡 Real Bitcoin Use Cases
**Example 1 - Bullish Reversal (March 2024):**
```
Situation: BTC falling from 73k to 60k
FR: -0.18% (shorts paying high premium)
OI: 0.12 (very low, short capitulation)
Result: Bounce to 67k (+11%)
```
**Example 2 - Local Top (February 2024):**
```
Situation: BTC at ATH 73.8k
FR: +0.42% (desperate longs paying)
OI: 0.91 (extremely high)
Result: Correction to 60k (-18%)
```
**Example 3 - Bullish Continuation:**
```
Situation: BTC consolidating at 45k
FR: +0.05% (neutral)
OI: 0.65 (steadily growing)
Result: Breakout to 52k (+15%)
```
---
## 🚨 Bitcoin-Calibrated Alert System
The indicator includes Bitcoin-specific alerts:
1. **BTC FR Spike Up:** FR > 0.15% (adjusted to BTC volatility)
2. **BTC FR Spike Down:** FR < -0.15%
3. **BTC OI Extreme High:** Normalized OI > 0.88
4. **BTC OI Extreme Low:** Normalized OI < 0.12
**Recommended BTC configuration:**
- **Scalping:** 5m and 15m
- **Swing Trading:** 1h and 4h
- **Position Trading:** Daily
- Always combine with BTC support/resistance
---
## 📈 Bitcoin Backtesting Results
**Testing period:** 12 months (July 2023 - July 2024)
**Exclusive pair:** BTCUSDTPERP
**Timeframes:** 15m, 1h, 4h, 1D
**BTC-specific results:**
- **Reversal accuracy:** ~78% (better than altcoins)
- **False signals:** Reduced 45% vs FR alone
- **Best timeframe:** 1h for swing, 15m for scalping
- **Worst period:** Sideways market (Nov-Dec 2023)
- **Best period:** Strong trends (Oct 2023, Mar 2024)
**Key statistics:**
- **23 major reversal signals:** 18 successful
- **Average gain:** +8.3% per successful trade
- **Average loss:** -2.1% per failed trade
- **Risk/reward ratio:** 1:3.9
Angular Volatility📘 Angular Volatility – Technical Indicator for Trend Intensity Analysis
Angular Volatility is an advanced technical analysis tool developed specifically for cryptocurrency markets on the Binance platform. Its primary objective is to detect structural shifts in price dynamics with greater precision by analyzing the combined behavior of market volume and the angular slope of a customizable moving average.
Unlike conventional indicators that operate directly over the price chart, this script displays all of its metrics within a dedicated secondary window, allowing a cleaner and more isolated view of critical movements such as acceleration, pause, or potential reversals. In addition, it includes a robust system for volatility intensity classification, automated alerts, and a live technical info table that summarizes key real-time values.
🎯 What does Angular Volatility analyze?
Angular Volatility measures the interaction between traded volume and the angle of a moving average selected by the user from six types (SMA, EMA, WMA, HMA, ALMA, and SWMA). From these variables, the system generates:
- Angular Volatility Index: A composite value representing the product of volume and angular slope, reflecting the true strength behind a move.
- Angular Oscillator: A standalone line that displays the directional angle (in degrees) of the selected moving average, limited between ±90°.
- Volatility Intensity Levels: Automatic classification of peaks into four levels—moderate, elevated, high, and extreme—displayed with distinct colors and geometric shapes.
- Technical Data Table: A real-time panel showing both the current angle of the moving average and the current value of the Angular Volatility Index in a compact, user-friendly format.
- Custom Alerts System: Five built-in alert conditions allow users to monitor key volatility events without needing to watch the chart constantly.
⚙️ Configuration Parameters
The script includes multiple configuration sections that allow users to fine-tune both its analytical precision and visual appearance:
- High Volume Detection: Adjustable historical depth and sensitivity to identify significant volume spikes.
- Initial Moving Average Settings: Selection of MA type, length, offset, and dynamic coloring based on slope angle.
- Volatility Index Options: Fully customizable visuals, synced with the angle values set in the moving average section.
- Volatile Intensity Styling: Choose which levels to display, customize their colors and icons, and optionally color the main chart candles for quick interpretation.
- Information Table: Options to show/hide the table, adjust size and position, and customize background/text colors.
🧠 Compatibility and Technical Recommendations
This indicator was developed to operate exclusively on Binance using the following timeframes only: 1m – 5m – 15m – 30m – 1h – 4h – 1D.
This restriction is deliberate, ensuring consistency in the mathematical model used to calculate angular data. Using this script on other platforms or timeframes may result in inaccurate readings or logic errors, as asset types like stocks, forex, or indices behave differently in terms of volume structure and slope normalization.
If applied to unsupported markets or timeframes, the script will automatically display a warning message without calculating or drawing technical values.
🔬 Practical Example
The following case study—applied to the BTC chart on a 1-hour timeframe—demonstrates how volatility intensity levels behave in structured scenarios such as channel breakdowns, rebound phases, false breakouts, and high-energy consolidation zones:
🔻 Letter A: Downward breakout and full intensity sequence
- The price was moving within a fairly uniform descending channel, which ends with a false breakout to the upside—quickly invalidated as a market trap.
- The true breakout occurs to the downside through a strong red candle, categorized by the system as moderate intensity (gray).
- This candle is followed by a Doji, then a smaller red candle also marked as moderate intensity, followed by a larger red candle showing high intensity (white), and finally a stronger red candle painted yellow, indicating extreme intensity.
- This full sequence (moderate → moderate → high → extreme) marks a technical climax, after which the price begins a progressive reversal.
- Although the drop unfolds over five red candles, the subsequent recovery takes place over 18 candles, mostly green and smaller in size, forming a “V” shape: sharp decline followed by a steady upward climb.
- This entire section is enclosed within an oval labeled A, with the four intensity levels clearly reflected on both the main chart and the Angular Volatility panel.
🔼 Letter B: Ascending channel and breakout with increasing bullish pressure
- After the rebound described in section A, the price begins forming a new ascending channel, marked with the letter B. This channel starts right where the previous range ends, with a very slight upward offset—nearly indistinguishable.
- In the final stage of this channel, a green candle classified as moderate intensity (gray) attempts a breakout. It is followed by a stronger green candle, painted brown, indicating elevated intensity and confirming bullish acceleration.
- Both candles and the corresponding peak on the Angular Volatility indicator are enclosed in an oval labeled B, representing a second wave of directional energy.
⛓️ Letter C: Resistance zone and consolidation following extreme volatility
- The upward movement continues until it reaches a resistance level, where a large green candle emerges, painted yellow to denote extreme intensity.
- Unlike the previous case in section A, this movement does not trigger a sharp reversal, but rather a technical pause followed by sideways consolidation, forming a horizontal range.
- This zone is marked on the chart with an oval labeled C, representing a classic case of stopping volume and range formation.
Fear and Greed Indicator [DunesIsland]The Fear and Greed Indicator is a TradingView indicator that measures market sentiment using five metrics. It displays:
Tiny green circles below candles when the market is in "Extreme Fear" (index ≤ 25), signalling potential buys.
Tiny red circles above candles when the market is in "Greed" (index > 75), indicating potential sells.
Purpose: Helps traders spot market extremes for contrarian trading opportunities.Components (each weighted 20%):
Market Momentum: S&P 500 (SPX) vs. its 125-day SMA, normalized over 252 days.
Stock Price Strength: Net NYSE 52-week highs (INDEX:HIGN) minus lows (INDEX:LOWN), normalized.
Put/Call Ratio: 5-day SMA of Put/Call Ratio (USI:PC).
Market Volatility: VIX (VIX), inverted and normalized.
Stochastic RSI: 14-period RSI on SPX with 3-period Stochastic SMA.
Alerts:
Buy: Index ≤ 25 ("Extreme Fear - Potential Buy").
Sell: Index > 75 ("Greed - Potential Sell").
Funding Ratio BinanceThis advanced indicator is designed for perpetual futures traders looking for an edge by understanding market dynamics on Binance. It provides key insights into the Premium Rate and Estimated Funding Rate, helping you make informed decisions about your trades.
What does this indicator offer you?
Premium Rate (4H): Displays the real-time difference between the perpetual futures price and the spot price on Binance. A positive premium can indicate bullish demand from futures buyers, while a negative premium suggests bearish demand. This data updates every 4 hours.
Estimated Funding Rate (4H): Calculates an estimate of the upcoming funding rate to be applied on Binance. This rate is crucial, as it determines payments between long and short positions. A positive rate means longs pay shorts, and vice versa. Knowing this estimate can help you anticipate market movements and manage your positions.
Suggested Position: Based on the current Premium Rate, the indicator provides a suggested position ("Long", "Short", or "Neutral"). This is a helpful guide for evaluating the overall sentiment of the perpetual futures market relative to the spot price.
Key Features:
Real-time Data: Obtains information directly from Binance (via TradingView) to ensure maximum accuracy.
Fixed Timeframe: Premium and funding calculations are performed on a fixed 4-hour timeframe, regardless of your current chart's timeframe.
Configurable: You can adjust the fixed Binance interest rate used in the Estimated Funding Rate calculation, as well as clamping limits to fine-tune its relevance. You can also customize the table's position on your chart to suit your preferred layout.
Automatic Pair Detection: For the Premium Rate, the indicator automatically detects the cryptocurrency pair you are currently viewing, ensuring relevant data without extra configuration.
HL/OL Histogram + (Close-Open)🧠 Core Concept
This indicator is designed to detect meaningful directional intent in price action using a combination of:
Intrabar candle structure (high - open, open - low)
Net price momentum (close - open)
Timed trigger levels (frozen buy/sell prices based on selected timeframe closes)
The core idea is to visually separate bullish and bearish energy in the current bar, and to mark the price at which momentum flips from down to up or vice versa, based on a change in the close - open differential.
🔍 Components Breakdown
1. Histogram Bars
Green Bars (high - open): Represent bullish upper wicks, showing intrabar strength above the open.
Red Bars (open - low): Represent bearish lower wicks, showing pressure below the open.
Plotted as histograms above and below the zero line.
2. Close–Open Line (White)
Plots the difference between close and open for each bar.
Helps you visually track when momentum flips from negative to positive, or vice versa.
A bold black zero line provides clear reference for these flips.
3. Buy/Sell Signal Logic
A Buy Trigger is generated when close - open crosses above zero
A Sell Trigger occurs when close - open crosses below zero
These trigger events are one-shot, meaning they’re only registered once per signal direction. No retriggers occur until the opposite condition is met.
📈 Trigger Price Table (Static)
On a signal trigger, the close price from a lower timeframe (15S, 30S, 1, 2, 3, or 5 min) is captured.
This price is frozen and displayed in a table at the top-right of the pane.
The price remains fixed until the opposite trigger condition fires, at which point it is replaced.
Why close price?
Using the close from the lower timeframe gives a precise, decisive reference point — ideal for planning limit entries or confirming breakout commitment.
🛠️ Use Cases
Momentum traders can use the histogram and line to time entries after strong open rejection or close breakouts.
Scalpers can quickly gauge intrabar sentiment reversals and react to new momentum without waiting for candle closes.
Algo builders can use the frozen price logic as precise entry or confirmation points in automated strategies.
VIX-Price Covariance MonitorThe VIX-Price Covariance Monitor is a statistical tool that measures the evolving relationship between a security's price and volatility indices such as the VIX (or VVIX).
It can give indication of potential market reversal, as typically, volatility and the VIX increase before markets turn red,
This indicator calculates the Pearson correlation coefficient using the formula:
ρ(X,Y) = cov(X,Y) / (σₓ × σᵧ)
Where:
ρ is the correlation coefficient
cov(X,Y) is the covariance between price and the volatility index
σₓ and σᵧ are the standard deviations of price and the volatility index
Enjoy!
Features
Dual Correlation Periods: Analyze both short-term and long-term correlation trends simultaneously
Adaptive Color Coding: Correlation strength is visually represented through color intensity
Market Condition Assessment: Automatic interpretation of correlation values into actionable market insights
Leading/Lagging Analysis: Optional time-shift analysis to detect predictive relationships
Detailed Information Panel: Real-time statistics including current correlation values, historical averages, and trading implications
Interpretation
Positive Correlation (Red): Typically bearish for price, as rising VIX correlates with falling markets. This is what traders should be looking for.
Negative Correlation (Green): Typically bullish for price, as falling VIX correlates with rising markets
How to use it
Apply the indicator to any chart to see its correlation with the default VIX index
Adjust the correlation length to match your trading timeframe (shorter for day trading, longer for swing trading)
Enable the secondary correlation period to compare different timeframes simultaneously
For advanced analysis, enable the Leading/Lagging feature to detect if VIX changes precede or follow price movements
Use the information panel to quickly assess the current market condition and potential trading implications
Time-Specific Volume AverageA volume indicator based on historic volume.
Checks for the average volume in the past few days at the same time of day. This helps you determine when there is truly volume in the markets.
We will see often see sustained volume above the average during a clear trend. If you see spikes in volume without it being sustained above the average, it is very likely that the trend will die off quickly.
This is very helpful in determining whether to trade based on a trend following system, or a range based system.
Settings are below:
Days to average: Number of days to look back(tradingview has limits depending on your plan)
SMA Length: Number of "volume averages" to look at. Keep this at 1 if you want the average volume at the exact moment in the day. If you increase it, will also average in the past few candles of "volume averages".
SMA Multiplier: Multiplies the SMA by this amount(helps to get higher quality trends)
Dynamic Ray BandsAbout Dynamic Ray Bands
Dynamic Ray Bands is a volatility-adaptive envelope indicator that adjusts in real time to evolving market conditions. It uses a Double Exponential Moving Average (DEMA) as its central trend reference, with upper and lower bands scaled according to current volatility measured by the Average True Range (ATR).
This creates a dynamic structure that visually frames price action, helping traders identify areas of potential trend continuation, overextension, or mean reversion.
How It Works
🟡 Centerline (DEMA)
The central yellow line is a Double Exponential Moving Average, which offers a smoother, less laggy trend signal than traditional moving averages. It represents the market’s short- to medium-term “equilibrium.”
🔵 Outer Bands
Plotted at:
Upper Band = DEMA + (ATR × outerMultiplier)
Lower Band = DEMA - (ATR × outerMultiplier)
These bands define the extreme bounds of current volatility. When price breaks above or below them, it can signal strong directional momentum or overbought/oversold conditions, depending on context. They're often used as trend breakout zones or to time exits after extended runs.
🟣 Inner Bands
Plotted closer to the DEMA:
Inner Upper = DEMA + (ATR × innerMultiplier)
Inner Lower = DEMA - (ATR × innerMultiplier)
These are preliminary volatility thresholds, offering early cues for potential expansion or reversal. They may be used for scalping, tight stop zones, or pre-breakout positioning.
🔁 Dynamic Width (Bands are Dynamically Adjusted Per Tick)
The width of both inner and outer bands is based on ATR (Average True Range), which is recalculated in real time. This means:
During high volatility, the bands expand, allowing for wider price fluctuations.
During low volatility, the bands contract, tightening range expectations.
Unlike fixed-width channels or standard Bollinger Bands (which use standard deviation), this per-tick adjustment via ATR enables Dynamic Ray Bands to reduce false signals in choppy markets and remain more reactive during trending conditions.
⚙️ Inputs
DMA Length — Period for the central DEMA.
ATR Length — Lookback used for ATR volatility calculations.
Outer Band Multiplier — Controls sensitivity of extreme bands.
Inner Band Multiplier — Controls proximity of inner bands.
Show Inner Bands — Toggle for plotting the inner zone.
🔔 Alerts
Alert conditions are included for:
Price closing above/below the outer bands (trend momentum or overextension)
Price closing above/below the inner bands (early signs of strength/weakness)
🧭 Use Cases
Breakout detection — Catch price continuation beyond the outer bands.
Volatility filtering — Adjust trade logic based on band width.
Mean reversion — Monitor for snapbacks toward the DEMA after price stretches too far.
Trend guidance — Use band slope and price position to confirm direction.
⚠️ Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice or a recommendation to trade any specific market or security. Always test indicators thoroughly before using them in live trading.
Adaptive Causal Wavelet Trend FilterThe Adaptive Causal Wavelet Trend Filter is a technical indicator implementing causal approximations of wavelet transform properties for better trend detection with adaptive volatility response.
The Adaptive Causal Wavelet Trend Filter (ACWTF) applies mathematical principles derived from wavelet analysis to financial time series, providing robust trend identification with minimal lag. Unlike conventional moving averages, it preserves significant price movements while filtering market noise through signal processing that i describe below.
I was inspired to build this indicator after reading " Wavelet-Based Trend Identification in Financial Time Series " by In, F., & Kim, S. 2013 and reading about Mexican Hat wavelet filters.
The ACWTF maintains optimal performance across varying market regimes without requiring parameter adjustments by adapting filter characteristics to current volatility conditions.
Mathematical Foundation
Inspired by the Mexican Hat wavelet (Ricker wavelet), this indicator implements causal approximations of wavelet filters optimized for real-time financial analysis. The multi-resolution approach identifies features at different scales and the adaptive component dynamically adjusts filtering characteristics based on local volatility measurements.
Key mathematical properties include:
Non-linear frequency response adaptation
Edge-preserving signal extraction
Scale-space analysis through dual filter implementation
Volatility-dependent coefficient adjustment, which I love
Filter Methods
Adaptive: Implements a volatility-weighted combination of multiple filter types to optimize the time-frequency resolution trade-off
Hull: Provides a causal approximation of wavelet edge detection properties with forward-projection characteristics
VWMA: Incorporates volume information into the filtering process for enhanced signal detection
EMA Cascade: Creates a multi-pole filter structure that approximates certain wavelet scaling properties
Suggestion: try all as they will provide slightly different signals. Try also different time-frames.
Practical Applications
Trend Direction Identification: Clear visual trend direction with reduced noise and lag
Regime Change Detection: Early identification of significant trend reversals
Market Condition Analysis: Integrated volatility metrics provide context for current market behavior
Multi-timeframe Confirmation: Alignment between primary and secondary filters offers additional confirmation
Entry/Exit Timing: Filter crossovers and trend changes provide potential trading signals
The comprehensive information panel provides:
Current filter method and trend state
Trend alignment between timeframes
Real-time volatility assessment
Price position relative to filter
Overall trading bias based on multiple factors
Implementation Notes
Log returns option provides improved statistical properties for financial time series
Primary and secondary filter lengths can be adjusted to optimize for specific instruments and timeframes
The indicator performs particularly well during trend transitions and regime changes
The indicator reduces the need for using additional indicators to check trend reversion
FVG Candle TYHE42This indicator highlights potential Fair Value Gaps (FVGs) directly on the relevant candle by changing its body color.
The logic is simple yet effective:
A bullish FVG is detected when the current low is above the high from two candles back.
A bearish FVG is detected when the current high is below the low from two candles back.
When such a gap is detected, the previous candle is colored (default: yellow) to provide a clean, unobtrusive visual cue. This helps traders quickly identify price imbalances without cluttering the chart with shapes or labels.
Users can customize the highlight color from the settings to better suit their chart theme or personal preference.
This indicator is especially useful for traders using Smart Money Concepts (SMC), ICT, or other price imbalance-based strategies.
Capital Risk OptimizerCapital Risk Optimizer 🛡️
The Capital Risk Optimizer is an educational tool designed to help traders study capital efficiency, risk management, and scaling strategies when using leverage.
This script calculates and visualizes essential metrics for managing leveraged positions, including:
Entry Price – The current market price.
Stop Loss Level – Automatically derived using the 30-bar lowest low minus 1 ATR (default: 14-period ATR), an approach designed to create a dynamic, volatility-adjusted stop loss.
Stop Loss Distance (%) – The percentage distance between entry and stop.
Maximum Safe Leverage – The highest leverage allowable without risking liquidation before your stop is reached.
Margin Required – The amount of collateral necessary to support the desired position size at the calculated leverage.
Position Size – The configurable notional value of your trade.
These outputs are presented in a clean, customizable table overlay so you can quickly understand how position sizing, volatility, and leverage interact.
By default, the script uses a 14-period ATR combined with the lowest low of the past 30 bars, providing an optimal balance between sensitivity and noise for defining stop placement. This methodology helps traders account for market volatility in a systematic way.
The Capital Risk Optimizer is particularly useful as a portfolio management tool, supporting traders who want to study how to scale into positions using risk-adjusted sizing and capital efficiency principles. It pairs best with backtested strategies, and does not directly produce signals of any kind.
How to Use:
Set your desired position size.
Adjust the ATR and lookback settings to fine-tune stop loss placement.
Study the resulting leverage and margin requirements in real time.
Use this information to simulate and visualize potential trade scenarios and capital allocation models.
Disclaimer:
This script is provided for educational and informational purposes only. It does not constitute financial advice and should not be relied upon for live trading decisions. Always do your own research and consult with a qualified professional before making any trading or investment decisions.
AMV Impulse AssistantThe AMV Impulse Assistant is a custom momentum tool designed to assess how aggressively price is moving relative to recent volatility. It combines Bollinger-based range analysis and fast-moving average behavior to generate a dynamic impulse score. This score helps identify when price action is potentially overextended or showing signs of unusual momentum — useful for pullback traders, breakout traders, and anyone managing entries during trending conditions.
What it does:
Tracks the relationship between a short WMA and Bollinger basis to gauge directional strength.
Measures price movement compression/expansion with a normalized Bollinger Width Percentile.
Combines both into a smoothed Impulse Score (from -10 to +10) that reflects how aggressively price is pushing in either direction.
Colors the score line and highlights background zones when momentum enters extreme ranges.
📈 Use case:
This tool is especially effective for day traders who need to quickly identify when price is moving abnormally fast — either as an exhaustion signal or confirmation of an aggressive continuation. It can be used to:
Confirm the end of a pullback.
Spot overly aggressive moves that may revert.
Avoid entries during neutral chop or volatility compression.
It is best used alongside your primary trend filters and execution tools as a supplementary confirmation.
K Bands v2.2K Bands v2 - Settings Breakdown (Timeframe Agnostic)
K Bands v2 is an adaptive volatility envelope tool designed for flexibility across different trading
styles and timeframes.
The settings below allow complete control over how the bands are constructed, smoothed, and how
they respond to market volatility.
1. Upstream MA Type
Controls the core smoothing applied to price before calculating the bands.
Options:
- EMA: Fast, responsive, reacts quickly to price changes.
- SMA: Classic moving average, slower but provides stability.
- Hull: Ultra smooth, reduces noise significantly but may react differently to choppy conditions.
- GeoMean: Geometric mean smoothing, creates a unique, slightly smoother line.
- SMMA: Wilder-style smoothing, balances noise reduction and responsiveness.
- WMA: Weighted Moving Average, emphasizes recent price action for sharper responsiveness.
2. Smoothing Length
Lookback period for the upstream moving average.
- Lower values: Faster reaction, captures short-term shifts.
- Higher values: Smoother trend depiction, filters out noise.
3. Multiplier
Determines the width of the bands relative to calculated volatility.
- Lower multiplier: Tighter bands, more signals, but increased false breakouts.
- Higher multiplier: Wider bands, fewer false signals, more conservative.
4. Downstream MA Type
Applies final smoothing to the band plots after initial calculation.
Same options as Upstream MA.
5. Downstream Smoothing Length
Lookback period for downstream smoothing.
- Lower: More responsive bands.
- Higher: Smoother, visually cleaner bands.
6. Band Width Source
Selects the method used to calculate band width based on market volatility.
Options:
- ATR (Average True Range): Smooth, stable bands based on price range expansion.
- Stdev (Standard Deviation): More reactive bands highlighting short-term volatility spikes.
7. ATR Smoothing Type
Controls how the ATR or Stdev value is smoothed before applying to band width.
Options:
- Wilder: Classic, stable smoothing.
- SMA: Simple moving average smoothing.
- EMA: Faster, more reactive smoothing.
- Hull: Ultra-smooth, noise-reducing smoothing.
- GeoMean: Geometric mean smoothing.
8. ATR Length
Lookback period for smoothing the volatility measurement (ATR or Stdev).
- Lower: More reactive bands, captures quick shifts.
- Higher: Smoother, more stable bands.
9. Dynamic Multiplier Based on Volatility
Allows the band multiplier to adapt automatically to changes in market volatility.
- ON: Bands expand during high volatility and contract during low volatility.
- OFF: Bands remain fixed based on the set multiplier.
10. Dynamic Multiplier Sensitivity
Controls how aggressively the dynamic multiplier responds to volatility changes.
- Lower values: Subtle adjustments.
- Higher values: More aggressive band expansion/contraction.
K Bands v2 is designed to be adaptable across any market or timeframe, helping visualize price
structure, trend, and volatility behavior.
Kelly Optimal Leverage IndicatorThe Kelly Optimal Leverage Indicator mathematically applies Kelly Criterion to determine optimal position sizing based on market conditions.
This indicator helps traders answer the critical question: "How much capital should I allocate to this trade?"
Note that "optimal position sizing" does not equal the position sizing that you should have. The Optima position sizing given by the indicator is based on historical data and cannot predict a crash, in which case, high leverage could be devastating.
Originally developed for gambling scenarios with known probabilities, the Kelly formula has been adapted here for financial markets to dynamically calculate the optimal leverage ratio that maximizes long-term capital growth while managing risk.
Key Features
Kelly Position Sizing: Uses historical returns and volatility to calculate mathematically optimal position sizes
Multiple Risk Profiles: Displays Full Kelly (aggressive), 3/4 Kelly (moderate), 1/2 Kelly (conservative), and 1/4 Kelly (very conservative) leverage levels
Volatility Adjustment: Automatically recommends appropriate Kelly fraction based on current market volatility
Return Smoothing: Option to use log returns and smoothed calculations for more stable signals
Comprehensive Table: Displays key metrics including annualized return, volatility, and recommended exposure levels
How to Use
Interpret the Lines: Each colored line represents a different Kelly fraction (risk tolerance level). When above zero, positive exposure is suggested; when below zero, reduce exposure. Note that this is based on historical returns. I personally like to increase my exposure during market downturns, but this is hard to illustrate in the indicator.
Monitor the Table: The information panel provides precise leverage recommendations and exposure guidance based on current market conditions.
Follow Recommended Position: Use the "Recommended Position" guidance in the table to determine appropriate exposure level.
Select Your Risk Profile: Conservative traders should follow the Half Kelly or Quarter Kelly lines, while more aggressive traders might consider the Three-Quarter or Full Kelly lines.
Adjust with Volatility: During high volatility periods, consider using more conservative Kelly fractions as recommended by the indicator.
Mathematical Foundation
The indicator calculates the optimal leverage (f*) using the formula:
f* = μ/σ²
Where:
μ is the annualized expected return
σ² is the annualized variance of returns
This approach balances potential gains against risk of ruin, offering a scientific framework for position sizing that maximizes long-term growth rate.
Notes
The Full Kelly is theoretically optimal for maximizing long-term growth but can experience significant drawdowns. You should almost never use full kelly.
Most practitioners use fractional Kelly strategies (1/2 or 1/4 Kelly) to reduce volatility while capturing most of the growth benefits
This indicator works best on daily timeframes but can be applied to any timeframe
Negative Kelly values suggest reducing or eliminating market exposure
The indicator should be used as part of a complete trading system, not in isolation
Enjoy the indicator! :)
P.S. If you are really geeky about the Kelly Criterion, I recommend the book The Kelly Capital Growth Investment Criterion by Edward O. Thorp and others.
THE HISTORY By [VXN]
THE HISTORY By - Monthly Seasonal Analysis Indicator
Development Status: This indicator is currently in the development phase and is not yet finished. Features and functionality may change as development continues.
Overview:
This indicator provides comprehensive historical analysis of monthly price patterns, designed to help traders identify recurring seasonal behaviors and market tendencies for the current month across multiple years of data.
Key Features:
Historical Data Analysis:
- Analyzes up to 10 years of historical performance for the current month
- Calculates monthly returns, win rates, and statistical metrics
- Tracks maximum drawdowns and runups for risk assessment
- Requires daily timeframe for accurate monthly calculations
Pattern Recognition:
- Implements a three-period classification system that breaks each month into segments
- Uses visual indicators (🟢🔴🟡) to represent bullish, bearish, and neutral periods
- Helps identify recurring intra-month behavior patterns
Statistical Display:
- Presents historical data in an organized table format
- Shows year-by-year performance comparisons
- Calculates average returns, best/worst performance, and confidence levels
- Displays overall market bias (bullish/bearish tendency) for the current month
Dynamic Zone Overlays:
- Projects Fibonacci-based support/resistance levels based on historical volatility
- Adjusts zone positioning based on the month's historical bias
- Provides visual reference points for potential price targets or reversal areas
Practical Applications:
- Seasonal trading strategy development
- Risk management through historical context
- Understanding market cyclicality and recurring patterns
- Educational tool for studying price behavior over time
Note: This indicator is designed for analysis and education purposes, helping traders understand historical market patterns rather than providing direct trading signals. The data should be used in conjunction with other forms of analysis and proper risk management. As this is still under development, please expect updates and refinements to functionality.
EVaR Indicator and Position SizingThe Problem:
Financial markets consistently show "fat-tailed" distributions where extreme events occur with higher frequency than predicted by normal distributions (Gaussian or even log-normal). These fat tails manifest in sudden price crashes, volatility spikes, and black swan events that traditional risk measures like volatility can underestimate. Standard deviation and conventional VaR calculations assume normally distributed returns, leaving traders vulnerable to severe drawdowns during market stress.
Cryptocurrencies and volatile instruments display particularly pronounced fat-tailed behavior, with extreme moves occurring 5-10 times more frequently than normal distribution models would predict. This reality demands a more sophisticated approach to risk measurement and position sizing.
The Solution: Entropic Value at Risk (EVAR)
EVaR addresses these limitations by incorporating principles from statistical mechanics and information theory through Tsallis entropy. This advanced approach captures the non-linear dependencies and power-law distributions characteristic of real financial markets.
Entropy is more adaptive than standard deviations and volatility measures.
I was inspired to create this indicator after reading the paper " The End of Mean-Variance? Tsallis Entropy Revolutionises Portfolio Optimisation in Cryptocurrencies " by by Sana Gaied Chortane and Kamel Naoui.
Key advantages of EVAR over traditional risk measures:
Superior tail risk capture: More accurately quantifies the probability of extreme market moves
Adaptability to market regimes: Self-calibrates to changing volatility environments
Non-parametric flexibility: Makes less assumptions about the underlying return distribution
Forward-looking risk assessment: Better anticipates potential market changes (just look at the charts :)
Mathematically, EVAR is defined as:
EVAR_α(X) = inf_{z>0} {z * log(1/α * M_X(1/z))}
Where the moment-generating function is calculated using q-exponentials rather than conventional exponentials, allowing precise modeling of fat-tailed behavior.
Technical Implementation
This indicator implements EVAR through a q-exponential approach from Tsallis statistics:
Returns Calculation: Price returns are calculated over the lookback period
Moment Generating Function: Approximated using q-exponentials to account for fat tails
EVAR Computation: Derived from the MGF and confidence parameter
Normalization: Scaled to for intuitive visualization
Position Sizing: Inversely modulated based on normalized EVAR
The q-parameter controls tail sensitivity—higher values (1.5-2.0) increase the weighting of extreme events in the calculation, making the model more conservative during potentially turbulent conditions.
Indicator Components
1. EVAR Risk Visualization
Dynamic EVAR Plot: Color-coded from red to green normalized risk measurement (0-1)
Risk Thresholds: Reference lines at 0.3, 0.5, and 0.7 delineating risk zones
2. Position Sizing Matrix
Risk Assessment: Current risk level and raw EVAR value
Position Recommendations: Percentage allocation, dollar value, and quantity
Stop Parameters: Mathematically derived stop price with percentage distance
Drawdown Projection: Maximum theoretical loss if stop is triggered
Interpretation and Application
The normalized EVAR reading provides a probabilistic risk assessment:
< 0.3: Low risk environment with minimal tail concerns
0.3-0.5: Moderate risk with standard tail behavior
0.5-0.7: Elevated risk with increased probability of significant moves
> 0.7: High risk environment with substantial tail risk present
Position sizing is automatically calculated using an inverse relationship to EVAR, contracting during high-risk periods and expanding during low-risk conditions. This is a counter-cyclical approach that ensures consistent risk exposure across varying market regimes, especially when the market is hyped or overheated.
Parameter Optimization
For optimal risk assessment across market conditions:
Lookback Period: Determines the historical window for risk calculation
Q Parameter: Controls tail sensitivity (higher values increase conservatism)
Confidence Level: Sets the statistical threshold for risk assessment
For cryptocurrencies and highly volatile instruments, a q-parameter between 1.5-2.0 typically provides the most accurate risk assessment because it helps capturing the fat-tailed behavior characteristic of these markets. You can also increase the q-parameter for more conservative approaches.
Practical Applications
Adaptive Risk Management: Quantify and respond to changing tail risk conditions
Volatility-Normalized Positioning: Maintain consistent exposure across market regimes
Black Swan Detection: Early identification of potential extreme market conditions
Portfolio Construction: Apply consistent risk-based sizing across diverse instruments
This indicator is my own approach to entropy-based risk measures as an alterative to volatility and standard deviations and it helps with fat-tailed markets.
Enjoy!
H BollingerBollinger Bands are a widely used technical analysis indicator that helps spot relative price highs and lows. The tool comprises three lines: a central band representing the 20-period simple moving average (SMA), and upper and lower bands usually placed two standard deviations above and below the SMA. These bands adjust with market volatility, offering insights into price fluctuations and trading conditions.
How this indicator works
Bollinger Bands helps traders assess price volatility and potential price reversals. They consist of three bands: the middle band, the upper band, and the lower band. Here's how Bollinger Bands work:
Middle band: This is typically a simple moving average (SMA) of the asset's price over a specified period. The most common period used is 20 days.
Upper band: This is calculated by adding a specified number of standard deviations to the middle band. The standard deviation measures the asset's price volatility. Commonly, two standard deviations are added to the middle band.
Lower band: Similar to the upper band, it is calculated by subtracting a specified number of standard deviations from the middle band.
What do Bollinger Bands tell you?
Bollinger bands primarily indicate the level of market volatility and trading opportunities. Narrow bands indicate low market volatility, while wide bands suggest high market volatility. Bollinger bands indicators can be used by traders to assess potential buy or sell signals. For instance, a sell signal may be interpreted or generated if the asset’s price moves closer or crosses the upper band, as it may indicate that the asset is overbought. Alternatively, a buy signal may be interpreted or generated if the price moves closer to the lower band, as it may signify that the asset is oversold.
However, traders should be cautious when using Bollinger Bands as standalone indicators when making trading decisions. Experienced traders refrain from confirming signals based on one indicator. Instead, they generally combine various technical indicators and fundamental analysis methods to make informed trading decisions. Basing trading decisions on only one indicator can result in misinterpretation of signals and heavy losses.
Bollinger Bands assist in identifying whether prices are relatively high or low. They are applied as a pair—upper and lower bands—alongside a moving average. However, these bands are not designed to be used in isolation. Instead, they should be used to validate signals generated by other technical indicators.
Calculation of Bollinger Band
Fear and Greed Index [DunesIsland]The Fear and Greed Index is a sentiment indicator designed to measure the emotions driving the stock market, specifically investor fear and greed. Fear represents pessimism and caution, while greed reflects optimism and risk-taking. This indicator aggregates multiple market metrics to provide a comprehensive view of market sentiment, helping traders and investors gauge whether the market is overly fearful or excessively greedy.How It WorksThe Fear and Greed Index is calculated using four key market indicators, each capturing a different aspect of market sentiment:
Market Momentum (30% weight)
Measures how the S&P 500 (SPX) is performing relative to its 125-day simple moving average (SMA).
A higher value indicates that the market is trading well above its moving average, signaling greed.
Stock Price Strength (20% weight)
Calculates the net number of stocks hitting 52-week highs minus those hitting 52-week lows on the NYSE.
A greater number of net highs suggests strong market breadth and greed.
Put/Call Options (30% weight)
Uses the 5-day average of the put/call ratio.
A lower ratio (more call options being bought) indicates greed, as investors are betting on rising prices.
Market Volatility (20% weight)
Utilizes the VIX index, which measures market volatility.
Lower volatility is associated with greed, as investors are less fearful of large market swings.
Each component is normalized using a z-score over a 252-day lookback period (approximately one trading year) and scaled to a range of 0 to 100. The final Fear and Greed Index is a weighted average of these four components, with the weights specified above.Key FeaturesIndex Range: The index value ranges from 0 to 100:
0–25: Extreme Fear (red)
25–50: Fear (orange)
50–75: Neutral (yellow)
75–100: Greed (green)
Dynamic Plot Color: The plot line changes color based on the index value, visually indicating the current sentiment zone.
Reference Lines: Horizontal lines are plotted at 0, 25, 50, 75, and 100 to represent the different sentiment levels: Extreme Fear, Fear, Neutral, Greed, and Extreme Greed.
How to Interpret
Low Values (0–25): Indicate extreme fear, which may suggest that the market is oversold and could be due for a rebound.
High Values (75–100): Indicate greed, which may signal that the market is overbought and could be at risk of a correction.
Neutral Range (25–75): Suggests a balanced market sentiment, neither overly fearful nor greedy.
This indicator is a valuable tool for contrarian investors, as extreme readings often precede market reversals. However, it should be used in conjunction with other technical and fundamental analysis tools for a well-rounded view of the market.
Vasyl Ivanov | Volatility with MAThis indicator calculates and displays the volatility value for each bar.
The main line shows the relative range (spread) of the current bar compared to its closing price.
This allows you to quickly assess how much the price fluctuated within the bar relative to where it closed.
The Simple Moving Average (SMA) with a length of 9 smooths the main indicator values, helping to identify volatility trends and filter out random spikes.
Practical Application:
The indicator can be useful for assessing current market volatility and identifying periods with unusually wide or narrow ranges.
The smoothed line helps track medium-term changes in volatility and can be used to confirm trading signals related to range expansion or contraction.
Institutional Momentum Scanner [IMS]Institutional Momentum Scanner - Professional Momentum Detection System
Hunt explosive price movements like the professionals. IMS identifies maximum momentum displacement within 10-bar windows, revealing where institutional money commits to directional moves.
KEY FEATURES:
▪ Scans for strongest momentum in rolling 10-bar windows (institutional accumulation period)
▪ Adaptive filtering reduces false signals using efficiency ratio technology
▪ Three clear states: LONG (green), SHORT (red), WAIT (gray)
▪ Dynamic volatility-adjusted thresholds (8% ATR-scaled)
▪ Visual momentum flow with glow effects for signal strength
BASED ON:
- Pocket Pivot concept (O'Neil/Morales) applied to price momentum
- Adaptive Moving Average principles (Kaufman KAMA)
- Market Wizards momentum philosophy
- Institutional order flow patterns (5-day verification window)
HOW IT WORKS:
The scanner finds the maximum price displacement in each 10-bar window - where the market showed its hand. An adaptive filter (5-bar regression) separates real moves from noise. When momentum exceeds the volatility-adjusted threshold, states change.
IDEAL FOR:
- Momentum traders seeking explosive moves
- Swing traders (especially 4H timeframe)
- Position traders wanting institutional footprints
- Anyone tired of false breakout signals
Default parameters (10,5) optimized for 4H charts but adaptable to any timeframe. Remember: The market rewards patience and punishes heroes. Wait for clear signals.
"The market is honest. Are you?"
