Hierarchical + K-Means Clustering Strategy===== USER GUIDE =====
Hierarchical + K-Means Clustering Strategy
OVERVIEW:
This strategy combines hierarchical clustering and K-means algorithms to analyze market volatility patterns
and generate trading signals. It uses a modified SuperTrend indicator with ATR-based volatility clustering
to identify potential trend changes and market conditions.
KEY FEATURES:
- Advanced volatility analysis using hierarchical clustering and K-means algorithms
- Modified SuperTrend indicator for trend identification
- Multiple filter options including moving average and ADX trend strength
- Volume-based exit mechanism to protect profits
- Customizable appearance settings
SETTINGS EXPLANATION:
1. SuperTrend Settings:
- ATR Length: Period for ATR calculation (default: 11)
- SuperTrend Factor: Multiplier for ATR to determine trend bands (default: 3)
2. Hierarchical Clustering Settings:
- Training Data Length: Number of bars used for clustering analysis (default: 200)
3. Appearance Settings:
- Transparency 1 & 2: Control the opacity of trend lines and fills
- Bullish/Bearish Color: Colors for uptrend and downtrend visualization
4. Time Settings:
- Start Year/Month: Define when the strategy should start executing trades
5. Filter Settings:
- Moving Average Filter: Uses SMA to filter trades (only enter when price is on correct side of MA)
- Trend Strength Filter: Uses ADX to ensure trades are taken in strong trend conditions
6. Volume Stop Loss Settings:
- Volume Ratio Threshold: Controls sensitivity of volume-based exits
- Monitoring Delay Bars: Number of bars to wait before monitoring volume for exit signals
HOW TO USE:
1. Apply the indicator to your chart
2. Adjust settings according to your trading preferences and timeframe
3. Long signals appear when price crosses above the SuperTrend line (▲k marker)
4. Short signals appear when price crosses below the SuperTrend line (▼k marker)
5. The strategy automatically manages exits based on volume balance conditions
INTERPRETATION:
- Green line/area: Bullish trend - consider long positions
- Red line/area: Bearish trend - consider short positions
- Yellow line: Moving average for additional trend confirmation
- Volume balance exits occur when buying/selling pressure equalizes
RECOMMENDED TIMEFRAMES:
This strategy works best on 1H, 4H, and daily charts for most markets.
For highly volatile assets, shorter timeframes may also be effective.
RISK MANAGEMENT:
Always use proper position sizing and consider setting additional stop losses
beyond the strategy's built-in exit mechanisms.
===== END OF USER GUIDE =====
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TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
[COG]TMS Crossfire 🔍 TMS Crossfire: Guide to Parameters
📊 Core Parameters
🔸 Stochastic Settings (K, D, Period)
- **What it does**: These control how the first stochastic oscillator works. Think of it as measuring momentum speed.
- **K**: Determines how smooth the main stochastic line is. Lower values (1-3) react quickly, higher values (3-9) are smoother.
- **D**: Controls the smoothness of the signal line. Usually kept equal to or slightly higher than K.
- **Period**: How many candles are used to calculate the stochastic. Standard is 14 days, lower for faster signals.
- **For beginners**: Start with the defaults (K:3, D:3, Period:14) until you understand how they work.
🔸 Second Stochastic (K2, D2, Period2)
- **What it does**: Creates a second, independent stochastic for stronger confirmation.
- **How to use**: Can be set identical to the first one, or with slightly different values for dual confirmation.
- **For beginners**: Start with the same values as the first stochastic, then experiment.
🔸 RSI Length
- **What it does**: Controls the period for the RSI calculation, which measures buying/selling pressure.
- **Lower values** (7-9): More sensitive, good for short-term trading
- **Higher values** (14-21): More stable, better for swing trading
- **For beginners**: The default of 11 is a good balance between speed and reliability.
🔸 Cross Level
- **What it does**: The centerline where crosses generate signals (default is 50).
- **Traditional levels**: Stochastics typically use 20/80, but 50 works well for this combined indicator.
- **For beginners**: Keep at 50 to focus on trend following strategies.
🔸 Source
- **What it does**: Determines which price data is used for calculations.
- **Common options**:
- Close: Most common and reliable
- Open: Less common
- High/Low: Used for specialized indicators
- **For beginners**: Stick with "close" as it's most commonly used and reliable.
🎨 Visual Theme Settings
🔸 Bullish/Bearish Main
- **What it does**: Sets the overall color scheme for bullish (up) and bearish (down) movements.
- **For beginners**: Green for bullish and red for bearish is intuitive, but choose any colors that are easy for you to distinguish.
🔸 Bullish/Bearish Entry
- **What it does**: Colors for the entry signals shown directly on the chart.
- **For beginners**: Use bright, attention-grabbing colors that stand out from your chart background.
🌈 Line Colors
🔸 K1, K2, RSI (Bullish/Bearish)
- **What it does**: Controls the colors of each indicator line based on market direction.
- **For beginners**: Use different colors for each line so you can quickly identify which line is which.
⏱️ HTF (Higher Timeframe) Settings
🔸 HTF Timeframe
- **What it does**: Sets which higher timeframe to use for filtering (e.g., 240 = 4 hour chart).
- **How to choose**: Should be at least 4x your current chart timeframe (e.g., if trading on 15min, use 60min or higher).
- **For beginners**: Start with a timeframe 4x higher than your trading chart.
🔸 Use HTF Filter
- **What it does**: Toggles whether the higher timeframe filter is applied or not.
- **For beginners**: Keep enabled to reduce false signals, especially when learning.
🔸 HTF Confirmation Bars
- **What it does**: How many bars must confirm a trend change on higher timeframe.
- **Higher values**: More reliable but slower to react
- **Lower values**: Faster signals but more false positives
- **For beginners**: Start with 2-3 bars for a good balance.
📈 EMA Settings
🔸 Use EMA Filter
- **What it does**: Toggles price filtering with an Exponential Moving Average.
- **For beginners**: Keep enabled for better trend confirmation.
🔸 EMA Period
- **What it does**: Length of the EMA for filtering (shorter = faster reactions).
- **Common values**:
- 5-13: Short-term trends
- 21-50: Medium-term trends
- 100-200: Long-term trends
- **For beginners**: 5-10 is good for short-term trading, 21 for swing trading.
🔸 EMA Offset
- **What it does**: Shifts the EMA forward or backward on the chart.
- **For beginners**: Start with 0 and adjust only if needed for visual clarity.
🔸 Show EMA on Chart
- **What it does**: Toggles whether the EMA appears on your main price chart.
- **For beginners**: Keep enabled to see how price relates to the EMA.
🔸 EMA Color, Style, Width, Transparency
- **What it does**: Customizes how the EMA line looks on your chart.
- **For beginners**: Choose settings that make the EMA visible but not distracting.
🌊 Trend Filter Settings
🔸 Use EMA Trend Filter
- **What it does**: Enables a multi-EMA system that defines the overall market trend.
- **For beginners**: Keep enabled for stronger trend confirmation.
🔸 Show Trend EMAs
- **What it does**: Toggles visibility of the trend EMAs on your chart.
- **For beginners**: Enable to see how price moves relative to multiple EMAs.
🔸 EMA Line Thickness
- **What it does**: Controls how the thickness of EMA lines is determined.
- **Options**:
- Uniform: All EMAs have the same thickness
- Variable: Each EMA has its own custom thickness
- Hierarchical: Automatically sized based on period (longer periods = thicker)
- **For beginners**: "Hierarchical" is most intuitive as longer-term EMAs appear more dominant.
🔸 EMA Line Style
- **What it does**: Sets the line style (solid, dotted, dashed) for all EMAs.
- **For beginners**: "Solid" is usually clearest unless you have many lines overlapping.
🎭 Trend Filter Colors/Width
🔸 EMA Colors (8, 21, 34, 55)
- **What it does**: Sets the color for each individual trend EMA.
- **For beginners**: Use a logical progression (e.g., shorter EMAs brighter, longer EMAs darker).
🔸 EMA Width Settings
- **What it does**: Controls the thickness of each EMA line.
- **For beginners**: Thicker lines for longer EMAs make them easier to distinguish.
🔔 How These Parameters Work Together
The power of this indicator comes from how these components interact:
1. **Base Oscillator**: The stochastic and RSI components create the main oscillator
2. **HTF Filter**: The higher timeframe filter prevents trading against larger trends
3. **EMA Filter**: The EMA filter confirms signals with price action
4. **Trend System**: The multi-EMA system identifies the overall market environment
Think of it as multiple layers of confirmation, each adding more reliability to your trading signals.
💡 Tips for Beginners
1. **Start with defaults**: Use the default settings first and understand what each element does
2. **One change at a time**: When customizing, change only one parameter at a time
3. **Keep notes**: Write down how each change affects your results
4. **Backtest thoroughly**: Test any changes on historical data before trading real money
5. **Less is more**: Sometimes simpler settings work better than complicated ones
Remember, no indicator is perfect - always combine this with proper risk management and other forms of analysis!
AEST High-Low MarkerOverview
This TradingView indicator, AEST High-Low Marker, is designed to mark the highest and lowest price levels observed between 5:00 PM and 6:00 PM AEST and extend these levels visually on the chart only between 5:00 PM and 12:00 AM AEST.
Functionality
Time Conversion for AEST
Since TradingView operates in UTC, the script translates AEST (UTC+10 or UTC+11 during daylight savings) into UTC time.
The script starts tracking from 5:00 PM AEST (7 AM UTC) to 6:00 PM AEST (8 AM UTC).
The high and low lines will be displayed only between 5:00 PM and 12:00 AM AEST (7 AM to 2 PM UTC).
Real-Time High & Low Calculation
The indicator dynamically updates the session high and low as new candles form during the 5 PM - 6 PM AEST period.
It captures the maximum high and minimum low during this timeframe.
Line Display Restrictions
The session high and low lines will only be drawn between 5:00 PM and 12:00 AM AEST to prevent chart clutter.
The lines disappear after 12:00 AM AEST.
Visual Representation
Blue Line: Marks the session high recorded between 5 PM - 6 PM AEST.
Red Line: Marks the session low recorded between 5 PM - 6 PM AEST.
Both lines extend until 12 AM AEST and then disappear.
Use Case
This indicator is useful for traders looking to track key price levels formed between 5 PM and 6 PM AEST and observe how price interacts with these levels until midnight.
It is particularly beneficial for intraday and short-term trading strategies, allowing users to identify potential support and resistance zones based on early evening price action.
Squeeze Momentum Indicator Strategy [LazyBear + PineIndicators]The Squeeze Momentum Indicator Strategy (SQZMOM_LB Strategy) is an automated trading strategy based on the Squeeze Momentum Indicator developed by LazyBear, which itself is a modification of John Carter's "TTM Squeeze" concept from his book Mastering the Trade (Chapter 11). This strategy is designed to identify low-volatility phases in the market, which often precede explosive price movements, and to enter trades in the direction of the prevailing momentum.
Concept & Indicator Breakdown
The strategy employs a combination of Bollinger Bands (BB) and Keltner Channels (KC) to detect market squeezes:
Squeeze Condition:
When Bollinger Bands are inside the Keltner Channels (Black Crosses), volatility is low, signaling a potential upcoming price breakout.
When Bollinger Bands move outside Keltner Channels (Gray Crosses), the squeeze is released, indicating an expansion in volatility.
Momentum Calculation:
A linear regression-based momentum value is used instead of traditional momentum indicators.
The momentum histogram is color-coded to show strength and direction:
Lime/Green: Increasing bullish momentum
Red/Maroon: Increasing bearish momentum
Signal Colors:
Black: Market is in a squeeze (low volatility).
Gray: Squeeze is released, and volatility is expanding.
Blue: No squeeze condition is present.
Strategy Logic
The script uses historical volatility conditions and momentum trends to generate buy/sell signals and manage positions.
1. Entry Conditions
Long Position (Buy)
The squeeze just released (Gray Cross after Black Cross).
The momentum value is increasing and positive.
The momentum is at a local low compared to the past 100 bars.
The price is above the 100-period EMA.
The closing price is higher than the previous close.
Short Position (Sell)
The squeeze just released (Gray Cross after Black Cross).
The momentum value is decreasing and negative.
The momentum is at a local high compared to the past 100 bars.
The price is below the 100-period EMA.
The closing price is lower than the previous close.
2. Exit Conditions
Long Exit:
The momentum value starts decreasing (momentum lower than previous bar).
Short Exit:
The momentum value starts increasing (momentum higher than previous bar).
Position Sizing
Position size is dynamically adjusted based on 8% of strategy equity, divided by the current closing price, ensuring risk-adjusted trade sizes.
How to Use This Strategy
Apply on Suitable Markets:
Best for stocks, indices, and forex pairs with momentum-driven price action.
Works on multiple timeframes but is most effective on higher timeframes (1H, 4H, Daily).
Confirm Entries with Additional Indicators:
The author recommends ADX or WaveTrend to refine entries and avoid false signals.
Risk Management:
Since the strategy dynamically sizes positions, it's advised to use stop-losses or risk-based exits to avoid excessive drawdowns.
Final Thoughts
The Squeeze Momentum Indicator Strategy provides a systematic approach to trading volatility expansions, leveraging the classic TTM Squeeze principles with a unique linear regression-based momentum calculation. Originally inspired by John Carter’s method, LazyBear's version and this strategy offer a refined, adaptable tool for traders looking to capitalize on market momentum shifts.
Pulse of Cycle Oscillator"Pulse of Cycle" Oscillator: Logic and Usage
What Is It and How Does It Work?
The "Pulse of Cycle" is an oscillator that measures the cycles of price rises and falls, helping you spot overbought and oversold conditions. Unlike classic indicators, it doesn’t focus on how much the price moves but tracks its direction (up or down) like a "pulse." Here’s the logic:
Price Movement:
If the price rises compared to the previous bar, it adds +1.
If the price falls, it subtracts -1.
If the price stays the same, it adds 0.
Decay Factor: Each step, the previous value is multiplied by a factor (e.g., 0.9) to shrink it slightly. This keeps the oscillator from growing too big and focuses it on recent price action.
Signals: The oscillator moves around zero. When it crosses certain levels (e.g., 5 and 10), it warns you about overbought or oversold zones:
Weak Signal: Above ±5, the market might be stretching a bit.
Strong Signal: Above ±10, a reversal is more likely.
In short, it tracks the "rhythm" of price streaks (consecutive ups or downs) and signals when things might be getting extreme.
How It Looks on the Chart
Line: The oscillator moves around a zero line.
Colors:
Blue: Normal zone (between -5 and +5).
Orange: Weak overbought (+5 and up) or oversold (-5 and down).
Red: Strong overbought (+10 and up).
Lime: Strong oversold (-10 and down).
Threshold Lines: You’ll see lines at 0, ±5, and ±10 on the chart to show where you are.
How to Use It?
Here’s how to trade with this oscillator:
Buy Opportunity (Long Position):
When?: The oscillator drops below -5 (weak) or -10 (strong), then starts moving back toward zero. This suggests the price has hit a bottom and might rise.
Example: It falls to -12 (lime), then rises to -8. You could buy, expecting a bounce.
Tip: Wait for a green candle to confirm if you want to be safer.
Sell Opportunity (Short Position):
When?: The oscillator rises above +5 (weak) or +10 (strong), then starts dropping back toward zero. This indicates the price might have peaked and could fall.
Example: It hits +11 (red), then drops to +7. You could sell, expecting a decline.
Tip: Look for a red candle to confirm the turn.
Neutral Zone: If it’s between -5 and +5, the market is balanced. You can wait for a clearer signal.
Practical Steps to Use
Add to TradingView:
Paste the code into Pine Editor and click “Add to Chart.”
Adjust Settings (Optional):
Decay (0.9): Lower to 0.7 for faster response, raise to 0.95 for smoother movement.
Thresholds (5 and 10): Change them (e.g., 4 and 8) based on your market.
Watch Signals:
Follow the color changes and threshold crossings.
Set Alerts:
Right-click the oscillator > “Add Alert” to get notified on overbought/oversold signals.
Things to Watch Out For
Confirmation: Pair it with support/resistance levels or candlestick patterns for stronger signals.
Market Type: Works best in range-bound (sideways) markets. In strong trends (all up or down), signals might mislead.
Risk: Always use a stop loss—below the last low for buys, above the last high for sells.
Summary
The "Pulse of Cycle" is a simple yet powerful tool that tracks price movement streaks. Use it to catch reversals at strong signals (-10/+10) or get early warnings at weak signals (±5). The colors and lines on the chart make it easy to see when to act.
TradFi Fundamentals: Momentum Trading with Macroeconomic DataIntroduction
This indicator combines traditional price momentum with key macroeconomic data. By retrieving GDP, inflation, unemployment, and interest rates using security calls, the script automatically adapts to the latest economic data. The goal is to blend technical analysis with fundamental insights to generate a more robust momentum signal.
Original Research Paper by Mohit Apte, B. Tech Scholar, Department of Computer Science and Engineering, COEP Technological University, Pune, India
Link to paper
Explanation
Price Momentum Calculation:
The indicator computes price momentum as the percentage change in price over a configurable lookback period (default is 50 days). This raw momentum is then normalized using a rolling simple moving average and standard deviation over a defined period (default 200 days) to ensure comparability with the economic indicators.
Fetching and Normalizing Economic Data:
Instead of manually inputting economic values, the script uses TradingView’s security function to retrieve:
GDP from ticker "GDP"
Inflation (CPI) from ticker "USCCPI"
Unemployment rate from ticker "UNRATE"
Interest rates from ticker "USINTR"
Each series is normalized over a configurable normalization period (default 200 days) by subtracting its moving average and dividing by its standard deviation. This standardization converts each economic indicator into a z-score for direct integration into the momentum score.
Combined Momentum Score:
The normalized price momentum and economic indicators are each multiplied by user-defined weights (default: 50% price momentum, 20% GDP, and 10% each for inflation, unemployment, and interest rates). The weighted components are then summed to form a comprehensive momentum score. A horizontal zero line is plotted for reference.
Trading Signals:
Buy signals are generated when the combined momentum score crosses above zero, and sell signals occur when it crosses below zero. Visual markers are added to the chart to assist with trade timing, and alert conditions are provided for automated notifications.
Settings
Price Momentum Lookback: Defines the period (in days) used to compute the raw price momentum.
Normalization Period for Price Momentum: Sets the window over which the price momentum is normalized.
Normalization Period for Economic Data: Sets the window over which each macroeconomic series is normalized.
Weights: Adjust the influence of each component (price momentum, GDP, inflation, unemployment, and interest rate) on the overall momentum score.
Conclusion
This implementation leverages TradingView’s economic data feeds to integrate real-time macroeconomic data into a momentum trading strategy. By normalizing and weighting both technical and economic inputs, the indicator offers traders a more holistic view of market conditions. The enhanced momentum signal provides additional context to traditional momentum analysis, potentially leading to more informed trading decisions and improved risk management.
The next script I release will be an improved version of this that I have added my own flavor to, improving the signals.
Harish algo for nifty and bankniftyHarish algo for nifty and banknifty
Overview
Harish Algo - Buy and Sell 11 is a powerful trading indicator designed for intraday traders, incorporating multiple technical analysis concepts to identify potential breakout and breakdown levels. It uses pivot points, exponential moving averages (EMAs), and volatility-based levels to generate buy and sell signals with visual markers for better decision-making.
Features & Functionality
✅ Pivot Points Calculation:
The indicator calculates daily pivot points along with resistance (R1) and support (S1) levels.
Helps in identifying potential reversal or breakout areas.
✅ EMA Trend Confirmation:
Uses three EMAs (21, 55, and 200) to confirm trend direction.
Ensures that buy signals align with uptrends and sell signals align with downtrends.
✅ 15-Minute Candle Analysis for Precision:
Captures the last three 15-minute closes of the previous day.
Computes an average and determines volatility-based price levels to anticipate price movements.
✅ Dynamic Buy & Sell Signals:
Bullish (Buy) Signals:
Price breaks above key resistance levels and EMAs confirm an uptrend.
Displayed as yellow (tiny) or green (small) upward triangles below candles.
Bearish (Sell) Signals:
Price drops below key support levels with EMA confirmation of a downtrend.
Displayed as fuchsia (tiny) or red (small) downward triangles above candles.
✅ Alerts for Trade Execution:
Get notified instantly with alerts when a buy or sell signal is triggered.
✅ Customizable Settings:
Modify EMA lengths and adjust parameters to fit different trading strategies.
Usage & Benefits
🔹 Helps traders identify potential entry and exit points with precision.
🔹 Reduces false signals by combining pivot points, EMAs, and price action.
🔹 Works best for intraday traders in the Indian stock markets, but can be applied to other markets as well.
🔹 Suitable for both beginners and experienced traders looking for a structured approach to trading.
How to Use
Add the indicator to your chart.
Observe the plotted pivot points, EMAs, and price levels.
Watch for triangle markers (buy/sell signals).
Use alerts to receive real-time notifications.
Combine with your own risk management strategy for best results.
🔹 Works on all timeframes but optimized for intraday trading.
Disclaimer
📢 This indicator is for educational purposes only and should not be considered financial advice. Always perform your own analysis before taking trades.
ICT NY Kill Zone Auto Trading### **ICT NY Kill Zone Auto Trading Strategy (5-Min Chart)**
#### **Overview:**
This strategy is based on Inner Circle Trader (ICT) concepts, focusing on the **New York Kill Zone**. It is designed for trading GBP/USD exclusively on the **5-minute chart**, automatically entering and exiting trades during the US session.
#### **Key Components:**
1. **Time Filter**
- The strategy only operates during the **New York Kill Zone (9:30 AM - 11:00 AM NY Time)**.
- It ensures execution only on the **5-minute timeframe**.
2. **Fair Value Gaps (FVGs) Detection**
- The script identifies areas where price action left an imbalance, known as Fair Value Gaps (FVGs).
- These gaps indicate potential liquidity zones where price may return before continuing in the original direction.
3. **Order Blocks (OBs) Identification**
- **Bullish Order Block:** Occurs when price forms a strong bullish pattern, suggesting further upside movement.
- **Bearish Order Block:** Identified when a strong bearish formation signals potential downside continuation.
4. **Trade Execution**
- **Long Trade:** Entered when a bullish order block forms within the NY Kill Zone and aligns with an FVG.
- **Short Trade:** Entered when a bearish order block forms within the Kill Zone and aligns with an FVG.
5. **Risk Management**
- **Stop Loss:** Fixed at **30 pips** to limit downside risk.
- **Take Profit:** Set at **60 pips**, providing a **2:1 risk-reward ratio**.
6. **Visual Aids**
- The **Kill Zone is highlighted in blue** to help traders visually confirm the active session.
**Objective:**
This script aims to **capitalize on institutional price movements** within the New York session by leveraging ICT concepts such as FVGs and Order Blocks. By automating trade entries and exits, it eliminates emotions and ensures a disciplined trading approach.
ICT Concepts: MML, Order Blocks, FVG, OTECore ICT Trading Concepts
These strategies are designed to identify high-probability trading opportunities by analyzing institutional order flow and market psychology.
1. Market Maker Liquidity (MML) / Liquidity Pools
Idea: Institutional traders ("market makers") place orders around key price levels where retail traders’ stop losses cluster (e.g., above swing highs or below swing lows).
Application: Look for "liquidity grabs" where price briefly spikes to these levels before reversing.
Example: If price breaks a recent high but reverses sharply, it may indicate a liquidity grab to trigger retail stops before a trend reversal.
2. Order Blocks (OB)
Idea: Institutional orders are often concentrated in specific price zones ("order blocks") where large buy/sell decisions occurred.
Application: Identify bullish order blocks (strong buying zones) or bearish order blocks (strong selling zones) on higher timeframes (e.g., 1H/4H charts).
Example: A bullish order block forms after a strong rally; price often retests this zone later as support.
3. Fair Value Gap (FVG)
Idea: A price imbalance occurs when candles gap without overlapping, creating an area of "unfair" price that the market often revisits.
Application: Trade the retracement to fill the FVG. A bullish FVG acts as support, and a bearish FVG acts as resistance.
Example: Three consecutive candles create a gap; price later returns to fill this gap, offering a entry point.
4. Time-Based Analysis (NY Session, London Kill Zones)
Idea: Institutional activity peaks during specific times (e.g., 7 AM – 11 AM New York time).
Application: Focus on trades during high-liquidity periods when banks and hedge funds are active.
Example: The "London Kill Zone" (2 AM – 5 AM EST) often sees volatility due to European market openings.
5. Optimal Trade Entry (OTE)
Idea: A retracement level (similar to Fibonacci retracement) where institutions re-enter trends after a pullback.
Application: Look for 62–79% retracements in a trend to align with institutional accumulation/distribution zones.
Example: In an uptrend, price retraces 70% before resuming upward—enter long here.
6. Stop Hunts
Idea: Institutions manipulate price to trigger retail stop losses before reversing direction.
Application: Avoid placing stops at obvious levels (e.g., above/below recent swings). Instead, use wider stops or wait for confirmation.
ICT Killzones + Macros [TakingProphets]The ICT Killzones indicator is a powerful tool designed to visualize key trading sessions and market timing elements used in ICT (Inner Circle Trader) methodology. It includes:
• Session Markers:
- Asia Session
- London Session
- NY AM Session
- NY Lunch Session
- NY PM Session
• Key Price Levels:
- Session high/low levels that extend until violated
- Midnight Open price level (dotted line)
- True Day Open price level (6 PM EST, dotted line)
• ICT Macro Timing:
- First Macro: 9:45 AM - 10:15 AM EST
- Second Macro: 10:45 AM - 11:15 AM EST
- Distinctive L-shaped brackets marking start and end times
Features:
• Fully customizable colors and styles for all elements
• Adjustable label positions and sizes
• Toggle options for each component
• Smart timeframe filtering
• Clean, uncluttered visual design
This indicator helps traders identify key market structure points, session transitions, and optimal trading windows based on ICT concepts.
MTF RSI CandlesThis Pine Script indicator is designed to provide a visual representation of Relative Strength Index (RSI) values across multiple timeframes. It enhances traditional candlestick charts by color-coding candles based on RSI levels, offering a clearer picture of overbought, oversold, and sideways market conditions. Additionally, it displays a hoverable table with RSI values for multiple predefined timeframes.
Key Features
1. Candle Coloring Based on RSI Levels:
Candles are color-coded based on predefined RSI ranges for easy interpretation of market conditions.
RSI Levels:
75-100: Strongest Overbought (Green)
65-75: Stronger Overbought (Dark Green)
55-65: Overbought (Teal)
45-55: Sideways (Gray)
35-45: Oversold (Light Red)
25-35: Stronger Oversold (Dark Red)
0-25: Strongest Oversold (Bright Red)
2. Multi-Timeframe RSI Table:
Displays RSI values for the following timeframes:
1 Min, 2 Min, 3 Min, 4 Min, 5 Min
10 Min, 15 Min, 30 Min, 1 Hour, 1 Day, 1 Week
Helps traders identify RSI trends across different time horizons.
3. Hoverable RSI Values:
Displays the RSI value of any candle when hovering over it, providing additional insights for analysis.
Inputs
1. RSI Length:
Default: 14
Determines the calculation period for the RSI indicator.
2. RSI Levels:
Configurable thresholds for RSI zones:
75-100: Strongest Overbought
65-75: Stronger Overbought
55-65: Overbought
45-55: Sideways
35-45: Oversold
25-35: Stronger Oversold
0-25: Strongest Oversold
How It Works:
1. RSI Calculation:
The RSI is calculated for the current timeframe using the input RSI Length.
It is also computed for 11 additional predefined timeframes using request.security.
2. Candle Coloring:
Candles are colored based on their RSI values and the specified RSI levels.
3. Hoverable RSI Values:
Each candle displays its RSI value when hovered over, via a dynamically created label.
Multi-Timeframe Table:
A table at the bottom-left of the chart displays RSI values for all predefined timeframes, making it easy to compare trends.
Usage:
1. Trend Identification:
Use candle colors to quickly assess market conditions (overbought, oversold, or sideways).
2. Timeframe Analysis:
Compare RSI values across different timeframes to determine long-term and short-term momentum.
3. Signal Confirmation:
Combine RSI signals with other indicators or patterns for higher-confidence trades.
Best Practices
Use this indicator in conjunction with volume analysis, support/resistance levels, or trendline strategies for better results.
Customize RSI levels and timeframes based on your trading strategy or market conditions.
Limitations
RSI is a lagging indicator and may not always predict immediate market reversals.
Multi-timeframe analysis can lead to conflicting signals; consider your trading horizon.
Timed Ranges [mktrader]The Timed Ranges indicator helps visualize price ranges that develop during specific time periods. It's particularly useful for analyzing market behavior in instruments like NASDAQ, S&P 500, and Dow Jones, which often show reactions to sweeps of previous ranges and form reversals.
### Key Features
- Visualizes time-based ranges with customizable lengths (30 minutes, 90 minutes, etc.)
- Tracks high/low range development within specified time periods
- Shows multiple cycles per day for pattern recognition
- Supports historical analysis across multiple days
### Parameters
#### Settings
- **First Cycle (HHMM-HHMM)**: Define the time range of your first cycle. The duration of this range determines the length of all subsequent cycles (e.g., "0930-1000" creates 30-minute cycles)
- **Number of Cycles per Day**: How many consecutive cycles to display after the first cycle (1-20)
- **Maximum Days to Display**: Number of historical days to show the ranges for (1-50)
- **Timezone**: Select the appropriate timezone for your analysis
#### Style
- **Box Transparency**: Adjust the transparency of the range boxes (0-100)
### Usage Example
To track 30-minute ranges starting at market open:
1. Set First Cycle to "0930-1000" (creates 30-minute cycles)
2. Set Number of Cycles to 5 (will show ranges until 11:30)
3. The indicator will display:
- Range development during each 30-minute period
- Visual progression of highs and lows
- Color-coded cycles for easy distinction
### Use Cases
- Identify potential reversal points after range sweeps
- Track regular time-based support and resistance levels
- Analyze market structure within specific time windows
- Monitor range expansions and contractions during key market hours
### Tips
- Use in conjunction with volume analysis for better confirmation
- Pay attention to breaks and sweeps of previous ranges
- Consider market opens and key session times when setting cycles
- Compare range sizes across different time periods for volatility analysis
Thrax - Pullback based short side scalping⯁ This indicator is built for short trades only.
⤞ Pullback based scalping is a strategy where a trader anticipates a pullback and makes a quick scalp in this pullback. This strategy usually works in a ranging market as probability of pullbacks occurrence in ranging market is quite high.
⤞ The strategy is built by first determining a possible candidate price levels having high chance of pullbacks. This is determined by finding out multiple rejection point and creating a zone around this price. A rejection is considered to be valid only if it comes to this zone after going down by a minimum pullback percentage. Once the price has gone down by this minimum pullback percentage multiple times and reaches the zone again chances of pullback goes high and an indication on chart for the same is given.
⯁ Inputs
⤞ Zone-Top : This input parameter determines the upper range for the price zone.
⤞ Zone bottom : This input parameter determines the lower range for price zone.
⤞ Minimum Pullback : This input parameter determines the minimum pullback percentage required for valid rejection. Below is the recommended settings
⤞ Lookback : lookback period before resetting all the variables
⬦Below is the recommended settings across timeframes
⤞ 15-min : lookback – 24, Pullback – 2, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ 5-min : lookback – 50, pullback – 1% - 1.5%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ 1-min : lookback – 100, pullback – 1%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ Anything > 30-min : lookback – 11, pullback – 3%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
✵ This indicator gives early pullback detection which can be used in below ways
1. To take short trades in the pullback.
2. To use this to exit an existing position in the next few candles as pullback may be incoming.
📌 Kindly note, it’s not necessary that pullback will happen at the exact point given on the chart. Instead, the indictor gives you early signals for the pullback
⯁ Trade Steup
1. Wait for pullback signal to occur on the chart.
2. Once the pullback warning has been displayed on the chart, you can either straight away enter the short position or wait for next 2-4 candles for initial sign of actual pullback to occurrence.
3. Once you have initiated short trade, since this is pullback-based strategy, a quick scalp should be made and closed as price may resume it’s original direction. If you have risk appetite you can stay in the trade longer and trial the stops if price keeps pulling back.
4. You can zone top as your stop, usually zone top + some% should be used as stop where ‘some %’ is based on your risk appetite.
5. It’s important to note that this indicator gives early sings of pullback so you may actually wait for 2-3 candles post ‘Pullback warning’ occurs on the chart before entering short trade.
Smart Money Breakouts [iskess 01-02 11:05]This is an big update to the excellent Smart Money Breakout Script published in Oct 2023 by ChartPrime who, to my knowledge, was the original author.
FULL CREDIT GOES TO CHARTPRIME FOR THIS ORIGINAL WORK.
Per the moderator's rules, you will find below a meaningful, detailed self-contained description that does not rely on delegation to the open source code or links to other content. You will find in the description details on what the script does, how it does that, how to use it, and how it is original.
The "Smart Money Breakouts" indicator is designed to identify breakouts based on changes in character (CHOCH) or breaks of structure (BOS) patterns, facilitating automated trading with user-defined Take Profit (TP) level.
The indicator incorporates essential elements such as volume analysis and a data table to assist traders in optimizing their strategies.
🔸Breakout Detection:
The indicator scans price movements for "Change in Character" (CHOCH) and "Break of Structure" (BOS) patterns, signaling potential breakout opportunities in the market.
🔸User-Defined TP/SL :
Traders can customize the Take Profit (TP) and Stop Loss (SL) through the indicator settings, with these levels dynamically calculated based on the Average True Range (ATR). This allows for precise risk management and profit targets that adapt to market volatility. Traders can also select the lookback period for the TP/SL calculations.
🔸Volume Analysis and Trade Direction Specific Analysis:
The indicator includes a volume checker that provides valuable insights into the strength of the breakout, taking into account trade direction.
🔸If the volume label is red and the trade is long, it suggests a higher likelihood of hitting the Stop Loss (SL).
🔸If the volume label is green and the trade is long, it indicates a higher probability of hitting the Take Profit (TP).
🔸For short trades, a red volume label suggests a higher likelihood of hitting TP, while a green label suggests a higher likelihood of hitting SL.
🔸A yellow volume label suggests that the volume is inconclusive, neither favoring bullish nor bearish movements.
🔸Data Table:
The indicator features a data table that keeps track of the number of winning and losing trades for specific timeframes or configurations. It also shows the percentage of profits vs losses, and the overall profit/loss for the selected lookback period.
This table serves as a valuable tool for traders to analyze performance and discover optimal settings and timeframes.
The "Smart Money Breakouts" indicator provides traders with a comprehensive solution for breakout trading, combining technical analysis of changes in character and breaks of structure, volume insights, and performance tracking while dynamically adjusting TP and SL levels based on market volatility through the ATR.
This version of the script is a "significant improvement" from Chart Prime's original work in the following ways:
- A selectable range of candles for the profit/loss calculations to look back on.
- An updated table that includes the percentage of wins/losses, and and overall P&L during the selected lookback range.
- The user can now select only Long trades, Short trades, or both.
- The percentage gain/loss is now indicated for every trade on the chart.
- The user can now select a different multiplier for Stop Loss or Take Profit thresholds.
Volatility IndicatorThe volatility indicator presented here is based on multiple volatility indices that reflect the market’s expectation of future price fluctuations across different asset classes, including equities, commodities, and currencies. These indices serve as valuable tools for traders and analysts seeking to anticipate potential market movements, as volatility is a key factor influencing asset prices and market dynamics (Bollerslev, 1986).
Volatility, defined as the magnitude of price changes, is often regarded as a measure of market uncertainty or risk. Financial markets exhibit periods of heightened volatility that may precede significant price movements, whether upward or downward (Christoffersen, 1998). The indicator presented in this script tracks several key volatility indices, including the VIX (S&P 500), GVZ (Gold), OVX (Crude Oil), and others, to help identify periods of increased uncertainty that could signal potential market turning points.
Volatility Indices and Their Relevance
Volatility indices like the VIX are considered “fear gauges” as they reflect the market’s expectation of future volatility derived from the pricing of options. A rising VIX typically signals increasing investor uncertainty and fear, which often precedes market corrections or significant price movements. In contrast, a falling VIX may suggest complacency or confidence in continued market stability (Whaley, 2000).
The other volatility indices incorporated in the indicator script, such as the GVZ (Gold Volatility Index) and OVX (Oil Volatility Index), capture the market’s perception of volatility in specific asset classes. For instance, GVZ reflects market expectations for volatility in the gold market, which can be influenced by factors such as geopolitical instability, inflation expectations, and changes in investor sentiment toward safe-haven assets. Similarly, OVX tracks the implied volatility of crude oil options, which is a crucial factor for predicting price movements in energy markets, often driven by geopolitical events, OPEC decisions, and supply-demand imbalances (Pindyck, 2004).
Using the Indicator to Identify Market Movements
The volatility indicator alerts traders when specific volatility indices exceed a defined threshold, which may signal a change in market sentiment or an upcoming price movement. These thresholds, set by the user, are typically based on historical levels of volatility that have preceded significant market changes. When a volatility index exceeds this threshold, it suggests that market participants expect greater uncertainty, which often correlates with increased price volatility and the possibility of a trend reversal.
For example, if the VIX exceeds a pre-determined level (e.g., 30), it could indicate that investors are anticipating heightened volatility in the equity markets, potentially signaling a downturn or correction in the broader market. On the other hand, if the OVX rises significantly, it could point to an upcoming sharp movement in crude oil prices, driven by changing market expectations about supply, demand, or geopolitical risks (Geman, 2005).
Practical Application
To effectively use this volatility indicator in market analysis, traders should monitor the alert signals generated when any of the volatility indices surpass their thresholds. This can be used to identify periods of market uncertainty or potential market turning points across different sectors, including equities, commodities, and currencies. The indicator can help traders prepare for increased price movements, adjust their risk management strategies, or even take advantage of anticipated price swings through options trading or volatility-based strategies (Black & Scholes, 1973).
Traders may also use this indicator in conjunction with other technical analysis tools to validate the potential for significant market movements. For example, if the VIX exceeds its threshold and the market is simultaneously approaching a critical technical support or resistance level, the trader might consider entering a position that capitalizes on the anticipated price breakout or reversal.
Conclusion
This volatility indicator is a robust tool for identifying market conditions that are conducive to significant price movements. By tracking the behavior of key volatility indices, traders can gain insights into the market’s expectations of future price fluctuations, enabling them to make more informed decisions regarding market entries and exits. Understanding and monitoring volatility can be particularly valuable during times of heightened uncertainty, as changes in volatility often precede substantial shifts in market direction (French et al., 1987).
References
• Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Christoffersen, P. F. (1998). Evaluating Interval Forecasts. International Economic Review, 39(4), 841-862.
• Whaley, R. E. (2000). Derivatives on Market Volatility. Journal of Derivatives, 7(4), 71-82.
• Pindyck, R. S. (2004). Volatility and the Pricing of Commodity Derivatives. Journal of Futures Markets, 24(11), 973-987.
• Geman, H. (2005). Commodities and Commodity Derivatives: Modeling and Pricing for Agriculturals, Metals and Energy. John Wiley & Sons.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
• French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987). Expected Stock Returns and Volatility. Journal of Financial Economics, 19(1), 3-29.
Ahtep 11
Here’s a brief description for your indicator:
Custom FCPO Indicator with Buy/Sell Signals
This custom indicator combines multiple technical analysis tools to generate buy and sell signals for FCPO trading. It uses two exponential moving averages (EMA) to identify market trends, Stochastic RSI for momentum analysis, and volume thresholds to filter signals. When the short EMA crosses above the long EMA with oversold conditions on the Stochastic RSI and high volume, a buy signal is triggered. Conversely, a sell signal is generated when the short EMA crosses below the long EMA with overbought conditions on the Stochastic RSI and high volume. The indicator also provides entry, stop loss, and target levels based on the market conditions.
Feel free to modify or expand this description based on your needs! Let me know if you'd like to make any adjustments.
Uptrick: Volatility Reversion BandsUptrick: Volatility Reversion Bands is an indicator designed to help traders identify potential reversal points in the market by combining volatility and momentum analysis within one comprehensive framework. It calculates dynamic bands around a simple moving average and issues signals when price interacts with these bands. Below is a fully expanded description, structured in multiple sections, detailing originality, usefulness, uniqueness, and the purpose behind blending standard deviation-based and ATR-based concepts. All references to code have been removed to focus on the written explanation only.
Section 1: Overview
Uptrick: Volatility Reversion Bands centers on a moving average around which various bands are constructed. These bands respond to changes in price volatility and can help gauge potential overbought or oversold conditions. Signals occur when the price moves beyond certain thresholds, which may imply a reversal or significant momentum shift.
Section 2: Originality, Usefulness, Uniqness, Purpose
This indicator merges two distinct volatility measurements—Bollinger Bands and ATR—into one cohesive system. Bollinger Bands use standard deviation around a moving average, offering a baseline for what is statistically “normal” price movement relative to a recent mean. When price hovers near the upper band, it may indicate overbought conditions, whereas price near the lower band suggests oversold conditions. This straightforward construction often proves invaluable in moderate-volatility settings, as it pinpoints likely turning points and gauges a market’s typical trading range.
Yet Bollinger Bands alone can falter in conditions marked by abrupt volatility spikes or sudden gaps that deviate from recent norms. Intraday news, earnings releases, or macroeconomic data can alter market behavior so swiftly that standard-deviation bands do not keep pace. This is where ATR (Average True Range) adds an important layer. ATR tracks recent highs, lows, and potential gaps to produce a dynamic gauge of how much price is truly moving from bar to bar. In quieter times, ATR contracts, reflecting subdued market activity. In fast-moving markets, ATR expands, exposing heightened volatility on each new bar.
By overlaying Bollinger Bands and ATR-based calculations, the indicator achieves a broader situational awareness. Bollinger Bands excel at highlighting relative overbought or oversold areas tied to an established average. ATR simultaneously scales up or down based on real-time market swings, signaling whether conditions are calm or turbulent. When combined, this means a price that barely crosses the Bollinger Band but also triggers a high ATR-based threshold is likely experiencing a volatility surge that goes beyond typical market fluctuations. Conversely, a price breach of a Bollinger Band when ATR remains low may still warrant attention, but not necessarily the same urgency as in a high-volatility regime.
The resulting synergy offers balanced, context-rich signals. In a strong trend, the ATR layer helps confirm whether an apparent price breakout really has momentum or if it is just a temporary spike. In a range-bound market, standard deviation-based Bollinger Bands define normal price extremes, while ATR-based extensions highlight whether a breakout attempt has genuine force behind it. Traders gain clarity on when a move is both statistically unusual and accompanied by real volatility expansion, thus carrying a higher probability of a directional follow-through or eventual reversion.
Practical advantages emerge across timeframes. Scalpers in fast-paced markets appreciate how ATR-based thresholds update rapidly, revealing if a sudden price push is routine or exceptional. Swing traders can rely on both indicators to filter out false signals in stable conditions or identify truly notable moves. By calibrating to changes in volatility, the merged system adapts naturally whether the market is trending, ranging, or transitioning between these phases.
In summary, combining Bollinger Bands (for a static sense of standard-deviation-based overbought/oversold zones) with ATR (for a dynamic read on current volatility) yields an adaptive, intuitive indicator. Traders can better distinguish fleeting noise from meaningful expansions, enabling more informed entries, exits, and risk management. Instead of relying on a single yardstick for all market conditions, this fusion provides a layered perspective, encouraging traders to interpret price moves in the broader context of changing volatility.
Section 3: Why Bollinger Bands and ATR are combined
Bollinger Bands provide a static snapshot of volatility by computing a standard deviation range above and below a central average. ATR, on the other hand, adapts in real time to expansions or contractions in market volatility. When combined, these measures offset each other’s limitations: Bollinger Bands add structure (overbought and oversold references), and ATR ensures responsiveness to rapid price shifts. This synergy helps reduce noisy signals, particularly during sudden market turbulence or extended consolidations.
Section 4: User Inputs
Traders can adjust several parameters to suit their preferences and strategies. These typically include:
1. Lookback length for calculating the moving average and standard deviation.
2. Multipliers to control the width of Bollinger Bands.
3. An ATR multiplier to set the distance for additional reversal bands.
4. An option to display weaker signals when the price merely approaches but does not cross the outer bands.
Section 5: Main Calculations
At the core of this indicator are four important steps:
1. Calculate a basis using a simple moving average.
2. Derive Bollinger Bands by adding and subtracting a product of the standard deviation and a user-defined multiplier.
3. Compute ATR over the same lookback period and multiply it by the selected factor.
4. Combine ATR-based distance with the Bollinger Bands to set the outer reversal bands, which serve as stronger signal thresholds.
Section 6: Signal Generation
The script interprets meaningful reversal points when the price:
1. Crosses below the lower outer band, potentially highlighting oversold conditions where a bullish reversal may occur.
2. Crosses above the upper outer band, potentially indicating overbought conditions where a bearish reversal may develop.
Section 7: Visualization
The indicator provides visual clarity through labeled signals and color-coded references:
1. Distinct colors for upper and lower reversal bands.
2. Markers that appear above or below bars to denote possible buying or selling signals.
3. A gradient bar color scheme indicating a bar’s position between the lower and upper bands, helping traders quickly see if the price is near either extreme.
Section 8: Weak Signals (Optional)
For those preferring early cues, the script can highlight areas where the price nears the outer bands. When weak signals are enabled:
1. Bars closer to the upper reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential selling area.
2. Bars closer to the lower reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential buying area.
Section 9: Simplicity, Effectiveness, and Lower Timeframes
Although combining standard deviation and ATR involves sophisticated volatility concepts, this indicator is visually straightforward. Reversal bands and gradient-colored bars make it easy to see at a glance when price approaches or crosses a threshold. Day traders operating on lower timeframes benefit from such clarity because it helps filter out minor fluctuations and focus on more meaningful signals.
Section 10: Adaptability across Market Phases
Because both the standard deviation (for Bollinger Bands) and ATR adapt to changing volatility, the indicator naturally adjusts to various environments:
1. Trending: The additional ATR-based outer bands help distinguish between temporary pullbacks and deeper reversals.
2. Ranging: Bollinger Bands often remain narrower, identifying smaller reversals, while the outer ATR bands remain relatively close to the main bands.
Section 11: Reduced Noise in High-Volatility Scenarios
By factoring ATR into the band calculations, the script widens or narrows the thresholds during rapid market fluctuations. This reduces the amount of false triggers typically found in indicators that rely solely on fixed calculations, preventing overreactions to abrupt but short-lived price spikes.
Section 12: Incorporation with Other Technical Tools
Many traders combine this indicator with oscillators such as RSI, MACD, or Stochastic, as well as volume metrics. Overbought or oversold signals in momentum oscillators can provide additional confirmation when price reaches the outer bands, while volume spikes may reinforce the significance of a breakout or potential reversal.
Section 13: Risk Management Considerations
All trading strategies carry risk. This indicator, like any tool, can and does produce losing trades if price unexpectedly reverses again or if broader market conditions shift rapidly. Prudent traders employ protective measures:
1. Stop-loss orders or trailing stops.
2. Position sizing that accounts for market volatility.
3. Diversification across different asset classes when possible.
Section 14: Overbought and Oversold Identification
Standard Bollinger Bands highlight regions where price might be overextended relative to its recent average. The extended ATR-based reversal bands serve as secondary lines of defense, identifying moments when price truly stretches beyond typical volatility bounds.
Section 15: Parameter Customization for Different Needs
Users can tailor the script to their unique preferences:
1. Shorter lookback settings yield faster signals but risk more noise.
2. Higher multipliers spread the bands further apart, filtering out small moves but generating fewer signals.
3. Longer lookback periods smooth out market noise, often leading to more stable but less frequent trading cues.
Section 16: Examples of Different Trading Styles
1. Day Traders: Often reduce the length to capture quick price swings.
2. Swing Traders: May use moderate lengths such as 20 to 50 bars.
3. Position Traders: Might opt for significantly longer settings to detect macro-level reversals.
Section 17: Performance Limitations and Reality Check
No technical indicator is free from false signals. Sudden fundamental news events, extreme sentiment changes, or low-liquidity conditions can render signals less reliable. Backtesting and forward-testing remain essential steps to gauge whether the indicator aligns well with a trader’s timeframe, risk tolerance, and instrument of choice.
Section 18: Merging Volatility and Momentum
A critical uniqueness of this indicator lies in how it merges Bollinger Bands (standard deviation-based) with ATR (pure volatility measure). Bollinger Bands provide a relative measure of price extremes, while ATR dynamically reacts to market expansions and contractions. Together, they offer an enhanced perspective on potential market turns, ideally reducing random noise and highlighting moments where price has traveled beyond typical bounds.
Section 19: Purpose of this Merger
The fundamental purpose behind blending standard deviation measures with real-time volatility data is to accommodate different market behaviors. Static standard deviation alone can underreact or overreact in abnormally volatile conditions. ATR alone lacks a baseline reference to normality. By merging them, the indicator aims to provide:
1. A versatile dynamic range for both typical and extreme moves.
2. A filter against frequent whipsaws, especially in choppy environments.
3. A visual framework that novices and experts can interpret rapidly.
Section 20: Summary and Practical Tips
Uptrick: Volatility Reversion Bands offers a powerful tool for traders looking to combine volatility-based signals with momentum-derived reversals. It emphasizes clarity through color-coded bars, defined reversal zones, and optional weak signal markers. While potentially useful across all major timeframes, it demands ongoing risk management, realistic expectations, and careful study of how signals behave under different market conditions. No indicator serves as a crystal ball, so integrating this script into an overall strategy—possibly alongside volume data, fundamentals, or momentum oscillators—often yields the best results.
Disclaimer and Educational Use
This script is intended for educational and informational purposes. It does not constitute financial advice, nor does it guarantee trading success. Sudden economic events, low-liquidity times, and unexpected market behaviors can all undermine technical signals. Traders should use proper testing procedures (backtesting and forward-testing) and maintain disciplined risk management measures.
Binary Options Pro Helper By Himanshu AgnihotryThe Binary Options Pro Helper is a custom indicator designed specifically for one-minute binary options trading. This tool combines technical analysis methods like moving averages, RSI, Bollinger Bands, and pattern recognition to provide precise Buy and Sell signals. It also includes a time-based filter to ensure trades are executed only during optimal market conditions.
Features:
Moving Averages (EMA):
Uses short-term (7-period) and long-term (21-period) EMA crossovers for trend detection.
RSI-Based Signals:
Identifies overbought/oversold conditions for entry points.
Bollinger Bands:
Highlights market volatility and potential reversal zones.
Chart Pattern Recognition:
Detects double tops (sell signals) and double bottoms (buy signals).
Time-Based Filter:
Trades only within specified hours (e.g., 9:30 AM to 11:30 AM) to avoid unnecessary noise.
Visual Signals:
Plots buy and sell markers directly on the chart for ease of use.
How to Use:
Setup:
Add this script to your TradingView chart and select a 1-minute timeframe.
Signal Interpretation:
Buy Signal: Triggered when EMA crossover occurs, RSI is oversold (<30), and a double bottom pattern is detected.
Sell Signal: Triggered when EMA crossover occurs, RSI is overbought (>70), and a double top pattern is detected.
Timing:
Ensure trades are executed only during the specified time window for better accuracy.
Best Practices:
Use this indicator alongside fundamental analysis or market sentiment.
Test it thoroughly with historical data (backtesting) and in a demo account before live trading.
Adjust parameters (e.g., EMA periods, RSI thresholds) based on your trading style.
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
[w3ss1] Timeframe SyncThe "Timeframe Sync" indicator provides a comprehensive view of price action across multiple timeframes for a single symbol, allowing traders to analyze market conditions from a multi-timeframe perspective with ease.
Key Features:
Flexible Symbol Selection: Choose between analyzing the symbol of the current chart or select another symbol to monitor.
Customizable Timeframes: Control which timeframes you want to analyze through toggle switches. Choose from 11 different timeframes ranging from 1-minute to Monthly charts, with the ability to customize each one:
1m, 5m, 15m, 30m, 1H, 4H, 8H, 12H, 1D, 1W, 1M
Visual Feedback:
-Candle Close Color: Each timeframe's last closed candle is color-coded. Bullish closes are highlighted in green, bearish in dark shades, and inside candles in orange.
-Bias Indicator: The indicator shows whether the close is "above", "below", or "inside" the previous candle's high/low range, providing insight into the market's momentum.
Table Display: Information is presented in a clear table format:
-The first row shows the symbol being analyzed.
-The second row displays "Candle close" to indicate the relevance of the information below.
-Each subsequent row represents a different timeframe, showing its abbreviation and the bias of the last close.
Conditional Display: Timeframes are only shown if they are relevant to the current chart's timeframe. This ensures that you're not looking at outdated data when on lower timeframes.
Customization:
-Adjust text size, table position, background color, text color, and colors for different candle close scenarios.
Usage:
Ideal for traders who need a quick multi-timeframe analysis without switching charts.
Helps in confirming short-term moves with longer-term trends or spotting divergences across timeframes.
Instructions:
Add the indicator to your chart.
Customize the timeframes you wish to monitor via the toggle switches.
Optionally, select a different symbol if not analyzing the current chart's symbol.
Adjust colors and table settings to your preference.
Observe how price action behaves across different timeframes to make informed trading decisions.
BK MA Horizontal Lines
Indicator Description:
I am incredibly proud and excited to share my first indicator with the TradingView community! This tool has been instrumental in helping me optimize my positioning and maximize my trades.
Moving Averages (MAs) are among the top three most crucial indicators for trading, and I believe that the Daily, Weekly, and Monthly MAs are especially critical. The way I’ve designed this indicator allows you to combine MAs from your Daily timeframe with one or two from the Weekly or Monthly timeframes, depending on what is most relevant for the specific product or timeframe you’re analyzing.
For optimal use, I recommend:
Spacing your chart about 11 spaces from the right side.
Setting the Labels at 10 in the indicator configuration.
Keeping the line thickness at size 1, while using size 2 for my other indicator, "BK BB Horizontal Lines", which follows a similar concept but applies to Bollinger Bands.
If you find success with this indicator, I kindly ask that you give back in some way through acts of philanthropy, helping others in the best way you see fit.
Good luck to everyone, and always remember: God gives us everything. May all the glory go to the Almighty!
ATT + Key Levels with SessionsKey Features:
ATT Turning Point Numbers:
This input allows the user to define specific numbers (e.g., "3,11,17,29,41,47,53,59") that mark turning points in price action, which are checked using the bar_index modulo 60. If the current bar index matches one of these turning points, it triggers potential buy or sell signals.
RSI (Relative Strength Index):
The RSI is calculated based on a user-defined period (rsi_period), typically 14, and used to indicate overbought or oversold conditions. The script defines overbought (70) and oversold (30) levels, which are used to filter buy or sell signals.
Session Times:
The script includes predefined session times for major trading markets:
New York: From 9:30 AM EST to 4:00 PM EST.
London: From 8:00 AM GMT to 4:30 PM GMT.
Asia: From 12:00 AM GMT to 9:00 AM GMT.
These session times are used to restrict the buy and sell signals to specific market sessions.
Key Levels:
The script calculates and plots key market levels for the current day and week:
Daily High and Low: The highest and lowest prices of the current day.
Weekly High and Low: The highest and lowest prices of the current week.
These levels are plotted with different colors for visual reference.
Signal Logic:
Buy Signal: Triggered when the current bar is a turning point (according to the ATT model), the RSI is below the oversold threshold, and the current time is within the active session times (New York, London, or Asia).
Sell Signal: Triggered when the current bar is a turning point, the RSI is above the overbought threshold, and the current time is within the active session times.
Signal Limitations:
A user-defined limit (max_signals_per_session) controls the maximum number of signals that can be plotted within each session. This prevents excessive signal generation.
Plotting and Background Highlights:
Buy and Sell Signals: The script plots shapes (labels) above or below the bars to indicate buy or sell signals when the conditions are met.
Background Highlight: The background color is highlighted in yellow when the current bar matches one of the defined ATT turning points.
In Summary:
The indicator combines multiple technical factors to generate trading signals:
Turning points in price action (based on custom ATT numbers),
RSI levels (overbought/oversold),
Market session times (New York, London, Asia),
Key price levels (daily and weekly highs and lows).
This combination helps traders identify potential buying and selling opportunities while considering broader market dynamics and limiting the number of signals during each session.
