Relative Strength RatioWhen comparing a stock’s strength against NIFTY 50, the Relative Strength (RS) is calculated to measure how the stock is performing relative to the index. This is different from the RSI but is often used alongside it.
How It Works:
Relative Strength (RS) Calculation:
𝑅
𝑆
=
Stock Price
NIFTY 50 Price
RS=
NIFTY 50 Price
Stock Price
This shows how a stock is performing relative to the NIFTY 50 index.
Relative Strength Ratio Over Time:
If the RS value is increasing, the stock is outperforming NIFTY 50.
If the RS value is decreasing, the stock is underperforming NIFTY 50.
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AntoQQE - BarsThis script is a variation on the QQE (Quantitative Qualitative Estimation) concept applied to RSI. It calculates a smoothed RSI line, then determines a “Dynamic Average Range” around that line. By tracking the RSI’s movement relative to these upper (shortBand) and lower (longBand) levels, it determines when price momentum shifts enough to suggest a possible trend flip. The script plots color-coded candles based on these momentum conditions:
• RSI Calculation and Smoothing
An RSI value is obtained over a specified period, then smoothed by an EMA. This smoothed RSI serves as the core measure of momentum.
• Dynamic Average Range (DAR)
The script computes the volatility of the smoothed RSI using two EMAs of its bar-to-bar movements. It multiplies this volatility factor by a QQE multiplier to create upper and lower bands that adapt to changes in RSI volatility.
• Trend Flips
When the smoothed RSI crosses above or below its previous band level (shortBand or longBand), the script interprets this as a shift in momentum and sets a trend state accordingly (long or short).
• Candle Coloring
Finally, the script colors each candle according to how far the smoothed RSI is from a neutral baseline of 50:
Candles turn green when the RSI is sufficiently above 50, suggesting bullish momentum.
Candles turn red when the RSI is sufficiently below 50, indicating bearish momentum.
Candles turn orange when they are near the 50 level, reflecting a more neutral or transitional phase.
Traders can use these colored candles to quickly see when the RSI’s momentum has moved into overbought/oversold zones—or is shifting between bullish and bearish conditions—without needing to consult a separate oscillator window. The adaptive nature of the band calculations can help in spotting significant shifts in market sentiment and volatility.
Oracle Fear and GreedCustom Fear and Greed Oscillator with Movement Table
This indicator provides a unique perspective on market sentiment by calculating a custom fear/greed oscillator based on Heikin-Ashi candles. The oscillator is centered at 50, with values above 50 suggesting bullish sentiment ("greed") and below 50 indicating bearish sentiment ("fear"). The calculation incorporates candle body size, range, and a custom "candle strength" measure, providing an innovative approach to understanding market behavior.
Key Features:
Heikin-Ashi Based Oscillator:
Utilizes Heikin-Ashi candles to compute a custom oscillator. The value is centered at 50, with deviations indicating the prevailing market sentiment.
Dynamic Gradient Coloring:
The oscillator line is dynamically colored with a smooth gradient—from blue (representing fear) at lower values to pink (representing greed) at higher values—making it visually intuitive.
Horizontal Levels:
Two additional horizontal lines are drawn at 40.62 ("Bottom") and 60.74 ("Top"), which may serve as potential oversold and overbought boundaries respectively.
Fast Movement Metrics:
Every 5 bars, the indicator calculates the percentage change in the Heikin-Ashi close. This fast movement analysis distinguishes rapid downward moves (fast fear) from rapid upward moves (fast greed), helping to capture sudden market shifts.
Information Table:
A table in the top-right corner displays the most recent fast movement values for both fear and greed, offering quick insights into short-term market dynamics.
Usage Tips:
Adjust the smoothing period to match your preferred trading timeframe.
Use the oscillator alongside other analysis tools for more robust trading decisions.
Ideal for those looking to experiment with new approaches to sentiment analysis and momentum detection.
Disclaimer:
This indicator is intended for educational and experimental purposes. It should not be used as the sole basis for any trading decisions. Always combine with comprehensive market analysis and risk management strategies.
You can add this description when publishing your indicator on TradingView to help other users understand its features and intended use.
[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!
Volume Flow Indicator Signals | iSolani
Volume Flow Indicator Signals | iSolani: Decoding Trend Momentum with Volume Precision
In markets where trends are fueled by institutional participation, discerning genuine momentum from false moves is critical. The Volume Flow Indicator Signals | iSolani cuts through this noise by synthesizing price action with volume dynamics, generating high-confidence signals when capital flows align with directional bias. This tool reimagines traditional volume analysis by incorporating volatility-adjusted thresholds and dual-layer smoothing, offering traders a laser-focused approach to trend identification.
Core Methodology
The indicator employs a multi-stage calculation to quantify volume-driven momentum:
Volatility-Adjusted Filter: Measures price changes via log returns, scaling significance using a 30-bar standard deviation multiplied by user-defined sensitivity (default: 2x).
Volume Normalization: Caps extreme volume spikes at 3x the 50-bar moving average, preventing distortion from anomalous trades.
Directional Volume Flow: Assigns positive/negative values to volume based on whether price movement exceeds volatility-derived thresholds.
Dual Smoothing: Applies consecutive SMA (3-bar) and EMA (14-bar) to create the Volume Flow Indicator (VFI) and its signal line, filtering out transient fluctuations.
Breaking New Ground
This implementation introduces three key innovations:
Adaptive Noise Gates: Unlike static volume oscillators, the sensitivity coefficient dynamically adjusts to market volatility, reducing false signals during choppy conditions.
Institutional Volume Capping: The vcoef parameter limits the influence of outlier volume spikes, focusing on sustained institutional activity rather than one-off trades.
Non-Repainting Signals: Generates single-per-trend labels (buy below bars, sell above) to avoid chart clutter while maintaining visual clarity.
Engine Under the Hood
The script executes through five systematic stages:
Data Preparation: Computes HLC3 typical price and its logarithmic rate of change.
Threshold Calculation: Derives dynamic cutoff levels using 30-period volatility scaled by user sensitivity.
Volume Processing: Filters raw volume through a 50-bar SMA, capping extremes at 3x average.
VFI Construction: Sums directional volume flow over 50 bars, smoothed with a 3-bar SMA.
Signal Generation: Triggers alerts when VFI crosses zero, confirmed by a 14-bar EMA crossover.
Standard Configuration
Optimized defaults balance responsiveness and reliability:
Volume MA: 50-bar smoothing window
Sensitivity: 2.0 (doubles volatility threshold)
Signal Smoothing: 14-bar EMA
Volume Cap: 3x average (hidden parameter)
VFI Smoothing: Enabled (3-bar SMA)
By fusing adaptive volume filtering with price confirmation logic, the Volume Flow Indicator Signals | iSolani transforms raw market data into institutional-grade trend signals. Its ability to mute choppy price action while amplifying high-conviction volume moves makes it particularly effective for spotting early trend reversals in equities, forex, and futures markets.
RSI of Accumulation/DistributionHow to Use the RSI of Accumulation/Distribution Indicator:
1. Identify Overbought/Oversold Conditions:
Overbought: When the RSI of the ADL is above 70, it indicates that the asset may be overbought and could be due for a pullback or correction.
Oversold: When the RSI of the ADL is below 30, it suggests that the asset may be oversold and could be poised for a rebound.
2. Look for Divergences:
Bullish Divergence: If the price is making lower lows while the RSI of the ADL is making higher lows, it can signal a potential reversal to the upside.
Bearish Divergence: If the price is making higher highs while the RSI of the ADL is making lower highs, it can indicate a potential reversal to the downside.
3. Confirm Trend Strength:
Use the RSI of the ADL to confirm the strength of a trend. For example, if the RSI is consistently above 50 during an uptrend, it suggests strong buying pressure and the trend is likely to continue.
Conversely, if the RSI is consistently below 50 during a downtrend, it indicates strong selling pressure and the trend is likely to persist.
4. Monitor for Reversals:
When the RSI of the ADL crosses above 50, it can signal a potential bullish reversal.
When the RSI of the ADL crosses below 50, it can signal a potential bearish reversal.
Is It Worth It?
The RSI of the Accumulation/Distribution Line can be a valuable tool for traders looking to gain insights into market momentum and trend strength. Here are a few reasons why it might be worth considering:
1. Volume and Price Combination: By combining price action (RSI) with volume-based analysis (ADL), this indicator provides a more comprehensive view of market dynamics.
2. Divergence Detection: It helps identify divergences between price and volume, which can be early signals of potential reversals.
3. Trend Confirmation: It offers additional confirmation of trend strength and potential reversal points, helping traders make more informed decisions.
However, like any indicator, it's important to use it in conjunction with other analysis methods and not rely on it solely for trading decisions. Backtesting the indicator on historical data and combining it with other technical analysis tools can improve its effectiveness.
Feel free to test the script in TradingView and see how it performs in different market conditions. If you have any specific questions or need further assistance, let me know! 😊
Moneyball EMA-MACD indicator [VinnieTheFish]Summary of the Moneyball EMA-MACD Indicator Script
Author: VinnieTheFish
Purpose:
This indicator helps traders identify trend direction, momentum shifts, and potential trade signals based on EMA and MACD crossovers.
This Pine Script is a custom indicator that combines Exponential Moving Averages (EMAs) and MACD (Moving Average Convergence Divergence) to analyze price trends and momentum. The script uses a custom 9/50 MACD with a 16 smoothing period. The script is written in a way that you can create your own custom MACD settings and create alerts based on those parameters. The chart bars are color coded based on the relative position of the MACD and Signal line primarily for bullish long trade setups.
Bar color coding helps the trader spot potential reversals based on where the price currently resides in relation to the custom 9/50 EMA based MACD and the 16 period smoothing period for the signal line. Indicator also has custom alerts to notify the trader when a potential trade setup exists that correspond with the bar color change.
Question: So why is this called the Moneywell EMA-MACD Indicator?
Answer: In the movie Moneyball the Oakland A's broke down how to win a championship based on data. To make the playoffs you needed so many wins, then broken down by runs and then broken down to base hits. A base hit was good as a walk. With trading often times we look too often for home runs and ignore the importance of getting on base with small wins. This indicator was designed on shorter timeframes to identify those base hits, but can also be adapted to higher timeframes for swing trading.
Key Features:
User Inputs:
Configurable fast and slow lengths for MACD calculation.
Choice between SMA and EMA for oscillator and signal line smoothing.
Customizable signal smoothing length.
EMA Calculation:
Computes 3 EMA, 9 EMA, 20 EMA, and 50 EMA to track short-term and long-term trends.
MACD Calculation:
Computes MACD using either SMA or EMA based on user selection.
Generates the MACD signal line for comparison.
Crossover Conditions:
Detects MACD and Signal line crossovers above and below the zero line.
Identifies price momentum shifts.
Bar Coloring Logic:
Green: MACD is above 0 and above the signal line.
White: MACD is below the signal line.
Orange: MACD is below 0 but above the signal line.
Fuchsia: Bullish EMA 3/9 cross but price is still below the 20/50 EMA.
Alerts for Key Trading Signals:
MACD crossing above/below the zero line.
Signal line crossing above/below the zero line.
MACD reaching new highs/lows.
Alerts for colored bar conditions.
True Strength Index with Zones & AlertsKey Features:
True Strength Index (TSI) Calculation
Uses double-smoothed exponential moving averages (EMA) to calculate TSI.
A signal line (EMA of TSI) helps confirm trends.
Dynamic Color Coding for TSI Line
Green: TSI is above the signal line (Bullish).
Red: TSI is below the signal line (Bearish).
Crossover & Crossunder Signals
Bullish Crossover (TSI crosses above Signal Line) → Green Circle.
Bearish Crossunder (TSI crosses below Signal Line) → Red Circle.
Alerts for Trading Signals
Buy Alert: TSI crosses above the signal line.
Sell Alert: TSI crosses below the signal line.
Overbought & Oversold Zones
Overbought: Between 40 and 50 (Red Zone).
Oversold: Between -40 and -50 (Green Zone).
Highlighted Background when TSI enters these zones.
Neutral Line at 0
Helps determine trend direction and momentum shifts.
How to Use These Values:
• TSI Crosses Above Signal Line → Bullish entry.
• TSI Crosses Below Signal Line → Bearish entry.
• Overbought (+40 to +50) & Oversold (-40 to -50) zones → Watch for trend reversals.
• Divergence Signals → If price makes a new high/low but TSI doesn’t, momentum is weakening.
prime rsiThe "PRIME RSI" is a custom variation of the traditional RSI (Relative Strength Index) that offers enhanced flexibility and precision. This indicator provides an adaptable approach for tracking market conditions across different timeframes, making it an ideal tool for both short-term and long-term traders.
Key Features:
Custom Timeframe Selection: Users can select any timeframe to calculate the RSI, providing the ability to analyze data beyond the current chart's timeframe.
Smoothing Methods: Choose between Exponential Moving Average (EMA), Simple Moving Average (SMA), or the Relative Moving Average (RMA) for smoother, more accurate RSI values.
Signal Line: The signal line is smoothed using the selected method and visualized with dynamic coloring to indicate bullish (green) or bearish (red) market conditions.
Overbought/Oversold Levels: Clear levels at 70 (overbought) and 30 (oversold), with fill zones to highlight extreme market conditions, helping traders spot potential reversal points.
Midline at 50: The centerline at 50 serves as a neutral zone, allowing traders to identify shifts in market momentum quickly.
Practical Use:
Trend Confirmation: Use the PRIME RSI to confirm the prevailing market trend, with signals above 50 suggesting bullish momentum and signals below 50 indicating bearish trends.
Overbought/Oversold Conditions: The indicator’s overbought and oversold regions help pinpoint potential market reversals, giving traders valuable entry and exit signals.
Ideal For: All types of traders who want a more flexible and customizable RSI for better trend analysis, especially those working with smaller timeframes or seeking a more responsive momentum indicator.
Golden/Death Cross HighlighterThis indicator helps you easily identify and visualize Golden Cross and Death Cross patterns combined with price action confirmation. It highlights chart backgrounds when specific conditions are met, making it easy to spot potential trend changes.
🔑 Key Features:
Highlights Golden Cross conditions (50 SMA crosses above 200 SMA) when price closes above both MAs
Highlights Death Cross conditions (50 SMA crosses below 200 SMA) when price closes below both MAs
Customizable MA lengths (default: 50 and 200)
Adjustable highlight opacity
Built-in alerts for cross events
Clear visualization of both moving averages
📈 Color Guide:
Yellow Background: Golden Cross active + price above both MAs
Red Background: Death Cross active + price below both MAs
⚙️ Settings:
Fast MA Length: Length of faster moving average (default 50)
Slow MA Length: Length of slower moving average (default 200)
Golden Cross Highlight Opacity: Adjust visibility of bullish highlights
Death Cross Highlight Opacity: Adjust visibility of bearish highlights
💡 Usage Tips:
Use in combination with other indicators for confirmation
Set up alerts for potential trend changes
Adjust opacity to match your chart style
Works best on higher timeframes (4H, Daily, Weekly)
Mean Reversion Pro Strategy [tradeviZion]Mean Reversion Pro Strategy : User Guide
A mean reversion trading strategy for daily timeframe trading.
Introduction
Mean Reversion Pro Strategy is a technical trading system that operates on the daily timeframe. The strategy uses a dual Simple Moving Average (SMA) system combined with price range analysis to identify potential trading opportunities. It can be used on major indices and other markets with sufficient liquidity.
The strategy includes:
Trading System
Fast SMA for entry/exit points (5, 10, 15, 20 periods)
Slow SMA for trend reference (100, 200 periods)
Price range analysis (20% threshold)
Position management rules
Visual Elements
Gradient color indicators
Three themes (Dark/Light/Custom)
ATR-based visuals
Signal zones
Status Table
Current position information
Basic performance metrics
Strategy parameters
Optional messages
📊 Strategy Settings
Main Settings
Trading Mode
Options: Long Only, Short Only, Both
Default: Long Only
Position Size: 10% of equity
Starting Capital: $20,000
Moving Averages
Fast SMA: 5, 10, 15, or 20 periods
Slow SMA: 100 or 200 periods
Default: Fast=5, Slow=100
🎯 Entry and Exit Rules
Long Entry Conditions
All conditions must be met:
Price below Fast SMA
Price below 20% of current bar's range
Price above Slow SMA
No existing position
Short Entry Conditions
All conditions must be met:
Price above Fast SMA
Price above 80% of current bar's range
Price below Slow SMA
No existing position
Exit Rules
Long Positions
Exit when price crosses above Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
Short Positions
Exit when price crosses below Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
💼 Risk Management
Position Sizing
Default: 10% of equity per trade
Initial capital: $20,000
Commission: 0.01%
Slippage: 2 points
Maximum one position at a time
Risk Control
Use daily timeframe only
Avoid trading during major news events
Consider market conditions
Monitor overall exposure
📊 Performance Dashboard
The strategy includes a comprehensive status table displaying:
Strategy Parameters
Current SMA settings
Trading direction
Fast/Slow SMA ratio
Current Status
Active position (Flat/Long/Short)
Current price with color coding
Position status indicators
Performance Metrics
Net Profit (USD and %)
Win Rate with color grading
Profit Factor with thresholds
Maximum Drawdown percentage
Average Trade value
📱 Alert Settings
Entry Alerts
Long Entry (Buy Signal)
Short Entry (Sell Signal)
Exit Alerts
Long Exit (Take Profit)
Short Exit (Take Profit)
Alert Message Format
Strategy name
Signal type and direction
Current price
Fast SMA value
Slow SMA value
💡 Usage Tips
Consider starting with Long Only mode
Begin with default settings
Keep track of your trades
Review results regularly
Adjust settings as needed
Follow your trading plan
⚠️ Disclaimer
This strategy is for educational and informational purposes only. It is not financial advice. Always:
Conduct your own research
Test thoroughly before live trading
Use proper risk management
Consider your trading goals
Monitor market conditions
Never risk more than you can afford to lose
📋 Release Notes
14 January 2025
Added New Fast & Slow SMA Options:
Fibonacci-based periods: 8, 13, 21, 144, 233, 377
Additional period: 50
Complete Fast SMA options now: 5, 8, 10, 13, 15, 20, 21, 34, 50
Complete Slow SMA options now: 100, 144, 200, 233, 377
Bug Fixes:
Fixed Maximum Drawdown calculation in the performance table
Now using strategy.max_drawdown_percent for accurate DD reporting
Previous version showed incorrect DD values
Performance metrics now accurately reflect trading results
Performance Note:
Strategy tested with Fast/Slow SMA 13/377
Test conducted with 10% equity risk allocation
Daily Timeframe
For Beginners - How to Modify SMA Levels:
Find this line in the code:
fastLength = input.int(title="Fast SMA Length", defval=5, options= )
To add a new Fast SMA period: Add the number to the options list, e.g.,
To remove a Fast SMA period: Remove the number from the options list
For Slow SMA, find:
slowLength = input.int(title="Slow SMA Length", defval=100, options= )
Modify the options list the same way
⚠️ Note: Keep the periods that make sense for your trading timeframe
💡 Tip: Test any new combinations thoroughly before live trading
"Trade with Discipline, Manage Risk, Stay Consistent" - tradeviZion
Landry Light Pine ScannerLandry Light Pine Scanner
The Landry Light Pine Scanner is a comprehensive technical analysis tool designed to identify stocks showing strong upward trends based on the Landry Light methodology. It scans for stocks where:
Today's low and yesterday's low are above the 30 EMA.
The low from two days ago is below the 30 EMA.
SMA 50 is above SMA 150, and SMA 150 is above SMA 200 (a strong bullish SMA hierarchy).
Features:
Trend Detection: Automatically highlights stocks with strong bullish trends based on EMA and SMA alignment.
Customizable Inputs: Users can adjust EMA and SMA lengths to fit their trading style.
Visual Clarity: Plots the 30 EMA, SMA 50, SMA 150, and SMA 200 directly on the chart for easy analysis.
Alert Ready: Integrated with TradingView's alert system to notify users when the conditions are met.
Chart Highlights: Automatically highlights bars that meet the conditions with a subtle green background.
Use Case:
This indicator is ideal for swing traders and position traders looking for potential breakout opportunities. By filtering stocks with a bullish structure, traders can focus on high-probability setups.
Conditions Used:
30 EMA Conditions:
Today's low is above the 30 EMA.
Yesterday's low is above the 30 EMA.
The low from two days ago is below the 30 EMA.
SMA Hierarchy:
SMA 50 is above SMA 150.
SMA 150 is above SMA 200.
Customization Options:
30 EMA Length: Adjustable to match user preferences.
SMA Lengths: SMA 50, SMA 150, and SMA 200 lengths are customizable for flexibility.
Alerts:
Users can set alerts for when the defined conditions are met, making it easy to monitor multiple stocks.
How to Use:
Apply the Indicator:
Add the indicator to your TradingView chart.
Set Alerts:
Use the built-in alert condition for automated notifications.
Analyze Trends:
Look for green-highlighted bars indicating stocks meeting the criteria.
Screen Stocks:
Use this tool as part of your screener to filter stocks efficiently.
Note:
This indicator does not provide buy or sell signals. Always combine it with other technical and fundamental analysis for informed trading decisions.
Publishing Tags:
Landry Light, EMA, SMA, Trend Analysis, Swing Trading, Position Trading, Technical Analysis, Breakout Scanner, TradingView, Pine Script
Enhanced SMA Signal Box With TargetsEnhanced SMA Signal Box With Targets
The Enhanced SMA Signal Box With Targets indicator is a versatile tool designed to help traders identify buy and sell signals based on various technical analysis methods, including Simple Moving Averages (SMA), Exponential Moving Averages (EMA), and Average True Range (ATR). This indicator provides clear visual signals and target levels to assist traders in making informed decisions.
Key Features
Simple Moving Averages (SMA):
20 SMA: Represents short-term price trends.
50 SMA: Represents long-term price trends.
Exponential Moving Average (EMA):
50 EMA: Adds additional trend confirmation to the SMA.
Signal Visualization:
Buy Signals: Displayed with a green "🚀" emoji below the candle when the closing price crosses above the 20 SMA.
Sell Signals: Displayed with a red "💣" emoji above the candle when the closing price crosses below the 20 SMA.
Yellow Box: Highlights the signal candle, making it easy to identify the most recent and historical signals.
Target Prices:
First Target: Based on the size of the signal candle.
Second and Third Targets: Calculated using the ATR multiplied by a user-defined factor to help set profit-taking levels.
Customizable Filters:
MACD Filter: Users can enable this filter to use MACD line crossings for signal confirmation.
Higher Timeframe SMA Filter: Users can set a higher timeframe SMA to filter signals based on the long-term trend.
Volume Filter: Users can set a minimum volume threshold for signals.
Alerts:
Users can enable alerts for buy and sell signals, ensuring they never miss a trading opportunity.
Customizable Settings:
Line Colors and Thickness: Users can adjust the colors and thickness of the SMAs, EMA, and signal boxes.
Signal Emojis: Users can choose custom emojis for buy and sell signals.
How It Works
Trend Calculation: The indicator calculates short-term and long-term trends using the 20 SMA, 50 SMA, and 50 EMA.
Signal Generation: Buy and sell signals are generated when the price crosses the 20 SMA, with optional confirmation from MACD and volume filters.
Target Calculation: Profit targets are based on the size of the signal candle and ATR, helping traders set realistic profit-taking levels.
Important Notice
This indicator is designed for educational purposes and should not be considered as financial advice. Past performance does not guarantee future results. Users should conduct their own research and analysis before making any trading decisions. Trading involves substantial risk and is not suitable for every investor. Always consider your financial situation, investment objectives, and risk tolerance before trading. Please ensure you comply with all the relevant regulations and TradingView's house rules while using this indicator.
Volatility Signaling 50SMAOverview of the Script:
The script implements a volatility signaling indicator using a 50-period Simple Moving Average (SMA). It incorporates Bollinger Bands and the Average True Range (ATR) to dynamically adjust the SMA's color based on volatility conditions. Here's a detailed breakdown:
Components of the Script:
1. Inputs:
The script allows the user to customize key parameters for flexibility:
Bollinger Bands Length (length): Determines the period for calculating the Bollinger Bands.
Source (src): The price data to use, defaulting to the closing price.
Standard Deviation Multiplier (mult): Scales the Bollinger Bands' width.
ATR Length (atrLength): Sets the period for calculating the ATR.
The 50-period SMA length (smaLength) is fixed at 50.
2. Bollinger Bands Calculation:
Basis: Calculated as the SMA of the selected price source over the specified length.
Upper and Lower Bands: Determined by adding/subtracting a scaled standard deviation (dev) from the basis.
3. ATR Calculation:
Computes the Average True Range over the user-defined atrLength.
4. Volatility-Based Conditions:
The script establishes thresholds for Bollinger Band width relative to ATR:
Yellow Condition: When the band width (upper - lower) is less than 1.25 times the ATR.
Orange Condition: When the band width is less than 1.5 times the ATR.
Red Condition: When the band width is less than 1.75 times the ATR.
5. Dynamic SMA Coloring:
The 50-period SMA is colored based on the above conditions:
Yellow: Indicates relatively low volatility.
Orange: Indicates moderate volatility.
Red: Indicates higher volatility.
White: Default color when no conditions are met.
6. Plotting the 50-Period SMA:
The script plots the SMA (sma50) with a dynamically assigned color, enabling visual analysis of market conditions.
Use Case:
This script is ideal for traders seeking to assess market volatility and identify changes using Bollinger Bands and ATR. The colored SMA provides an intuitive way to gauge market dynamics directly on the chart.
Example Visualization:
Yellow SMA: The market is in a low-volatility phase.
Orange SMA: Volatility is picking up but remains moderate.
Red SMA: Higher volatility, potentially signaling significant market activity.
White SMA: Neutral/default state.
MACD Aggressive Scalp SimpleComment on the Script
Purpose and Structure:
The script is a scalping strategy based on the MACD indicator combined with EMA (50) as a trend filter.
It uses the MACD histogram's crossover/crossunder of zero to trigger entries and exits, allowing the trader to capitalize on short-term momentum shifts.
The use of strategy.close ensures that positions are closed when specified conditions are met, although adjustments were made to align with Pine Script version 6.
Strengths:
Simplicity and Clarity: The logic is straightforward and focuses on essential scalping principles (momentum-based entries and exits).
Visual Indicators: The plotted MACD line, signal line, and histogram columns provide clear visual feedback for the strategy's operation.
Trend Confirmation: Incorporating the EMA(50) as a trend filter helps avoid trades that go against the prevailing trend, reducing the likelihood of false signals.
Dynamic Exit Conditions: The conditional logic for closing positions based on weakening momentum (via MACD histogram change) is a good way to protect profits or minimize losses.
Potential Improvements:
Parameter Inputs:
Make the MACD (12, 26, 9) and EMA(50) values adjustable by the user through input statements for better customization during backtesting.
Example:
pine
Copy code
macdFast = input(12, title="MACD Fast Length")
macdSlow = input(26, title="MACD Slow Length")
macdSignal = input(9, title="MACD Signal Line Length")
emaLength = input(50, title="EMA Length")
Stop Loss and Take Profit:
The strategy currently lacks explicit stop-loss or take-profit levels, which are critical in a scalping strategy to manage risk and lock in profits.
ATR-based or fixed-percentage exits could be added for better control.
Position Size and Risk Management:
While the script uses 50% of equity per trade, additional options (e.g., fixed position sizes or risk-adjusted sizes) would be beneficial for flexibility.
Avoid Overlapping Signals:
Add logic to prevent overlapping signals (e.g., opening a new position immediately after closing one on the same bar).
Backtesting Optimization:
Consider adding labels or markers (label.new or plotshape) to visualize entry and exit points on the chart for better debugging and analysis.
The inclusion of performance metrics like max drawdown, Sharpe ratio, or profit factor would help assess the strategy's robustness during backtesting.
Compatibility with Live Trading:
The strategy could be further enhanced with alert conditions using alertcondition to notify the trader of buy/sell signals in real-time.
LiquidFusion SignalPro [CHE] LiquidFusion SignalPro – Indicator Overview
The LiquidFusion SignalPro is a powerful and sophisticated TradingView indicator designed to identify high-quality trade entries and exits. By combining seven unique sub-indicators, it provides comprehensive market analysis, ensuring traders can make informed decisions. This tool is suitable for all market conditions and supports customization to fit individual trading strategies.
Key Components (Sub-Indicators):
1. RPM (Relative Price Momentum):
- Measures cumulative price momentum over a specified period.
- Provides insights into price strength and directional bias.
- Input Customization:
- Source: Data for momentum calculation.
- Period: Length for momentum measurement.
- Resolution: Timeframe for data fetching.
2. BBO (Bull-Bear Oscillator):
- Calculates the strength of bullish or bearish momentum based on price movement and RSI conditions.
- Uses a super-smoothing technique for reliable signals.
- Customizable parameters include the oscillator's period and repainting options.
3. MACD (Moving Average Convergence Divergence):
- A classic momentum indicator for trend direction and strength.
- Provides buy/sell signals based on the crossover of the MACD line and signal line.
- Input Customization:
- Fast/Slow EMA Periods.
- Signal Line Period.
- Resolution and Source Data.
4. RSI (Relative Strength Index):
- Tracks overbought and oversold conditions.
- A key tool to validate trend continuation or reversals.
- Customizable period, resolution, and source.
5. CCI (Commodity Channel Index):
- Measures the deviation of price from its average.
- Useful for identifying cyclical trends.
- Input Customization includes period, resolution, and source.
6. Stochastic Oscillator:
- Indicates momentum by comparing closing prices to a range of highs and lows.
- Includes smoothing factors for %K and %D lines.
- Customizable parameters:
- %K Length and Smoothing.
- Resolution and Repainting Options.
7. Supertrend:
- A trailing stop-and-reverse system for trend-following strategies.
- Excellent for identifying strong trends and potential reversals.
- Inputs include the multiplier factor and period for ATR-like calculations.
Inputs Overview:
The indicator supports extensive customization for each sub-indicator, grouped under intuitive categories:
- Color Settings: Define bullish and bearish plot colors.
- RPM, BBO, MACD, RSI, CCI, Stochastic, and Supertrend Settings: Tailor each sub-indicator's behavior with adjustable parameters.
- UI Options: Toggle features such as bar coloring, indicator names, and plotted candles.
Trade Signals:
- Long Signal:
- All indicators align in a bullish state:
- RPM > 0, MACD > 0, RSI > 50, Stochastic > 50, CCI > 0, BBO > 0, Supertrend below price.
- Plot: Green triangle below the candle.
- Alert: Notifies the trader of a potential long entry.
- Short Signal:
- All indicators align in a bearish state:
- RPM < 0, MACD < 0, RSI < 50, Stochastic < 50, CCI < 0, BBO < 0, Supertrend above price.
- Plot: Red triangle above the candle.
- Alert: Notifies the trader of a potential short entry.
Features:
- Enhanced Visuals: Plots sub-indicator statuses using labels and color-coded shapes for clarity.
- Alerts: Integrated alert conditions for both long and short trades.
- Bar Coloring: Provides overall trend bias with green (bullish), red (bearish), or gray (neutral) bars.
- Customizable Table: Displays the indicator's status in the chart’s top-right corner.
Trading Benefits:
The LiquidFusion SignalPro excels in generating high-quality entries and exits by:
- Reducing noise through multiple indicator alignment.
- Supporting multiple timeframes and resolutions for flexibility.
- Offering customizable inputs for personalized trading strategies.
Use this tool to enhance your market analysis and improve your trading performance.
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
This indicator is inspired by the Super 6x Indicators: RSI, MACD, Stochastic, Loxxer, CCI, and Velocity . A special thanks to Loxx for their relentless effort, creativity, and contributions to the TradingView community, which served as a foundation for this work.
Happy trading and best regards
Chervolino
WiseOwl Indicator - 1.0 The WiseOwl Indicator - 1.0 is a technical analysis tool designed to help traders identify potential entry points and market trends based on Exponential Moving Averages (EMAs) across multiple timeframes. It focuses on providing clear visual cues for bullish and bearish market conditions, as well as potential breakout opportunities.
Key Features
Multi-Timeframe EMA Analysis: Calculates EMAs on the current timeframe, Daily timeframe, and 15-minute timeframe to confirm trends.
Bullish and Bearish Market Identification: Determines market conditions based on the 200-period EMA on the Daily timeframe.
Directional Candle Coloring: Highlights candles based on their position relative to EMAs to provide immediate visual feedback.
Entry Signals: Plots buy and sell signals on the chart when specific conditions are met on the 1-hour and 4-hour timeframes.
Breakout Candle Highlighting: Colors candles differently when significant price movements occur, indicating potential breakout opportunities.
How It Works
Market Condition Determination:
Bullish Market: When the close price is above the 200-period EMA on the Daily timeframe.
Bearish Market: When the close price is below the 200-period EMA on the Daily timeframe.
Directional Candle Coloring:
Green Background: Applied when the close is above the 50-period EMA and the market is not bearish.
Red Background: Applied when the close is below the 50-period EMA and the market is not bullish.
Uses the Average True Range (ATR) to define a range threshold.
Suppresses signals when EMAs are within this range, indicating a sideways market.
Plotting Entry Signals:
Plots arrows on the chart for potential long and short entries on the 1-hour and 4-hour timeframes.
Breakout Candle Coloring:
Colors candles blue when a bullish breakout condition is met.
Colors candles orange when a bearish breakout condition is met.
How to Use
Trend Identification: Use the background coloring to quickly identify the overall market trend.
Green Background: Suggests bullish conditions; consider looking for long opportunities.
Red Background: Suggests bearish conditions; consider looking for short opportunities.
Entry Signals: Look for plotted arrows on the chart.
Green Upward Arrow: Indicates a potential long entry signal on the 1-hour or 4-hour timeframe.
Red Downward Arrow: Indicates a potential short entry signal on the 1-hour or 4-hour timeframe.
Breakout Opportunities: Watch for candles colored blue or orange.
Blue Candles: Highlight significant upward price movements.
Orange Candles: Highlight significant downward price movements.
Avoiding Ranging Markets: Be cautious when signals are suppressed due to ranging conditions; the market may not have a clear direction.
Example Usage
Identifying a Bullish Market:
The background turns green.
Price crosses above the 50 EMA.
A green upward arrow appears below a candle on the 1-hour or 4-hour chart.
Identifying a Bearish Market:
The background turns red.
Price crosses below the 50 EMA.
A red downward arrow appears above a candle on the 1-hour or 4-hour chart.
Notes
Open-Source Code: The script is open-source, allowing users to review and understand the logic behind the indicator.
Educational Purpose: This indicator is intended to aid in technical analysis and should not be used as the sole basis for trading decisions.
Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Trading involves risk, and you should consult with a qualified financial advisor before making any investment decisions.
AutoCorrelation Test [OmegaTools]Overview
The AutoCorrelation Test indicator is designed to analyze the correlation patterns of a financial asset over a specified period. This tool can help traders identify potential predictive patterns by measuring the relationship between sequential returns, effectively assessing the autocorrelation of price movements.
Autocorrelation analysis is useful in identifying the consistency of directional trends (upward or downward) and potential cyclical behavior. This indicator provides an insight into whether recent price movements are likely to continue in a similar direction (positive correlation) or reverse (negative correlation).
Key Features
Multi-Period Autocorrelation: The indicator calculates autocorrelation across three periods, offering a granular view of price movement consistency over time.
Customizable Length & Sensitivity: Adjustable parameters allow users to tailor the length of analysis and sensitivity for detecting correlation.
Visual Aids: Three separate autocorrelation plots are displayed, along with an average correlation line. Dotted horizontal lines mark the thresholds for positive and negative correlation, helping users quickly assess potential trend continuation or reversal.
Interpretive Table: A table summarizing correlation status for each period helps traders make quick, informed decisions without needing to interpret the plot details directly.
Parameters
Source: Defines the price source (default: close) for calculating autocorrelation.
Length: Sets the analysis period, ranging from 10 to 2000 (default: 200).
Sensitivity: Adjusts the threshold sensitivity for defining correlation as positive or negative (default: 2.5).
Interpretation
Above 50 + Sensitivity: Indicates Positive Correlation. The price movements over the selected period are likely to continue in the same direction, potentially signaling a trend continuation.
Below 50 - Sensitivity: Indicates Negative Correlation. The price movements show a likelihood of reversing, which could signal an upcoming trend reversal.
Between 50 ± Sensitivity: Indicates No Correlation. Price movements are less predictable in direction, with no clear trend continuation or reversal tendency.
How It Works
The indicator calculates the logarithmic returns of the selected source price over each length period.
It then compares returns over consecutive periods, categorizing them as either "winning" (consistent direction) or "losing" (inconsistent direction) movements.
The result for each period is displayed as a percentage, with values above 50% indicating a higher degree of directional consistency (positive or negative).
A table updates with descriptive labels (Positive Correlation, Negative Correlation, No Correlation) for each tested period, providing a quick overview.
Visual Elements
Plots:
AutoCorrelation Test : Displays autocorrelation for the closest period (lag 1).
AutoCorrelation Test : Displays autocorrelation for the second period (lag 2).
AutoCorrelation Test : Displays autocorrelation for the third period (lag 3).
Average: Displays the simple moving average of the three test periods for a smoothed view of overall correlation trends.
Horizontal Lines:
No Correlation (50%): A baseline indicating neutral correlation.
Positive/Negative Correlation Thresholds: Dotted lines set at 50 ± Sensitivity, marking the thresholds for significant correlation.
Usage Guide
Adjust Parameters:
Select the Source to define which price metric (e.g., close, open) will be analyzed.
Set the Length based on your preferred analysis window (e.g., shorter for intraday trends, longer for swing trading).
Modify Sensitivity to fine-tune the thresholds based on market volatility and personal trading preference.
Interpret Table and Plots:
Use the table to quickly check the correlation status of each lag period.
Analyze the plots for changes in correlation. If multiple lags show positive correlation above the sensitivity threshold, a trend continuation may be expected. Conversely, negative values suggest a potential reversal.
Integrate with Other Indicators:
For enhanced insights, consider using the AutoCorrelation Test indicator in conjunction with other trend or momentum indicators.
This indicator offers a powerful method to assess market conditions, identify potential trend continuations or reversals, and better inform trading decisions. Its customization options provide flexibility for various trading styles and timeframes.
Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Dont make me crossStrategy Overview
This trading strategy utilizes Exponential Moving Averages (EMAs) to generate buy and sell signals based on the crossover of two EMAs, which are shifted downwards by 50 points. The strategy aims to identify potential market reversals and trends based on these crossovers.
Components of the Strategy
Exponential Moving Averages (EMAs):
Short EMA: This is calculated over a shorter period (default is 9 periods) and is more responsive to recent price changes.
Long EMA: This is calculated over a longer period (default is 21 periods) and provides a smoother view of the price trend.
Both EMAs are adjusted by a fixed shift amount of -50 points.
Input Parameters:
Short EMA Length: The period used to calculate the short-term EMA. This can be adjusted based on the trader's preference or market conditions.
Long EMA Length: The period used for the long-term EMA, also adjustable.
Shift Amount: A fixed value (default -50) that is subtracted from both EMAs to shift their values downwards. This is useful for visual adjustments or specific strategy requirements.
Plotting:
The adjusted EMAs are plotted on the price chart. The short EMA is displayed in blue, and the long EMA is displayed in red. This visual representation helps traders identify the crossover points easily.
Signal Generation:
Buy Signal: A buy signal is generated when the short EMA crosses above the long EMA. This is interpreted as a bullish signal, indicating potential upward price movement.
Sell Signal: A sell signal occurs when the short EMA crosses below the long EMA, indicating potential downward price movement.
Trade Execution:
When a buy signal is triggered, the strategy enters a long position.
Conversely, when a sell signal is triggered, the strategy enters a short position.
Trading Logic
Market Conditions: The strategy is most effective in trending markets. During sideways or choppy market conditions, it may generate false signals.
Risk Management: While this script does not include explicit risk management features (like stop-loss or take-profit), traders should consider implementing these to manage their risk effectively.
Customization
Traders can customize the EMA lengths and the shift amount based on their analysis and preferences.
The strategy can also be enhanced with additional indicators, such as volume or volatility measures, to filter signals further.
Use Cases
This strategy can be applied to various timeframes, such as intraday, daily, or weekly charts, depending on the trader's style.
It is suitable for both novice and experienced traders, offering a straightforward approach to trading based on technical analysis.
Summary
The EMA Crossover Strategy with a -50 shift is a straightforward technical analysis approach that capitalizes on the momentum generated by the crossover of short and long-term EMAs. By shifting the EMAs downwards, the strategy can help traders visualize potential entry and exit points more clearly, although it's important to consider additional risk management and market context for effective trading.
Crypto Volatility Bitcoin Correlation Strategy Description:
The Crypto Volatility Bitcoin Correlation Strategy is designed to leverage market volatility specifically in Bitcoin (BTC) using a combination of volatility indicators and trend-following techniques. This strategy utilizes the VIXFix (a volatility indicator adapted for crypto markets) and the BVOL7D (Bitcoin 7-Day Volatility Index from BitMEX) to identify periods of high volatility, while confirming trends with the Exponential Moving Average (EMA). These components work together to offer a comprehensive system that traders can use to enter positions when volatility and trends are aligned in their favor.
Key Features:
VIXFix (Volatility Index for Crypto Markets): This indicator measures the highest price of Bitcoin over a set period and compares it with the current low price to gauge market volatility. A rise in VIXFix indicates increasing market volatility, signaling that large price movements could occur.
BVOL7D (Bitcoin 7-Day Volatility Index): This volatility index, provided by BitMEX, measures the volatility of Bitcoin over the past 7 days. It helps traders monitor the recent volatility trend in the market, particularly useful when making short-term trading decisions.
Exponential Moving Average (EMA): The 50-period EMA acts as a trend indicator. When the price is above the EMA, it suggests the market is in an uptrend, and when the price is below the EMA, it suggests a downtrend.
How It Works:
Long Entry: A long position is triggered when both the VIXFix and BVOL7D indicators are rising, signaling increased volatility, and the price is above the 50-period EMA, confirming that the market is trending upward.
Exit: The strategy exits the position when the price crosses below the 50-period EMA, which signals a potential weakening of the uptrend and a decrease in volatility.
This strategy ensures that traders only enter positions when the volatility aligns with a clear trend, minimizing the risk of entering trades during periods of market uncertainty.
Testing and Timeframe:
This strategy has been tested on Bitcoin using the daily timeframe, which provides a longer-term perspective on market trends and volatility. However, users can adjust the timeframe according to their trading preferences. It is crucial to note that this strategy does not include comprehensive risk management, aside from the exit condition when the price crosses below the EMA. Users are strongly advised to implement their own risk management techniques, such as setting appropriate stop-loss levels, to safeguard their positions during high volatility periods.
Utility:
The Crypto Volatility Bitcoin Correlation Strategy is particularly well-suited for traders who aim to capitalize on the high volatility often seen in the Bitcoin market. By combining volatility measurements (VIXFix and BVOL7D) with a trend-following mechanism (EMA), this strategy helps identify optimal moments for entering and exiting trades. This approach ensures that traders participate in potentially profitable market moves while minimizing exposure during times of uncertainty.
Use Cases:
Volatility-Based Entries: Traders looking to take advantage of market volatility spikes will find this strategy useful for timing entry points during market swings.
Trend Confirmation: By using the EMA as a confirmation tool, traders can avoid entering trades that go against the trend, which can result in significant losses during volatile market conditions.
Risk Management: While the strategy exits when price falls below the EMA, it is important to recognize that this is not a full risk management system. Traders should use caution and integrate additional risk measures, such as stop-losses and position sizing, to better manage potential losses.
How to Use:
Step 1: Monitor the VIXFix and BVOL7D indicators. When both are rising and the Bitcoin price is above the EMA, the strategy will trigger a long entry, indicating that the market is experiencing increased volatility with a confirmed uptrend.
Step 2: Exit the position when the price drops below the 50-period EMA, signaling that the trend may be reversing or weakening, reducing the likelihood of continued upward price movement.
This strategy is open-source and is intended to help traders navigate volatile market conditions, particularly in Bitcoin, using proven indicators for volatility and trend confirmation.
Risk Disclaimer:
This strategy has been tested on the daily timeframe of Bitcoin, but users should be aware that it does not include built-in risk management except for the below-EMA exit condition. Users should be extremely cautious when using this strategy and are encouraged to implement their own risk management, such as using stop-losses, position sizing, and setting appropriate limits. Trading involves significant risk, and this strategy does not guarantee profits or prevent losses. Past performance is not indicative of future results. Always test any strategy in a demo environment before applying it to live markets.
Enhanced Economic Composite with Dynamic WeightEnhanced Economic Composite with Dynamic Weight
Overview of the Indicator :
The "Enhanced Economic Composite with Dynamic Weight" is a comprehensive tool that combines multiple economic indicators, technical signals, and dynamic weighting to provide insights into market and economic health. It adjusts based on current volatility and recession risk, offering a detailed view of market conditions.
What This Indicator Does :
Tracks Economic Health: Uses key economic and market indicators to assess overall market conditions.
Dynamic Weighting: Adjusts the importance of components like stock indices, gold, and bonds based on volatility (VIX) and yield curve inversion.
Technical Signals: Identifies market momentum shifts through key crossovers like the Golden Cross, Death Cross, Silver Cross, and Hospice Cross.
Recession Shading: Marks known recessions for historical context.
Economic Factors Considered :
TIP (Treasury Inflation-Protected Securities): Reflects inflation expectations.
Gold: A safe-haven asset, increases in weight during volatility or rising momentum.
US Dollar Index (DXY): Measures USD strength, fixed weight of 10%, smoothed with EMA.
Commodities (DBC): Indicates global demand; weight increases with momentum or volatility.
Volatility Index (VIX): Reflects market risk, inversely related to market confidence.
Stock Indices (S&P 500, DJIA, NASDAQ, Russell 2000): Represent market performance, with weights reduced during high volatility or negative yield spread.
Yield Spread (10Y - 2Y Treasuries): Predicts recessions; negative spread reduces stock weighting.
Credit Spread (HYG - TLT): Indicates market risk through corporate vs. government bond yields.
How and Why Factors are Weighted:
Stock Indices get more weight in stable markets (low VIX, positive yield spread), while safe-haven assets like gold and bonds gain weight in volatile markets or during yield curve inversions. This dynamic adjustment ensures the composite reflects current market sentiment.
Technical Signals:
Golden Cross: 50 EMA crossing above 200 SMA, signaling bullish momentum.
Death Cross: 50 EMA below 200 SMA, indicating bearish momentum.
Silver Cross: 21 EMA crossing above 50 EMA, plotted only if below the 200-day SMA, signaling potential upside in downtrend conditions.
Hospice Cross: 50 EMA crosses below 21 EMA, plotted only if 21 EMA is below 200 SMA, a leading bearish signal.
Recession Shading:
Recession periods like the Great Recession, Early 2000s Recession, and COVID-19 Recession are shaded to provide historical context.
Benefits of Using This Indicator:
Comprehensive Analysis: Combines economic fundamentals and technical analysis for a full market view.
Dynamic Risk Adjustment: Weights shift between growth and safe-haven assets based on volatility and recession risk.
Early Signals: The Silver Cross and Hospice Cross provide early warnings of potential market shifts.
Recession Forecasting: Helps predict downturns through the yield curve and recession indicators.
Who Can Benefit:
Traders: Identify market momentum shifts early through crossovers.
Long-term Investors: Use recession warnings and dynamic adjustments to protect portfolios.
Analysts: A holistic tool for analyzing both economic trends and market movements.
This indicator helps users navigate varying market conditions by dynamically adjusting based on economic factors and providing early technical signals for market momentum shifts.
Autotable█ OVERVIEW
The library allows to automatically draw a table based on a string or float matrix (or both) controlling all of the parameters of the table (including merging cells) with parameter matrices (like, e.g. matrix of cell colors).
All things you would normally do with table.new() and table.cell() are now possible using respective parameters of library's main function, autotable() (as explained further below).
Headers can be supplied as arrays.
Merging of the cells is controlled with a special matrix of "L" and "U" values which instruct a cell to merged with the cell to the left or upwards (please see examples in the script and in this description).
█ USAGE EXAMPLES
The simplest and most straightforward:
mxF = matrix.new(3,3, 3.14)
mxF.autotable(bgcolor = color.rgb(249, 209, 29)) // displays float matrix as a table in the top right corner with defalult settings
mxS = matrix.new(3,3,"PI")
// displays string matrix as a table in the top right corner with defalult settings
mxS.autotable(Ypos = "bottom", Xpos = "right", bgcolor = #b4d400)
// displays matrix displaying a string value over a float value in each cell
mxS.autotable(mxF, Ypos = "middle", Xpos = "center", bgcolor = color.gray, text_color = #86f62a)
Draws this:
Tables with headers:
if barstate.islast
mxF = matrix.new(3,3, 3.14)
mxS = matrix.new(3,3,"PI")
arColHeaders = array.from("Col1", "Col2", "Col3")
arRowHeaders = array.from("Row1", "Row2", "Row3")
// float matrix with col headers
mxF.autotable(
bgcolor = #fdfd6b
, arColHeaders = arColHeaders
)
// string matrix with row headers
mxS.autotable(arRowHeaders = arRowHeaders, Ypos = "bottom", Xpos = "right", bgcolor = #b4d400)
// string/float matrix with both row and column headers
mxS.autotable(mxF
, Ypos = "middle", Xpos = "center"
, arRowHeaders = arRowHeaders
, arColHeaders = arColHeaders
, cornerBgClr = #707070, cornerTitle = "Corner\ncell", cornerTxtClr = #ffdc13
, bgcolor = color.gray, text_color = #86f62a
)
Draws this:
█ FUNCTIONS
One main function is autotable() which has only one required argument mxValS, a string matrix.
Please see below the description of all of the function parameters:
The table:
tbl (table) (Optional) If supplied, this table will be deleted.
The data:
mxValS (matrix ) (Required) Cell text values
mxValF (matrix) (Optional) Numerical part of cell text values. Is concatenated to the mxValS values via `string_float_separator` string (default "\n")
Table properties, have same effect as in table.new() :
defaultBgColor (color) (Optional) bgcolor to be used if mxBgColor is not supplied
Ypos (string) (Optional) "top", "bottom" or "center"
Xpos (string) (Optional) "left", "right", or "center"
frame_color (color) (Optional) frame_color like in table.new()
frame_width (int) (Optional) frame_width like in table.new()
border_color (color) (Optional) border_color like in table.new()
border_width (int) (Optional) border_width like in table.new()
force_overlay (simple bool) (Optional) If true draws table on main pane.
Cell parameters, have same effect as in table.cell() ):
mxBgColor (matrix) (Optional) like bgcolor argument in table.cell()
mxTextColor (matrix) (Optional) like text_color argument in table.cell()
mxTt (matrix) (Optional) like tooltip argument in table.cell()
mxWidth (matrix) (Optional) like width argument in table.cell()
mxHeight (matrix) (Optional) like height argument in table.cell()
mxHalign (matrix) (Optional) like text_halign argument in table.cell()
mxValign (matrix) (Optional) like text_valign argument in table.cell()
mxTextSize (matrix) (Optional) like text_size argument in table.cell()
mxFontFamily (matrix) (Optional) like text_font_family argument in table.cell()
Other table properties:
tableWidth (float) (Optional) Overrides table width if cell widths are non zero. E.g. if there are four columns and cell widths are 20 (either as set via cellW or via mxWidth) then if tableWidth is set to e.g. 50 then cell widths will be 50 * (20 / 80), where 80 is 20*4 = total width of all cells. Works simialar for widths set via mxWidth - determines max sum of widths across all cloumns of mxWidth and adjusts cell widths proportionally to it. If cell widths are 0 (i.e. auto-adjust) tableWidth has no effect.
tableHeight (float) (Optional) Overrides table height if cell heights are non zero. E.g. if there are four rows and cell heights are 20 (either as set via cellH or via mxHeight) then if tableHeigh is set to e.g. 50 then cell heights will be 50 * (20 / 80), where 80 is 20*4 = total height of all cells. Works simialar for heights set via mxHeight - determines max sum of heights across all cloumns of mxHeight and adjusts cell heights proportionally to it. If cell heights are 0 (i.e. auto-adjust) tableHeight has no effect.
defaultTxtColor (color) (Optional) text_color to be used if mxTextColor is not supplied
text_size (string) (Optional) text_size to be used if mxTextSize is not supplied
font_family (string) (Optional) cell text_font_family value to be used if a value in mxFontFamily is no supplied
cellW (float) (Optional) cell width to be used if a value in mxWidth is no supplied
cellH (float) (Optional) cell height to be used if a value in mxHeight is no supplied
halign (string) (Optional) cell text_halign value to be used if a value in mxHalign is no supplied
valign (string) (Optional) cell text_valign value to be used if a value in mxValign is no supplied
Headers parameters:
arColTitles (array) (Optional) Array of column titles. If not na a header row is added.
arRowTitles (array) (Optional) Array of row titles. If not na a header column is added.
cornerTitle (string) (Optional) If both row and column titles are supplied allows to set the value of the corner cell.
colTitlesBgColor (color) (Optional) bgcolor for header row
colTitlesTxtColor (color) (Optional) text_color for header row
rowTitlesBgColor (color) (Optional) bgcolor for header column
rowTitlesTxtColor (color) (Optional) text_color for header column
cornerBgClr (color) (Optional) bgcolor for the corner cell
cornerTxtClr (color) (Optional) text_color for the corner cell
Cell merge parameters:
mxMerge (matrix) (Optional) A matrix determining how cells will be merged. "L" - cell merges to the left, "U" - upwards.
mergeAllColTitles (bool) (Optional) Allows to print a table title instead of column headers, merging all header row cells and leaving just the value of the first cell. For more flexible options use matrix arguments leaving header/row arguments na.
mergeAllRowTitles (bool) (Optional) Allows to print one text value merging all header row cells and leaving just the value of the first cell. For more flexible options use matrix arguments leaving header/row arguments na.
Format:
string_float_separator (string) (Optional) A string used to separate string and float parts of cell values (mxValS and mxValF). Default is "\n"
format (string) (Optional) format string like in str.format() used to format numerical values
nz (string) (Optional) Determines how na numerical values are displayed.
The only other available function is autotable(string,... ) with a string parameter instead of string and float matrices which draws a one cell table.
█ SAMPLE USE
E.g., CSVParser library demo uses Autotable's for generating complex tables with merged cells.
█ CREDITS
The library was inspired by @kaigouthro's matrixautotable . A true master. Many thanks to him for his creative, beautiful and very helpful libraries.
