GlocksFibsA modded Version of AlgoAlphas fib script. reworked it into my fib set. same rules apply 868 924 entry. first tp 50% mark. using it to help speed up my charting process overall. This is by far one of the best ones ive found that wont print the fib weird once the new numbers are in. all credits to AlgoAlpha and this gem they made!
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Future is hereOverview
"Future is Here" is an original, multi-faceted Pine Script indicator designed to provide traders with a comprehensive toolset for identifying high-probability trading opportunities. By integrating volatility-based entry zones, trend-based price targets, momentum confirmation, dynamic support/resistance levels, and risk-reward ratio (RRR) calculations, this indicator offers a cohesive and actionable trading framework. Each feature is carefully designed to complement the others, ensuring a synergistic approach that enhances decision-making across various market conditions. This script is unique in its ability to combine these elements into a single, streamlined interface with clear visual cues and customizable alerts, making it suitable for both novice and experienced traders.
Key Features and How They Work Together
Volatility-Based Entry Zones
Purpose: Identifies overbought and oversold conditions using a volatility-adjusted moving average, helping traders spot potential reversal zones.
Mechanism: Utilizes a user-defined volatility length and multiplier to calculate dynamic overbought/oversold thresholds based on the standard deviation of price. Crossovers and crossunders of these levels trigger "Buy Zone" or "Sell Zone" labels.
Synergy: These zones act as the foundation for entry signals, which are later confirmed by momentum and trend filters to reduce false signals.
Trend-Based Price Targets
Purpose: Projects potential price targets based on the prevailing trend, giving traders clear objectives for profit-taking.
Mechanism: Combines a fast and slow moving average to determine trend direction, then calculates target prices using a multiplier of the price deviation from the slow MA. Labels display bullish or bearish targets when the fast MA crosses the slow MA.
Synergy: Works in tandem with entry zones and momentum signals to align targets with market conditions, ensuring traders aim for realistic price levels supported by trend strength.
Momentum Confirmation
Purpose: Validates entry signals by assessing momentum strength, filtering out weak setups.
Mechanism: Uses the momentum indicator to detect bullish or bearish momentum crossovers, labeling them as "Strong" or "Weak" based on a comparison with a smoothed momentum average.
Synergy: Enhances the reliability of buy/sell signals by ensuring momentum aligns with volatility zones and trend direction, reducing the risk of premature entries.
Dynamic Support/Resistance Levels
Purpose: Highlights key price levels where the market is likely to react, aiding in trade planning and risk management.
Mechanism: Detects pivot highs and lows over a user-defined lookback period, drawing horizontal lines for the most recent support and resistance levels (limited to two each for clarity). Labels mark these levels with price values.
Synergy: Complements entry zones and price targets by providing context for potential reversal or continuation points, helping traders set logical stop-losses or take-profits.
Buy/Sell Signals with Risk-Reward Ratios
Purpose: Generates precise buy/sell signals with integrated take-profit (TP), stop-loss (SL), and RRR calculations for disciplined trading.
Mechanism: Combines volatility zone crossovers, trend confirmation, and positive momentum to trigger signals. ATR-based TP and SL levels are calculated, and the RRR is displayed in labels for quick assessment.
Synergy: This feature ties together all previous components, ensuring signals are only generated when volatility, trend, and momentum align, while providing clear risk-reward metrics for trade evaluation.
Customizable Alerts
Purpose: Enables traders to stay informed of trading opportunities without constant chart monitoring.
Mechanism: Alert conditions are set for buy and sell signals, delivering notifications with the entry price for seamless integration into trading workflows.
Synergy: Enhances usability by allowing traders to act on high-probability setups identified by the indicator’s combined logic.
Originality
"Future is Here" is an original creation that distinguishes itself through its holistic approach to technical analysis. Unlike single-purpose indicators, it integrates volatility, trend, momentum, and support/resistance into a unified system, reducing the need for multiple scripts. The inclusion of RRR calculations directly in signal labels is a unique feature that empowers traders to evaluate trade quality instantly. The script’s design emphasizes clarity and efficiency, with cooldowns to prevent label clutter and a limit on support/resistance lines to maintain chart readability. This combination of features, along with its customizable parameters, makes it a versatile and novel tool for traders seeking a robust, all-in-one solution.
How to Use
Setup: Add the indicator to your TradingView chart and adjust input parameters (e.g., Volatility Length, Trend Length, TP/SL Multipliers) to suit your trading style and timeframe.
Interpretation:
Look for "Buy Zone" or "Sell Zone" labels to identify potential entry points.
Confirm entries with "Bull Mom" or "Bear Mom" labels and trend direction (Bull/Bear Target labels).
Use Support/Resistance lines to set logical TP/SL levels or anticipate reversals.
Evaluate Buy/Sell signals with TP, SL, and RRR for high-probability trades.
Alerts: Set up alerts for Buy/Sell signals to receive real-time notifications.
Customization: Fine-tune multipliers and lengths to adapt the indicator to different markets (e.g., stocks, forex, crypto) or timeframes.
RRC Sniper SetupElaborates Mike's RRC method.
his is how the pros time high-conviction options plays without chasing or bleeding theta.
We use the RRC Method: Reclaim → Retrace → Confirm
This is your sniper playbook for clean, high-odds entries. Let’s break it down 👇
5m chart: Draw VWAP, EMA 21, prior high/low
1m chart: Watch for reclaim + retrace + confirmation
THEN
Options flow or volume spike = green light
RRC is a reaction model. Use 5-min for setup, 1-min for execution. Hope this helps
🔁 1. RECLAIM – Momentum Trigger
Price reclaims a key level:
– VWAP
– Prior support/resistance
-EMA 113 1 MIN/ EMA 21 5 MIN
– Psychological zone (e.g., 5000 on SPX)
– Opening range high/low
This move traps sellers and signals bulls are back.
Most traders FOMO here — don’t. You wait.
📉 2. RETRACE – Setup Zone
Price pulls back to retest the reclaim level.
You want: – Tight candles
– Lower volume
– Wick holds
– No panic selling
This is where you prepare the strike, expiration, and plan.
✅ 3. CONFIRMATION – Green Light
Buyers step in, trendline breaks, or volume surges.
Once price holds and pushes, it confirms the setup.
👉 This is your entry.
ORB + Fib ZoneAllows user to adjust range of ORB. The box in the middle is the Fibonacci range between 38.2% and 61.8% designed for pullbacks into the ORB as confirmation before entry. Alerts can be set if the candle closes above or below the ORB.
Quantum Reversal# 🧠 Quantum Reversal
## **Quantitative Mean Reversion Framework**
This algorithmic trading system employs **statistical mean reversion theory** combined with **adaptive volatility modeling** to capitalize on Bitcoin's inherent price oscillations around its statistical mean. The strategy integrates multiple technical indicators through a **multi-layered signal processing architecture**.
---
## ⚡ **Core Technical Architecture**
### 📊 **Statistical Foundation**
- **Bollinger Band Mean Reversion Model**: Utilizes 20-period moving average with 2.2 standard deviation bands for volatility-adjusted entry signals
- **Adaptive Volatility Threshold**: Dynamic standard deviation multiplier accounts for Bitcoin's heteroscedastic volatility patterns
- **Price Action Confluence**: Entry triggered when price breaches lower volatility band, indicating statistical oversold conditions
### 🔬 **Momentum Analysis Layer**
- **RSI Oscillator Integration**: 14-period Relative Strength Index with modified oversold threshold at 45
- **Signal Smoothing Algorithm**: 5-period simple moving average applied to RSI reduces noise and false signals
- **Momentum Divergence Detection**: Captures mean reversion opportunities when momentum indicators show oversold readings
### ⚙️ **Entry Logic Architecture**
```
Entry Condition = (Price ≤ Lower_BB) OR (Smoothed_RSI < 45)
```
- **Dual-Condition Framework**: Either statistical price deviation OR momentum oversold condition triggers entry
- **Boolean Logic Gate**: OR-based entry system increases signal frequency while maintaining statistical validity
- **Position Sizing**: Fixed 10% equity allocation per trade for consistent risk exposure
### 🎯 **Exit Strategy Optimization**
- **Profit-Lock Mechanism**: Positions only closed when showing positive unrealized P&L
- **Trend Continuation Logic**: Allows winning trades to run until momentum exhaustion
- **Dynamic Exit Timing**: No fixed profit targets - exits based on profitability state rather than arbitrary levels
---
## 📈 **Statistical Properties**
### **Risk Management Framework**
- **Long-Only Exposure**: Eliminates short-squeeze risk inherent in cryptocurrency markets
- **Mean Reversion Bias**: Exploits Bitcoin's tendency to revert to statistical mean after extreme moves
- **Position Management**: Single position limit prevents over-leveraging
### **Signal Processing Characteristics**
- **Noise Reduction**: SMA smoothing on RSI eliminates high-frequency oscillations
- **Volatility Adaptation**: Bollinger Bands automatically adjust to changing market volatility
- **Multi-Timeframe Coherence**: Indicators operate on consistent timeframe for signal alignment
---
## 🔧 **Parameter Configuration**
| Technical Parameter | Value | Statistical Significance |
|-------------------|-------|-------------------------|
| Bollinger Period | 20 | Standard statistical lookback for volatility calculation |
| Std Dev Multiplier | 2.2 | Optimized for Bitcoin's volatility distribution (95.4% confidence interval) |
| RSI Period | 14 | Traditional momentum oscillator period |
| RSI Threshold | 45 | Modified oversold level accounting for Bitcoin's momentum characteristics |
| Smoothing Period | 5 | Noise reduction filter for momentum signals |
---
## 📊 **Algorithmic Advantages**
✅ **Statistical Edge**: Exploits documented mean reversion tendency in Bitcoin markets
✅ **Volatility Adaptation**: Dynamic bands adjust to changing market conditions
✅ **Signal Confluence**: Multiple indicator confirmation reduces false positives
✅ **Momentum Integration**: RSI smoothing improves signal quality and timing
✅ **Risk-Controlled Exposure**: Systematic position sizing and long-only bias
---
## 🔬 **Mathematical Foundation**
The strategy leverages **Bollinger Band theory** (developed by John Bollinger) which assumes that prices tend to revert to the mean after extreme deviations. The RSI component adds **momentum confirmation** to the statistical price deviation signal.
**Statistical Basis:**
- Mean reversion follows the principle that extreme price deviations from the moving average are temporary
- The 2.2 standard deviation multiplier captures approximately 97.2% of price movements under normal distribution
- RSI momentum smoothing reduces noise inherent in oscillator calculations
---
## ⚠️ **Risk Considerations**
This algorithm is designed for traders with understanding of **quantitative finance principles** and **cryptocurrency market dynamics**. The strategy assumes mean-reverting behavior which may not persist during trending market phases. Proper risk management and position sizing are essential.
---
## 🎯 **Implementation Notes**
- **Market Regime Awareness**: Most effective in ranging/consolidating markets
- **Volatility Sensitivity**: Performance may vary during extreme volatility events
- **Backtesting Recommended**: Historical performance analysis advised before live implementation
- **Capital Allocation**: 10% per trade sizing assumes diversified portfolio approach
---
**Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
TradePlanner ProPlan smarter. Trade with precision.
TradePlanner Pro is a professional-grade overlay tool designed to streamline your trading decisions by visually organizing your trade plans directly on the chart. Built for traders who value preparation and clarity, this script enables precise entry planning, risk management, and target visualization—all tailored per symbol.
Core Purpose
TradePlanner Pro helps you map out potential trades using pre-defined symbol-based presets. It dynamically calculates position sizes based on your account size or fixed risk, then visualizes key trade levels (Entry, Take Profits, Stop Loss) with profit/loss metrics in both dollar and percentage terms. It's the perfect companion for traders who prepare their setups in advance and want their plans clearly represented on the chart.
Key Features
🔹 Per-Symbol Presets: Define entries, up to 3 take-profit levels, and stop-losses for each ticker.
🔹 Dynamic Risk Sizing: Choose between percentage-based risk or fixed dollar risk per trade.
🔹 Visual Trade Mapping: Automatically plots Entry, TP1–TP3, and SL lines on your chart.
🔹 Real-Time P&L Labels: Displays profit/loss amounts and percentages, with optional R/R ratios.
🔹 Custom Investment Display: Shows how much capital is allocated per trade.
🔹 Clean, Configurable UI: Adjust label positions, font sizes, opacity, and label visibility to match your style.
Whether you're swing trading or day trading, TradePlanner Pro helps you stay disciplined, organized, and confident in your execution.
How to Use TradePlanner Pro – Step-by-Step Guide
TradePlanner Pro is designed to be easy to set up while giving you full control over how your trades are visualized and calculated. Here’s how to get started:
1. Start with Default Settings
By default, the script assumes:
Account Size: $10,000
Max Money per Trade (%): 1.0%
Max Risk (USD): 0 (disabled; only percentage risk is used)
This means the script will size each trade to risk 1% of your account balance per trade unless you override it with a fixed USD risk amount.
2. Set Up Your Symbol Presets
The "Symbol Presets" input is a flexible text area where you define trade setups for each ticker.
Format (one per line):
SYMBOL:Entry,TP1 ,SL
Example:
AAPL:250,260,270,240
MSFT:100,110,90
TSLA:180,200,170
You can include 1 to 3 take-profit levels.
The script will only activate for the current chart’s symbol, matching what's listed.
3. Customize Risk Parameters
You can use:
Account % Risk – Based on account size and % risk.
Fixed USD Risk – When a dollar amount is entered (>0), it takes priority and calculates share size based on the risk per share.
There's also an option to round share quantities down to whole units, which is useful for stock or crypto trading platforms that only allow whole-number units.
4. Choose What to Display
Toggle on/off these elements as needed:
Show Entry/TP/SL Lines
Show P&L Labels – Profit/loss amounts at each target and SL.
Show Amount Invested – Includes total dollar value in the quantity label.
Show Percentages – Adds % gain/loss to each label.
Show Risk/Reward Ratios – Optionally displayed beside or below TP labels.
You can further adjust:
Font size and label opacity
Label position offset – In percent of price range, so they don’t overlap the actual levels.
5. Read the Visual Outputs
Once the preset matches the current chart symbol:
Lines will appear for Entry, TP1-TP3, and Stop Loss.
Labels will display your:
Trade quantity (and invested amount)
Dollar and % profit at each target
Total loss at stop loss
Optional R/R ratios
Everything updates dynamically and adjusts to your current chart scale and bar availabilit
RSI Divergence StrategyOverview
The RSI Divergence Strategy Indicator is a trading tool that uses the RSI and divergences created to generate high-probability buy and sell signals.
I have provided the best formula of numbers to use for BTC on a 30 minute timeframe.
You can change where on RSI you enter and exit both long or short trades. This way you can experiment on different tokens using different entry/exit points. Can use on multiple timeframes.
This strategy is designed to open and close long or short trades based on the levels you provide it. You can then check on the RSI where the best levels are for each token you want to trade and amend it as required to generate a profitable strategy.
How It Works
The RSI Divergence Strategy Indicator uses bear and bull divergences in conjuction with a level you have input on the RSI.
RSI for Overbought/Oversold:
• Input variables for entry and exit levels and when the entry levels combine with a bear or bull divergence signal, a trade is alerted.
RSI Divergence:
• Buy and sell signals are confirmed when the RSI creates bearish or bullish divergences and these divergences are in the same area as your levels you input for entry to short or long.
After 7 years of experience and testing I have calculated the exact numbers required and produced a formula to calculate the exact input variables for a 30 minute Bitcoin chart.
Key Features
1️⃣ Divergence Identification – Ensures trades are taken only when a bull or bear divergence has formed.
2️⃣ Overbought/Oversold Input Filtering – Set up your own variables on the RSI for different markets after identifying patterns on the RSI in relation to a bearish or bullish divergence.
3️⃣ Works on any chart – Suitable for all markets and timeframes once you input the correct variables for entry and exit levels.
How to Use
🟢 Basic Trading:
• Use on any timeframe.
• Enter trade only when alert has fired off. Close when it says to exit.
• Change entry and exit levels in the properties of the strategy indicator.
• Make entry and exit levels coincide with bearish or bullish divergences on the RSI.
Check the strategy tester to see backtesting so you know if the indicator is profitable or not for that market and timeframe as each crypto token is different and so is the timeframe you choose.
📢 Webhook Automation:
• Set up TradingView Alerts to auto-execute trades via Webhook-compatible platforms.
Key additions for divergence visualization:
Divergence Arrows:
Bullish divergence: Green label with white 'bull ' text
Bearish divergence: Red label with white 'bear' text
Positioned at the pivot point
Divergence Lines:
Connects consecutive RSI pivot points
Automatically drawn between consecutive pivot points
Enhanced RSI Coloring:
Overbought zone: Red
Oversold zone: Green
Neutral zone: Gray
The visualization helps you instantly spot:
Where divergences are forming on the RSI
The pattern of higher lows (bullish) or lower highs (bearish)
Contextual coloring of RSI relative to standard levels
All divergence markers appear at the correct historical pivot points, making it easy to visually confirm divergence patterns as they develop.
Strategy levels and background zones also shown to help visual look.
Why This Combination?
This indicator is just a simple RSI tool.
It is designed to filter out weak trades and only execute trades that have:
✅ RSI Divergence
✅ Overbought or Oversold Conditions
It does not calculate downtrends or bear markets so care is recommended taking long trades during these times.
Why It’s Worth Using?
📈 Open Source – Free to use and learn from.
📉 Long or Short Term Trading Style – Entry/Exit parameters options are designed for both short or long term trades allowing you to experiment until you find a profitable strategy for that market you want to trade.
📢 Seamless Webhook Automation – Execute trades automatically with TradingView alerts.
💲 Ready to trade smarter?
✅ Add the RSI Divergence Strategy Indicator to your TradingView chart.
GStrategy 1000Pepe 15mTrend Following Candlestick Strategy with EMA Filter and Exit Delay
Strategy Concept
This strategy combines candlestick patterns with EMA trend filtering to identify high-probability trade entries, featuring:
Entry Signals: Hammer and Engulfing patterns confirmed by EMA trend
Trend Filter: Fast EMA (20) vs Slow EMA (50) crossover system
Risk Management: 5% stop-loss + 1% trailing stop
Smart Exit: 2-bar delay after exit signals to avoid whipsaws
Key Components
Trend Identification:
Uptrend: Fast EMA > Slow EMA AND rising
Downtrend: Fast EMA < Slow EMA AND falling
Entry Conditions:
pinescript
// Bullish Entry (Long)
longCondition = (Hammer OR Bullish Engulfing)
AND Uptrend
AND no existing position
// Bearish Entry (Short)
shortCondition = Bearish Engulfing
AND Downtrend
AND no existing position
Exit Mechanics:
Primary Exit: EMA crossover (Fast crosses Slow)
Delayed Execution: Waits 2 full candles after signal
Emergency Exits:
5% fixed stop-loss
1% trailing stop
Visual Dashboard:
Colored EMA lines (Blue=Fast, Red=Slow)
Annotated candlestick patterns
Background highlighting for signals
Distinct markers for entries/exits
Unique Features
Pattern Recognition:
Enhanced Hammer detection (strict body/wick ratios)
Multi-candle engulfing confirmation
Trend-Confirmation:
Requires price and EMA alignment
Filters counter-trend patterns
Exit Optimization:
pinescript
// Delay implementation
if exit_signal_triggered
counter := 2 // Start countdown
else if counter > 0
counter -= 1 // Decrement each bar
exit_trade = (counter == 1) // Execute on final bar
Risk Parameters
Parameter Value Description
Stop Loss 5% Fixed risk per trade
Trailing Stop 1% Locks in profits
Exit Delay 2 bars Reduces false exits
Position Size 100% No pyramiding
Visualization Examples
🟢 Green Triangle: Bullish entry
🔴 Red Triangle: Bearish entry
⬇️ Blue X: Long exit (after delay)
⬆️ Green X: Short exit (after delay)
🎯 Pattern Labels: Identifies hammer/engulfing
Recommended Use
Timeframes: 1H-4H (reduces noise)
Markets: Trend-prone assets (FX, indices)
Best Conditions: Strong trending markets
Avoid: Choppy/Ranging markets
EMA Pullback System 1:5 RRR [SL]EMA Trend Pullback System (1:5 RRR)
Summary:
This indicator is designed to identify high-probability pullback opportunities along the main trend, providing trade signals that target a high 1:5 Risk/Reward Ratio. It is a trend-following strategy built for patient traders who wait for optimal setups.
Strategy Logic:
The system is based on three Exponential Moving Averages (EMAs): 21, 50, and 200.
BUY Signal:
Trend (Uptrend): The price must be above the 200 EMA.
Pullback: The price must pull back into the "Dynamic Support Zone" between the 21 EMA and 50 EMA.
Confirmation: A strong Bullish Confirmation Candle (e.g., Bullish Engulfing) must form within this zone.
SELL Signal:
Trend (Downtrend): The price must be below the 200 EMA.
Pullback: The price must rally back into the "Dynamic Resistance Zone" between the 21 EMA and 50 EMA.
Confirmation: A strong Bearish Confirmation Candle (e.g., Bearish Engulfing) must form within this zone.
Key Features:
Clearly plots the 21, 50, and 200 EMAs on the chart.
Displays BUY and SELL labels when the rules are met.
Automatically calculates and plots Stop Loss (SL) and Take Profit (TP) levels for each signal.
The Risk/Reward Ratio for the Take Profit level is customizable in the settings (Default: 1:5).
How to Use:
Best suited for higher timeframes like H1 and H4.
It is crucial to wait for the signal candle to close before considering an entry.
While this is an automated tool, for best results, combine its signals with your own analysis of Price Action and Market Structure.
Disclaimer:
This is an educational tool and not financial advice. Trading involves substantial risk. Always use proper risk management. It is essential to backtest any strategy before deploying it with real capital.
Options Risk Manager v2.2.0 - Priority 7 CompleteScript Description for TradingView Publication
Options Risk Manager v2.2.0 - Priority 7 Complete
What does this script do?
Options Risk Manager v2.2.0 is a comprehensive position management system designed specifically for options traders. The indicator calculates precise stop loss levels, risk/reward targets, and position sizing based on user-defined risk parameters. It provides real-time profit/loss tracking, options Greeks monitoring, and automated alert systems for critical price levels.
The script displays entry points, stop losses, and profit targets directly on the chart while continuously calculating position metrics including dollar risk, account exposure, and probability of success. Version 2.2.0 introduces Priority 7 advanced alerts with dynamic risk warnings and multi-condition notifications.
How does it do it?
The script performs several key calculations:
1. Risk-Based Stop Loss Calculation - Determines stop loss levels based on percentage of entry price, automatically adjusting for calls versus puts. Put positions place stops above entry, while calls place stops below.
2. Position Sizing Algorithm - Calculates optimal contract quantities using account size, risk
percentage, and stop distance to ensure consistent risk per trade regardless of underlying price.
3. Options-Specific P&L Tracking - Incorporates Delta, Gamma, Vega, and Theta to provide accurate profit/loss calculations for options positions, including time decay effects.
4. Three-Phase Trade Management - Implements systematic position management through Entry
Phase (initial risk), Profit Phase (approaching target), and Trailing Phase (EMA-based exit
management).
5. Multi-Level Alert System - Monitors price action, Greeks thresholds, time decay acceleration, and account risk levels to generate context-aware notifications.
How to use it?
Initial Setup:
1. Apply indicator to any optionable security
2. Toggle "In Position" ON when entering a trade
3. Set Direction (Call/Put) and Side (Long/Short)
4. Enter the underlying price at position entry
5. Specify number of contracts and risk percentage
Position Management:
Blue line shows entry price
Red line indicates stop loss level
Orange line displays risk/reward target
Purple EMA line activates after target hit
Monitor real-time P&L in trade panels
Alert Configuration:
Enable Advanced Alerts in settings
Set profit/loss notification thresholds
Configure Greek-based warnings
Activate time decay alerts for expiration
Risk Parameters:
Risk % determines stop distance from entry
Account Value sets position sizing limits
Contract Multiplier (standard = 100)
R:R Ratio defines profit targets
What makes it unique?
Options Risk Manager addresses the specific challenges of options trading that generic indicators miss. The script accounts for the inverse relationship in put options (profiting from price declines), incorporates Greeks for accurate P&L calculations, and provides options-specific limit orders for TradeStation integration.
The three-phase management system removes emotional decision-making by defining clear rules for position management. Phase transitions occur automatically based on price action, shifting from initial risk management to profit protection to trend-following modes.
Version 2.2.0's Priority 7 alert system provides intelligent notifications that include live metrics, risk warnings, and market context rather than simple price crosses.
Key Features Summary
Options-Specific Calculations - Proper handling of calls/puts with inverse relationships
Risk-Based Position Sizing - Consistent risk regardless of underlying price
Greeks Integration - Delta, Gamma, Vega, Theta for accurate tracking
Phase Management System - Systematic three-stage position handling
Advanced Alert System - Context-aware notifications with metrics
TradeStation Integration - Option limit orders for execution
Visual Risk Display - Clear chart overlays for all levels
Probability Calculator - Win/loss probability with expected value
Multi-Account Support - Scales from small to large accounts
Important Notes
This indicator requires manual input of option prices and Greeks (available from your broker's option chain). It functions as a risk management overlay and does not generate entry signals. The calculations assume standard options contracts of 100 shares.
Designed for TradeStation platform with full functionality. Basic features available on other platforms
without options data integration. Always verify calculations with your broker's risk system before placing
trades.
Kaufman Trend Strength Signal█ Overview
Kaufman Trend Strength Signal is an advanced trend detection tool that decomposes price action into its underlying directional trend and localized oscillation using a vector-based Kalman Filter.
By integrating adaptive smoothing and dynamic weighting via a weighted moving average (WMA), this indicator provides real-time insight into both trend direction and trend strength — something standard moving averages often fail to capture.
The core model assumes that observed price consists of two components:
(1) a directional trend, and
(2) localized noise or oscillation.
Using a two-step Predict & Update cycle, the filter continuously refines its trend estimate as new market data becomes available.
█ How It Works
This indicator employs a Kalman Filter model that separates the trend from short-term fluctuations in a price series.
Predict & Update Cycle : With each new bar, the filter predicts the price state and updates that prediction using the latest observed price, producing a smooth but adaptive trend line.
Trend Strength Normalization : Internally, the oscillator component is normalized against recent values (N periods) to calculate a trend strength score between -100 and +100.
(Note: The oscillator is not plotted on the chart but is used for signal generation.)
Filtered MA Line : The trend component is plotted as a smooth Kalman Filter-based moving average (MA) line on the main chart.
Threshold Cross Signals : When the internal trend strength crosses a user-defined threshold (default: ±60), visual entry arrows are displayed to signal momentum shifts.
█ Key Features
Adaptive Trend Estimation : Real-time filtering that adjusts dynamically to market changes.
Visual Buy/Sell Signals : Entry arrows appear when the trend strength crosses above or below the configured threshold.
Built-in Range Filter : The MA line turns blue when trend strength is weak (|value| < 10), helping you filter out choppy, sideways conditions.
█ How to Use
Trend Detection :
• Green MA = bullish trend
• Red MA = bearish trend
• Blue MA = no trend / ranging market
Entry Signals :
• Green triangle = trend strength crossed above +Threshold → potential bullish entry
• Red triangle = trend strength crossed below -Threshold → potential bearish entry
█ Settings
Entry Threshold : Level at which the trend strength triggers entry signals (default: 60)
Process Noise 1 & 2 : Control the filter’s responsiveness to recent price action. Higher = more reactive; lower = smoother.
Measurement Noise : Sets how much the filter "trusts" price data. High = smoother MA, low = faster response but more noise.
Trend Lookback (N2) : Number of bars used to normalize trend strength. Lower = more sensitive; higher = more stable.
Trend Smoothness (R2) : WMA smoothing applied to the trend strength calculation.
█ Visual Guide
Green MA Line → Bullish trend
Red MA Line → Bearish trend
Blue MA Line → Sideways/range
Green Triangle → Entry signal (trend strengthening)
Red Triangle → Entry signal (trend weakening)
█ Best Practices
In high-volatility conditions, increase Measurement Noise to reduce false signals.
Combine with other indicators (e.g., RSI, MACD, EMA) for confirmation and filtering.
Adjust "Entry Threshold" and noise settings depending on your timeframe and trading style.
❗ Disclaimer
This script is provided for educational purposes only and should not be considered financial advice or a recommendation to buy/sell any asset.
Trading involves risk. Past performance does not guarantee future results.
Always perform your own analysis and use proper risk management when trading.
Chaikin Oscillator Multi-Timeframe BiasOverview
Chaikin Oscillator Multi-Timeframe Bias is an indicator designed to help traders align with institutional buying and selling activity by analyzing Chaikin Oscillator signals across two timeframes—a higher timeframe (HTF) for trend bias and a lower timeframe (LTF) for timing. This dual-confirmation model helps traders avoid false breakouts and trade in sync with market momentum and accumulation or distribution dynamics.
Core Concepts
The Chaikin Oscillator measures the momentum of accumulation and distribution based on price and volume. Institutional traders typically accumulate slowly and steadily, and the Chaikin Oscillator helps reveal this pattern. Multi-timeframe analysis confirms whether short-term price action supports the longer-term trend. This indicator applies a smoothing EMA to each Chaikin Oscillator to help confirm direction and reduce noise.
How to Use the Indicator
Start by selecting your timeframes. The higher timeframe, set by default to Daily, establishes the broader directional bias. The lower timeframe, defaulted to 30 minutes, identifies short-term momentum confirmation. The indicator displays one of five labels: CALL Bias, CALL Wait, PUT Bias, PUT Wait, or NEUTRAL. CALL Bias means both HTF and LTF are bullish, signaling a potential opportunity for long or call trades. CALL Wait indicates that the HTF is bullish, but the LTF hasn’t confirmed yet. PUT Bias signals bearish alignment in both HTF and LTF, while PUT Wait indicates HTF is bearish and LTF has not yet confirmed. NEUTRAL means there is no alignment between timeframes and directional trades are not advised.
Interpretation
When the Chaikin Oscillator is above zero and also above its EMA, this indicates bullish momentum and accumulation. When the oscillator is below zero and below its EMA, it suggests bearish momentum and distribution. Bias labels identify when both timeframes are aligned for a higher-probability directional setup. When a “Wait” label appears, it means one timeframe has confirmed bias but the other has not, suggesting the trader should monitor closely but delay entry.
Notes
This indicator includes alerts for both CALL and PUT bias confirmation when both timeframes are aligned. It works on all asset classes, including stocks, ETFs, cryptocurrencies, and futures. Timeframes are fully customizable, and users may explore combinations such as 1D and 1H, or 4H and 15M depending on their strategy. For best results, consider pairing this tool with volume, volatility, or price action analysis.
[Kpt-Ahab] Poor Mans Orderflow SimulatorScript Description – Poor Mans Orderflow Simulator
Purpose of the Script
This script simulates a simplified order flow approach ("Poor Man's Orderflow") without access to actual Bid/Ask data. The goal is to detect, quantify, and visualize patterns such as absorption, impulsive moves, and structured re-entry behaviors.
Calculation Logic
Absorption Candles
A candle is classified as "absorption" if:
The ratio of body size to full candle range is below a defined threshold,
Volume is significantly higher than the average of the last N periods,
The candle direction is negative (for long absorption) or positive (for short absorption).
These conditions define a candle with high activity but minimal price movement in the respective direction.
Impulse Candles
A candle is classified as "impulse" if:
The body-to-range ratio is high (indicating a strong directional move),
Volume exceeds the average significantly,
The price closes in the direction of the candle body (bullish or bearish).
Additionally, the average range of previous candles serves as a minimum benchmark for the impulse.
Cluster Detection
A cluster is detected when:
A minimum number of absorption candles is counted within a defined lookback period,
Either the long or short version of the absorption logic is used,
The result is a binary condition: cluster active or inactive.
Entry Signals (Re-entry)
An entry signal is generated when:
One or more absorption candles occurred in the last two bars,
A pullback against the direction of absorption occurs,
The current candle shows a directional move confirmed by a close in the expected direction.
These re-entry signals are evaluated separately for long and short scenarios.
Cluster-Confirmed Signals
A separate signal is generated when a valid re-entry setup occurs while a cluster is active. This represents a combined logic condition.
Alert Logic
The script provides a multi-layer alert framework:
Signal selection (Alertmode):
The user defines which signal type should trigger an alert (e.g. re-entry only, cluster only, combination, or impulse).
Optional filter (Filtermode):
A secondary filter limits alerts to cases where an additional condition (e.g. absorption cluster) is active.
Signal output:
As a simple binary value (+1 / –1) for classic alerts,
Or via an encoded Multibit signal, compatible with other modules in the djmad ecosystem.
These alerts are intended for integration with external systems or for use within platform-native visual or automation features.
magic wand STSM"Magic Wand STSM" Strategy: Trend-Following with Dynamic Risk Management
Overview:
The "Magic Wand STSM" (Supertrend & SMA Momentum) is an automated trading strategy designed to identify and capitalize on sustained trends in the market. It combines a multi-timeframe Supertrend for trend direction and potential reversal signals, along with a 200-period Simple Moving Average (SMA) for overall market bias. A key feature of this strategy is its dynamic position sizing based on a user-defined risk percentage per trade, and a built-in daily and monthly profit/loss tracking system to manage overall exposure and prevent overtrading.
How it Works (Underlying Concepts):
Multi-Timeframe Trend Confirmation (Supertrend):
The strategy uses two Supertrend indicators: one on the current chart timeframe and another on a higher timeframe (e.g., if your chart is 5-minute, the higher timeframe Supertrend might be 15-minute).
Trend Identification: The Supertrend's direction output is crucial. A negative direction indicates a bearish trend (price below Supertrend), while a positive direction indicates a bullish trend (price above Supertrend).
Confirmation: A core principle is that trades are only considered when the Supertrend on both the current and the higher timeframe align in the same direction. This helps to filter out noise and focus on stronger, more confirmed trends. For example, for a long trade, both Supertrends must be indicating a bearish trend (price below Supertrend line, implying an uptrend context where price is expected to stay above/rebound from Supertrend). Similarly, for short trades, both must be indicating a bullish trend (price above Supertrend line, implying a downtrend context where price is expected to stay below/retest Supertrend).
Trend "Readiness": The strategy specifically looks for situations where the Supertrend has been stable for a few bars (checking barssince the last direction change).
Long-Term Market Bias (200 SMA):
A 200-period Simple Moving Average is plotted on the chart.
Filter: For long trades, the price must be above the 200 SMA, confirming an overall bullish bias. For short trades, the price must be below the 200 SMA, confirming an overall bearish bias. This acts as a macro filter, ensuring trades are taken in alignment with the broader market direction.
"Lowest/Highest Value" Pullback Entries:
The strategy employs custom functions (LowestValueAndBar, HighestValueAndBar) to identify specific price action within the recent trend:
For Long Entries: It looks for a "buy ready" condition where the price has found a recent lowest point within a specific number of bars since the Supertrend turned bearish (indicating an uptrend). This suggests a potential pullback or consolidation before continuation. The entry trigger is a close above the open of this identified lowest bar, and also above the current bar's open.
For Short Entries: It looks for a "sell ready" condition where the price has found a recent highest point within a specific number of bars since the Supertrend turned bullish (indicating a downtrend). This suggests a potential rally or consolidation before continuation downwards. The entry trigger is a close below the open of this identified highest bar, and also below the current bar's open.
Candle Confirmation: The strategy also incorporates a check on the candle type at the "lowest/highest value" bar (e.g., closevalue_b < openvalue_b for buy signals, meaning a bearish candle at the low, suggesting a potential reversal before a buy).
Risk Management and Position Sizing:
Dynamic Lot Sizing: The lotsvalue function calculates the appropriate position size based on your Your Equity input, the Risk to Reward ratio, and your risk percentage for your balance % input. This ensures that the capital risked per trade remains consistent as a percentage of your equity, regardless of the instrument's volatility or price. The stop loss distance is directly used in this calculation.
Fixed Risk Reward: All trades are entered with a predefined Risk to Reward ratio (default 2.0). This means for every unit of risk (stop loss distance), the target profit is rr times that distance.
Daily and Monthly Performance Monitoring:
The strategy tracks todaysWins, todaysLosses, and res (daily net result) in real-time.
A "daily profit target" is implemented (day_profit): If the daily net result is very favorable (e.g., res >= 4 with todaysLosses >= 2 or todaysWins + todaysLosses >= 8), the strategy may temporarily halt trading for the remainder of the session to "lock in" profits and prevent overtrading during volatile periods.
A "monthly stop-out" (monthly_trade) is implemented: If the lres (overall net result from all closed trades) falls below a certain threshold (e.g., -12), the strategy will stop trading for a set period (one week in this case) to protect capital during prolonged drawdowns.
Trade Execution:
Entry Triggers: Trades are entered when all buy/sell conditions (Supertrend alignment, SMA filter, "buy/sell situation" candle confirmation, and risk management checks) are met, and there are no open positions.
Stop Loss and Take Profit:
Stop Loss: The stop loss is dynamically placed at the upTrendValue for long trades and downTrendValue for short trades. These values are derived from the Supertrend indicator, which naturally adjusts to market volatility.
Take Profit: The take profit is calculated based on the entry price, the stop loss, and the Risk to Reward ratio (rr).
Position Locks: lock_long and lock_short variables prevent immediate re-entry into the same direction once a trade is initiated, or after a trend reversal based on Supertrend changes.
Visual Elements:
The 200 SMA is plotted in yellow.
Entry, Stop Loss, and Take Profit lines are plotted in white, red, and green respectively when a trade is active, with shaded areas between them to visually represent risk and reward.
Diamond shapes are plotted at the bottom of the chart (green for potential buy signals, red for potential sell signals) to visually indicate when the buy_sit or sell_sit conditions are met, along with other key filters.
A comprehensive trade statistics table is displayed on the chart, showing daily wins/losses, daily profit, total deals, and overall profit/loss.
A background color indicates the active trading session.
Ideal Usage:
This strategy is best applied to instruments with clear trends and sufficient liquidity. Users should carefully adjust the Your Equity, Risk to Reward, and risk percentage inputs to align with their individual risk tolerance and capital. Experimentation with different ATR Length and Factor values for the Supertrend might be beneficial depending on the asset and timeframe.
Realtime ATR-Based Stop Loss Numerical OverlayRealtime ATR-Based Stop Loss Numerical Overlay
A simple, effective tool for dynamic risk management based on ATR (Average True Range) without adding cluttered and distracting lines all over your chart.
📌 Description
This script plots a real-time stop loss level using the Average True Range (ATR) on your chart, helping you set consistent, volatility-based stops. It supports both:
✅ Current chart timeframe
✅ Custom fixed timeframe inputs (1m, 5m, 15m, 1h, etc.)
The stop level is calculated as:
Stop = ATR × Multiplier
and updates in real-time. An overlay table displays on the bottom-right of your chart with the calculated stop value in a clean, simple way.
⚙️ Settings
ATR Timeframe Source:
Choose between using the current chart's timeframe or a fixed one (e.g. 5, 15, 60, D, etc).
ATR Length:
Period used to calculate the ATR (default is 14).
Stop Loss Multiplier:
Multiplies the ATR value to define your stop (e.g., 1.5 × ATR).
Wait for Timeframe Closes:
If enabled, the ATR value waits for the selected timeframe’s candle to close before updating. If unselected, it will update in real time.
🛠️ How to Use
Add this script to your chart from your indicators list.
Configure your desired timeframe, ATR length, and multiplier in the settings panel.
Use the value shown in the table overlay as your suggested stop loss distance from entry.
Adjust your position sizing accordingly to fit your risk tolerance.
This tool is especially useful for traders looking for adaptive risk management that evolves with market volatility — whether scalping intraday or swing trading.
💡 Pro Tip
The ATR stop can also be used to dynamically trail your stop behind price movement.
Ultimate Scalping Tool[BullByte]Overview
The Ultimate Scalping Tool is an open-source TradingView indicator built for scalpers and short-term traders released under the Mozilla Public License 2.0. It uses a custom Quantum Flux Candle (QFC) oscillator to combine multiple market forces into one visual signal. In plain terms, the script reads momentum, trend strength, volatility, and volume together and plots a special “candlestick” each bar (the QFC) that reflects the overall market bias. This unified view makes it easier to spot entries and exits: the tool labels signals as Strong Buy/Sell, Pullback (a brief retracement in a trend), Early Entry, or Exit Warning . It also provides color-coded alerts and a small dashboard of metrics. In practice, traders see green/red oscillator bars and symbols on the chart when conditions align, helping them scalp or trend-follow without reading multiple separate indicators.
Core Components
Quantum Flux Candle (QFC) Construction
The QFC is the heart of the indicator. Rather than using raw price, it creates a candlestick-like bar from the underlying oscillator values. Each QFC bar has an “open,” “high/low,” and “close” derived from calculated momentum and volatility inputs for that period . In effect, this turns the oscillator into intuitive candle patterns so traders can recognize momentum shifts visually. (For comparison, note that Heikin-Ashi candles “have a smoother look because take an average of the movement”. The QFC instead represents exact oscillator readings, so it reflects true momentum changes without hiding price action.) Colors of QFC bars change dynamically (e.g. green for bullish momentum, red for bearish) to highlight shifts. This is the first open-source QFC oscillator that dynamically weights four non-correlated indicators with moving thresholds, which makes it a unique indicator on its own.
Oscillator Normalization & Adaptive Weights
The script normalizes its oscillator to a fixed scale (for example, a 0–100 range much like the RSI) so that various inputs can be compared fairly. It then applies adaptive weighting: the relative influence of trend, momentum, volatility or volume signals is automatically adjusted based on current market conditions. For instance, in very volatile markets the script might weight volatility more heavily, or in a strong trend it might give extra weight to trend direction. Normalizing data and adjusting weights helps keep the QFC sensitive but stable (normalization ensures all inputs fit a common scale).
Trend/Momentum/Volume/Volatility Fusion
Unlike a typical single-factor oscillator, the QFC oscillator fuses four aspects at once. It may compute, for example, a trend indicator (such as an ADX or moving average slope), a momentum measure (like RSI or Rate-of-Change), a volume-based pressure (similar to MFI/OBV), and a volatility measure (like ATR) . These different values are combined into one composite oscillator. This “multi-dimensional” approach follows best practices of using non-correlated indicators (trend, momentum, volume, volatility) for confirmation. By encoding all these signals in one line, a high QFC reading means that trend, momentum, and volume are all aligned, whereas a neutral reading might mean mixed conditions. This gives traders a comprehensive picture of market strength.
Signal Classification
The script interprets the QFC oscillator to label trades. For example:
• Strong Buy/Sell : Triggered when the oscillator crosses a high-confidence threshold (e.g. breaks clearly above zero with strong slope), indicating a well-confirmed move. This is like seeing a big green/red QFC candle aligned with the trend.
• Pullbacks : Identified when the trend is up but momentum dips briefly. A Pullback Buy appears if the overall trend is bullish but the oscillator has a short retracement – a typical buying opportunity in an uptrend. (A pullback is “a brief decline or pause in a generally upward price trend”.)
• Early Buy/Sell : Marks an initial swing in the oscillator suggesting a possible new trend, before it is fully confirmed. It’s a hint of momentum building (an early-warning signal), not as strong as the confirmed “Strong” signal.
• Exit Warnings : Issued when momentum peaks or reverses. For instance, if the QFC bars reach a high and start turning red/green opposite, the indicator warns that the move may be ending. In other words, a Momentum Peak is the point of maximum strength after which weakness may follow.
These categories correspond to typical trading concepts: Pullback (temporary reversal in an uptrend), Early Buy (an initial bullish cross), Strong Buy (confirmed bullish momentum), and Momentum Peak (peak oscillator value suggesting exhaustion).
Filters (DI Reversal, Dynamic Thresholds, HTF EMA/ADX)
Extra filters help avoid bad trades. A DI Reversal filter uses the +DI/–DI lines (from the ADX system) to require that the trend direction confirms the signal . For example, it might ignore a buy signal if the +DI is still below –DI. Dynamic Thresholds adjust signal levels on-the-fly: rather than fixed “overbought” lines, they move with volatility so signals happen under appropriate market stress. An optional High-Timeframe EMA or ADX filter adds a check against a larger timeframe trend: for instance, only taking a trade if price is above the weekly EMA or if weekly ADX shows a strong trend. (Notably, the ADX is “a technical indicator used by traders to determine the strength of a price trend”, so requiring a high-timeframe ADX avoids trading against the bigger trend.)
Dashboard Metrics & Color Logic
The Dashboard in the Ultimate Scalping Tool (UST) serves as a centralized information hub, providing traders with real-time insights into market conditions, trend strength, momentum, volume pressure, and trade signals. It is highly customizable, allowing users to adjust its appearance and content based on their preferences.
1. Dashboard Layout & Customization
Short vs. Extended Mode : Users can toggle between a compact view (9 rows) and an extended view (13 rows) via the `Short Dashboard` input.
Text Size Options : The dashboard supports three text sizes— Tiny, Small, and Normal —adjustable via the `Dashboard Text Size` input.
Positioning : The dashboard is positioned in the top-right corner by default but can be moved if modified in the script.
2. Key Metrics Displayed
The dashboard presents critical trading metrics in a structured table format:
Trend (TF) : Indicates the current trend direction (Strong Bullish, Moderate Bullish, Sideways, Moderate Bearish, Strong Bearish) based on normalized trend strength (normTrend) .
Momentum (TF) : Displays momentum status (Strong Bullish/Bearish or Neutral) derived from the oscillator's position relative to dynamic thresholds.
Volume (CMF) : Shows buying/selling pressure levels (Very High Buying, High Selling, Neutral, etc.) based on the Chaikin Money Flow (CMF) indicator.
Basic & Advanced Signals:
Basic Signal : Provides simple trade signals (Strong Buy, Strong Sell, Pullback Buy, Pullback Sell, No Trade).
Advanced Signal : Offers nuanced signals (Early Buy/Sell, Momentum Peak, Weakening Momentum, etc.) with color-coded alerts.
RSI : Displays the Relative Strength Index (RSI) value, colored based on overbought (>70), oversold (<30), or neutral conditions.
HTF Filter : Indicates the higher timeframe trend status (Bullish, Bearish, Neutral) when using the Leading HTF Filter.
VWAP : Shows the V olume-Weighted Average Price and whether the current price is above (bullish) or below (bearish) it.
ADX : Displays the Average Directional Index (ADX) value, with color highlighting whether it is rising (green) or falling (red).
Market Mode : Shows the selected market type (Crypto, Stocks, Options, Forex, Custom).
Regime : Indicates volatility conditions (High, Low, Moderate) based on the **ATR ratio**.
3. Filters Status Panel
A secondary panel displays the status of active filters, helping traders quickly assess which conditions are influencing signals:
- DI Reversal Filter: On/Off (confirms reversals before generating signals).
- Dynamic Thresholds: On/Off (adjusts buy/sell thresholds based on volatility).
- Adaptive Weighting: On/Off (auto-adjusts oscillator weights for trend/momentum/volatility).
- Early Signal: On/Off (enables early momentum-based signals).
- Leading HTF Filter: On/Off (applies higher timeframe trend confirmation).
4. Visual Enhancements
Color-Coded Cells : Each metric is color-coded (green for bullish, red for bearish, gray for neutral) for quick interpretation.
Dynamic Background : The dashboard background adapts to market conditions (bullish/bearish/neutral) based on ADX and DI trends.
Customizable Reference Lines : Users can enable/disable fixed reference lines for the oscillator.
How It(QFC) Differs from Traditional Indicators
Quantum Flux Candle (QFC) Versus Heikin-Ashi
Heikin-Ashi candles smooth price by averaging (HA’s open/close use averages) so they show trend clearly but hide true price (the current HA bar’s close is not the real price). QFC candles are different: they are oscillator values, not price averages . A Heikin-Ashi chart “has a smoother look because it is essentially taking an average of the movement”, which can cause lag. The QFC instead shows the raw combined momentum each bar, allowing faster recognition of shifts. In short, HA is a smoothed price chart; QFC is a momentum-based chart.
Versus Standard Oscillators
Common oscillators like RSI or MACD use fixed formulas on price (or price+volume). For example, RSI “compares gains and losses and normalizes this value on a scale from 0 to 100”, reflecting pure price momentum. MFI is similar but adds volume. These indicators each show one dimension: momentum or volume. The Ultimate Scalping Tool’s QFC goes further by integrating trend strength and volatility too. In practice, this means a move that looks strong on RSI might be downplayed by low volume or weak trend in QFC. As one source notes, using multiple non-correlated indicators (trend, momentum, volume, volatility) provides a more complete market picture. The QFC’s multi-factor fusion is unique – it is effectively a multi-dimensional oscillator rather than a traditional single-input one.
Signal Style
Traditional oscillators often use crossovers (RSI crossing 50) or fixed zones (MACD above zero) for signals. The Ultimate Scalping Tool’s signals are custom-classified: it explicitly labels pullbacks, early entries, and strong moves. These terms go beyond a typical indicator’s generic “buy”/“sell.” In other words, it packages a strategy around the oscillator, which traders can backtest or observe without reading code.
Key Term Definitions
• Pullback : A short-term dip or consolidation in an uptrend. In this script, a Pullback Buy appears when price is generally rising but shows a brief retracement. (As defined by Investopedia, a pullback is “a brief decline or pause in a generally upward price trend”.)
• Early Buy/Sell : An initial or tentative entry signal. It means the oscillator first starts turning positive (or negative) before a full trend has developed. It’s an early indication that a trend might be starting.
• Strong Buy/Sell : A confident entry signal when multiple conditions align. This label is used when momentum is already strong and confirmed by trend/volume filters, offering a higher-probability trade.
• Momentum Peak : The point where bullish (or bearish) momentum reaches its maximum before weakening. When the oscillator value stops rising (or falling) and begins to reverse, the script flags it as a peak – signaling that the current move could be overextended.
What is the Flux MA?
The Flux MA (Moving Average) is an Exponential Moving Average (EMA) applied to a normalized oscillator, referred to as FM . Its purpose is to smooth out the fluctuations of the oscillator, providing a clearer picture of the underlying trend direction and strength. Think of it as a dynamic baseline that the oscillator moves above or below, helping you determine whether the market is trending bullish or bearish.
How it’s calculated (Flux MA):
1.The oscillator is normalized (scaled to a range, typically between 0 and 1, using a default scale factor of 100.0).
2.An EMA is applied to this normalized value (FM) over a user-defined period (default is 10 periods).
3.The result is rescaled back to the oscillator’s original range for plotting.
Why it matters : The Flux MA acts like a support or resistance level for the oscillator, making it easier to spot trend shifts.
Color of the Flux Candle
The Quantum Flux Candle visualizes the normalized oscillator (FM) as candlesticks, with colors that indicate specific market conditions based on the relationship between the FM and the Flux MA. Here’s what each color means:
• Green : The FM is above the Flux MA, signaling bullish momentum. This suggests the market is trending upward.
• Red : The FM is below the Flux MA, signaling bearish momentum. This suggests the market is trending downward.
• Yellow : Indicates strong buy conditions (e.g., a "Strong Buy" signal combined with a positive trend). This is a high-confidence signal to go long.
• Purple : Indicates strong sell conditions (e.g., a "Strong Sell" signal combined with a negative trend). This is a high-confidence signal to go short.
The candle mode shows the oscillator’s open, high, low, and close values for each period, similar to price candlesticks, but it’s the color that provides the quick visual cue for trading decisions.
How to Trade the Flux MA with Respect to the Candle
Trading with the Flux MA and Quantum Flux Candle involves using the MA as a trend indicator and the candle colors as entry and exit signals. Here’s a step-by-step guide:
1. Identify the Trend Direction
• Bullish Trend : The Flux Candle is green and positioned above the Flux MA. This indicates upward momentum.
• Bearish Trend : The Flux Candle is red and positioned below the Flux MA. This indicates downward momentum.
The Flux MA serves as the reference line—candles above it suggest buying pressure, while candles below it suggest selling pressure.
2. Interpret Candle Colors for Trade Signals
• Green Candle : General bullish momentum. Consider entering or holding a long position.
• Red Candle : General bearish momentum. Consider entering or holding a short position.
• Yellow Candle : A strong buy signal. This is an ideal time to enter a long trade.
• Purple Candle : A strong sell signal. This is an ideal time to enter a short trade.
3. Enter Trades Based on Crossovers and Colors
• Long Entry : Enter a buy position when the Flux Candle turns green and crosses above the Flux MA. If it turns yellow, this is an even stronger signal to go long.
• Short Entry : Enter a sell position when the Flux Candle turns red and crosses below the Flux MA. If it turns purple, this is an even stronger signal to go short.
4. Exit Trades
• Exit Long : Close your buy position when the Flux Candle turns red or crosses below the Flux MA, indicating the bullish trend may be reversing.
• Exit Short : Close your sell position when the Flux Candle turns green or crosses above the Flux MA, indicating the bearish trend may be reversing.
•You might also exit a long trade if the candle changes from yellow to green (weakening strong buy signal) or a short trade from purple to red (weakening strong sell signal).
5. Use Additional Confirmation
To avoid false signals, combine the Flux MA and candle signals with other indicators or dashboard metrics (e.g., trend strength, momentum, or volume pressure). For example:
•A yellow candle with a " Strong Bullish " trend and high buying volume is a robust long signal.
•A red candle with a " Moderate Bearish " trend and neutral momentum might need more confirmation before shorting.
Practical Example
Imagine you’re scalping a cryptocurrency:
• Long Trade : The Flux Candle turns yellow and is above the Flux MA, with the dashboard showing "Strong Buy" and high buying volume. You enter a long position. You exit when the candle turns red and dips below the Flux MA.
• Short Trade : The Flux Candle turns purple and crosses below the Flux MA, with a "Strong Sell" signal on the dashboard. You enter a short position. You exit when the candle turns green and crosses above the Flux MA.
Market Presets and Adaptation
This indicator is designed to work on any market with candlestick price data (stocks, crypto, forex, indices, etc.). To handle different behavior, it provides presets for major asset classes. Selecting a “Stocks,” “Crypto,” “Forex,” or “Options” preset automatically loads a set of parameter values optimized for that market . For example, a crypto preset might use a shorter lookback or higher sensitivity to account for crypto’s high volatility, while a stocks preset might use slightly longer smoothing since stocks often trend more slowly. In practice, this means the same core QFC logic applies across markets, but the thresholds and smoothing adjust so signals remain relevant for each asset type.
Usage Guidelines
• Recommended Timeframes : Optimized for 1 minute to 15 minute intraday charts. Can also be used on higher timeframes for short term swings.
• Market Types : Select “Crypto,” “Stocks,” “Forex,” or “Options” to auto tune periods, thresholds and weights. Use “Custom” to manually adjust all inputs.
• Interpreting Signals : Always confirm a signal by checking that trend, volume, and VWAP agree on the dashboard. A green “Strong Buy” arrow with green trend, green volume, and price > VWAP is highest probability.
• Adjusting Sensitivity : To reduce false signals in fast markets, enable DI Reversal Confirmation and Dynamic Thresholds. For more frequent entries in trending environments, enable Early Entry Trigger.
• Risk Management : This tool does not plot stop loss or take profit levels. Users should define their own risk parameters based on support/resistance or volatility bands.
Background Shading
To give you an at-a-glance sense of market regime without reading numbers, the indicator automatically tints the chart background in three modes—neutral, bullish and bearish—with two levels of intensity (light vs. dark):
Neutral (Gray)
When ADX is below 20 the market is considered “no trend” or too weak to trade. The background fills with a light gray (high transparency) so you know to sit on your hands.
Bullish (Green)
As soon as ADX rises above 20 and +DI exceeds –DI, the background turns a semi-transparent green, signaling an emerging uptrend. When ADX climbs above 30 (strong trend), the green becomes more opaque—reminding you that trend-following signals (Strong Buy, Pullback) carry extra weight.
Bearish (Red)
Similarly, if –DI exceeds +DI with ADX >20, you get a light red tint for a developing downtrend, and a darker, more solid red once ADX surpasses 30.
By dynamically varying both hue (green vs. red vs. gray) and opacity (light vs. dark), the background instantly communicates trend strength and direction—so you always know whether to favor breakout-style entries (in a strong trend) or stay flat during choppy, low-ADX conditions.
The setup shown in the above chart snapshot is BTCUSD 15 min chart : Binance for reference.
Disclaimer
No indicator guarantees profits. Backtest or paper trade this tool to understand its behavior in your market. Always use proper position sizing and stop loss orders.
Good luck!
- BullByte
Levels & Flow📌 Overview
Levels & Flow is a visual trading tool that combines daily pivot levels with a dynamic EMA ribbon to help traders identify structure, momentum, and key decision zones in the market.
This script is designed for discretionary traders who rely on clean visual cues for intraday and swing trading strategies.
⚙️ Key Features
Daily Pivot, Support, and Resistance Lines
Automatically plots the daily pivot level based on the previous day’s OHLC data, along with calculated support and resistance levels.
Fibonacci Retracement Levels
Two dashed lines above and below the pivot represent the retracement of the pivot-resistance and pivot-support range, forming the boundaries of the “no-trade zone.”
No-Trade Zone (Shaded Box)
A gray shaded box between the two Fibonacci levels to visually mark a high-chop/low-conviction zone.
Trend-Based Candle Coloring (Current Day Only)
Candles are colored green if the close is above the pivot, red if below (only on the current trading day).
Bullish/Bearish Trend Label
A small table in the bottom-right corner displays “Bullish” or “Bearish” depending on whether price is above or below the pivot.
20-EMA Gradient Ribbon
A stack of 20 EMAs, each smoothed and color-coded from blue to green to reflect short- to long-term trend alignment.
Cumulative EMA with Adaptive Weighting
An intelligent moving average line that adjusts weight distribution among the 20 EMAs based on recent predictive accuracy using a learning rate and lookback period.
🧠 How It Works
📍 Levels
The script calculates daily pivot, resistance, and support levels using standard formulas:
Pivot = (High + Low + Close) / 3
Resistance = (2 × Pivot) – Low
Support = (2 × Pivot) – High
These levels update each day and extend 143 bars to the right.
📏 Fib Lines
Fib Up = Pivot + (Resistance – Pivot) × 0.382
Fib Down = Pivot – (Pivot – Support) × 0.382
These lines form the “no-trade zone” box.
📈 EMA Ribbon
20 EMAs starting from the user-defined Base Length, each incremented by 1
Each EMA is smoothed using the Smoothing Period
Color-coded from blue to green for intuitive visual flow
Filled between EMAs to visualize trend strength and alignment
🧠 Cumulative EMA Learning
Each EMA’s historical error is calculated over a Lookback Period
Lower-error EMAs receive higher weight; weights are normalized to sum to 1
The result is a cumulative EMA that adapts based on historical predictive power
🔧 User Inputs
Input
Base EMA Length: Sets the period for the shortest EMA (default: 20)
Smoothing Period: Smooths all EMAs and the cumulative EMA
Lookback for Learning: Number of bars to evaluate EMA prediction accuracy
Learning Rate: Adjusts how quickly weights shift in favor of more accurate EMAs
✅ How to Use It
Use the pivot level to define directional bias.
Watch for price breakouts above resistance or breakdowns below support to consider entry.
Avoid trading inside the shaded zone, where direction is less reliable.
Use the EMA ribbon gradient to confirm short/long alignment.
The cumulative EMA helps define trend with noise reduction.
🧪 Best For
Intraday traders who want to blend structure with flow
Swing traders needing clean daily levels with dynamic confirmation
Anyone looking to avoid choppy zones and improve visual clarity
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a trading recommendation. Always test scripts in simulation or on demo accounts before live use. Use at your own risk.
Stoch Quad Oscillator📘 Stoch Quad Oscillator – User Guide
✅ Purpose
The Stoch Quad Oscillator is a multi-timeframe stochastic oscillator tool that helps traders detect oversold and overbought conditions, momentum shifts, and quad rotation signals using four distinct stochastic configurations. It includes visual cues, customizable parameters, and background highlights to improve decision-making during trend reversals or momentum surges.
🛠️ Inputs & Parameters
⏱ Timeframe
Timeframe for Stochastic Calculation: Defines which chart timeframe to use for stochastic calculations (default is "1" minute). This enables multi-timeframe analysis while on a lower timeframe chart.
📈 Stochastic Parameters
Four different stochastic configurations are used:
Label %K Length %D Smoothing Notes
K9 D3 9 3 Fastest, short-term view
K14 D3 14 3 Moderately short-term
K40 D4 40 4 Medium-term trend view
K60 D10 60 10 Long-term strength
Smoothing Type: Choose between SMA or EMA to control how smoothed the %D line is.
🎯 Levels
Overbought Level: Default 80
Oversold Level: Default 20
These are used to indicate overextended price conditions on any of the stochastic plots.
🔄 Quad Rotation Detection Settings
When enabled, the script detects synchronized oversold/overbought conditions with strong momentum using all 4 stochastic readings.
Enable Quad Rotation: Toggles detection on or off
Slope Calculation Bars: Number of bars used to calculate slope of %D lines
Slope Threshold: Minimum slope strength for signal (higher = stronger confirmation)
Oversold Quad Level: Total of all four stochastic values that define a quad oversold zone
Overbought Quad Level: Total of all four stochastic values that define a quad overbought zone
Oversold Quad Highlight Color: Background color when oversold quad is triggered
Overbought Quad Highlight Color: Background color when overbought quad is triggered
Slope Averaging Method: Either Simple Average or Weighted Average (puts more weight on higher timeframes)
Max Signal Bar Window: Defines how recent the signal must be to be considered valid
📊 Plots & Visual Elements
📉 Stochastic %D Lines
Each stochastic is plotted separately:
K9 D3 – Red
K14 D3 – Orange
K40 D4 – Fuchsia
K60 D10 – Silver
These help visualize short to long-term momentum simultaneously.
📏 Horizontal Reference Lines
Overbought Line (80) – Red
Oversold Line (20) – Green
These help you identify threshold breaches visually.
🌈 Background Highlighting
The indicator provides background highlights to mark potential signal zones:
✅ All Oversold or Overbought Conditions
When all four stochastics are either above overbought or below oversold:
Bright Red if all are overbought
Bright Green if all are oversold
🚨 Quad Rotation Signal Zones (if enabled)
Triggered when:
The combined sum of all four stochastic levels is extremely low/high (below/above oversoldQuadLevel or overboughtQuadLevel)
The average slope of the 4 %D lines is sharply positive (> slopeThreshold)
Highlights:
Custom Red Tint = Strong overbought quad signal
Custom Green Tint = Strong oversold quad signal
These zones can indicate momentum shifts or reversal potential when used with price action or other tools.
⚠️ Limitations & Considerations
This indicator does not provide trade signals. It visualizes conditions and potential setups.
It is best used in confluence with price action, support/resistance levels, and other indicators.
False positives may occur in ranging markets. Reduce reliance on slope thresholds during low volatility.
Quad signals rely on slope strength, which may lag slightly behind sudden reversals.
🧠 Tips for Use
Combine with volume, MACD, or PSAR to confirm direction before entry.
Watch for divergences between price and any of the stochastics.
Use on higher timeframes (e.g., 5m–30m) to filter for swing trading setups; use shorter TFs (1m–5m) for scalping signals.
Adjust oversoldQuadLevel and overboughtQuadLevel based on market conditions (e.g., in trending vs ranging markets).
Smart Fib StrategySmart Fibonacci Strategy
This advanced trading strategy combines the power of adaptive SMA entries with Fibonacci-based exit levels to create a comprehensive trend-following system that self-optimizes based on historical market conditions. Credit goes to Julien_Eche who created the "Best SMA Finder" which received an Editors Pick award.
Strategy Overview
The Smart Fibonacci Strategy employs a two-pronged approach to trading:
1. Intelligent Entries: Uses a self-optimizing SMA (Simple Moving Average) to identify optimal entry points. The system automatically tests multiple SMA lengths against historical data to determine which period provides the most robust trading signals.
2. Fibonacci-Based Exits: Implements ATR-adjusted Fibonacci bands to establish precise exit targets, with risk-management options ranging from conservative to aggressive.
This dual methodology creates a balanced system that adapts to changing market conditions while providing clear visual reference points for trade management.
Key Features
- **Self-Optimizing Entries**: Automatically calculates the most profitable SMA length based on historical performance
- **Adjustable Risk Parameters**: Choose between low-risk and high-risk exit targets
- **Directional Flexibility**: Trade long-only, short-only, or both directions
- **Visualization Tools**: Customizable display of entry lines and exit bands
- **Performance Statistics**: Comprehensive stats table showing key metrics
- **Smoothing Option**: Reduces noise in the Fibonacci bands for cleaner signals
Trading Rules
Entry Signals
- **Long Entry**: When price crosses above the blue center line (optimal SMA)
- **Short Entry**: When price crosses below the blue center line (optimal SMA)
### Exit Levels
- **Low Risk Option**: Exit at the first Fibonacci band (1.618 * ATR)
- **High Risk Option**: Exit at the second Fibonacci band (2.618 * ATR)
Strategy Parameters
Display Settings
- Toggle visibility of the stats table and indicator components
Strategy Settings
- Select trading direction (long, short, or both)
- Choose exit method (low risk or high risk)
- Set minimum trades threshold for SMA optimization
SMA Settings
- Option to use auto-optimized or fixed-length SMA
- Customize SMA length when using fixed option
Fibonacci Settings
- Adjust ATR period and SMA basis for Fibonacci bands
- Enable/disable smoothing function
- Customize Fibonacci ratio multipliers
Appearance Settings
- Modify colors, line widths, and transparency
Optimization Methodology
The strategy employs a sophisticated optimization algorithm that:
1. Tests multiple SMA lengths against historical data
2. Evaluates performance based on trade count, profit factor, and win rate
3. Calculates a "robustness score" that balances profitability with statistical significance
4. Selects the SMA length with the highest robustness score
This ensures that the strategy's entry signals are continuously adapting to the most effective parameters for current market conditions.
Risk Management
Position sizing is fixed at $2,000 per trade, allowing for consistent exposure across all trading setups. The Fibonacci-based exit system provides two distinct risk management approaches:
- **Conservative Approach**: Using the first Fibonacci band for exits produces more frequent but smaller wins
- **Aggressive Approach**: Using the second Fibonacci band allows for larger potential gains at the cost of increased volatility
Ideal Usage
This strategy is best suited for:
- Trending markets with clear directional moves
- Timeframes from 4H to Daily for most balanced results
- Instruments with moderate volatility (stocks, forex, commodities)
Traders can further enhance performance by combining this strategy with broader market analysis to confirm the prevailing trend direction.
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
Guppy Multiple Moving Average (GMMA)The GMMA Momentum Indicator plots 12 EMAs on your chart, divided into two groups:
Short-term EMAs (6 lines, default periods: 3, 5, 8, 10, 12, 15): Represent short-term trader sentiment and momentum.
Long-term EMAs (6 lines, default periods: 30, 35, 40, 45, 50, 60): Reflect long-term investor behavior and broader market trends.
By analyzing the interaction between these two groups, the indicator identifies:
Bullish and bearish trends based on the relative positions of the short- and long-term EMAs.
Momentum strength through the spread or convergence of the EMAs.
Potential reversals or breakouts via compression signals.
This PineScript version enhances the traditional GMMA by adding visual cues like background colors, bearish signals, and compression detection, making it ideal for swing traders seeking clear, actionable insights.
The GMMA Momentum Indicator provides several key features:
1. Trend Identification
Bullish Trend: When the short-term EMAs (green lines) are above the long-term EMAs (blue lines) and spreading apart, it signals strong upward momentum. The chart background turns light green to highlight this condition.
Bearish Trend: When the short-term EMAs cross below the long-term EMAs and converge, it indicates downward momentum. The background turns light red, and an orange downward triangle appears above the bar to mark a new bearish signal.
2. Momentum Analysis
The spread between the short-term EMAs reflects the strength of short-term momentum. A wide spread suggests strong momentum, while a tight grouping indicates weakening momentum or consolidation. Similarly, the long-term EMAs act as dynamic support or resistance, guiding traders on the broader trend.
3. Compression Detection
Compression occurs when both the short-term and long-term EMAs converge, signaling low volatility and a potential breakout or reversal. A yellow upward triangle appears below the bar when compression is detected, alerting traders to watch for price action.
4. Visual Cues
Green short-term EMAs: Show short-term trader activity.
Blue long-term EMAs: Represent long-term investor sentiment.
Background colors: Light green for bullish trends, light red for bearish trends, and transparent for neutral conditions.
Orange downward triangles: Mark new bearish trends.
Yellow upward triangles: Indicate compression, hinting at potential breakouts.
How to Use the GMMA Momentum Indicator for Swing Trading
Swing trading involves capturing price moves over days to weeks, and the GMMA Momentum Indicator is an excellent tool for this strategy. Here’s how to use it effectively:
1. Identifying Trade Entries
Buy Opportunities:
Look for a bullish trend (green background) where the short-term EMAs are above the long-term EMAs and spreading apart, indicating strong momentum.
A compression signal (yellow triangle) followed by a breakout above resistance or a bullish candlestick pattern can confirm an entry.
Example: On a daily chart, if the short-term EMAs cross above the long-term EMAs and the background turns green, consider entering a long position, especially if volume supports the move.
Sell Opportunities:
Watch for a bearish signal (orange downward triangle) or a bearish trend (red background) where the short-term EMAs cross below the long-term EMAs.
Example: If the short-term EMAs collapse below the long-term EMAs and an orange triangle appears, it may signal a shorting opportunity or a time to exit longs.
2. Managing Trades
Use the long-term EMAs as dynamic support (in uptrends) or resistance (in downtrends) to set stop-loss levels or trail stops.
Monitor the spread of the short-term EMAs. A widening spread suggests the trend is strong, while convergence may indicate it’s time to take profits or tighten stops.
3. Anticipating Reversals
Compression signals (yellow triangles) highlight periods of low volatility, often preceding significant price moves. Combine these with price action (e.g., breakouts or reversals) or other indicators (e.g., RSI or volume) for confirmation.
Example: If a compression signal appears near a key support level and the price breaks upward, it could signal the start of a new bullish swing.
4. Best Practices
Timeframes: The indicator works well on daily or 4-hour charts for swing trading, but you can adjust the EMA periods for shorter (e.g., 1-hour) or longer (e.g., weekly) timeframes.
Confirmation: Combine the GMMA with other tools like support/resistance levels, candlestick patterns, or oscillators (e.g., MACD) to reduce false signals.
Risk Management: Always use proper position sizing and stop-losses, as EMAs are lagging indicators and may produce delayed signals in choppy markets.
OTE & A-B-C Zone Indicator SwiftEdgeOTE & A-B-C Zone Indicator SwiftEdge
Overview
The OTE & A-B-C Zone Indicator SwiftEdge is a versatile tool designed to help traders identify high-probability trading setups using a combination of Optimal Trade Entry (OTE) zones, Fibonacci levels, and A-B-C price patterns. This indicator is particularly useful for traders who rely on price action and Fibonacci-based strategies to find entry points, set stop-losses, and target potential take-profit levels. By integrating swing point detection, trend analysis, and Fibonacci projections, SwiftEdge provides a clear visual framework for making informed trading decisions across various timeframes.
What It Does
SwiftEdge identifies key price levels and zones to guide your trading:
OTE Zone: Highlights the Optimal Trade Entry zone between swing points A (swing high) and B (swing low) using Fibonacci retracement levels (default: 0.618 to 0.786). This zone represents a high-probability area for price reversals, making it an ideal entry point for trades.
A-B-C Pattern: Marks the latest swing points as A (swing high), B (swing low), and C (projected take-profit level) with dashed lines and labels. A solid line connects A to B to C, visually illustrating the price movement from entry to target.
Take-Profit Zones: Projects three customizable take-profit levels (TP1, TP2, TP3) based on Fibonacci extensions (default: 1.272, 1.618, 2.0) from the A-B swing, helping traders plan exits with favorable risk-reward ratios.
How It Works
SwiftEdge combines several technical components to create a cohesive trading system:
Swing Point Detection: Identifies significant swing highs (A) and swing lows (B) using a dynamic lookback period that adjusts to the selected timeframe. On lower timeframes like 1-minute charts, an ATR-based filter reduces noise by requiring price movements to exceed a threshold (0.5 * ATR(14)).
Trend Analysis: Uses an Exponential Moving Average (EMA) to determine the trend direction (default: 50-period EMA on 1H). The indicator marks uptrends (price above EMA) in green and downtrends (price below EMA) in red, ensuring trades align with the market's direction.
Fibonacci Levels: Applies Fibonacci retracement to define the OTE zone between A and B, and Fibonacci extensions to project take-profit levels (C) beyond the initial swing. This approach leverages the natural tendency of markets to respect Fibonacci ratios for reversals and extensions.
Visual Clarity: Displays only the latest A-B-C pattern with three dashed lines (A, B, C) and a solid connecting line, ensuring the chart remains uncluttered and easy to interpret.
The combination of these elements creates a structured setup where the OTE zone (between A and B) serves as an entry point, while the projected C level offers a target, all within the context of the prevailing trend. This synergy makes SwiftEdge a powerful tool for traders seeking to combine price action, trend analysis, and Fibonacci strategies.
How to Use
Add the Indicator: Apply the indicator to your chart via TradingView's indicator menu.
Identify the Trend: The OTE zone and A-B-C pattern will be colored green in uptrends (price above EMA) or red in downtrends (price below EMA). Use this to determine the market direction.
Entry Point: Look for price reversals within the OTE zone (between A and B). This zone is typically between the 0.618 and 0.786 Fibonacci retracement levels of the A-B swing, making it a high-probability area for entries.
Stop-Loss: Place your stop-loss below the OTE zone in an uptrend (or above in a downtrend) to protect against false breakouts.
Take-Profit Targets: Use the projected take-profit zones (TP1, TP2, TP3) as potential exit levels. These are based on Fibonacci extensions and can be toggled on/off in the settings.
Customization:
Adjust the Fibonacci levels for the OTE zone (Fibonacci Level 1 and Fibonacci Level 2) to suit your strategy.
Modify the take-profit levels (Fibonacci Extension Level for TP1/TP2/TP3) to target different extension ratios.
Change the lookback period (Base Lookback Period) and EMA period (Base EMA Period) to fine-tune swing point detection and trend sensitivity.
Customize colors for uptrends, downtrends, and A-B-C lines to match your preferences.
What Makes It Unique
SwiftEdge stands out by integrating swing point detection, Fibonacci-based OTE zones, and A-B-C price patterns into a single, visually intuitive indicator. Unlike standalone Fibonacci tools or trend indicators, SwiftEdge combines these elements to provide a complete trading setup: it identifies entry zones (OTE), confirms trend direction (EMA), and projects take-profit targets (Fibonacci extensions). The dynamic timeframe adjustment ensures consistent performance across all chart intervals, while the clean A-B-C visualization (with only the latest pattern displayed) prevents chart clutter, making it easier to focus on the most relevant price levels.
Notes
This indicator is designed for traders familiar with price action and Fibonacci strategies. It does not guarantee profits and should be used in conjunction with other analysis tools and proper risk management.
Performance may vary depending on market conditions and timeframe. Test the indicator on a demo account before using it in live trading.
nineLivesUtilLibLibrary "nineLivesUtilLib"
isDateInRange(currentTime, useTimeFilter, startDate, endDate)
Checks if the current time is within the specified date range.
Parameters:
currentTime (int) : The current bar's time (time).
useTimeFilter (bool) : Bool 📅: Enable the date range filter.
startDate (int) : Timestamp 📅: The start date for the filter.
endDate (int) : Timestamp 📅: The end date for the filter.
Returns: True if the current time is within the range or filtering is disabled, false otherwise.
@example
inDateRange = nineLivesUtilLib.isDateInRange(time, useTimeFilter, startDate, endDate)
if inDateRange
// Execute trading logic
checkVolumeCondition(currentVolume, useVolumeFilter, volumeThresholdMultiplier, volumeLength)
Checks if the current volume meets the threshold condition.
Parameters:
currentVolume (float) : The current bar's volume (volume).
useVolumeFilter (bool) : Bool 📊: Enable the volume filter.
volumeThresholdMultiplier (float) : Float 📊: Volume threshold relative to average (e.g., 1.5 for 1.5x average).
volumeLength (int) : Int 📊: Lookback length for the volume average.
Returns: True if the volume condition is met or filtering is disabled, false otherwise.
@example
volumeOk = nineLivesUtilLib.checkVolumeCondition(volume, useVolumeFilter, volumeThreshold, volumeLength)
if volumeOk
// Proceed with trading logic
checkMultiTimeframeCondition(currentClose, currentOpen, htfClose, htfOpen, useMultiTimeframe, alignment)
Checks alignment with higher timeframe direction.
Parameters:
currentClose (float) : Float: The current bar's closing price (close).
currentOpen (float) : Float: The current bar's opening price (open).
htfClose (float) : Float: The closing price from the higher timeframe (must be fetched by the calling script using request.security).
htfOpen (float) : Float: The opening price from the higher timeframe (must be fetched by the calling script using request.security).
useMultiTimeframe (bool) : Bool ⏱️: Enable multi-timeframe analysis.
alignment (string) : String ⏱️: Desired alignment ("same", "opposite", "any").
Returns: True if the timeframe alignment condition is met or analysis is disabled, false otherwise.
@example
// In the calling script:
= request.security(syminfo.tickerid, higherTimeframe, )
tfOk = nineLivesUtilLib.checkMultiTimeframeCondition(close, open, htfClose, htfOpen, useMultiTimeframe, tfAlignment)
if tfOk
// Proceed with trading logic
checkMarketRegime(useMarketRegime, regimeIndicator, regimeThreshold, regimeLength, regimeMode)
Detects the market regime (trending or ranging) and checks if trading is allowed.
Parameters:
useMarketRegime (bool) : Bool 🔍: Enable market regime detection.
regimeIndicator (string) : String 🔍: Indicator to use ("ADX" or "Volatility").
regimeThreshold (int) : Int 🔍: Threshold for trend strength/volatility.
regimeLength (simple int) : Int 🔍: Lookback length for the indicator.
regimeMode (string) : String 🔍: Trading mode based on regime ("trend_only", "range_only", "adaptive").
Returns: A tuple containing:
: conditionMet (bool) - True if trading is allowed based on the regime mode and detection, false otherwise.
: inTrendingRegime (bool) - True if the current regime is trending based on the indicator and threshold.
@example
= nineLivesUtilLib.checkMarketRegime(useMarketRegime, regimeIndicator, regimeThreshold, regimeLength, regimeMode)
if regimeOk
// Proceed with trading logic
applyCooldown(buySignal, sellSignal, cooldownBars)
Applies a cooldown period after a signal.
Parameters:
buySignal (bool) : Bool: Buy signal (potentially after primary entry logic).
sellSignal (bool) : Bool: Sell signal (potentially after primary entry logic).
cooldownBars (int) : Int ⏳: The number of bars to wait after a signal before allowing another.
Returns: A tuple containing:
: cooldownFilteredBuy (bool) - Buy signal after cooldown filter.
: cooldownFilteredSell (bool) - Sell signal after cooldown filter.
@example
= nineLivesUtilLib.applyCooldown(rawBuySignal, rawSellSignal, iCool)
applyAllFilters(rawBuy, rawSell, inDateRange, tradeDirection, volumeOk, tfOk, regimeOk, drawdownOk, cooldownOkBuy, cooldownOkSell)
Applies all filtering conditions to the buy and sell signals.
Parameters:
rawBuy (bool) : Bool: The initial buy signal candidate (from primary entry logic, e.g., after cooldown).
rawSell (bool) : Bool: The initial sell signal candidate (from primary entry logic, e.g., after cooldown).
inDateRange (bool) : Bool 📅: Result from isDateInRange.
tradeDirection (string) : String 🔄: Overall trade direction preference ("longs_only", "shorts_only", "both").
volumeOk (bool) : Bool 📊: Result from checkVolumeCondition.
tfOk (bool) : Bool ⏱️: Result from checkMultiTimeframeCondition.
regimeOk (bool) : Bool 🔍: Result from checkMarketRegime.
drawdownOk (bool) : Bool 📉: Result from checkDrawdownExceeded (or equivalent).
cooldownOkBuy (bool) : Bool ⏳: Result from applyCooldown for buy.
cooldownOkSell (bool) : Bool ⏳: Result from applyCooldown for sell.
Returns: A tuple containing:
: finalBuySignal (bool) - The final buy signal after all filters.
: finalSellSignal (bool) - The final sell signal after all filters.
@example
= nineLivesUtilLib.applyAllFilters(cooldownBuy, cooldownSell, inDateRange, tradeDirection, volumeOk, tfOk, regimeOk, !drawdownExceeded, cooldownBuy, cooldownSell)
NOTE: This function filters signals generated by your primary entry logic (e.g., EMA crossover).
checkDrawdownExceeded(currentEquity, useMaxDrawdown, maxDrawdownPercent)
Tracks maximum equity and checks if current drawdown exceeds a threshold.
Parameters:
currentEquity (float) : Float: The strategy's current equity (strategy.equity).
useMaxDrawdown (bool) : Bool 📉: Enable max drawdown protection.
maxDrawdownPercent (float) : Float 📉: The maximum allowed drawdown as a percentage.
Returns: True if drawdown protection is enabled and the current drawdown exceeds the threshold, false otherwise.
@example
drawdownExceeded = nineLivesUtilLib.checkDrawdownExceeded(strategy.equity, useMaxDrawdown, maxDrawdownPercent)
if drawdownExceeded
// Consider stopping entries or exiting positions in the strategy script
calculateExitPrice(positionAvgPrice, percentage, isStop, isLong)
Calculates a stop loss or take profit price based on a percentage from the average entry price.
Parameters:
positionAvgPrice (float) : Float: The average price of the current position (strategy.position_avg_price).
percentage (float) : Float: The stop loss or take profit percentage (e.g., 2.0 for 2%).
isStop (bool) : Bool: True if calculating a stop loss price, false if calculating a take profit price.
isLong (bool) : Bool: True if the position is long, false if short.
Returns: The calculated stop price or take profit price, or na if no position or percentage is invalid.
@example
longSL = nineLivesUtilLib.calculateExitPrice(strategy.position_avg_price, stopLossPercent, true, true)
shortTP = nineLivesUtilLib.calculateExitPrice(strategy.position_avg_price, takeProfitPercent, false, false)
calculateTrailingStopLevel(positionAvgPrice, trailOffsetPercent, trailPercent, currentHigh, currentLow, isLong)
Calculates the current trailing stop level for a position.
Parameters:
positionAvgPrice (float) : Float: The average price of the current position (strategy.position_avg_price).
trailOffsetPercent (float) : Float 🔄: The percentage price movement to activate the trailing stop.
trailPercent (float) : Float 🔄: The percentage distance the stop trails behind the price.
currentHigh (float) : Float: The current bar's high (high).
currentLow (float) : Float: The current bar's low (low).
isLong (bool) : Bool: True if the position is long, false if short.
Returns: The calculated trailing stop price if active, otherwise na.
@example
longTrailStop = nineLivesUtilLib.calculateTrailingStopLevel(strategy.position_avg_price, trailOffset, trailPercent, high, low, true)
shortTrailStop = nineLivesUtilLib.calculateTrailingStopLevel(strategy.position_avg_price, trailOffset, trailPercent, high, low, false)
if not na(longTrailStop)
strategy.exit("Long Trail", from_entry="Long", stop=longTrailStop)
