Bear Market Defender [QuantraSystems]Bear Market Defender
A system to short Altcoins when BTC is ranging or falling - benefit from Altcoin bleed or collapse .
QuantraSystems guarantees that the information created and published within this document and on the TradingView platform is fully compliant with applicable regulations, does not constitute investment advice, and is not exclusively intended for qualified investors.
Important Note!
The system equity curve presented here has been generated as part of the process of testing and verifying the methodology behind this script.
Crucially, it was developed after the system was conceptualized, designed, and created, which helps to mitigate the risk of overfitting to historical data. In other words, the system was built for robustness, not for simply optimizing past performance.
This ensures that the system is less likely to degrade in performance over time, compared to hyper-optimized systems that are tailored to past data. No tweaks or optimizations were made to this system post-backtest.
Even More Important Note!!
The nature of markets is that they change quickly and unpredictably. Past performance does not guarantee future results - this is a fundamental rule in trading and investing.
While this system is designed with broad, flexible conditions to adapt quickly to a range of market environments, it is essential to understand that no assumptions should be made about future returns based on historical data. Markets are inherently uncertain, and this system - like all trading systems - cannot predict future outcomes.
INTRODUCTION TO THE STAR FRAMEWORK
The STAR Framework – an abbreviation for Strategic Trading with Adaptive Risk - is a bespoke portfolio-level infrastructure for dynamic, multi-asset crypto trading systems. It combines systematic position management, adaptive sizing, and “intra-system” diversification, all built on a rigorous foundation of Risk-based position sizing .
At its core, STAR is designed to facilitate:
Adaptive position sizing based on user-defined maximum portfolio risk
Capital allocation across multiple assets with dynamic weight adjustment
Execution-aware trading with robust fee and slippage adjustment
Realistic equity curve logic based on a compounding realized PnL and additive unrealized PnL
The STAR Framework is intended for use as both a standalone portfolio system or preferred as a modular component within a broader trading “global portfolio” - delivering a balance of robustness and scalability across strategy types, timeframes, and market regimes.
RISK ALLOCATION VIA "R" CALCULATIONS
The foundational concept behind STAR is the use of the R unit - a dynamic representation of risk per trade. R is defined by the distance between a trade's entry and its stoploss, making it an intuitive and universally adaptive sizing unit across any token, timeframe, or market.
Example: Suppose the entry price is $100, and the stoploss is $95. A $5 move against the position represents a 1R loss. A 15% price increase to $115 would equal a +3R gain.
This makes R-based systems highly flexible: the user defines the percentage of capital that is put at risk per R and all positions are scaled accordingly - whether the token is volatile, illiquid, or slow-moving.
R is an advantageous method for determine position sizing - instead of being tied to complex value at risk mechanisms with having layered exit criteria, or continuous volatility-based sizing criteria that need to be adjusted while in an open trade, R allows for very straightforward sizing, invalidation and especially risk control – which is the most fundamental.
REALIZED BALANCE, FEES & SLIPPAGE ACCOUNTING
All position sizing, risk metrics, and the base equity curve within STAR are calculated based on realized balance only .
This means:
No sizing adjustments are made based on unrealized profit and loss ✅
No active positions are included in the system's realized equity until fully closed ✅
Every trade is sized precisely according to current locked-in realized portfolio balance ✅
This creates the safest risk profile - especially when multiple trades are open. Unrealized gains are not used to inflate sizing, ensuring margin safety across all assets.
All calculations also incorporate slippage and fees, based on user-defined estimates – which can and should be based upon user-collected data - and updated frequently forwards in time. These are not cosmetic, or simply applied to the final equity curve - they are fully integrated into the dynamic position sizing and equity performance , ensuring:
Stoploss hits result in exactly a −1R loss, even after slippage and fees ✅
Winners are discounted based on realistic execution costs ✅
No trade is oversized due to unaccounted execution costs ✅
Example - Slippage in R Units:
Let R be defined as the distance from entry to stoploss.
Suppose that distance is $1, and the trade is closed at a win of +$2.
If execution slippage leads to a 50 cent worse entry and a 50 cent worse exit, you’ve lost $1 extra - which is an additional 1R in execution slippage. This makes the effective return 1.0R instead of the intended 2.0R.
This is equivalent to a slippage value of 50%.
Thus, slippage in STAR is tracked and modelled on an R-adjusted basis , enabling more accurate long-term performance modelling.
MULTI-ASSET, LONG/SHORT SUPPORT
STAR supports concurrent long and short positions across multiple tokens. This can sometimes result in partially hedged exposure - for example, being long one asset and short another.
This structure has key benefits:
Diversifies idiosyncratic risk by distributing exposure across multiple tokens
Allows simultaneous exploitation of relative strength and weakness
Reduces portfolio volatility via natural hedging during reduced trending periods
Even in a highly correlated market like crypto, short-term momentum behaviour often varies between tokens - making diversified, multi-directional exposure a strategic advantage .
EQUITY CURVE
The STAR framework only updates the underlying realized equity when a position is closed, and the trade outcome is known. This approach ensures:
True representation of actual capital available for trading
No exposure distortion due to unrealized gains
Risk remains tightly linked to realized results
This trade-to-trade basis for realized equity modelling eliminates the common pitfall of overallocation based on unrealized profits.
The visual equity curve represents an accurate visualization of the Total Equity however, which is equivalent to what would be the realized equity if all trades were closed on the prior bar close.
TIMEFRAME CONSIDERATIONS
Lower timeframes typically yield better performance for STAR due to:
Greater data density per day - more observations = better statistical inference
Faster compounding - more trades per week = faster capital rotation
However, lower timeframes also suffer from increased slippage and fees. STAR's execution-aware structure helps mitigate this, but users must still choose timeframes appropriate to their liquidity, costs, and operational availability.
INPUT OPTIONS
Fees (direct trading costs - the percentage of capital removed from the initial position size)
Slippage (execution delay, as a percentage. In practice, the fill price is often worse than the signal price. This directly affects R and hence position sizing)
Risk % ( Please note : this is the risk level if every position is opened at once. 5% risk for 5 assets is 1% risk per position)
System Start date
Float Precision value of displayed numbers
Table visualization - positioning and table sizes
Adjustable color options
VISUAL SIMPLICITY
To avoid usual unnecessary complexity and empower fast at-a-glance action taking, as well as enable mobile compatibility, only the most relevant information is presented.
This includes all information required to open positions in one table.
As well as a quick and straightforward overview for the system stats
Lastly, there is an optional table that can be enabled
displaying more detailed information if desired:
USAGE GUIDELINES
To use STAR effectively:
Input your average slippage and fees %
Input your maximum portfolio risk % (this controls overall leverage and is equivalent to the maximum loss that the allocation to STAR would bring if ALL positions are allocated AND hit their stop loss at the same time)
Wait for signal alerts with entry, stop, and size details
STAR will dynamically calculate sizing, risk exposure, and portfolio allocation on your behalf. Position multipliers, stop placement, and asset-specific risk are all embedded in the system logic.
Note: Leverage must be manually set to ISOLATED on your exchange platform to prevent unwanted position linking.
ABOUT THE BEAR MARKET DEFENDER STRATEGY
The first strategy to launch on the STAR Framework is the BEAR MARKET DEFENDER (BMD) - a fast-acting, trend following system based upon the Trend Titan NEUTRONSTAR. For the details of the logic behind NEUTRONSTAR, please refer to the methodology and trend aggregation section of the following indicator:
The BMD ’s short side exit calculation methodology is slightly improved compared to NEUTRONSTAR, to capture downtrends more consistently and also cut positions faster – which is crucial when considering general jump risk in the Crypto space.
Accordingly, the only focus of the BMD is to capture trends to the short side, providing the benefit of being in a spectrum from no correlation to being negatively correlated in risk and return behavior to classical Crypto long exposure.
More precisely, Crypto behavior showcases that when Bitcoin is in a ranging/mean reverting environment, most tokens that don’t fall into the “Blue-Chip” category tend to find themselves in a trend towards 0.
Typically during this period most Crypto portfolios suffer heavily due to a “Crypto-long” biased exposure.
The Bear Market Defender thrives in these chaotic, high volatility markets where most coins trend towards zero while the traditional Crypto long exposure is either flat or in a drawdown, therefore the BMD adds a source of uncorrelated risk and returns to hedge typical long exposure and bolster portfolio volatility.
Because of the BMD's short-only exposure, it will often suffer small losses during strong uptrends. During these periods, long exposure performs the best and the goal is to outperform the temporary underperformance in the BMD .
To take advantage of the abovementioned behavior of most tokens trending to zero, assets traded in the BMD are systematically updated on a quarterly basis with available liquidity being an important consideration for the tokens to be eligible for selection.
FINAL SUMMARY
The STAR Framework represents a new generation of portfolio grade trading infrastructure, built around disciplined execution, realized equity, and adaptive position sizing. It is designed to support any number of future methodologies - beginning with BMD .
The Bear Market Defender is here to hedge out commonly long biased portfolio allocations in the Crypto market, specializing in bringing uncorrelated returns during periods of sideways price action on Bitcoin, or whole-market downturns.
Together, STAR + BMD deliver a scalable, volatility tuned system that prioritizes capital preservation, signal accuracy, and adaptive risk allocation. Whether deployed standalone or within a broader portfolio, this framework is engineered for high performance, longevity, and adaptability in the ever-evolving crypto landscape.
Volatility
Timeframe LoopThe Timeframe Loop publication aims to visualize intrabar price progression in a new, different way.
🔶 CONCEPTS and USAGE
I got inspiration from the Pressure/Volume loop, which is used in Mechanical Ventilation with Critical Care patients to visualize pressure/volume evolution during inhalation/exhalation.
The main idea is that intrabar prices are visualized by a loop, going to the right during the first half and returning to the left towards its closing point. Here, the main chart timeframe (CTF) is 4 hours, and we see the movements of eight 30-minute lower timeframe (LTF) periods, highlighted by four yellow dots/lines (first 2 hours -> "Right") and four blue dots/lines (last 2 hours <- "Left"):
🔹 BTF
If "Show Lowest TF" is enabled, the LTF is split into another lower TF (BTF - "Base TF"); in this case, the 30-minute LTF is split into 10 parts of 3 minutes (BTF):
Enabling "Loop Lowest TF" will enable the BTF to react similarly to the largest loop; from halfway, it will return to its startpoint:
Here is a more detailed example:
🔹 Mini-Candles
The included option "Mini-Candles" will bring even more detail, showing the LTF as Japanese candlesticks with user-defined colors and adjustable body width; in this example, the mini-candles associated with the first half (yellow lines/dots) are green/red, while blue/fuchsia in the second half (blue lines/dots):
CTF 10 minutes, LTF 1 minute, BTF 5 seconds
One can see the detailed intrabar price progression in one glance.
CTF 5 minutes, LTF 1 minute, BTF 5 seconds
If the LTF/BTF ratio, divided by two, results in a non-integer number, the right side will be a vertical line instead of just a turning point. In that case, the smaller, most right blue loop will be situated at the right of that line.
10 minutes / 1 minute = 10 -> 10 / 2 = 5 parts
5 minutes / 1 minute = 5 -> 5 / 2 = 2.5 parts
🔶 SETTINGS
🔹 Timeframes
Lower Timeframe 1
Lower Timeframe 2
No need to worry about the order of both timeframes; BTF will be the lowest TF of the 2, LTF the highest; both have to be lower than the main chart TF (CTF); otherwise, it will result in the error: "`Lower Timeframes` should be lower than current chart timeframe".
The ratio LTF / BTF should be equal or higher than 2; otherwise, this error will show: "`Lower Timeframe` should minimally be twice the `Base (smallest) Timeframe`"
Lastly, the ratio CTF / BTF should be lower than 500; otherwise, this error will pop up: "`Current Chart timeframe` / `Lower Timeframe` should be less than 500."
I have tried to capture runtime errors as best I could. If one should be triggered (red exclamation mark next to the title), it is best to increase the lowest TF.
🔹 Options
Show Lowest TF: Show BTF progression.
Loop Lowest TF: Enabling will let the BTF line return halfway.
Show Mini-Candles
Show Steps
"Show Steps" can be useful to see how the script works, where the location of the current price is compared against the position of the left (L) and right (R) labels:
🔹 Style
EWMA Volatility EstimatorThis script calculates EWMA Volatility (Exponentially Weighted Moving Average Volatility).
Commonly used model in financial risk management.
It estimates recent price volatility by applying more weight to the most recent returns, capturing volatility clustering while remaining responsive to fast market shifts.
The method uses a decay factor (λ) of 0.94, the standard value used in models like RiskMetrics, and converts the variance estimate into annualized volatility in percentage terms.
This is not a forecasting tool. It’s an estimator that reflects the magnitude of recent price moves in a statistically robust way.
It can be helpful for:
Understanding regime shifts in market behavior
Designing position sizing rules based on recent volatility
Filtering entries during high or low volatility phases
How It Works
Computes log returns of the closing price.
Squares the returns to get a proxy for variance.
Applies an exponential moving average to the squared returns using an equivalent EMA period based on λ = 0.94.
Converts the result to volatility by taking the square root and scaling to a percentage.
Key Characteristics
Backward-looking estimator
Reacts faster than standard rolling-window volatility
Smooths noise while still being sensitive to recent spikes
This script is educational and informational. It is not financial advice or a guarantee of performance. Always test any tool as part of a broader strategy before using it in live markets.
Percent Change of Range Candles - FullPercent Change of Range Candles – Full (PCR Full)
Description:
PCR Full is a custom momentum indicator that measures the percentage price change relative to a defined range, offering traders a unique way to evaluate strength, direction, and potential reversals in price movement.
How it works:
The main value (PCR) is calculated by comparing the price change over a selected number of candles (length) to the range between the highest high and lowest low in the same period.
This percentage change is normalized and visualized with dynamic candles on the subgraph.
Reference levels at +100, +50, 0, -50, and -100 serve as key zones to indicate potential overbought/oversold conditions, continuation, or neutrality.
How to read the indicator:
1. Trend continuation:
When PCR breaks above +50 and holds, it often confirms a strong bullish move.
Similarly, values below -50 and staying low signal a bearish continuation.
2. Wick behavior (volatility insight):
Long wicks on PCR candles suggest uncertainty or failed breakout attempts.
Short or no wicks with strong body color show stable momentum and conviction.
On the chart, multiple long wicks near -50 suggest bulls are attempting to push price upward, but lack the strength — until a confirmed breakout.
3. Polarity transition (Bearish to Bullish or vice versa):
A transition from negative PCR values to above zero shows that the market is possibly turning.
Especially if PCR climbs gradually and stabilizes above zero, it indicates a developing bullish phase.
Components:
Main PCR line: Color-coded (green for rising, red for falling).
Open Average (gray line): Smooths recent PCR values, indicating balance.
High/Low adaptive bands: Adjust dynamically to PCR polarity.
PCR Candles: Visualize OHLC of PCR data for enhanced interpretation.
Suggested use cases:
Enter trend trades when PCR crosses +50 or -50 with volume or price confirmation.
Watch for reversal signs near ±100 if PCR fails to break further.
Use 0 line as a neutral zone — markets hovering near 0 are often in consolidation.
Combine with price action or oscillators like RSI/MACD for additional signals.
Customization:
The length input allows users to define the range for PCR calculations, making it adjustable to various timeframes and strategies (scalping, intraday, swing).
Volatility Barometer (VB)Volatility Barometer (VB)
The Volatility Barometer (VB) is a comprehensive market sentiment indicator designed to measure aggregate stress and fear in the equity market. It consolidates three critical volatility metrics into a single, easy-to-interpret score, providing a broader view of market conditions than any single metric alone.
Core Components
The barometer synthesizes information from:
VIX Index (VIX): The standard measure of implied 30-day stock market volatility.
VVIX Index (VVIX): The volatility of the VIX itself, often seen as the "volatility of volatility." High VVIX readings can signal uncertainty about the VIX's future path.
VIX Futures Term Structure (VX1!−VX2!): The spread between the front-month and second-month VIX futures. A positive spread (contango) is typical, while a negative spread (backwardation) often signals imminent market stress.
How It Works
To create a unified view, the indicator normalizes each of these three components using a Z-score. The Z-score measures how many standard deviations a value is from its historical mean over a user-defined period (defaulting to 252 days, or one trading year).
These three standardized Z-scores are then combined into a final VB Score using a weighted average. Users can customize these weights in the indicator's settings to emphasize the components they find most important.
How to Interpret
The VB Score is plotted as a single line that oscillates around a zero level, with its color changing to reflect the prevailing market regime:
High Stress (Red Line): When the score rises above the "High stress threshold" (default: 1.5), it indicates heightened market fear and risk-off sentiment. This is a period of significant stress, often associated with market downturns.
Low Stress (Green Line): When the score falls below the "Low stress threshold" (default: -1.0), it signals complacency and low perceived risk in the market. Extreme low readings can sometimes precede volatility spikes.
Neutral (Blue Line): Scores between the high and low thresholds represent normal market conditions.
By providing a weighted, multi-faceted view of volatility, the Volatility Barometer helps traders and investors identify market regimes, confirm trading biases, and anticipate potential shifts in market sentiment.
ATR Stop Loss BandsATR Stop Loss Bands Indicator
Overview
The ATR Stop Loss Bands indicator creates dynamic support and resistance levels based on the Average True Range (ATR), providing traders with volatility-adjusted price bands that can be used for stop loss placement and trend analysis.
How It Works
This indicator calculates two bands around the current closing price using the ATR value:
Upper Band: Close price + ATR value
Lower Band: Close price - ATR value
The bands automatically adjust to market volatility, expanding during volatile periods and contracting during calmer market conditions.
Key Features
Customizable ATR Period: Default 14-period length (adjustable from 1 to any desired value)
Multiple Smoothing Options: Choose from RMA (default), SMA, EMA, or WMA for ATR calculation
Dynamic Volatility Adjustment: Bands automatically adapt to current market volatility
Clean Visual Design: Gray bands that don't clutter your chart
Trading Applications
Stop Loss Placement: Use the bands as dynamic stop loss levels - long positions might use the lower band as a stop, while short positions could use the upper band
Volatility Assessment: Wide bands indicate high volatility periods, narrow bands suggest low volatility
Breakout Identification: Price movements beyond the bands may signal potential breakouts or trend changes
Support/Resistance Levels: The bands can act as dynamic support and resistance zones
Settings
Length: ATR calculation period (default: 14)
Smoothing: Method for ATR smoothing (RMA, SMA, EMA, or WMA)
Best Practices
Use in conjunction with other technical analysis tools for confirmation
Consider the overall trend direction when interpreting band breaks
Adjust the length parameter based on your trading timeframe and strategy
Remember that ATR bands are reactive, not predictive - they respond to price movements rather than forecasting them
This indicator is particularly useful for traders who want to incorporate market volatility into their risk management and entry/exit decisions.
CM RSI-Stoch Hybrid D&K%CM RSI-Stoch Hybrid D&K% Indicator
The CM RSI-Stoch Hybrid D&K% Indicator is a sophisticated momentum and trend analysis tool that combines the Relative Strength Index (RSI), Stochastic %K, and %D into a single, cohesive signal, enhanced by dynamic volume weighting and customizable smoothing. Unlike standalone RSI or Stochastic indicators, this hybrid approach integrates multiple data points to reduce noise, filter false signals, and provide traders with a clearer, more actionable view of market dynamics. Designed for versatility, it’s suitable for day trading, swing trading, or long-term investing across stocks, forex, cryptocurrencies, and commodities.
Why This Indicator Is Unique
Traditional RSI measures momentum based on price changes, while Stochastic tracks price cycles relative to highs and lows. However, both can generate conflicting or noisy signals in volatile markets. The CM RSI-Stoch Hybrid D&K% addresses this by:
Merging Complementary Signals: It calculates a composite signal by averaging RSI, Stochastic %K, and %D, balancing momentum and cyclical insights to produce a smoother, more reliable indicator.
Volume-Weighted Context: A dynamic colour system adjusts the composite signal’s appearance based on volume surges, helping traders prioritize moves backed by strong market participation.
Customizable Smoothing: A user-defined moving average (SMA, EMA, or WMA) smooths the composite signal, allowing traders to adapt the indicator to their preferred timeframe or strategy. This unique combination reduces the lag and false positives common in individual indicators, offering a novel perspective on market momentum and reversals.
How It Works
The indicator operates through a multi-layered approach:
Composite Signal Calculation: The core feature is a composite line derived by averaging RSI (based on closing prices), Stochastic %K, and %D (calculated from price highs and lows). This fusion creates a balanced momentum signal that mitigates the limitations of each indicator, such as RSI’s sensitivity to price spikes or Stochastic’s tendency to oscillate in choppy markets.
Volume-Weighted Colouring: The composite line changes colour (navy for high volume, blue for normal) based on a comparison of current trading volume to a user-defined volume moving average. This highlights when momentum aligns with significant market activity, improving trade timing.
Customizable Moving Average: Traders can apply an SMA, EMA, or WMA to the composite signal, adjusting its sensitivity to suit scalping, swing trading, or trend-following strategies.
Overbought/Oversold Zones: User-defined thresholds for overbought and oversold conditions (based on RSI) are visually marked with semi-transparent red (overbought) and green (oversold) backgrounds, making it easy to spot potential reversals or continuation patterns.
Key Features
Hybrid Momentum Signal: Combines RSI, Stochastic %K, and %D into a single, noise-filtered line for enhanced clarity.
Volume-Driven Insights: Dynamically adjusts the composite line’s colour to reflect high-volume conditions, emphasizing significant market moves.
Flexible Smoothing: Choose from SMA, EMA, or WMA to tailor the indicator to your trading style.
Customizable Parameters: Adjust RSI length, Stochastic periods, volume MA length, and overbought/oversold thresholds to match any market or timeframe.
Clear Visuals: Displays RSI, Stochastic %K, %D, composite signal, and moving average in a single panel, with intuitive overbought/oversold zones.
How to Use It
Trend Confirmation: Monitor the composite signal relative to its moving average. A composite line above its MA suggests bullish momentum, while a line below indicates bearish momentum.
Reversal Opportunities: Use the overbought (red background) and oversold (green background) zones to identify potential reversals, especially when confirmed by high-volume signals (navy composite line).
Scalping and Swing Trading: Adjust RSI and Stochastic lengths for faster or slower signals, using the moving average to filter noise for precise entries and exits.
Cross-Market Application: Customize settings to suit the volatility of stocks, forex, crypto, or commodities, ensuring versatility across timeframes.
Hint - watch for the back ground to change colour to reflect oversold or overbought conditions and then watch for the composite signal line to cross the moving average and for the back ground colour to go. High volume (navy blue) would also then add to directional bias.
Why Traders Will Benefit
The CM RSI-Stoch Hybrid D&K% goes beyond traditional indicators by integrating RSI, Stochastic, and volume analysis into a unified system that reduces false signals and enhances decision-making. Its dynamic volume weighting and customizable options make it a powerful tool for traders seeking to navigate complex markets with confidence. Whether you’re scalping intraday moves or tracking long-term trends, this indicator provides a clear, actionable edge.
Note: Combine this indicator with proper risk management and complementary analysis tools. Past performance is not indicative of future results.
Full setup support will be given
Session Range ProjectionsSession Range Projections
Purpose & Concept:
Session Range Projections is a comprehensive trading tool that identifies and analyzes price ranges during user-defined time periods. The indicator visualizes high-probability reversal zones and profit targets by projecting Fibonacci levels from custom session ranges, making it ideal for traders who focus on time-based market structure analysis.
Key Features & Calculations:
1. Custom Time Range Analysis
- Define any time period for range calculation - from traditional sessions (Asian, London, NY) to custom periods like opening ranges, hourly ranges, or 4-hour blocks
- Automatically captures the highest and lowest prices within your specified timeframe
- Supports multiple timezone selections for global market analysis
- Flexible enough for intraday scalping ranges or longer-term swing trading setups
2. Premium & Discount Zones
- Automatically divides the range into premium (above 50%) and discount (below 50%) zones
- Visual differentiation helps identify institutional buying and selling areas
- Color-coded boxes clearly mark these critical price zones
3. Optimal Trade Entry (OTE) Zones
- Highlights the 79-89% retracement zone in premium territory
- Highlights the 11-21% retracement zone in discount territory
- These zones represent high-probability reversal areas based on institutional order flow concepts
4. Fibonacci Projections
- Projects 11 customizable Fibonacci extension levels from the range extremes
- Levels extend both above and below the range for symmetrical analysis
- Each level can be individually toggled and color-customized
- Default levels include common retracement ratios: -0.5, -1.0, -2.0, -2.33, -2.5, -3.0, -4.0, -4.5, -6.0, -7.0, -8.0
How to Use:
Set Your Time Range: Input your desired session start and end times (24-hour format)
Select Timezone: Choose the appropriate timezone for your trading session
Customize Display: Toggle various visual elements based on your preferences
Monitor Price Action: Watch for reactions at projected levels and OTE zones
Set Alerts: Configure sweep alerts for when price breaks above/below range extremes
Input Parameters Explained:
Time Range Settings
Range Start/End Hour & Minute: Define your analysis period
Time Zone: Ensure accurate session timing across different markets
Visual Settings
Range Box: Toggle the premium/discount zone visualization
Horizontal Lines: Customize high/low line appearance
Internal Range Levels: Show/hide equilibrium and OTE zones
Labels: Configure text display for key levels
Fibonacci Projections: Enable/disable extension levels
Display Settings
Historical Ranges: Show up to 10 previous session ranges
Alert Type: Choose between high sweep, low sweep, or both
Trading Applications:
Session-Based Trading: Analyze specific market sessions (Asian, London, New York, opening ranges, hourly ranges)
Reversal Trading: Identify high-probability reversal zones at OTE levels
Breakout/Reversal Trading: Monitor range breaks/reversals with built-in sweep alerts
Risk Management: Use Fibonacci projections as profit targets or rejection areas
Multi-Timeframe Analysis: Apply to any timeframe for various trading styles
Important Notes:
This indicator is for educational purposes only and should not be considered financial advice
Past performance does not guarantee future results
Always use proper risk management when trading
The indicator automatically manages historical data to maintain chart performance
ADR et %+Vol (ADR ou %)This indicator identifies breakout bars based on significant price movements combined with increased trading volume. It allows you to define breakout thresholds in two ways:
Key Features:
Threshold Method: Choose between:
Fixed Percentage (%): Specify an exact percentage move.
ADR-based (%): Utilize the Average Daily Range (ADR) multiplied by a factor of your choice.
ADR Calculation: Offers two distinct calculation methods to suit your trading style:
True Range (TR): Incorporates overnight gaps, making it ideal for swing trading.
High-Low (H-L): Purely intraday measure, suitable for day trading without gap consideration.
Timeframe Flexibility:
Select the desired timeframe for ADR calculation (e.g., Daily, Weekly, Hourly), providing flexibility to match your specific trading horizon.
Visual Signals:
Blue Bar Coloring: Highlights breakout candles clearly.
Blue Circle Markers: Signals bars with significant price movement accompanied by strong volume.
Information Display:
Shows the ADR percentage, selected timeframe, and calculation method directly on the chart (top-right), providing instant clarity about the current settings.
Usage Recommendations:
Use True Range ADR if you hold positions overnight or trade multi-day swings.
Opt for High-Low ADR if you're trading purely intraday and prefer simpler measures.
This versatile indicator is suited for both swing and intraday traders looking for reliable volatility measures combined with volume confirmation.
Daily ATR TrackerDaily ATR Tracker
The Daily ATR Tracker is a simple yet powerful tool designed to help traders monitor the daily price movement relative to the average daily range (ATR). This indicator provides an objective view of how much price has moved compared to its recent daily volatility.
🔎 Key Features:
Customizable ATR period (default 14 days)
Live calculation of the current day's price range
ATR value displayed in pips for clear reference
Percentage of ATR covered by the current day's range
Color-coded table for quick visual interpretation:
🟢 Green: less than 60% of ATR covered
🟠 Orange: 60% to 100% of ATR covered
🔴 Red: more than 100% of ATR covered
Alert condition when daily range exceeds 100% of the ATR average
Movable table position to fit your chart layout
🎯 Why use Daily ATR Tracker?
✅ Identify exhaustion zones: When price has already covered a large portion of its typical daily range, the odds of further strong movement may diminish, helping you to manage entries, exits, and risk.
✅ Objective daily bias: Get a quantitative sense of how "stretched" the market is in real time.
✅ Works with any timeframe: While designed for daily ranges, you can monitor intraday movements with this context in mind.
⚠️ Usage Note:
This tool does not provide buy or sell signals by itself. It is designed to complement your existing strategies by offering additional context regarding daily range exhaustion.
Rolling Z-Score Trend [QuantAlgo]🟢 Overview
The Rolling Z-Score Trend measures how far the current price deviates from its rolling mean in terms of standard deviations. It transforms price data into standardized scores to identify overbought and oversold conditions while tracking momentum shifts.
The indicator displays a Z-Score line showing price deviation from statistical norms, with background momentum columns showing the rate of change in these deviations. This helps traders and investors identify mean reversion opportunities and momentum shifts across different asset classes and timeframes.
🟢 How It Works
The indicator uses the Z-Score formula: Z = (X - μ) / σ, where X is the current closing price, μ is the rolling mean, and σ is the rolling standard deviation over a user-defined lookback period. This creates a dynamic baseline that adapts to changing market conditions and standardizes price movements for interpretation across different assets and volatility conditions. The raw Z-Score undergoes 3-period EMA smoothing to reduce noise while maintaining responsiveness to market signals.
Beyond the basic Z-Score calculation, the indicator measures the rate of change in Z-Score values between successive bars, displayed as background momentum columns. This momentum component shows acceleration and deceleration of statistical deviations. All calculations are processed through confirmation filters, displaying signals only on confirmed bars to reduce premature signals based on incomplete price action.
🟢 How to Use
1. Z-Score Interpretation and Threshold Zones
Positive Values (Above Zero) : Price trading above statistical mean, suggesting bullish momentum or potential overbought conditions
Negative Values (Below Zero) : Price trading below statistical mean, suggesting bearish momentum or potential oversold conditions
Zero Line Crosses : Signal transitions between statistical regimes and potential trend changes
Upper Threshold Zone : Area above entry threshold (default 1.5) indicating potential overbought conditions
Lower Threshold Zone : Area below negative entry threshold (default -1.5) indicating potential oversold conditions
Extreme Values (±2.0 or higher) : Statistically significant deviations that may indicate reversal opportunities
2. Momentum Background Analysis and Info Table
Green Columns : Accelerating positive momentum in Z-Score values
Red Columns : Accelerating negative momentum in Z-Score values
Column Height : Magnitude of momentum change between bars
Momentum Divergence : When columns contradict primary Z-Score direction, often signals impending reversals
Info Table : Displays real-time numerical values for both Z-Score and momentum, including trend direction indicators and bar-to-bar change calculations for position management
3. Preconfigured Settings
Default : Balanced performance across multiple timeframes and asset classes for general trading and medium-term position management.
Scalping : Responsive setup for ultra-short-term trading on 1-15 minute charts with frequent signals and increased sensitivity to quick price movements.
Swing Trading : Optimized for multi-day positions with noise filtering, focusing on larger price swings. Most effective on 1-4 hour and daily timeframes.
Trend Following : Maximum smoothing that prioritizes established trends over short-term volatility. Generates fewer signals for daily and weekly charts.
Bollinger Band Breakout With Volatility StoplossDetailed Explanation of the Bollinger Band Breakout With Volatility Stoploss System
Introduction
The "Bollinger Band Breakout With Volatility Stoploss" system is a trading strategy designed to exploit price volatility in financial markets using the Bollinger Bands indicator, a widely recognized tool developed by John Bollinger. This system adapts the traditional Bollinger Bands framework into a Volatility Breakout strategy, focusing on capturing significant price movements by leveraging customized parameters and precise trading rules. The system operates exclusively on long positions, employs a daily timeframe, and incorporates dynamic risk management techniques to optimize trade outcomes while preserving capital.
System Parameters
The system modifies the standard Bollinger Bands configuration to suit its breakout methodology:
Standard Deviation (SD): Set to 1x, determining the width of the bands relative to the central moving average. This tighter setting enhances sensitivity to price movements, making the system responsive to smaller volatility shifts compared to the conventional 2x SD.
Period: A 30-day (1-month) lookback period is used to calculate the bands, providing a balance between capturing medium-term price trends and avoiding excessive noise from shorter timeframes.
Moving Average Type: The system uses an Exponential Moving Average (EMA) instead of the Simple Moving Average (SMA). The EMA places greater weight on recent price data, making it more responsive to current market conditions and better suited for detecting breakout opportunities in dynamic markets.
Core Concept
The Bollinger Band Breakout system is built on the principle of Volatility Breakout, which seeks to capitalize on significant price movements when the price breaks out of a defined volatility range. The Bollinger Bands, consisting of an EMA as the central line and two bands (Upper and Lower) calculated as the EMA plus or minus 1x SD, define this range. The system operates on a Daily Chart (D) timeframe, making it suitable for traders who prefer analyzing and executing trades based on daily price action. By focusing solely on Long Positions (buying low and selling high), the system avoids short-selling, aligning with strategies that capitalize on upward price momentum.
The core idea is to use the 1x SD multiplier over a 30-day period to establish a dynamic price range that reflects recent market volatility. Breakouts above the Upper Band signal potential buying opportunities, while penetrations below the Lower Band indicate exits, ensuring trades are aligned with significant price movements.
Trading Signals
The system generates clear entry and exit signals based on price interactions with the Bollinger Bands:
Buy Signal: A buy signal is triggered when the closing price of a daily candle exceeds the Upper Bollinger Band (EMA + 1x SD over 30 days). The trade is entered at the opening price of the subsequent candle, ensuring the breakout is confirmed by the close of the prior day. This approach minimizes false signals by waiting for a definitive breach of the volatility threshold.
Sell Signal: A sell signal occurs when the closing price falls below the Lower Bollinger Band (EMA - 1x SD over 30 days). The position is exited at the opening price of the next candle, allowing the trader to lock in profits or limit losses when the price reverses or loses momentum.
Risk Management
Risk management is a cornerstone of the system, ensuring capital preservation and disciplined trade execution:
Initial Stoploss: The stoploss is set at the Lower Bollinger Band of the candle that triggered the buy signal. This level acts as a volatility-based threshold, below which the trade is deemed invalid, prompting an immediate exit to protect capital. Traders have two options for implementing the stoploss:
Pending Stoploss: A predefined stoploss order placed at the Lower Band level.
Conditional Exit: Using the sell signal condition (price closing below the Lower Band) as the exit trigger, effectively aligning the stoploss with the system’s exit rules.
Position Sizing: The system employs Fixed Fractional Position Sizing with a risk per trade capped at 3% of the account balance. The position size is calculated based on the distance between the entry price and the Initial Stoploss, incorporating Volatility Position Sizing. This method adjusts the trade size according to the market’s volatility, ensuring that risk remains consistent across varying market conditions. Two options are available for managing capital:
Gear Up Option: Profits from previous trades are reinvested into the account’s capital, increasing the base for calculating the next position size. This compounding approach can amplify returns but also increases risk exposure.
Fixed Equity Option: Profits from previous trades are withdrawn, and only the remaining capital is used for calculating the next position size. This conservative approach prioritizes capital preservation by not compounding gains.
Trailing Stop: The system uses the Lower Bollinger Band as a dynamic trailing stop, which adjusts with price movements and volatility. This ensures that profits are protected during favorable trends while allowing the trade to remain open as long as the price stays above the Lower Band. The trailing stop aligns with the sell signal condition, maintaining consistency in the system’s exit strategy.
Supporting Indicators
The system incorporates two additional indicators to enhance market analysis and decision-making:
Bollinger Band Width (BBW): BBW measures the distance between the Upper and Lower Bollinger Bands relative to the EMA, serving as a proxy for market volatility.
A high BBW indicates significant price volatility, often associated with strong trends or large price movements, which may confirm the strength of a breakout.
A low BBW suggests low volatility, potentially signaling a period of consolidation or "squeeze" that could precede a breakout. This can help traders anticipate potential trade setups.
The BBW calculation uses the EMA to maintain consistency with the system’s core parameters.
Bollinger Band Ratio (BBR) or %B: BBR measures the price’s position relative to the Bollinger Bands, providing insight into market conditions.
BBR > 1: The price is above the Upper Band, indicating potential overbought conditions or strong upward momentum, which aligns with the system’s buy signal.
BBR < 0: The price is below the Lower Band, suggesting oversold conditions or downward momentum, corresponding to the sell signal or stoploss trigger.
BBR between 0 and 1: The price is within the bands, indicating a neutral state where no immediate action is required.
Like BBW, BBR is calculated using the EMA for consistency.
Backtesting and Implementation
To evaluate the system’s performance, traders can utilize the Backtest Parameter function, which allows for testing the strategy across user-defined time periods. This feature enables traders to assess the system’s effectiveness under various market conditions, optimize parameters, and refine their approach based on historical data.
Conclusion
The Bollinger Band Breakout With Volatility Stoploss system is a robust, volatility-driven trading strategy that combines the predictive power of Bollinger Bands with disciplined risk management. By focusing on long positions, using a 1x SD multiplier, and incorporating EMA-based calculations, the system is designed to capture significant price breakouts while minimizing risk through dynamic stoplosses and volatility-adjusted position sizing. The inclusion of BBW and BBR indicators provides additional context for assessing market conditions, enhancing the trader’s ability to make informed decisions. With its structured approach and backtesting capabilities, this system is well-suited for traders seeking a systematic, data-driven method to trade in volatile markets.
Liquidity Hunter HeatmapLiquidity Hunter (GPS Companion Tool)
Liquidity Hunter is a specialized script designed to help traders visualize and track potential liquidation zones, clusters, and imbalance traps in real-time. It is particularly useful for scalpers and short-term traders who rely on liquidity sweeps, stop hunts, and reversion plays.
This tool does not replicate open-source liquidation trackers. Instead, it uses a proprietary combination of volume surges, candle displacement, VWAP deviation, and high-timeframe wicks to infer areas of trapped traders and display them with clear, color-coded markers.
Key Features:
• Real-Time Liquidation Estimates: Detects where major stop losses (and potential liquidations) may have occurred, based on proprietary volume + price action logic.
• Cluster Strength Bubbles: Visual bubbles (scaled by cluster size) show where liquidations are stacking. Purple for bearish, white for bullish — intensity reflects strength.
• Pre-Liquidation Warning Zones: Highlights areas where price is likely to sweep liquidity before reversing, helping traders avoid chasing moves.
• Dollar-Based Labels (Optional): Displays the estimated value liquidated, helping traders size the significance of a move (e.g., $8.4M).
• Minimal Clutter Mode: Designed for intraday clarity — hides excess lines and uses bubbles, not shapes, for cleaner visualization.
Consolidation Zones[RanaAlgo]Overview
This indicator helps traders identify price consolidation zones (ranges) and potential breakouts in the market. It is useful for spotting periods of low volatility before significant price movements.
How It Works
Detects Consolidation Zones
Uses the ADX (Average Directional Index) to determine when the market is in a consolidation phase .
When ADX is below the threshold , the indicator marks the start of a consolidation zone.
Draws a semi-transparent box around the price range, adjusting its height as new highs/lows form.
Tracks Breakouts
When price breaks above/below the consolidation box, it signals a potential trend continuation.
Displays breakout arrows/labels (configurable shape & style) when price exits the range.
Visual Features
Boxes highlight consolidation areas (customizable color, border, and style).
Labels show real-time status ("CONSOLIDATING" or "TRENDING").
Breakout signals appear as arrows or shapes (up/down).
Usefulness in Trading
Range Trading: Helps traders identify sideways markets for buying low and selling high.
Breakout Trading: Signals potential trend entries when price exits consolidation.
Trend Confirmation: Low ADX + consolidation box = weak trend; breakout = possible trend start.
Example: If price stays in a blue box (consolidation) and then breaks above with an arrow, it suggests a bullish move.
Adaptive Momentum Deviation Oscillator | QuantMACAdaptive Momentum Deviation Oscillator | QuantMAC 📊
Overview 🎯
The Adaptive Momentum Deviation Oscillator (AMDO) is an advanced technical analysis indicator that combines the power of Bollinger Bands with adaptive momentum calculations to identify optimal entry and exit points in financial markets. This sophisticated oscillator creates dynamic bands that adapt to market volatility while providing clear visual signals for both trending and ranging market conditions.
How It Works 🔧
Core Methodology
The AMDO employs a sophisticated multi-layered approach to market analysis through four distinct phases:
Bollinger Band Foundation : The indicator begins by establishing a volatility baseline using traditional Bollinger Bands. These bands are calculated using a simple moving average as the center line, with upper and lower bands positioned at a specific number of standard deviations away from this centerline. The distance between these bands expands and contracts based on market volatility, creating a dynamic envelope around price action.
BB% Normalization Process : The raw price data is then transformed into a normalized percentage format that represents where the current price sits within the Bollinger Band envelope. When price is at the lower band, this percentage reads 0%; at the upper band, it reads 100%. This normalization allows for consistent comparison across different timeframes and price levels, creating a standardized oscillator that oscillates between extreme values.
Adaptive Momentum Band Construction : The normalized BB% values undergo a secondary volatility analysis where their own standard deviation is calculated over a specified period. This creates "bands around the bands" - upper and lower boundaries that adapt to the volatility of the normalized price position itself. These adaptive bands expand during periods of high momentum volatility and contract during consolidation phases.
Intelligent Signal Synthesis : The final layer combines the adaptive momentum bands with user-defined threshold levels to create a sophisticated trigger system. The indicator monitors when the dynamic bands cross above or below these thresholds, filtering out noise while capturing significant momentum shifts. This creates a dual-confirmation system where both volatility adaptation and threshold breaches must align for signal generation.
Key Components 🛠️
Adaptive Momentum Bands 📈
Dynamic Volatility Response : These bands automatically widen during periods of high momentum volatility and narrow during consolidation phases. Unlike fixed oscillator boundaries, they continuously recalibrate based on recent price behavior within the Bollinger Band framework.
Dual-Layer Calculation : The bands are derived from the volatility of the normalized price position itself, creating a "volatility of volatility" measurement. This provides early warning signals when momentum characteristics are changing, even before price breakouts occur.
State-Aware Visualization : The bands employ intelligent color coding that transitions between active and neutral states based on their interaction with threshold levels. Active states indicate high-probability momentum conditions, while neutral states suggest consolidation or indecision.
Momentum Persistence Tracking : The bands maintain memory of recent momentum characteristics, allowing them to distinguish between genuine momentum shifts and temporary price spikes or dips.
Threshold Levels 🎚️
Statistical Significance Boundaries : The threshold levels (default 83 for long, 40 for short) are positioned to capture statistically significant momentum events while filtering out market noise. These levels represent points where momentum probability shifts meaningfully in favor of directional moves.
Asymmetric Design Philosophy : The intentional asymmetry between long and short thresholds (83 vs 40) reflects the natural upward bias of many financial markets and the different risk/reward profiles of long versus short positions.
Contextual Sensitivity : The thresholds work in conjunction with the adaptive bands to create context-sensitive triggers. A threshold breach is only meaningful when it occurs in the proper sequence with band interactions.
Risk-Adjusted Positioning : The threshold levels are calibrated to provide favorable risk-adjusted entry points, considering both the probability of success and the potential magnitude of subsequent moves.
Bollinger Bands Overlay 📊
Multi-Timeframe Context : The price chart overlay provides essential context by showing traditional Bollinger Bands alongside the oscillator. This dual perspective allows traders to see both the absolute price position and the momentum characteristics simultaneously.
Support/Resistance Identification : The filled band area creates a visual representation of dynamic support and resistance levels. Price interaction with these bands provides additional confirmation for oscillator signals.
Volatility Environment Assessment : The width and slope of the bands offer immediate visual feedback about the current volatility environment, helping traders adjust their expectations and risk management accordingly.
Confluence Analysis : The overlay enables traders to identify confluence between price action at Bollinger Band levels and oscillator signals, creating higher-probability trade setups.
Signal Generation ⚡
The AMDO generates signals through precise mathematical crossover events:
Long Signals 🟢
Momentum Accumulation Detection : Long signals are generated when the lower adaptive momentum band crosses above the 83 threshold, indicating that downside momentum has exhausted and bullish momentum is beginning to accumulate. This represents a shift from defensive to offensive market posture.
Statistical Edge Confirmation : The crossing event occurs only when momentum characteristics have shifted sufficiently to provide a statistical edge for long positions. The adaptive nature ensures the signal quality remains consistent across different market volatility regimes.
Visual State Synchronization : Upon signal generation, the entire indicator ecosystem shifts to a bullish state - bar colors change, band states update, and the visual hierarchy emphasizes the long bias until conditions change.
Momentum Persistence Validation : The signal incorporates momentum persistence analysis to distinguish between genuine trend starts and false breakouts, reducing whipsaw trades in choppy market conditions.
Short Signals 🔴
Momentum Exhaustion Recognition : Short signals trigger when the upper adaptive momentum band crosses below the 40 threshold, signaling that bullish momentum has peaked and bearish momentum is emerging. This asymmetric threshold reflects the different dynamics of bullish versus bearish market phases.
Volatility-Adjusted Timing : The adaptive band system ensures that short signals are generated with appropriate timing regardless of the underlying volatility environment, maintaining signal quality in both high and low volatility conditions.
Regime-Aware Activation : Short signals are only active in Long/Short trading mode, recognizing that not all trading strategies benefit from short positions. The indicator adapts its behavior based on the selected trading approach.
Risk-Calibrated Thresholds : The 40 threshold is specifically calibrated to capture meaningful bearish momentum shifts while accounting for the higher risk typically associated with short positions.
Cash Signals 💰
Defensive Positioning Logic : In Long/Cash mode, cash signals are generated when short conditions are met, allowing traders to move to a defensive cash position rather than taking on short exposure. This preserves capital during unfavorable market conditions.
Risk Mitigation Strategy : Cash signals represent a risk-off approach that removes market exposure when momentum conditions favor the short side, protecting long-biased portfolios from adverse market movements.
Opportunity Cost Optimization : The cash position allows traders to avoid negative returns while maintaining flexibility to re-enter long positions when momentum conditions improve, optimizing the risk-adjusted return profile.
Features & Customization ⚙️
Color Schemes 🎨
9 pre-built color schemes (Classic through Classic9)
Custom color override option
Dynamic color changes based on signal states
Trading Modes 📈
Long/Short : Full bidirectional trading capability
Long/Cash : Long-only strategy with cash positions
Performance Metrics 📊
The indicator includes a comprehensive suite of advanced performance analytics that provide deep insights into strategy effectiveness:
Risk-Adjusted Return Metrics
Sortino Ratio : Measures returns relative to downside deviation only, providing a more accurate assessment of risk-adjusted performance by focusing on harmful volatility rather than total volatility. This metric is particularly valuable for asymmetric return distributions.
Sharpe Ratio : Calculates excess return per unit of total risk, offering a standardized measure of risk-adjusted performance that allows for comparison across different strategies and timeframes.
Omega Ratio : Employs probability-weighted analysis to compare the likelihood and magnitude of gains versus losses, providing insights into the overall shape of the return distribution and tail risk characteristics.
Drawdown and Risk Analysis
Maximum Drawdown : Tracks the largest peak-to-trough equity decline, providing crucial information about the worst-case scenario and helping traders understand the emotional and financial stress they might encounter.
Dynamic Drawdown Monitoring : Continuously updates drawdown calculations in real-time, allowing traders to monitor current drawdown levels relative to historical maximums.
Trade Statistics and Profitability
Profit Factor Analysis : Compares gross profits to gross losses, revealing the efficiency of the trading approach and the relationship between winning and losing trades.
Win Rate Calculation : Provides the percentage of profitable trades, which must be interpreted in conjunction with profit factor and average trade size for meaningful analysis.
Trade Frequency Tracking : Monitors total trade count to assess strategy turnover and transaction cost implications.
Position Sizing Guidance
Half Kelly Percentage : Calculates optimal position sizing based on Kelly Criterion methodology, then applies a conservative 50% reduction to account for parameter uncertainty and reduce volatility. This provides mathematically-based position sizing guidance that balances growth with risk management.
Parameters & Settings 🔧
BMD Settings
- Base Length : Period for Bollinger Band calculation (default: 10)
- Source : Price data source (default: close)
- Standard Deviation Length : Period for volatility calculation (default: 35)
- SD Multiplier : Bollinger Band width multiplier (default: 1.0)
- BB% Multiplier : Scaling factor for BB% calculation (default: 100)
BMD Settings
Base Length : Period for Bollinger Band calculation (default: 10)
Source : Price data source (default: close)
Standard Deviation Length : Period for volatility calculation (default: 35)
SD Multiplier : Bollinger Band width multiplier (default: 1.0)
BB% Multiplier : Scaling factor for BB% calculation (default: 100)
Signal Thresholds 🎯
Long Threshold : Trigger level for long signals (default: 83)
Short Threshold : Trigger level for short signals (default: 40)
Display Options 🖥️
Toggleable metrics table with 6 position options
Customizable date range limiter
Multiple visual elements for comprehensive analysis
Use Cases & Applications 💡
Trend Following
Identifies momentum shifts in trending markets
Provides early entry signals during trend continuations
Adaptive bands adjust to changing volatility conditions
Mean Reversion
Detects oversold/overbought conditions
Signals potential reversal points
Works effectively in ranging markets
Risk Management
Built-in performance metrics for strategy evaluation
Half Kelly percentage for position sizing guidance
Maximum drawdown monitoring
Advantages ✅
Adaptive Nature : Automatically adjusts to market volatility
Dual Display : Oscillator and price chart components work together
Comprehensive Metrics : Built-in performance analysis
Flexible Trading Modes : Supports different trading strategies
Visual Clarity : Color-coded signals and states
Customizable : Extensive parameter adjustment options
Important Considerations ⚠️
This indicator is designed for educational and analysis purposes
Should be used in conjunction with other technical analysis tools
Proper risk management is essential when trading
Backtest thoroughly before implementing in live trading
Market conditions can change rapidly, affecting indicator performance
Disclaimer ⚠️
Past performance is not indicative of future results. Trading involves substantial risk of loss and is not suitable for all investors. The information provided by this indicator should not be considered as financial advice. Always conduct your own research.
No indicator guarantees profitable trades - Always use proper risk management! 🛡️
Daily Bias on 5 minutes Reversal StrategyThis strategy combines higher-timeframe bias (daily and 1-hour) with 5-minute reversal signals to identify intraday trades. It aims to capitalize on false breakouts of the previous day's high/low, with strict risk management (Strict position sizing, max risk cap, and R:R enforcement), Avoids Over-Trading (1 trade/day rule prevents chasing), SL buffer adapts to volatility.
#1. This strategy does not utilize indicators. We will use the daily (D) price range and look for breakout attempts and rejections at the extreme points on the lower time frame (1h). If rejection occurs, it establishes our bias (bullish or bearish). For final confirmation, we move to the 5-minute timeframe to observe attempts to retest that daily price range. If significant rejection occurs again, that becomes our entry point.
#2. When rejection occurs, the 1-hour candle may form a new extreme point (low/high). Therefore, we will no longer use the daily price range as our trade exit point but instead the new extreme level established after the breakout attempt and price rejection.
To prevent premature trade exits, we also add an SL buffer using ATR while still capping the maximum acceptable risk per trade (as a percentage). Take profit is calculated using a risk-to-reward ratio, with a default setting of 1.5x.
#3. Key Input Parameters
a. Timeframes :
1. Daily TF ((Anchor for daily high/low (default: D).)
2. 1H Bias TF (Bias confirmation timeframe (default: 60))
3. Execution TF (Entry signal timeframe (default: 5, should match chart).
b. Trade Management
1. SL Buffer ATR Multiplier (Buffer beyond swing low/high (default: 6.0))
2. Min ATR Threshold (Minimum buffer size (default: 1.0))
3. Risk Reward Ratio (TP distance multiplier (default: 1.5))
4. Max Risk Allowed (Max risk % of entry (default: 3.0%))
Lookback Bars for SL Bars for swing low/high (default: 60))
c. Break Thresholds
1. 1H Candle Break Threshold (ATR multiplier for 1H break (default: 0.75))
2. 5M Candle Break Threshold (ATR multiplier for 5M break (default: 0.5))
Improved Historical Volatility Calculator (No Options)Improved Historical Volatility Calculator (No Options)
Description
The "Improved Historical Volatility Calculator (No Options)" is a Pine Script indicator designed to calculate the historical volatility (HV) of assets without relying on options data. This tool is particularly useful for markets like forex, indices, or stocks where options trading might be limited or unavailable. It provides a customizable way to measure volatility based on historical price movements, with options to adjust the calculation period, trading days per year, and use an exponentially weighted moving average (EWMA) for enhanced sensitivity to recent data.
This indicator can be used standalone to visualize volatility trends or integrated with other scripts (e.g., option pricing models) to provide a manual input for implied volatility (IV).
Features
Customizable Period: Adjust the number of days (5 to 365) for volatility calculation.
Flexible Annualization: Set the number of trading days per year (default 252) to suit different markets (e.g., 365 for forex).
EWMA Option: Toggle between standard deviation and EWMA for a more responsive volatility measure.
Trend Adjustment: Removes the influence of price trends using an EMA-based detrending method.
Visual Output: Displays volatility as a histogram and labels the latest value on the chart.
How to Use
Add the Indicator: Load the indicator onto your chart via the Pine Script editor or the Indicators menu.
Configure Settings:
Period for Calculation: Set the lookback period (e.g., 30 days) to calculate volatility.
Trading Days per Year: Adjust for your market (e.g., 252 for stocks, 365 for continuous markets).
Use EWMA: Enable for a weighted approach focusing on recent volatility.
Interpret the Results: The histogram shows volatility in decimal form (e.g., 0.03136 = 3.136%), and the label displays the percentage on the last bar.
Integration: Use the calculated volatility value (in decimal form) as a manual IV input in other scripts, such as option pricing models.
Example
For the DXY index, with a 60-day period and 252 trading days per year, the indicator might output a volatility of 0.03136 (3.136%). You can input this value into an options model to estimate standard deviation levels, adjusting for the days to expiry.
Notes
Accuracy: The indicator provides a reliable estimate of historical volatility, with improvements like trend removal and EWMA. For precision, use a period that matches your trading horizon (e.g., 30-90 days).
Limitations: Volatility is based on historical data and may not reflect future market conditions or implied volatility from options.
Compatibility: Tested on TradingView as of June 16, 2025. Ensure sufficient historical data is available for the chosen period.
Suggestions
Increase the period for volatile assets to smooth out noise.
Share feedback or request enhancements in the comments!
Momentum Candle by Sekolah Trading## 🔷 Introduction
**Momentum Candle by Sekolah Trading** is a proprietary price action tool that identifies high-conviction candles with large bodies and minimal wicks, based on dynamically adjusted thresholds tailored to each pair and timeframe. This script helps traders recognize moments of price acceleration that often precede breakouts, trend continuation, or sharp reversals.
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## 🔷 What Makes This Script Unique (Originality & Utility)
Unlike traditional candle filters that rely on static size comparisons, this indicator uses:
- **Instrument-specific pip sensitivity**: Automatically detects if the pair is XAUUSD, JPY-based, or other Forex instruments.
- **Timeframe-based calibration**: Adjusts body size thresholds dynamically for 5m, 15m, 30m, and 1h.
- **Wick ratio control**: Validates only candles with short wicks (<30%), filtering indecisive moves.
- **Non-repainting logic**: Signals appear after candle close, with no future data lookahead.
This logic has been tested and refined internally by **Sekolah Trading**, designed for scalpers and intraday traders who rely on clean price action structure.
---
## 🔷 How It Works
1. **Pair & Timeframe Detection**
Adjusts `minRange` dynamically based on:
- Gold (XAUUSD), JPY pairs, or other Forex
- Timeframe: 5m to 1h
2. **Candle Structure Analysis**
- Calculates body = `abs(open - close)`
- Wick = `upper + lower shadows`
- Valid only if wick is under 30% of total candle
3. **Conditions for Signal**
- Body ≥ minRange
- Wick ≤ 30%
- Clear bullish or bearish direction
4. **Plots**
- 🔺 Blue triangle = Bullish momentum candle
- 🔻 Red triangle = Bearish momentum candle
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## 🔷 How to Use
1. **Add to any 5m–1h chart**, ideally on XAUUSD or major Forex pairs
2. **Wait for signal triangle** to appear at the close of a candle
3. Use with:
- Trend indicators (MA, Supertrend, etc.)
- Support/resistance zones
- Breakout levels
4. **Set alerts** using:
`Momentum Candle (Body)`
---
## 🔷 Why This Script is Closed-Source
This indicator includes proprietary logic created by **Sekolah Trading** for professional and community use:
- Original dynamic pip sensitivity calibration
- Custom multi-condition filtering
- Non-reused, non-public logic with adaptive precision
The source is protected to prevent unauthorized duplication. However, all relevant logic and intent have been clearly explained above as required by TradingView’s House Rules.
---
## 🔷 Disclaimer
This indicator does not provide financial advice or guaranteed signals. Always combine with your own analysis and risk management. Historical performance does not guarantee future results.
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## 🔷 Suggested Tags
`momentum`, `price action`, `breakout`, `forex`, `xauusd`, `jpy`, `scalping`, `candle`, `non-repainting`, `trend confirmation`
Adaptive Multi-MA OptimizerAdaptive Multi-MA Optimizer
This indicator provides a powerful, customizable solution for traders seeking dynamically optimized moving averages with precision and control. It integrates multiple custom-built moving average types, applies real-time volatility-based optimization, and includes an optional composite smoothing engine.
🧠 Key Features
Dynamic Optimization:
Automatically selects the optimal lookback length based on market volatility stability using a custom standard deviation differential model.
Multiple Custom MA Types:
Includes fully custom implementations of:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume Weighted MA)
DEMA (Double EMA)
TEMA (Triple EMA)
Hull MA
ALMA (Arnaud Legoux MA)
Composite MA Option:
A unique "Composite" mode blends all supported MAs into a single average, then applies optional smoothing for enhanced signal clarity.
Dynamic Smoothing:
The composite mode supports volatility-adjusted smoothing (based on optimized lookback), making it adaptable to different market regimes.
Fully Custom Logic:
No built-in MA functions are used — every moving average is hand-coded for transparency and educational value.
⚙️ How It Works
Optimization:
The script evaluates a range of lengths (minLen to maxLen) using the standard deviation of price returns. It selects the length with the most stable recent volatility profile.
Calculation:
The selected MA type is calculated using that optimized length. If "Composite" is chosen, all MA types are averaged and smoothed dynamically.
Visualization:
The adaptive MA is plotted on the chart, changing color based on its position relative to price.
📌 Use Cases
Trend-following strategies that adapt to different market conditions.
Traders wanting a high-fidelity composite of multiple MAs.
Analysts interested in visualizing market smoothness without lag-heavy signals.
Coders looking to learn how to build custom indicators from scratch.
🧪 Inputs
MA Type: Choose from 8 MA types or a blended Composite.
Lookback Range: Control min/max and step size for optimization.
Source: Choose any price series (e.g., close, hl2).
⚠️ Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice, trading advice, or investment recommendations. Use of this script is at your own risk. Past performance does not guarantee future results. Always perform your own analysis and consult with a qualified financial advisor before making trading decisions.
Dynamic Laguerre Filter Bands | OttoThis indicator combines trend-following and volatility analysis by enhancing the traditional Laguerre filter with a dynamic, volatility-adjusted band system. Instead of using fixed thresholds, the bands adapt in real-time to changing market conditions by applying smoothed standard deviation calculations. This design keeps the indicator responsive to significant price movements while effectively filtering out short-term market noise, resulting in more accurate trend identification and breakout signals.
Core Concept
The indicator is built around the following key components:
Laguerre Filter:
The Laguerre filter is designed to smooth out price data by reducing market noise while still being quick enough to detect real changes in price direction. Its goal is to create a clear, smooth trend line that helps traders/investors focus on the overall market trend without getting distracted by small, random price swings.
It uses a parameter called gamma to control how it balances smoothness and responsiveness:
A lower gamma gives more weight to recent price data, making the filter react faster to new price changes. This means the trend line is more sensitive but may also be less smooth and more prone to small fluctuations.
A higher gamma gives more weight to past price data, making the filter smoother and less sensitive to quick changes. This helps reduce noise and produces a steadier trend line, but it also introduces more lag, meaning the filter reacts slower to new price moves.
By adjusting gamma, the Laguerre filter lets you choose the balance between following price changes quickly and having a stable, noise-free trend signal.
Standard Deviation:
shows how much price varies from the mean. In this indicator, it’s used to measure market volatility.
Volatility Bands: The upper and lower bands are based on an EMA-smoothed standard deviation of price. The EMA reduces sudden jumps in volatility, creating smoother and more stable bands that still respond to changing market conditions. These bands are plotted around the Laguerre filter line, expanding and contracting in a controlled way to stay aligned with real market movement while avoiding short-term noise.
Signal Logic:
A long signal is triggered when the close price crosses above the upper band.
A short signal occurs when the close price falls below the lower band.
⚙️ Inputs
Source: Price source used in calculations
Gamma: Adjusts how much the Laguerre filter responds to price changes. Lower gamma values make the filter react more to recent prices, while higher values give more influence to older data, making the line smoother but slower to respond.
Volatility Length: Period used to calculate standard deviation
Volatility Smoothing Length: EMA smoothing length for standard deviation
Multiplier: Scales the width of the bands based on volatility
📈 Visual Output
Laguerre Filter Line: Plots the laguerre filter line, colored dynamically based on signal direction (green for bullish, purple for bearish)
Upper & Lower Bands: Volatility-based bands that adjust with market conditions. (green for bullish, purple for bearish)
Glow Effect: Optional glow layer to enhance visibility of the laguerre filter trend line (green for bullish, purple for bearish)
Bar Coloring: Candlesticks and bar colors reflect the active signal state for fast visual interpretation (green for bullish, purple for bearish)
How to Use
Apply the indicator to your chart and monitor for signal events:
Long Signal: When price closes above the upper band
Short Signal: When price closes below the lower band
🔔 Alerts
This indicator supports optional alert conditions you can enable for:
Long Signal: Close price crossing above the upper band
Short Signal: Close price crossing below the lower band
⚠️ Disclaimer:
This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
VWAP Multi-Timeframe VWAP Multi-Timeframe - Complete Professional Indicator
🚀 WHAT IS IT?
The VWAP Multi-Timeframe is an advanced indicator that combines 5 different VWAP periods in a single tool, providing a complete view of market fair value levels across multiple time scales.
⭐ KEY FEATURES
📊 5 Configurable VWAPs:
🟡 Daily VWAP - Ideal for day trading and intraday operations
🟠 Weekly VWAP - Perfect for swing trading
🔵 Monthly VWAP - Excellent for medium-term analysis
🔴 Quarterly VWAP - Essential for quarterly strategies
🟢 Yearly VWAP - Fundamental for long-term investments
🎯 Multiple Price Sources:
Choose the source that best fits your strategy:
Close - Closing price (most common)
OHLC4 - Complete average (smoother)
HLC3 - Typical price (default)
HL2 - Period midpoint
Open/High/Low - Specific prices
💡 HOW TO USE
For Day Traders:
Use Daily VWAP as main fair value reference
Prices above = buying pressure / Prices below = selling pressure
For Swing Traders:
Combine Weekly and Monthly VWAP to identify trends
Look for confluences between different timeframes
For Investors:
Quarterly and Yearly VWAP show long-term value levels
Excellent for identifying entry points in investments
🔧 TECHNICAL FEATURES
✅ Pine Script v6 - Latest and optimized version
✅ Clean Interface - User-friendly design
Adaptive Normalized Global Liquidity OscillatorAdaptive Normalized Global Liquidity Oscillator
A dynamic, non-repainting oscillator built on real central bank balance sheet data. This tool visualizes global liquidity shifts by aggregating monetary asset flows from the world’s most influential central banks.
🔍 What This Script Does:
Aggregates Global Liquidity:
Includes Federal Reserve (FED) assets and subtracts liabilities like the Treasury General Account (TGA) and Reverse Repo Facility (RRP), combined with asset positions from the ECB, BOJ, PBC, BOE, and over 10 other central banks. All data is normalized into USD using FX rates.
Adaptive Normalization:
Optimizes the lookback period dynamically based on rate-of-change stability—no fixed lengths, enabling adaptation across macro conditions.
Self-Optimizing Weighting:
Applies inverse standard deviation to balance raw liquidity, smoothed momentum (HMA), and standardized deviation from the mean.
Percentile-Ranked Highlights:
Liquidity readings are ranked relative to history—extremes are visually emphasized using gradient color and adaptive transparency.
Non-Repainting Design:
Data is anchored with bar index awareness and offset techniques, ensuring no forward-looking bias. What you see is what was known at that time.
⚠️ Important Interpretation Note:
This is not a zero-centered oscillator like RSI or MACD. The signal line does not represent neutrality at zero.
Instead, a dynamic baseline is calculated using a rolling mean of scaled liquidity.
0 is irrelevant on its own—true directional signals come from crosses above or below this adaptive baseline.
Even negative values may signal strength if they are rising above the moving average of past liquidity conditions.
✅ What to Watch For:
Crossover Above Dynamic Baseline:
Indicates liquidity is expanding relative to recent conditions—supports a risk-on interpretation.
Crossover Below Dynamic Baseline:
Suggests deteriorating liquidity conditions—may align with risk-off shifts.
Percentile Extremes:
Readings near the top or bottom historical percentiles can act as contrarian or confirmation signals, depending on momentum.
⚙️ How It Works:
Bounded Normalization:
The final oscillator is passed through a tanh function, keeping values within and reducing distortion.
Adaptive Transparency:
The strength of deviations dynamically adjusts plot intensity—visually highlighting stronger liquidity shifts.
Fully Customizable:
Toggle which banks are included, adjust dynamic optimization ranges, and control visual display options for plot and background layers.
🧠 How to Use:
Trend Confirmation:
Sustained rises in the oscillator above baseline suggest underlying monetary support for asset prices.
Macro Turning Points:
Reversals or divergences, especially near OB/OS zones, can foreshadow broader risk regime changes.
Visual Context:
Use the dynamic baseline to see if liquidity is supportive or suppressive relative to its own adaptive history.
📌 Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always consult a qualified financial advisor before making trading or investment decisions.
Adaptive RSI Oscillator📌 Adaptive RSI Oscillator
This indicator transforms the classic RSI into a fully adaptive, self-optimizing oscillator — normalized between -1 and 1, dynamically smoothed, and enhanced with divergence detection.
🔧 Key Features
Self-Optimizing RSI: Automatically selects the optimal RSI lookback length based on return stability (no hardcoded periods).
Dynamic Smoothing: Adapts to market conditions using a fraction of the optimized length.
Normalized Output : Converts traditional RSI to a consistent scale across all assets and timeframes.
Divergence Detection: Compares RSI behavior vs. price percentile ranks and scales the signal accordingly.
Gradient Visualization: Color-coded background and plot lines reflect the strength and direction of the signal with soft transitions.
Neutral Zone Adaptation: Dynamically widens or narrows the zone of inaction based on volatility, reducing noise.
🎯 Use Cases
Identify extreme momentum zones without relying on fixed 70/30 RSI levels
Detect divergences early with adaptive filtering
Highlight potential exhaustion or continuation
⚠️ Disclaimer: This indicator is for informational and educational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security. Always conduct your own research and consult a licensed financial advisor before making investment decisions. Use at your own risk.
