RSI Crossover dipali parikhThis script generates buy and sell signals based on the crossover of the Relative Strength Index (RSI) and the RSI-based Exponential Moving Average (EMA). It also includes an additional condition for both buy and sell signals that the RSI-based EMA must be either above or below 50.
Key Features:
Buy Signal: Triggered when:
The RSI crosses above the RSI-based EMA.
The RSI-based EMA is above 50.
A green "BUY" label will appear below the bar when the buy condition is met.
Sell Signal: Triggered when:
The RSI crosses below the RSI-based EMA.
The RSI-based EMA is below 50.
A red "SELL" label will appear above the bar when the sell condition is met.
Customizable Inputs:
RSI Length: Adjust the period for calculating the RSI (default is 14).
RSI-based EMA Length: Adjust the period for calculating the RSI-based EMA (default is 9).
RSI Threshold: Adjust the threshold (default is 50) for when the RSI-based EMA must be above or below.
Visuals:
The RSI is plotted as a blue line.
The RSI-based EMA is plotted as an orange line.
Buy and sell signals are indicated by green "BUY" and red "SELL" labels.
Alerts:
Alerts can be set for both buy and sell conditions to notify you when either condition is met.
How to Use:
Use this script to identify potential buy and sell opportunities based on the behavior of the RSI relative to its EMA.
The buy condition indicates when the RSI is strengthening above its EMA, and the sell condition signals when the RSI is weakening below its EMA.
Strategy Use:
Ideal for traders looking to leverage RSI momentum for entering and exiting positions.
The RSI-based EMA filter helps smooth out price fluctuations, focusing on stronger signals.
This script is designed for both discretionary and algorithmic traders, offering a simple yet effective method for spotting trend reversals and continuation opportunities using RSI.
Göstergeler ve stratejiler
Machine Learning SupertrendThe Machine Learning Supertrend is an advanced trend-following indicator that enhances the traditional Supertrend with Gaussian Process Regression (GPR) and kernel-based learning. Unlike conventional methods that rely purely on historical ATR values, this indicator integrates machine learning techniques to dynamically estimate volatility and forecast future price movements, resulting in a more adaptive and robust trend detection system.
At the core of this indicator lies Gaussian Process Regression (GPR), which utilizes a Radial Basis Function (RBF) kernel to model price distributions and anticipate future trends. Instead of simply looking at past price action, it constructs a kernel matrix, enabling a probabilistic approach to price forecasting. This allows the indicator to not only detect current trends but also project potential trend reversals with greater accuracy.
By applying machine learning to ATR estimation, the ML Supertrend dynamically adjusts its thresholds based on predicted values rather than a fixed multiplier. This makes the trend signals more responsive to market conditions, reducing false signals and minimizing whipsaws often seen with traditional Supertrend indicators. The upper and lower bands are no longer static but evolve based on the underlying price structure, improving the reliability of trend shifts.
When the price crosses these adaptive levels, the indicator detects a trend change and plots it accordingly. Green signifies a bullish trend, while red indicates a bearish one. Alerts can also be triggered when the trend shifts, allowing traders to react quickly to potential reversals.
What makes this approach powerful is its ability to adapt to different market conditions. Traditional ATR-based methods use fixed parameters that might not always be optimal, whereas this ML-driven Supertrend continuously refines its estimations based on real-time data. The result is a more intelligent, less lagging, and highly adaptive trend-following tool.
This indicator is particularly useful for traders looking to enhance trend-following strategies with AI-driven insights. It reduces noise, improves signal reliability, and even offers a degree of trend forecasting, making it ideal for those who want a more advanced and dynamic alternative to standard Supertrend indicators.
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, and past performance is not indicative of future results. Trading involves risk, and users should conduct their own research and use proper risk management before making investment decisions.
200-Week EMA % Difference200-Week EMA Percentage Difference Indicator – Understanding Market Stretch & Reversion
What This Indicator Does
Even if an individual stock is delivering strong earnings and solid fundamentals, it is still influenced by overall market sentiment. When the broader market begins reverting to its long-term mean, stocks—no matter how strong—are often pulled down along with it. Unrealized gains can erode if one ignores these macro movements.
The 200-Week EMA Percentage Difference indicator measures how far the price of an asset or index has moved away from its 200-week Exponential Moving Average (EMA) in percentage terms. This provides a reliable gauge of whether the market is overstretched (overbought) or pulling back to support (oversold) relative to a long-term trend.
How It Helps Investors
Identifying Market Extremes:
When the indicator moves into the 50-80% range, historical trends show that broad-based indices like BSE Smallcap, Nifty 500, Nifty Microcap, and Nifty Smallcap 250 have often experienced corrections.
This suggests that the market may be overextended, and investors should exercise caution.
Spotting Support Zones:
Past data indicates that when the percentage difference falls back to around 30%, the market often finds a new support level, leading to fresh buying opportunities.
This can help long-term investors identify favorable entry points.
Mean Reversion & Market Cycles:
The indicator essentially measures how far these indices have stretched from their long-term mean (200-week EMA).
Extreme deviations from the EMA often result in mean reversion, where prices eventually return to more sustainable levels.
How to Use It in Broad-Based Indices
Above 50-80% → Caution Zone: Historically associated with market tops or overheated conditions.
Around 30% → Support Zone: A potential level where corrections stabilize and new market uptrends begin.
By applying this indicator to indices like BSE Smallcap, Nifty 500, Nifty Microcap, and Nifty Smallcap 250, investors can gauge market strength, anticipate corrections, and position themselves strategically for long-term opportunities.
NDTECH Tool-N1CPR (Central Pivot Range) is a popular trading indicator used in technical analysis to identify potential support and resistance levels. It is based on the concept of pivot points, which are calculated using the high, low, and close prices of the previous trading session. The CPR indicator provides three key levels: the Central Pivot (P), the Bottom Central Pivot (BC), and the Top Central Pivot (TC).
Key Components of CPR:
Central Pivot (P): This is the primary level and is calculated as the average of the high, low, and close prices of the previous session.
P=High+Low+Close3
P=3High+Low+Close
Bottom Central Pivot (BC): This level acts as a support level and is calculated as the average of the Central Pivot and the low of the previous session.
BC=P+Low2
BC=2P+Low
Top Central Pivot (TC): This level acts as a resistance level and is calculated as the average of the Central Pivot and the high of the previous session.
TC=P+High2
TC=2P+High
Explanation:
request.security: This function is used to fetch the high, low, and close prices of the previous day. The "D" parameter specifies the daily timeframe.
plot: This function is used to plot the CPR levels on the chart.
fill: This function is used to highlight the area between the BC and TC levels, providing a visual representation of the CPR range.
Usage:
Support and Resistance: Traders use the CPR levels to identify potential support (BC) and resistance (TC) levels. Price action around these levels can provide insights into market sentiment.
Trend Identification: If the price is consistently above the Central Pivot (P), it may indicate a bullish trend, while prices below P may indicate a bearish trend.
Breakout Trading: Breakouts above TC or below BC can signal potential trading opportunities.
Conclusion:
The CPR indicator is a versatile tool that can be used in various trading strategies. By implementing it in Pine Script, traders can customize and automate their analysis on the TradingView platform, making it easier to identify key levels and make informed trading decisions.
Delta SMA 1-Year High/Low Strategy### Summary:
This Pine Script code implements a trading strategy based on the **Delta SMA (Simple Moving Average)** of buy and sell volumes over a 1-year lookback period. The strategy identifies potential buy and sell signals by analyzing the relationship between the Delta SMA and its historical high/low thresholds. Key features include:
1. **Delta Calculation**:
- The Delta is calculated as the difference between buy volume (when close > open) and sell volume (when close < open).
- A 14-period SMA is applied to the Delta to smooth the data.
2. **1-Year High/Low Thresholds**:
- The strategy calculates the 1-year high and low of the Delta SMA.
- Buy and sell conditions are derived from thresholds set at 70% of the 1-year low and 90% and 50% of the 1-year high, respectively.
3. **Buy Condition**:
- A buy signal is triggered when the Delta SMA crosses above 0 after being below 70% of the 1-year low.
4. **Sell Condition**:
- A sell signal is triggered when the Delta SMA drops below 60% of the 1-year high after crossing above 90% of the 1-year high.
5. **Visualization**:
- The Delta SMA and its thresholds are plotted on the chart for easy monitoring.
- Optional buy/sell signals can be plotted as labels on the chart.
This strategy is designed to capture trends in volume-based momentum over a long-term horizon, making it suitable for swing or position trading.
High-Low Breakout Strategy with ATR traling Stop LossThis script is a TradingView Pine Script strategy that implements a High-Low Breakout Strategy with ATR Trailing Stop.created by SK WEALTH GURU, Here’s a breakdown of its key components:
Features and Functionality
Custom Timeframe and High-Low Detection
Allows users to select a custom timeframe (default: 30 minutes) to detect high and low levels.
Tracks the high and low within a user-specified period (e.g., first 30 minutes of the session).
Draws horizontal lines for high and low, persisting for a specified number of days.
Trade Entry Conditions
Long Entry: If the closing price crosses above the recorded high.
Short Entry: If the closing price crosses below the recorded low.
The user can choose to trade Long, Short, or Both.
ATR-Based Trailing Stop & Risk Management
Uses Average True Range (ATR) with a multiplier (default: 3.5) to determine a dynamic trailing stop-loss.
Trades reset daily, ensuring a fresh start each day.
Trade Execution and Partial Profit Taking
Stop-loss: Default at 1% of entry price.
Partial profit: Books 50% of the position at 3% profit.
Max 2 trades per day: If the first trade hits stop-loss, the strategy allows one re-entry.
Intraday Exit Condition
All positions close at 3:15 PM to ensure no overnight risk.
Ultimate Stochastics Strategy by NHBprod Use to Day Trade BTCHey All!
Here's a new script I worked on that's super simple but at the same time useful. Check out the backtest results. The backtest results include slippage and fees/commission, and is still quite profitable. Obviously the profitability magnitude depends on how much capital you begin with, and how much the user utilizes per order, but in any event it seems to be profitable according to backtests.
This is different because it allows you full functionality over the stochastics calculations which is designed for random datasets. This script allows you to:
Designate ANY period of time to analyze and study
Choose between Long trading, short trading, and Long & Short trading
It allows you to enter trades based on the stochastics calculations
It allows you to EXIT trades using the stochastics calculations or take profit, or stop loss, Or any combination of those, which is nice because then the user can see how one variable effects the overall performance.
As for the actual stochastics formula, you get control, and get to SEE the plot lines for slow K, slow D, and fast K, which is usually not considered.
You also get the chance to modify the smoothing method, which has not been done with regular stochastics indicators. You get to choose the standard simple moving average (SMA) method, but I also allow you to choose other MA's such as the HMA and WMA.
Lastly, the user gets the option of using a custom trade extender, which essentially allows a buy or sell signal to exist for X amount of candles after the initial signal. For example, you can use "max bars since signal" to 1, and this will allow the indicator to produce an extra sequential buy signal when a buy signal is generated. This can be useful because it is possible that you use a small take profit (TP) and quickly exit a profitable trade. With the max bars since signal variable, you're able to reenter on the next candle and allow for another opportunity.
Let me know if you have any questions! Please take a look at the performance report and let me know your thoughts! :)
Overnight vs Intra-day Performance█ STRATEGY OVERVIEW
The "Overnight vs Intra-day Performance" indicator quantifies price behaviour differences between trading hours and overnight periods. It calculates cumulative returns, compound growth rates, and visualizes performance components across user-defined time windows. Designed for analytical use, it helps identify whether returns are primarily generated during market hours or overnight sessions.
█ USAGE
Use this indicator on Stocks and ETFs to visualise and compare intra-day vs overnight performance
█ KEY FEATURES
Return Segmentation : Separates total returns into overnight (close-to-open) and intraday (open-to-close) components
Growth Tracking : Shows simple cumulative returns and compound annual growth rates (CAGR)
█ VISUALIZATION SYSTEM
1. Time-Series
Overnight Returns (Red)
Intraday Returns (Blue)
Total Returns (White)
2. Summary Table
Displays CAGR
3. Price Chart Labels
Floating annotations showing absolute returns and CAGR
Color-coded to match plot series
█ PURPOSE
Quantify market behaviour disparities between active trading sessions and overnight positioning
Provide institutional-grade attribution analysis for returns generation
Enable tactical adjustment of trading schedules based on historical performance patterns
Serve as foundational research for session-specific trading strategies
█ IDEAL USERS
1. Portfolio Managers
Analyse overnight risk exposure across holdings
Optimize execution timing based on return distributions
2. Quantitative Researchers
Study market microstructure through time-segmented returns
Develop alpha models leveraging session-specific anomalies
3. Market Microstructure Analysts
Identify liquidity patterns in overnight vs daytime sessions
Research ETF premium/discount mechanics
4. Day Traders
Align trading hours with highest probability return windows
Avoid overnight gaps through informed position sizing
Johnny's Volatility-Driven Trend Identifier w/ Reversal SignalsJohnny's Volatility-Driven Trend Identifier w/ Reversal Signals is designed to identify high-probability trend shifts and reversals by incorporating volatility, momentum, and impulse-based filtering. It is specifically built for traders who want to capture strong trend movements while minimizing false signals caused by low volatility noise.
By leveraging Rate of Change (ROC), Relative Strength Index (RSI), and Average True Range (ATR)-based volatility detection, the indicator dynamically adapts to market conditions. It highlights breakout trends, reversals, and early signs of momentum shifts using strategically placed labels and color-coded trend visualization.
Inspiration taken from Top G indicator .
What This Indicator Does
The Volatility-Driven Trend Identifier works by:
Measuring Market Extremes & Momentum:
Uses ROC normalization with standard deviation to identify impulse moves in price action.
Implements RSI filtering to determine overbought/oversold conditions that validate trend strength.
Utilizes ATR-based volatility tracking to ensure signals only appear when meaningful market movements are occurring.
Identifying Key Trend Events:
Power Peak (🔥): Marks a confirmed strong downtrend, ideal for shorting opportunities.
Surge (🚀): Indicates a confirmed strong uptrend, signaling a potential long entry.
Soft Surge (↗): Highlights a mild bullish reentry or early uptrend formation.
Soft Peak (↘): Shows a mild bearish reentry or early downtrend formation.
Providing Adaptive Filtering for Reliable Signals:
Filters out weak trends with a volatility check, ensuring signals appear only in strong market conditions.
Implements multi-level confirmation by combining trend strength metrics, preventing false breakouts.
Uses gradient-based visualization to color-code market sentiment for quick interpretation.
What This Indicator Signals
Breakouts & Impulse Moves: 🚀🔥
The Surge (🚀) and Power Peak (🔥) labels indicate confirmed momentum breakouts, where the trend has been validated by a combination of ROC impulse, RSI confirmation, and ATR volatility filtering.
These signals suggest that the market is entering a strong trend, and traders can align their entries accordingly.
Early Trend Formation & Reentries: ↗ ↘
The Soft Surge (↗) and Soft Peak (↘) labels indicate areas where a trend might be forming, but is not yet fully confirmed.
These signals help traders anticipate potential entries before the trend gains full strength.
Volatility-Adaptive Trend Filtering: 📊
Since the indicator only activates in volatile conditions, it avoids the pitfalls of low-range choppy markets where false signals frequently occur.
ATR-driven adaptive windowing allows the indicator to dynamically adjust its sensitivity based on real-time volatility conditions.
How to Use This Indicator
1. Identifying High-Probability Entries
Bullish Entries (Long Trades)
Look for 🚀 Surge signals in an uptrend.
Confirm with RSI (should be above 50 for momentum).
Ensure volatility is increasing to validate the breakout.
Use ↗ Soft Surge signals for early entries before the trend fully confirms.
Bearish Entries (Short Trades)
Look for 🔥 Power Peak signals in a downtrend.
RSI should be below 50, indicating downward momentum.
Volatility should be rising, ensuring market momentum is strong.
Use ↘ Soft Peak signals for early entries before a full bearish confirmation.
2. Avoiding False Signals
Ignore signals when the market is ranging (low ATR).
Check RSI and ROC alignment to ensure trend confirmation.
Use additional confluences (e.g., price action, support/resistance levels, moving averages) for enhanced accuracy.
3. Trend Confirmation & Filtering
The stronger the trend, the higher the likelihood that Surge (🚀) and Power Peak (🔥) signals will continue in their direction.
Soft Surge (↗) and Soft Peak (↘) act as early warning signals before major breakouts occur.
What Makes This a Machine Learning-Inspired Moving Average?
While this indicator is not a direct implementation of machine learning (as Pine Script lacks AI/ML capabilities), it mimics machine learning principles by adapting dynamically to market conditions using the following techniques:
Adaptive Trend Selection:
It does not rely on fixed moving averages but instead adapts dynamically based on volatility expansion and momentum detection.
ATR-based filtering adjusts the indicator’s sensitivity to real-time conditions.
Multi-Factor Confirmation (Feature Engineering Equivalent in ML):
Combines ROC, RSI, and ATR in a structured way, similar to how ML models use multiple inputs to filter and classify data.
Implements conditional trend recognition, ensuring that only valid signals pass through the filter.
Noise Reduction with Data Smoothing:
The algorithm avoids false signals by incorporating trend intensity thresholds, much like how ML models remove outliers to refine predictions.
Adaptive filtering ensures that low-volatility environments do not produce misleading signals.
Why Use This Indicator?
✔ Reduces False Signals: Multi-factor validation ensures only high-confidence signals are triggered.
✔ Works in All Market Conditions: Volatility-adaptive nature allows the indicator to perform well in both trending and ranging markets.
✔ Great for Swing & Intraday Trading: It helps spot momentum shifts early and allows traders to catch major market moves before they fully develop.
✔ Visually Intuitive: Color-coded trends and clear signal markers make it easy to interpret.
Average Candle Size (Points)ATR but with the ability to add threshold lines (UP TO 3) that help gauge how volatile the market is. Also, note that the default threshold values are set up for NQ Futures so you will need to change your values to your specific needs.
High/Low LabelsThis simple Version 6 script labels each bar on the chart with Green labels noting HH for higher highs and HL for higher lows. And Red labels noting LH for lower highs and LL for lower lows. Works on any Trading View chart and any time frame. Any comments or suggestions, please do!
Gold Pro StrategyHere’s the strategy description in a chat format:
---
**Gold (XAU/USD) Trend-Following Strategy**
This **trend-following strategy** is designed for trading gold (XAU/USD) by combining moving averages, MACD momentum indicators, and RSI filters to capture sustained trends while managing volatility risks. The strategy uses volatility-adjusted stops to protect gains and prevent overexposure during erratic price movements. The aim is to take advantage of trending markets by confirming momentum and ensuring entries are not made at extreme levels.
---
**Key Components**
1. **Trend Identification**
- **50 vs 200 EMA Crossover**
- **Bullish Trend:** 50 EMA crosses above 200 EMA, and the price closes above the 200 EMA
- **Bearish Trend:** 50 EMA crosses below 200 EMA, and the price closes below the 200 EMA
2. **Momentum Confirmation**
- **MACD (12,26,9)**
- **Buy Signal:** MACD line crosses above the signal line
- **Sell Signal:** MACD line crosses below the signal line
- **RSI (14 Period)**
- **Bullish Zone:** RSI between 50-70 to avoid overbought conditions
- **Bearish Zone:** RSI between 30-50 to avoid oversold conditions
3. **Entry Criteria**
- **Long Entry:** Bullish trend, MACD bullish crossover, and RSI between 50-70
- **Short Entry:** Bearish trend, MACD bearish crossover, and RSI between 30-50
4. **Exit & Risk Management**
- **ATR Trailing Stops (14 Period):**
- Initial Stop: 3x ATR from entry price
- Trailing Stop: Adjusts to lock in profits as price moves favorably
- **Position Sizing:** 100% of equity per trade (high-risk strategy)
---
**Key Logic Flow**
1. **Trend Filter:** Use the 50/200 EMA relationship to define the market's direction
2. **Momentum Confirmation:** Confirm trend momentum with MACD crossovers
3. **RSI Validation:** Ensure RSI is within non-extreme ranges before entering trades
4. **Volatility-Based Risk Management:** Use ATR stops to manage market volatility
---
**Visual Cues**
- **Blue Line:** 50 EMA
- **Red Line:** 200 EMA
- **Green Triangles:** Long entry signals
- **Red Triangles:** Short entry signals
---
**Strengths**
- **Clear Trend Focus:** Avoids counter-trend trades
- **RSI Filter:** Prevents entering overbought or oversold conditions
- **ATR Stops:** Adapts to gold’s inherent volatility
- **Simple Rules:** Easy to follow with minimal inputs
---
**Weaknesses & Risks**
- **Infrequent Signals:** 50/200 EMA crossovers are rare
- **Potential Missed Opportunities:** Strict RSI criteria may miss some valid trends
- **Aggressive Position Sizing:** 100% equity allocation can lead to large drawdowns
- **No Profit Targets:** Relies on trailing stops rather than defined exit targets
---
**Performance Profile**
| Metric | Expected Range |
|----------------------|---------------------|
| Annual Trades | 4-8 |
| Win Rate | 55-65% |
| Max Drawdown | 25-35% |
| Profit Factor | 1.8-2.5 |
---
**Optimization Recommendations**
1. **Increase Trade Frequency**
Adjust the EMAs to shorter periods:
- `emaFastLen = input.int(30, "Fast EMA")`
- `emaSlowLen = input.int(150, "Slow EMA")`
2. **Relax RSI Filters**
Adjust the RSI range to:
- `rsiBullish = rsi > 45 and rsi < 75`
- `rsiBearish = rsi < 55 and rsi > 25`
3. **Add Profit Targets**
Introduce a profit target at 1.5% above entry:
```pine
strategy.exit("Long Exit", "Long",
stop=longStopPrice,
profit=close*1.015, // 1.5% target
trail_offset=trailOffset)
```
4. **Reduce Position Sizing**
Risk a smaller percentage per trade:
- `default_qty_value=25`
---
**Best Use Case**
This strategy excels in **strong trending markets** such as gold rallies during economic or geopolitical crises. However, during sideways or choppy market conditions, the strategy might require manual intervention to avoid false signals. Additionally, integrating fundamental analysis—like monitoring USD weakness or geopolitical risks—can enhance its effectiveness.
---
This strategy offers a balanced approach for trading gold, combining trend-following principles with risk management tailored to the volatility of the market.
Zero Lag Signals (Pine Script) - CorrectedZero-Lag EMA: It calculates a zero-lag EMA using a custom function. This type of EMA aims to reduce lag compared to a traditional EMA, providing a more responsive indicator of price movement.
Volatility: It calculates volatility using the Average True Range (ATR) indicator and a user-defined multiplier.
Angle: It calculates the angle of the zero-lag EMA by comparing its current value to its value 10 bars ago. This helps determine the trend and momentum of the price.
Buy/Sell Signals:
Buy Signal: Triggered when the angle of the zero-lag EMA is above a certain threshold and the current price is above the EMA.
Sell Signal: Triggered when the angle of the zero-lag EMA is below a certain threshold and the current price is below the EMA.
Key Features:
Zero-Lag EMA: Reduces lag for a more responsive indicator.
Volatility Bands: Helps identify potential entry and exit points based on volatility.
Angle Calculation: Provides insights into the trend and momentum of the price.
Customizable Parameters: Allows users to adjust the length of the EMA, volatility multiplier, and signal angle threshold.
Visual Signals and Alerts: Displays buy and sell signals on the chart and triggers alerts.
This indicator can be used to:
Identify potential buy and sell opportunities in trending markets.
Filter out false signals in choppy markets.
Confirm the strength of a trend.
Time entries and exits based on momentum and volatility.
Trend & ADX by Gideon for Indian MarketsThis indicator is designed to help traders **identify strong trends** using the **Kalman Filter** and **ADX** (Average Directional Index). It provides **Buy/Sell signals** based on trend direction and ADX strength. I wanted to create something for Indian markets since there are not much available.
In a nut-shell:
✅ **Buy when the Kalman Filter turns green, and ADX is strong.
❌ **Sell when the Kalman Filter turns red, and ADX is strong.
📌 **Ignore signals if ADX is weak (below threshold).
📊 Use on 5-minute timeframes for intraday trading.
------------------------------------------------------------------------
1. Understanding the Indicator Components**
- **Green Line:** Indicates an **uptrend**.
- **Red Line:** Indicates a **downtrend**.
- The **line color change** signals a potential **trend reversal**.
**ADX Strength Filter**
- The **ADX (orange line)** measures trend strength.
- The **blue horizontal line** marks the **ADX threshold** (default: 20).
- A **Buy/Sell signal is only valid if ADX is above the threshold**, ensuring a strong trend.
**Buy & Sell Signals**
- **Buy Signal (Green Up Arrow)**
- Appears **one candle before** the Kalman line turns green.
- ADX must be **above the threshold** (default: 20).
- Suggests entering a **long position**.
- **Sell Signal (Red Down Arrow)**
- Appears **one candle before** the Kalman line turns red.
- ADX must be **above the threshold** (default: 20).
- Suggests entering a **short position**.
2. Best Settings for 5-Minute Timeframe**
For day trading on the **5-minute chart**, the following settings work best:
- **Kalman Filter Length:** `50`
- **Process Noise (Q):** `0.1`
- **Measurement Noise (R):** `0.01`
- **ADX Length:** `14`
- **ADX Threshold:** `20`
- **(Increase to 25-30 for more reliable signals in volatile markets)**
3. How to Trade with This Indicator**
**Entry Rules**
✅ **Buy Entry**
- Wait for a **green arrow (Buy Signal).
- Kalman Line must **turn green**.
- ADX must be **above the threshold** (strong trend confirmed).
- Enter a **long position** on the next candle.
❌ **Sell Entry**
- Wait for a **red arrow (Sell Signal).
- Kalman Line must **turn red**.
- ADX must be **above the threshold** (strong trend confirmed).
- Enter a **short position** on the next candle.
**Exit & Risk Management**
📌 **Stop Loss**:
- Place stop-loss **below the previous swing low** (for buys) or **above the previous swing high** (for sells).
📌 **Take Profit:
- Use a **Risk:Reward Ratio of 1:2 or 1:3.
- Exit when the **Kalman Filter color changes** (opposite trend signal).
📌 **Avoid Weak Trends**:
- **No trades when ADX is below the threshold** (low trend strength).
4. Additional Tips
- Works best on **liquid assets** like **Bank Nifty, Nifty 50, and large-cap stocks**.
- **Avoid ranging markets** with low ADX values (<20).
- Use alongside **volume analysis and support/resistance levels** for confirmation.
- Experiment with **ADX Threshold (increase for stronger signals, decrease for more trades).**
Best of Luck traders ! 🚀
Volume with EMA and Coloring RulesSummary
This indicator plots the market’s volume as a histogram in a separate panel (not overlaid on the main price chart). An EMA (Exponential Moving Average) is then calculated based on the volume. The color of each volume bar switches dynamically:
• Blue when the bar’s volume is higher than the EMA
• White when the bar’s volume is lower than or equal to the EMA
This simple visual cue allows you to quickly see if the market’s current volume is above or below its average trend.
How to Use
1. Add to Chart
Apply the indicator to your TradingView chart, and it will open in a separate panel beneath the price.
2. Adjust EMA Length
Modify the “EMA Length” to control how quickly the average volume adapts to changes.
3. Interpretation
• Blue bars may indicate stronger-than-usual participation.
• White bars indicate volume is relatively lower compared to its recent average.
This indicator provides an at-a-glance way to see if trading activity is intensifying or easing, which can be paired with other technical or fundamental tools to help confirm market shifts or potential opportunities.
Johnny's Machine Learning Moving Average (MLMA) w/ Trend Alerts📖 Overview
Johnny's Machine Learning Moving Average (MLMA) w/ Trend Alerts is a powerful adaptive moving average indicator designed to capture market trends dynamically. Unlike traditional moving averages (e.g., SMA, EMA, WMA), this indicator incorporates volatility-based trend detection, Bollinger Bands, ADX, and RSI, offering a comprehensive view of market conditions.
The MLMA is "machine learning-inspired" because it adapts dynamically to market conditions using ATR-based windowing and integrates multiple trend strength indicators (ADX, RSI, and volatility bands) to provide an intelligent moving average calculation that learns from recent price action rather than being static.
🛠 How It Works
1️⃣ Adaptive Moving Average Selection
The MLMA automatically selects one of four different moving averages:
📊 EMA (Exponential Moving Average) – Reacts quickly to price changes.
🔵 HMA (Hull Moving Average) – Smooth and fast, reducing lag.
🟡 WMA (Weighted Moving Average) – Gives recent prices more importance.
🔴 VWAP (Volume Weighted Average Price) – Accounts for volume impact.
The user can select which moving average type to use, making the indicator customizable based on their strategy.
2️⃣ Dynamic Trend Detection
ATR-Based Adaptive Window 📏
The Average True Range (ATR) determines the window size dynamically.
When volatility is high, the moving average window expands, making the MLMA more stable.
When volatility is low, the window shrinks, making the MLMA more responsive.
Trend Strength Filters 📊
ADX (Average Directional Index) > 25 → Indicates a strong trend.
RSI (Relative Strength Index) > 70 or < 30 → Identifies overbought/oversold conditions.
Price Position Relative to Upper/Lower Bands → Determines bullish vs. bearish momentum.
3️⃣ Volatility Bands & Dynamic Support/Resistance
Bollinger Bands (BB) 📉
Uses standard deviation-based bands around the MLMA to detect overbought and oversold zones.
Upper Band = Resistance, Lower Band = Support.
Helps traders identify breakout potential.
Adaptive Trend Bands 🔵🔴
The MLMA has built-in trend envelopes.
When price breaks the upper band, bullish momentum is confirmed.
When price breaks the lower band, bearish momentum is confirmed.
4️⃣ Visual Enhancements
Dynamic Gradient Fills 🌈
The trend strength (ADX-based) determines the gradient intensity.
Stronger trends = More vivid colors.
Weaker trends = Lighter colors.
Trend Reversal Arrows 🔄
🔼 Green Up Arrow: Bullish reversal signal.
🔽 Red Down Arrow: Bearish reversal signal.
Trend Table Overlay 🖥
Displays ADX, RSI, and Trend State dynamically on the chart.
📢 Trading Signals & How to Use It
1️⃣ Bullish Signals 📈
✅ Conditions for a Long (Buy) Trade:
The MLMA crosses above the lower band.
The ADX is above 25 (confirming trend strength).
RSI is above 55, indicating positive momentum.
Green trend reversal arrow appears (confirmation of a bullish reversal).
🔹 How to Trade It:
Enter a long trade when the MLMA turns bullish.
Set stop-loss below the lower Bollinger Band.
Target previous resistance levels or use the upper band as take-profit.
2️⃣ Bearish Signals 📉
✅ Conditions for a Short (Sell) Trade:
The MLMA crosses below the upper band.
The ADX is above 25 (confirming trend strength).
RSI is below 45, indicating bearish pressure.
Red trend reversal arrow appears (confirmation of a bearish reversal).
🔹 How to Trade It:
Enter a short trade when the MLMA turns bearish.
Set stop-loss above the upper Bollinger Band.
Target the lower band as take-profit.
💡 What Makes This a Machine Learning Moving Average?
📍 1️⃣ Adaptive & Self-Tuning
Unlike static moving averages that rely on fixed parameters, this MLMA automatically adjusts its sensitivity to market conditions using:
ATR-based dynamic windowing 📏 (Expands/contracts based on volatility).
Adaptive smoothing using EMA, HMA, WMA, or VWAP 📊.
Multi-indicator confirmation (ADX, RSI, Volatility Bands) 🏆.
📍 2️⃣ Intelligent Trend Confirmation
The MLMA "learns" from recent price movements instead of blindly following a fixed-length average.
It incorporates ADX & RSI trend filtering to reduce noise & false signals.
📍 3️⃣ Dynamic Color-Coding for Trend Strength
Strong trends trigger more vivid colors, mimicking confidence levels in machine learning models.
Weaker trends appear faded, suggesting uncertainty.
🎯 Why Use the MLMA?
✅ Pros
✔ Combines multiple trend indicators (MA, ADX, RSI, BB).
✔ Automatically adjusts to market conditions.
✔ Filters out weak trends, making it more reliable.
✔ Visually intuitive (gradient colors & reversal arrows).
✔ Works across all timeframes and assets.
⚠️ Cons
❌ Not a standalone strategy → Best used with volume confirmation or candlestick analysis.
❌ Can lag slightly in fast-moving markets (due to smoothing).
Volume Delta with Bollinger Bands [EMA]TL;DR
This indicator displays a “Volume Delta” candle chart based on a lower timeframe approximation of up vs. down volume. Bollinger Bands (using an EMA and a configurable standard deviation multiplier) highlight when Volume Delta exceeds typical volatility thresholds. Green bars will darken when Volume Delta is above the upper Bollinger band, and red bars will darken when Volume Delta is below the lower Bollinger band. You can optionally include wicks in the Bollinger calculations. Note : TradingView uses tick-based volume data, so these values may not precisely match true market orders.
What Is Volume Delta ?
• Volume Delta is a metric that identifies buying vs. selling activity in a market by distinguishing between orders transacting at the ask (buy volume) and orders transacting at the bid (sell volume).
• A positive Volume Delta indicates more buy volume during a bar, while a negative Volume Delta indicates more sell volume.
How TradingView Calculates Volume Delta
• TradingView relies on tick data to approximate up/down volume. This may not perfectly capture true order-flow distribution, particularly on higher timeframes or illiquid symbols.
• While it can provide useful insights into volume flow, keep in mind the underlying data’s limitations.
Key Features of This Indicator
1. Automatic or Custom Lower Timeframe Data
• The script can automatically select a lower timeframe for Volume Delta, or you can manually specify one in the settings.
2. Bollinger Bands on Volume Delta
• Uses an EMA of the Volume Delta (or a wick-based average) and calculates a standard deviation.
• The upper and lower bands highlight when activity deviates from typical volatility.
3. Configurable Wick Inclusion
• Decide whether to use only the “close” (lastVolume) of the Volume Delta bar or the average of its wicks ((maxVolume + minVolume) / 2) for Bollinger calculations.
4. Dynamic Bar Colors
• Positive Volume Delta bars turn dark green if they exceed the upper Bollinger band, otherwise lighter green .
• Negative Volume Delta bars turn dark red if they fall below the lower Bollinger band, otherwise lighter red .
How To Use
1. Add the Indicator to Your Chart
• Apply it to any symbol and timeframe in TradingView.
• Configure the lower timeframe for Volume Delta if desired.
2. Adjust Bollinger Settings
• Bollinger Length defines the EMA and standard deviation period.
• Bollinger Multiplier sets how far the bands lie from the EMA.
3. Choose Whether To Use Wicks
• Toggle to use the average of high/low for a potentially more volatile reading.
• Turn it off to rely solely on the Volume Delta “close.”
4. Interpret the Signals
• Dark Green Above the Upper Band : Suggests strong buying pressure above normal.
• Lighter Green : Positive but within typical volatility bounds.
• Dark Red Below the Lower Band : Suggests strong selling pressure below normal.
• Lighter Red : Negative but within typical volatility.
Important Caveats
• TradingView Volume Data : Tick-based and aggregated data may not reflect actual order-flow precisely.
• Context Matters : Combine Volume Delta with other forms of analysis (price action, support/resistance, etc.) to form a more comprehensive strategy.
VWAP Bands with ML [CryptoSea]VWAP Machine Learning Bands is an advanced indicator designed to enhance trading analysis by integrating VWAP with a machine learning-inspired adaptive smoothing approach. This tool helps traders identify trend-based support and resistance zones, predict potential price movements, and generate dynamic trade signals.
Key Features
Adaptive ML VWAP Calculation: Uses a dynamically adjusted SMA-based VWAP model with volatility sensitivity for improved trend analysis.
Forecasting Mechanism: The 'Forecast' parameter shifts the ML output forward, providing predictive insights into potential price movements.
Volatility-Based Band Adjustments: The 'Sigma' parameter fine-tunes the impact of volatility on ML smoothing, adapting to market conditions.
Multi-Tier Standard Deviation Bands: Includes two levels of bands to define potential breakout or mean-reversion zones.
Dynamic Trend-Based Colouring: The VWAP and ML lines change colour based on their relative positions, visually indicating bullish and bearish conditions.
Custom Signal Detection Modes: Allows traders to choose between signals from Band 1, Band 2, or both, for more tailored trade setups.
In the image below, you can see an example of the bands on higher timeframe showing good mean reversion signal opportunities, these tend to work better in ranging markets rather than strong trending ones.
How It Works
VWAP & ML Integration: The script computes VWAP and applies a machine learning-inspired adjustment using SMA smoothing and volatility-based adaptation.
Forecasting Impact: The 'Forecast' setting shifts the ML output forward in time, allowing for anticipatory trend analysis.
Volatility Scaling (Sigma): Adjusts the ML smoothing sensitivity based on market volatility, providing more responsive or stable trend lines.
Trend Confirmation via Colouring: The VWAP line dynamically switches colour depending on whether it is above or below the ML output.
Multi-Level Band Analysis: Two standard deviation-based bands provide a framework for identifying breakouts, trend reversals, or continuation patterns.
In the example below, we can see some of the most reliable signals where we have mean reversion signals from the band whilst the price is also pulling back into the VWAP, these signals have the additional confluence which can give you a higher probabilty move.
Alerts
Bullish Signal Band 1: Alerts when the price crosses above the lower ML Band 1.
Bearish Signal Band 1: Alerts when the price crosses below the upper ML Band 1.
Bullish Signal Band 2: Alerts when the price crosses above the lower ML Band 2.
Bearish Signal Band 2: Alerts when the price crosses below the upper ML Band 2.
Filtered Bullish Signal: Alerts when a bullish signal is triggered based on the selected signal detection mode.
Filtered Bearish Signal: Alerts when a bearish signal is triggered based on the selected signal detection mode.
Application
Trend & Momentum Analysis: Helps traders identify key market trends and potential momentum shifts.
Dynamic Support & Resistance: Standard deviation bands serve as adaptive price zones for potential breakouts or reversals.
Enhanced Trade Signal Confirmation: The integration of ML smoothing with VWAP provides clearer entry and exit signals.
Customizable Risk Management: Allows users to adjust parameters for fine-tuned signal detection, aligning with their trading strategy.
The VWAP Machine Learning Bands indicator offers traders an innovative tool to improve market entries, recognize potential reversals, and enhance trend analysis with intelligent data-driven signals.
Instantaneous Trendline with Cloud Instantaneous Trendline with Cloud
Introduction & History
The Instantaneous Trendline was introduced by John Ehlers, a well-known figure in the field of technical analysis, particularly for applying digital signal processing concepts to financial markets. Ehlers aimed to create an indicator that reacts to market price changes more quickly than traditional moving averages, yet remains smooth enough to avoid excessive noise. By incorporating concepts from digital filtering, he devised a formula that calculates a trendline with minimal lag—hence the term “instantaneous.”
Purpose
The primary purpose of the Instantaneous Trendline with Cloud is to provide traders and analysts with a responsive, smoothed line that closely follows market price movements. Additionally, this script enhances the visual cues by adding a cloud fill to highlight bullish and bearish zones:
Trend Identification
The ITL (Instantaneous Trendline) is plotted alongside the price. When price consistently stays above the ITL, it may signal an uptrend. Conversely, when price dips below the ITL, it can suggest a downtrend.
Signal Generation
Crossover points between the price and the ITL can serve as potential entry or exit signals. A bullish crossover (price moving above the ITL) often indicates the start of upward momentum, while a bearish crossover (price dropping below the ITL) may point to downward momentum.
Noise Reduction
By applying digital filtering concepts and smoothing through the alpha (smoothing coefficient), the ITL reduces noise while still responding relatively quickly to price changes. Traders can adjust alpha to make the trendline more reactive (higher alpha) or smoother (lower alpha).
Clarity via Cloud Fill
A color-coded cloud between the price and the ITL provides an at-a-glance view of market bias. The green cloud highlights potentially bullish phases, while the red cloud highlights potentially bearish phases.
Experiment with the alpha value (commonly between 0.2 and 0.3) to find a balance that suits your preference for responsiveness versus smoothness.
This indicator implements John Ehlers’ Instantaneous Trendline concept and plots a smoothed trendline (ITL) alongside the price. The trendline is controlled by a user-defined smoothing coefficient (alpha). A higher alpha makes the trendline respond more quickly to price changes, while a lower alpha produces a smoother line.
A color-filled cloud helps traders identify bullish and bearish conditions:
Green cloud if the price is above the ITL (bullish potential).
Red cloud if the price is below the ITL (bearish potential).
Key Benefits
Trend Visualization: Quickly see if the market is in an uptrend or downtrend based on the position of the price relative to the trendline.
Crossover Signals: Identify potential shifts in trend or momentum when the price crosses the ITL.
Customizable Sensitivity: Adjust the alpha parameter to make the ITL more or less reactive to price moves. Use this tool to better visualize short-term trend changes and potential entry/exit signals in conjunction with other technical analysis methods.
BB ATR Fractal MMThe Bollinger Bands + ATR with Fractal indicator is a powerful combination of Bollinger Bands, ATR (Average True Range), and Fractal to help identify market volatility and potential entry/exit points on the chart.
Bollinger Bands help to assess the market’s volatility by calculating upper and lower bands based on the simple moving average (SMA) and standard deviation. It’s an excellent tool for identifying overbought and oversold conditions.
ATR (Average True Range) is used to measure market volatility. It helps determine how much the price is moving, and it can be used to adjust the Bollinger Bands, creating bands that reflect the current volatility more accurately.
Fractal helps to identify peaks and troughs in the market, supporting decision-making by highlighting potential reversal points. Fractals mark regions where price may reverse direction, making it easier to spot possible trade opportunities.
How to Use:
Bollinger Bands Upper and Lower Bands: These bands help to identify overbought or oversold conditions. If the price breaks above the upper band, the market may be overbought. If the price breaks below the lower band, the market may be oversold.
ATR: It indicates the volatility level of the market. When the market shows large volatility (ATR increases), the Bollinger Bands expand to reflect higher price swings.
Fractal: Arrows appear at the market’s peaks and troughs, helping identify entry points for buying (at fractal lows) or selling (at fractal highs). These signals can help you make trading decisions based on potential price reversals.
TOTAL3/BTC This Pine Script™ code, named "TOTAL3/BTC with Arrow," is designed for cryptocurrency analysis on TradingView.
This script essentially provides a visual tool for traders to gauge when altcoins might be gaining or losing ground relative to Bitcoin through moving average analysis and color-coded trend indication.
Intention was to help the community with a script based on classic TA only.
Use it with SASDv2r indicator.
Feel free to make it better. If you did so, please let me know.
Main elements:
Data Fetching: It retrieves market cap data for all cryptocurrencies excluding Bitcoin and Ethereum (TOTAL3) and for Bitcoin (BTC).
Ratio Calculation: The script calculates the ratio of TOTAL3 to BTC market caps, which indicates how altcoins (excluding ETH) are performing relative to Bitcoin.
Plotting the Ratio: This ratio is plotted on the chart with a blue line, allowing traders to see the relative performance visually.
Moving Averages: Two Simple Moving Averages (SMA) are calculated for this ratio, one for 20 periods (ma20) and another for 50 periods (ma50), though these are not plotted in the current version of the code.
Reference Lines: Horizontal lines are added at ratios of 0.3 and 0.8 to serve as visual equilibrium points or thresholds for analysis.
Complex Moving Average: The script uses constants (len, len2, cc, smoothe) from another script, suggesting it's adapting or simplifying another's logic for multi-timeframe analysis.
Average Calculation: Two SMAs (avg and avg2) are computed using the constants defined, focusing on different lengths for trend analysis.
Direction Determination: It checks if the moving average is trending up or down by comparing the current value with its value smoothe bars earlier.
Color Coding: The color of the plotted moving average changes based on its direction (lime for up, red for down, aqua if no clear direction), aiding in quick visual interpretation of trends.
Plotting: Finally, the script plots this multi-timeframe moving average with a dynamic color to reflect the current market trend of the TOTAL3/BTC ratio, with a thicker line for visibility.
SASDv2rSensitive Altcoin Season Detector V2
This Pine Script™ code, titled "SASDv2r" (Sensitive Altcoin Season Detector version 2 revised), is designed for cryptocurrency trading analysis on the TradingView platform and tailored for those interested in tracking when altcoins might be outperforming Bitcoin, potentially indicating a market shift towards altcoins.
Feel free to use and modify. If you made it better, please let me know. Intention was to help the community with a tool for retail traders have no access to advanced, MV indicators. Solution uses classic TA only.
Use it witl TOTAL3/BTC indicator.
Please check: it gave signal just before last alt season % rose more than 250%.
Market Cap Data Fetching: The script fetches market capitalization data for Bitcoin, Ethereum, and all other altcoins (excluding Bitcoin and Ethereum) using request.security function.
Altcoin to Bitcoin Ratio: It calculates the ratio of total market cap of altcoins to Bitcoin's market cap (altToBtcRatio), which is central to identifying an "altcoin season."
Moving Averages: Several moving averages are computed for different time frames (50-day SMA, 200-day SMA, 20-day SMA, and 10-day EMA) to analyze trends in the altcoin to Bitcoin ratio.
Momentum Indicators: The script uses RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) to gauge momentum and potential reversal points in the market.
Custom Indicators: It includes Volume Weighted Moving Average (VWMA) and a custom momentum indicator (altMomentum and altMomentumAvg) to provide additional insights into market movements.
Volatility Measurement: Bollinger Bands are calculated to assess volatility in the altcoin to Bitcoin ratio, which helps identify periods of high or low market activity.
Visual Analysis: Various plots are added to the chart for visual interpretation, including the altcoin to Bitcoin ratio, different moving averages, and Bollinger Bands.
Alt Season Detection: The script defines conditions for detecting when an "altcoin season" might be starting, based on crossovers of moving averages, RSI levels, MACD signals, and other custom criteria.
Performance Tracking: After signaling an alt season, the script evaluates the performance over the next 30 days by checking if there's been an increase in the altcoin to Bitcoin ratio, adding labels for positive or negative trends.(this one is in progress). Logic still gives false signals and aim is to identify failed signals.
Visual Signals: Labels are placed on the chart to visually indicate the beginning of a potential alt season or the performance outcome after a signal, aiding traders in making informed decisions.
Aggregated Volume (Multi-Exchange)Indicator: Aggregated Volume (Multi-Exchange)
Overview:
The Aggregated Volume (Multi-Exchange) indicator is designed to aggregate trading volume data from multiple exchanges for a specific cryptocurrency pair. The goal is to provide a consolidated view of the total trading volume across different platforms, helping traders and analysts gauge the overall market activity for a given asset.
Features:
Multi-Exchange Support: The indicator allows you to aggregate trading volume data from various exchanges. Users can enable or disable volume data from specific exchanges (e.g., Binance, Bybit, Kucoin, etc.).
Spot and Futures Volumes: The indicator can sum the volume for spot trading and futures trading separately if desired. However, in the current version, it only sums the volume for specific pairs across multiple exchanges, without distinguishing between spot and futures volumes (though this feature can be added if necessary).
Customizable Exchange Selection: Users can select which exchanges' volume data to include in the aggregation.
Real-Time Updates: The volume data is updated in real-time as new bars are formed on the chart, providing an up-to-date picture of the trading volume.
Purpose:
The primary purpose of this indicator is to consolidate trading volume information from multiple exchanges for the same trading pair (e.g., BTC/USD). Traders can use this aggregated volume to gain a better understanding of market activity across various platforms, as well as assess the level of liquidity and interest in a particular asset.
By viewing the total aggregated volume, traders can:
Track market trends: Higher aggregated volume can signal increased market interest, making it easier to spot trends or potential breakouts.
Analyze liquidity: This indicator can help traders assess liquidity in the market, especially when using multiple exchanges.
Identify potential market manipulation: If there is a sudden spike in volume on multiple exchanges, it could signal market manipulation or an event-driven surge.
How it Works:
Volume Aggregation: The indicator collects and sums the volume data for a given symbol (e.g., BTC/USD) from different exchanges like Binance, Bybit, Kucoin, and others.
Multiple Exchanges: The volume data is aggregated from each selected exchange and plotted as a single volume value on the chart.
Real-Time Volume Plotting: The total aggregated volume is then plotted as a histogram on the chart, with the color of the bars changing depending on whether the price is rising or falling (typically green for rising prices and red for falling prices).
Inputs/Settings:
Exchange Selection: A list of checkboxes where users can choose which exchanges' volume data to include (e.g., Binance, Bybit, Kucoin, etc.).
Color Settings: Users can set the color for the histogram bars based on price direction (e.g., green for rising and red for falling).
Volume Calculation: The indicator calculates the volume for a specific cryptocurrency pair across selected exchanges in real-time.
