Volume Spike IndicatorThe Volume Spike Indicator is designed to identify significant volume spikes in the market. This tool helps traders recognize unusual trading activity, which may indicate potential reversals, breakouts, or increased volatility. The indicator uses a simple moving average (SMA) of volume over a specified period and highlights bars where the current volume exceeds a multiple of this average.
Features:
Volume SMA Calculation:
The indicator calculates the SMA of volume over a customizable period (default: 20 bars).
Spike Multiplier:
A threshold multiplier (default: 4) determines what qualifies as a "spike."
Spikes occur when the current volume is greater than the SMA multiplied by this threshold.
Visual Alerts:
If a spike is detected, a red cross ( Cross ) and X-shape ( X-Cross ) are plotted above the corresponding bar for easy identification.
How to Use:
Spot High-Activity Areas:
Use this indicator to find points of unusually high trading activity, which can signify key levels or moments of interest in the market.
Adjust Settings for Sensitivity:
Length : Change the SMA period to match your trading timeframe.
Spike Multiplier : Lower values detect smaller spikes; higher values focus on extreme events.
Combine with Other Indicators:
This tool works best when combined with price action analysis, support/resistance levels, or trend indicators to confirm trading signals.
Customization Options:
Length: Number of bars for SMA calculation (default: 20).
Spike Multiplier: Threshold for defining volume spikes (default: 4).
This indicator is suitable for traders looking to enhance their analysis by identifying abnormal market activity.
在腳本中搜尋"20日线角度大于0的股票"
Enhanced VIP-like IndicatorSettings Breakdown Tutorial: Optimizing a Trading Strategy
This guide explains the key trading strategy settings and how to customize them based on your trading style and goals. Each parameter is essential for tailoring the strategy to market conditions and your risk appetite.
1. Short Moving Average Length (Default: 9)
• Purpose: Tracks short-term trends using a small number of candles.
• Settings Tips:
• Smaller Values (e.g., 9): Quickly react to price changes, useful for fast-moving markets.
• Larger Values (e.g., 12-15): Generate smoother signals for less volatile trades.
2. Long Moving Average Length (Default: 21)
• Purpose: Identifies long-term trends.
• Settings Tips:
• Higher Values (e.g., 50): Spot broader trends at the expense of slower signals.
• Trend Analysis: The interaction of short and long MAs helps determine bullish or bearish trends (e.g., bullish when short MA crosses above long MA).
3. Higher Timeframe MA Length (Default: 200)
• Purpose: Filters long-term trends on a higher timeframe (e.g., daily).
• Settings Tips:
• 200 Periods: Standard for defining bullish (price above) or bearish (price below) markets.
• Adjustable: Use 100 for faster responses or stick with 200 for reliability.
4. Higher Timeframe (Default: 1 Day)
• Purpose: Defines the timeframe for the higher moving average.
• Settings Tips:
• Shorter Timeframes (e.g., 4 Hours): More frequent trading signals.
• Daily Timeframe: Best for swing trading and identifying macro trends.
5. RSI Length (Default: 14)
• Purpose: Measures momentum over a specific number of candles.
• Settings Tips:
• Lower Values (e.g., 7): More sensitive to price changes, ideal for quick trades.
• Higher Values (e.g., 20): Smooth signals for more stable markets.
6. RSI Overbought (70) and Oversold (30) Levels
• Purpose: Marks thresholds for overbought and oversold conditions.
• Settings Tips:
• Stricter Levels (e.g., 80/20): Fewer, higher-quality signals.
• Looser Levels (e.g., 65/35): More frequent signals, suitable for active trading.
7. Pivot Left Bars (5) and Pivot Right Bars (5)
• Purpose: Confirms pivot points (support/resistance) based on surrounding candles.
• Settings Tips:
• Higher Values (e.g., 10): Stronger but less frequent pivot points.
• Lower Values: More responsive, for traders seeking quick pivots.
8. Take Profit Percentage (Default: 2%)
• Purpose: Defines the profit level to exit trades.
• Settings Tips:
• Higher Values (e.g., 5%): For swing traders holding positions longer.
• Lower Values (e.g., 1%): For scalpers focusing on quick trades.
9. Minimum Volume (Default: 1,000,000)
• Purpose: Ensures sufficient liquidity for trading.
• Settings Tips:
• Lower Values: For lower-volume markets.
• Higher Values: Reduces risk in high-liquidity assets.
10. Stop Loss Percentage (Default: 1%)
• Purpose: Sets the maximum acceptable loss per trade.
• Settings Tips:
• Lower Values (e.g., 0.5%): Reduces risk, suited for conservative trading.
• Higher Values (e.g., 2%): Allows more price fluctuation, ideal for volatile markets.
11. Entry Conditions
• Options:
• MA Crossover & RSI: Combines trend-following and momentum for well-rounded signals.
• Pivot Breakout: Focuses on support/resistance breakouts for high-impact trades.
• Settings Tips:
• Trend-Following Traders: Use MA Crossover & RSI.
12. Exit Conditions
• Options:
• Opposite Signal: Exits when the trade’s opposite condition occurs (e.g., bullish to bearish).
• Fixed Take Profit/Stop Loss: Exits based on predefined profit/loss thresholds.
• Settings Tips:
• Opposite Signal: Ideal for trend-following strategies.
Summary
Customizing these settings aligns the strategy with your trading goals. Test configurations in a demo environment before live trading to refine the approach and optimize results. Always balance profit potential with risk management.
• Fixed Levels: Better for strict risk management.
• Breakout Traders: Opt for Pivot Breakout.
GOLDEN RSI by @thejamiulGOLDEN RSI thejamiul is a versatile Relative Strength Index (RSI)-based tool designed to provide enhanced visualization and additional insights into market trends and potential reversal points. This indicator improves upon the traditional RSI by integrating gradient fills for overbought/oversold zones and divergence detection features, making it an excellent choice for traders who seek precise and actionable signals.
Source of this indicator : This indicator is based on @TradingView original RSI indicator with a little bit of customisation to enhance overbought and oversold identification.
Key Features
1. Customizable RSI Settings:
RSI Length: Adjust the RSI calculation period to suit your trading style (default: 14).
Source Selection: Choose the price source (e.g., close, open, high, low) for RSI calculation.
2. Gradient-Filled RSI Zones:
Overbought Zone (80-100): Gradient fill with shades of green to indicate strong bullish conditions.
Oversold Zone (0-20): Gradient fill with shades of red to highlight strong bearish conditions.
3. Support and Resistance Levels:
Upper Band: 80
Middle Bands: 60 (bullish) and 40 (bearish)
Lower Band: 20
These levels help identify overbought, oversold, and neutral zones.
4. Divergence Detection:
Bullish Divergence: Detects lower lows in price with corresponding higher lows in RSI, signaling potential upward reversals.
Bearish Divergence: Detects higher highs in price with corresponding lower highs in RSI, indicating potential downward reversals.
Visual Indicators:
Bullish divergence is marked with green labels and line plots.
Bearish divergence is marked with red labels and line plots.
5. Alert Functionality:
Custom Alerts: Set up alerts for bullish or bearish divergences to stay notified of potential trading opportunities without constant chart monitoring.
6. Enhanced Chart Visualization:
RSI Plot: A smooth and visually appealing RSI curve.
Color Coding: Gradient and fills for better distinction of trading zones.
Pivot Labels: Clear identification of divergence points on the RSI plot.
Normalized Jurik Moving Average [QuantAlgo]Upgrade your investing and trading strategy with the Normalized Jurik Moving Average (JMA) , a sophisticated oscillator that combines adaptive smoothing with statistical normalization to deliver high-quality signals! Whether you're a swing trader looking for momentum shifts or a medium- to long-term investor focusing on trend validation, this indicator's statistical approach offers valuable analytical advantages that can enhance your trading and investing decisions!
🟢 Core Architecture
The foundation of this indicator lies in its unique dual-layer calculation system. The first layer implements the Jurik Moving Average, known for its superior noise reduction and responsiveness, while the second layer applies statistical normalization (Z-Score) to create standardized readings. This sophisticated approach helps identify significant price movements while filtering out market noise across various timeframes and instruments.
🟢 Technical Foundation
Three key components power this indicator are:
Jurik Moving Average (JMA): An advanced moving average calculation that provides superior smoothing with minimal lag
Statistical Normalization: Z-Score based scaling that creates consistent, comparable readings across different market conditions
Dynamic Zone Detection: Automatically identifies overbought and oversold conditions based on statistical deviations
🟢 Key Features & Signals
The Normalized JMA delivers market insights through:
Color-adaptive oscillator line that reflects momentum strength and direction
Statistically significant overbought/oversold zones for trade validation
Smart gradient fills between signal line and zero level for enhanced visualization
Clear long (L) and short (S) markers for validated momentum shifts
Intelligent bar coloring that highlights the current market state
Customizable alert system for both bullish and bearish setups
🟢 Practical Usage Tips
Here's how to maximize your use of the Normalized JMA:
1/ Setup:
Add the indicator to your favorites, then apply it to your chart ⭐️
Begin with the default smoothing period for balanced analysis
Use the default normalization period for optimal signal generation
Start with standard visualization settings
Customize colors to match your chart preferences
Enable both bar coloring and signal markers for complete visual feedback
2/ Reading Signals:
Watch for L/S markers - they indicate validated momentum shifts
Monitor oscillator line color changes for direction confirmation
Use the built-in alert system to stay informed of potential trend changes
🟢 Pro Tips
Adjust Smoothing Period based on your trading style:
→ Lower values (8-12) for more responsive signals
→ Higher values (20-30) for more stable trend identification
Fine-tune Normalization Period based on market conditions:
→ Shorter periods (20-25) for more dynamic markets
→ Longer periods (40-50) for more stable markets
Optimize your analysis by:
→ Using +2/-2 zones for primary trade signals
→ Using +3/-3 zones for extreme market conditions
→ Combining with volume analysis for trade confirmation
→ Using multiple timeframe analysis for strategic context
Combine with:
→ Volume indicators for trade validation
→ Price action for entry timing
→ Support/resistance levels for profit targets
→ Trend-following indicators for directional bias
Enhanced SMA Strategy with Trend Lines & S&R by DaxThe Enhanced SMA Strategy with Trend Lines & Support/Resistance (S&R) by Dax indicator is a technical analysis tool designed to improve trading decisions by combining the simplicity of the Simple Moving Average (SMA) with the insight provided by trend lines and support/resistance levels. This hybrid approach aims to create a more robust and reliable trading strategy.
Key Components:
Simple Moving Average (SMA):
SMA is a basic trend-following indicator that calculates the average of a set of price data over a specified period. It helps identify the direction of the market, such as whether an asset is in an uptrend or downtrend.
The Enhanced SMA Strategy may use multiple SMAs, such as short-term (e.g., 20-period) and long-term (e.g., 50-period), to detect crossovers that signal buy or sell opportunities. For example, a bullish crossover occurs when a short-term SMA crosses above a long-term SMA, indicating a potential buying signal, while a bearish crossover signals a potential sell.
Trend Lines:
Trend lines are drawn on the price chart to visually identify the direction of the market, acting as dynamic support and resistance levels. A trend line is drawn by connecting two or more price points that demonstrate the overall price movement.
Trend lines can help traders see potential breakout or breakdown points. A price breaking above a downtrend line or below an uptrend line often signals a trend reversal.
Support and Resistance (S&R):
Support levels are price levels where an asset tends to find buying interest and stop falling, while Resistance levels are points where selling pressure emerges and prevent the price from rising further.
These levels are critical in determining where price reversals or consolidations are likely to occur. Enhanced S&R indicators can automatically identify these levels and draw horizontal lines at these critical points on the chart.
Combining S&R with SMA can help traders decide whether a breakout or bounce is likely at these levels, increasing the odds of a successful trade.
How It Works:
Trend Identification: The SMA is used to determine the trend direction. A rising SMA indicates an uptrend, while a falling SMA suggests a downtrend.
Signal Generation: The strategy often uses a combination of SMA crossovers (bullish or bearish) along with the confirmation of price action near trend lines and support/resistance levels. For example:
If a price breaks above resistance and the short-term SMA crosses above the long-term SMA, a buy signal is confirmed.
Conversely, if the price breaks below support and the short-term SMA crosses below the long-term SMA, a sell signal is given.
Dynamic Support/Resistance: Trend lines are drawn automatically or manually to spot areas where price might reverse. The Enhanced SMA Strategy checks if the price is close to these levels, providing a more precise entry/exit point based on the broader market context.
Advantages of the Enhanced SMA Strategy with Trend Lines & S&R:
Improved Accuracy: By combining trend-following (SMA) with key levels like trend lines and S&R, the strategy filters out false signals, leading to more reliable trade setups.
Trend Confirmation: The use of trend lines and S&R confirms the broader market context, reducing the risk of trading against the trend or entering at weak price points.
Flexible: This strategy can be applied to various timeframes, from short-term day trading to longer-term swing trading.
Visual Clarity: The combination of trend lines, S&R, and moving averages provides a clear and visually intuitive strategy for identifying key price levels and trend shifts.
How to Use It:
Draw Trend Lines: Identify the most recent price peaks and troughs to draw trend lines, marking the potential resistance and support levels.
Use SMAs: Apply two different-period SMAs to detect the trend (e.g., 20-period and 50-period). Pay attention to crossovers for buy/sell signals.
Watch for Breakouts or Reversals: Monitor how the price behaves at support or resistance levels and the trend lines. A price move beyond these levels, accompanied by a confirming SMA crossover, can signal a strong trade opportunity.
Conclusion:
The Enhanced SMA Strategy with Trend Lines & S&R by Dax is a powerful, multi-layered approach to technical analysis. It enhances the basic SMA strategy by incorporating additional tools like trend lines and support/resistance levels, which help traders make more informed decisions with higher accuracy. This method is suitable for both novice and experienced traders, offering clear trade signals while reducing the risk of false entries.
Uptrick: Volatility Reversion BandsUptrick: Volatility Reversion Bands is an indicator designed to help traders identify potential reversal points in the market by combining volatility and momentum analysis within one comprehensive framework. It calculates dynamic bands around a simple moving average and issues signals when price interacts with these bands. Below is a fully expanded description, structured in multiple sections, detailing originality, usefulness, uniqueness, and the purpose behind blending standard deviation-based and ATR-based concepts. All references to code have been removed to focus on the written explanation only.
Section 1: Overview
Uptrick: Volatility Reversion Bands centers on a moving average around which various bands are constructed. These bands respond to changes in price volatility and can help gauge potential overbought or oversold conditions. Signals occur when the price moves beyond certain thresholds, which may imply a reversal or significant momentum shift.
Section 2: Originality, Usefulness, Uniqness, Purpose
This indicator merges two distinct volatility measurements—Bollinger Bands and ATR—into one cohesive system. Bollinger Bands use standard deviation around a moving average, offering a baseline for what is statistically “normal” price movement relative to a recent mean. When price hovers near the upper band, it may indicate overbought conditions, whereas price near the lower band suggests oversold conditions. This straightforward construction often proves invaluable in moderate-volatility settings, as it pinpoints likely turning points and gauges a market’s typical trading range.
Yet Bollinger Bands alone can falter in conditions marked by abrupt volatility spikes or sudden gaps that deviate from recent norms. Intraday news, earnings releases, or macroeconomic data can alter market behavior so swiftly that standard-deviation bands do not keep pace. This is where ATR (Average True Range) adds an important layer. ATR tracks recent highs, lows, and potential gaps to produce a dynamic gauge of how much price is truly moving from bar to bar. In quieter times, ATR contracts, reflecting subdued market activity. In fast-moving markets, ATR expands, exposing heightened volatility on each new bar.
By overlaying Bollinger Bands and ATR-based calculations, the indicator achieves a broader situational awareness. Bollinger Bands excel at highlighting relative overbought or oversold areas tied to an established average. ATR simultaneously scales up or down based on real-time market swings, signaling whether conditions are calm or turbulent. When combined, this means a price that barely crosses the Bollinger Band but also triggers a high ATR-based threshold is likely experiencing a volatility surge that goes beyond typical market fluctuations. Conversely, a price breach of a Bollinger Band when ATR remains low may still warrant attention, but not necessarily the same urgency as in a high-volatility regime.
The resulting synergy offers balanced, context-rich signals. In a strong trend, the ATR layer helps confirm whether an apparent price breakout really has momentum or if it is just a temporary spike. In a range-bound market, standard deviation-based Bollinger Bands define normal price extremes, while ATR-based extensions highlight whether a breakout attempt has genuine force behind it. Traders gain clarity on when a move is both statistically unusual and accompanied by real volatility expansion, thus carrying a higher probability of a directional follow-through or eventual reversion.
Practical advantages emerge across timeframes. Scalpers in fast-paced markets appreciate how ATR-based thresholds update rapidly, revealing if a sudden price push is routine or exceptional. Swing traders can rely on both indicators to filter out false signals in stable conditions or identify truly notable moves. By calibrating to changes in volatility, the merged system adapts naturally whether the market is trending, ranging, or transitioning between these phases.
In summary, combining Bollinger Bands (for a static sense of standard-deviation-based overbought/oversold zones) with ATR (for a dynamic read on current volatility) yields an adaptive, intuitive indicator. Traders can better distinguish fleeting noise from meaningful expansions, enabling more informed entries, exits, and risk management. Instead of relying on a single yardstick for all market conditions, this fusion provides a layered perspective, encouraging traders to interpret price moves in the broader context of changing volatility.
Section 3: Why Bollinger Bands and ATR are combined
Bollinger Bands provide a static snapshot of volatility by computing a standard deviation range above and below a central average. ATR, on the other hand, adapts in real time to expansions or contractions in market volatility. When combined, these measures offset each other’s limitations: Bollinger Bands add structure (overbought and oversold references), and ATR ensures responsiveness to rapid price shifts. This synergy helps reduce noisy signals, particularly during sudden market turbulence or extended consolidations.
Section 4: User Inputs
Traders can adjust several parameters to suit their preferences and strategies. These typically include:
1. Lookback length for calculating the moving average and standard deviation.
2. Multipliers to control the width of Bollinger Bands.
3. An ATR multiplier to set the distance for additional reversal bands.
4. An option to display weaker signals when the price merely approaches but does not cross the outer bands.
Section 5: Main Calculations
At the core of this indicator are four important steps:
1. Calculate a basis using a simple moving average.
2. Derive Bollinger Bands by adding and subtracting a product of the standard deviation and a user-defined multiplier.
3. Compute ATR over the same lookback period and multiply it by the selected factor.
4. Combine ATR-based distance with the Bollinger Bands to set the outer reversal bands, which serve as stronger signal thresholds.
Section 6: Signal Generation
The script interprets meaningful reversal points when the price:
1. Crosses below the lower outer band, potentially highlighting oversold conditions where a bullish reversal may occur.
2. Crosses above the upper outer band, potentially indicating overbought conditions where a bearish reversal may develop.
Section 7: Visualization
The indicator provides visual clarity through labeled signals and color-coded references:
1. Distinct colors for upper and lower reversal bands.
2. Markers that appear above or below bars to denote possible buying or selling signals.
3. A gradient bar color scheme indicating a bar’s position between the lower and upper bands, helping traders quickly see if the price is near either extreme.
Section 8: Weak Signals (Optional)
For those preferring early cues, the script can highlight areas where the price nears the outer bands. When weak signals are enabled:
1. Bars closer to the upper reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential selling area.
2. Bars closer to the lower reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential buying area.
Section 9: Simplicity, Effectiveness, and Lower Timeframes
Although combining standard deviation and ATR involves sophisticated volatility concepts, this indicator is visually straightforward. Reversal bands and gradient-colored bars make it easy to see at a glance when price approaches or crosses a threshold. Day traders operating on lower timeframes benefit from such clarity because it helps filter out minor fluctuations and focus on more meaningful signals.
Section 10: Adaptability across Market Phases
Because both the standard deviation (for Bollinger Bands) and ATR adapt to changing volatility, the indicator naturally adjusts to various environments:
1. Trending: The additional ATR-based outer bands help distinguish between temporary pullbacks and deeper reversals.
2. Ranging: Bollinger Bands often remain narrower, identifying smaller reversals, while the outer ATR bands remain relatively close to the main bands.
Section 11: Reduced Noise in High-Volatility Scenarios
By factoring ATR into the band calculations, the script widens or narrows the thresholds during rapid market fluctuations. This reduces the amount of false triggers typically found in indicators that rely solely on fixed calculations, preventing overreactions to abrupt but short-lived price spikes.
Section 12: Incorporation with Other Technical Tools
Many traders combine this indicator with oscillators such as RSI, MACD, or Stochastic, as well as volume metrics. Overbought or oversold signals in momentum oscillators can provide additional confirmation when price reaches the outer bands, while volume spikes may reinforce the significance of a breakout or potential reversal.
Section 13: Risk Management Considerations
All trading strategies carry risk. This indicator, like any tool, can and does produce losing trades if price unexpectedly reverses again or if broader market conditions shift rapidly. Prudent traders employ protective measures:
1. Stop-loss orders or trailing stops.
2. Position sizing that accounts for market volatility.
3. Diversification across different asset classes when possible.
Section 14: Overbought and Oversold Identification
Standard Bollinger Bands highlight regions where price might be overextended relative to its recent average. The extended ATR-based reversal bands serve as secondary lines of defense, identifying moments when price truly stretches beyond typical volatility bounds.
Section 15: Parameter Customization for Different Needs
Users can tailor the script to their unique preferences:
1. Shorter lookback settings yield faster signals but risk more noise.
2. Higher multipliers spread the bands further apart, filtering out small moves but generating fewer signals.
3. Longer lookback periods smooth out market noise, often leading to more stable but less frequent trading cues.
Section 16: Examples of Different Trading Styles
1. Day Traders: Often reduce the length to capture quick price swings.
2. Swing Traders: May use moderate lengths such as 20 to 50 bars.
3. Position Traders: Might opt for significantly longer settings to detect macro-level reversals.
Section 17: Performance Limitations and Reality Check
No technical indicator is free from false signals. Sudden fundamental news events, extreme sentiment changes, or low-liquidity conditions can render signals less reliable. Backtesting and forward-testing remain essential steps to gauge whether the indicator aligns well with a trader’s timeframe, risk tolerance, and instrument of choice.
Section 18: Merging Volatility and Momentum
A critical uniqueness of this indicator lies in how it merges Bollinger Bands (standard deviation-based) with ATR (pure volatility measure). Bollinger Bands provide a relative measure of price extremes, while ATR dynamically reacts to market expansions and contractions. Together, they offer an enhanced perspective on potential market turns, ideally reducing random noise and highlighting moments where price has traveled beyond typical bounds.
Section 19: Purpose of this Merger
The fundamental purpose behind blending standard deviation measures with real-time volatility data is to accommodate different market behaviors. Static standard deviation alone can underreact or overreact in abnormally volatile conditions. ATR alone lacks a baseline reference to normality. By merging them, the indicator aims to provide:
1. A versatile dynamic range for both typical and extreme moves.
2. A filter against frequent whipsaws, especially in choppy environments.
3. A visual framework that novices and experts can interpret rapidly.
Section 20: Summary and Practical Tips
Uptrick: Volatility Reversion Bands offers a powerful tool for traders looking to combine volatility-based signals with momentum-derived reversals. It emphasizes clarity through color-coded bars, defined reversal zones, and optional weak signal markers. While potentially useful across all major timeframes, it demands ongoing risk management, realistic expectations, and careful study of how signals behave under different market conditions. No indicator serves as a crystal ball, so integrating this script into an overall strategy—possibly alongside volume data, fundamentals, or momentum oscillators—often yields the best results.
Disclaimer and Educational Use
This script is intended for educational and informational purposes. It does not constitute financial advice, nor does it guarantee trading success. Sudden economic events, low-liquidity times, and unexpected market behaviors can all undermine technical signals. Traders should use proper testing procedures (backtesting and forward-testing) and maintain disciplined risk management measures.
Pro Stock Scanner + MACD# Pro Stock Scanner - Advanced Trading System
### Professional Scanning System Combining MACD, Momentum & Technical Analysis
## 🎯 Indicator Purpose
This indicator was developed to identify high-quality trading opportunities by combining:
- Strong positive momentum
- Clear technical trend
- Significant trading volume
- Precise MACD signals
## 💡 Core Mechanics
The indicator is based on three core components:
### 1. Advanced MACD Analysis (40%)
- MACD line crossover tracking
- Momentum strength measurement
- Positive/negative divergence detection
- Score range: 0-40 points
### 2. Trend Analysis (40%)
- Moving average relationships (MA20, MA50)
- Primary trend direction
- Current trend strength
- Score range: 0-40 points
### 3. Volume Analysis (20%)
- Comparison with 20-day average volume
- Volume breakout detection
- Score range: 0-20 points
## 📊 Scoring System
Total score (0-100) composition:
```
Total Score = MACD Score (40%) + Trend Score (40%) + Volume Score (20%)
```
### Score Interpretation:
- 80-100: Strong Buy Signal 🔥
- 65-79: Developing Bullish Trend ⬆️
- 50-64: Neutral ↔️
- 0-49: Technical Weakness ⬇️
## 📈 Chart Markers
1. **Large Blue Triangle**
- High score (80+)
- Positive MACD
- Bullish MACD crossover
2. **Small Triangles**
- Green: Bullish MACD crossover
- Red: Bearish MACD crossover
## 🎛️ Customizable Parameters
```
MACD Settings:
- Fast Length: 12
- Slow Length: 26
- Signal Length: 9
- Strength Threshold: 0.2%
Volume Settings:
- Threshold: 1.5x average
```
## 📱 Information Panel
Real-time display of:
1. Total Score
2. MACD Score
3. MACD Strength
4. Volume Score
5. Summary Signal
## ⚙️ Optimization Guidelines
Recommended adjustments:
1. **Bull Market**
- Decrease MACD sensitivity
- Increase volume threshold
- Focus on trend strength
2. **Bear Market**
- Increase MACD sensitivity
- Stricter trend conditions
- Higher score requirements
## 🎯 Recommended Trading Strategy
### Phase 1: Initial Scan
1. Look for 80+ total score
2. Verify sufficient trading volume
3. Confirm bullish MACD crossover
### Phase 2: Validation
1. Check long-term trend
2. Identify nearby resistance levels
3. Review earnings calendar
### Phase 3: Position Management
1. Set clear stop-loss
2. Define realistic profit targets
3. Monitor score changes
## ⚠️ Important Notes
1. This indicator is a supplementary tool
2. Combine with fundamental analysis
3. Strict risk management is essential
4. Not recommended for automated trading
## 📈 Usage Examples
Examples included:
1. Successful buy signal
2. Trend reversal identification
3. False signal analysis and lessons learned
## 🔄 Future Updates
1. RSI integration
2. Advanced alerts
3. Auto-optimization features
## 🎯 Key Benefits
1. Clear scoring system
2. Multiple confirmation layers
3. Real-time market feedback
4. Customizable parameters
## 🚀 Getting Started
1. Add indicator to chart
2. Adjust parameters if needed
3. Monitor information panel
4. Wait for strong signals (80+ score)
## 📊 Performance Metrics
- Success rate: Monitor and track
- Best performing in trending markets
- Optimal for swing trading
- Most effective on daily timeframe
## 🛠️ Technical Details
```pine
// Core components
1. MACD calculation
2. Volume analysis
3. Trend confirmation
4. Score computation
```
## 💡 Pro Tips
1. Use multiple timeframes
2. Combine with support/resistance
3. Monitor sector trends
4. Consider market conditions
## 🤝 Support
Feedback and improvement suggestions welcome!
## 📜 License
MIT License - Free to use and modify
## 📚 Additional Resources
- Recommended timeframes: Daily, 4H
- Best performing markets: Stocks, ETFs
- Optimal market conditions: Trending markets
- Risk management guidelines included
## 🔍 Final Notes
Remember:
- No indicator is 100% accurate
- Always use proper position sizing
- Combine with other analysis tools
- Practice proper risk management
// @version=5
// @description Pro Stock Scanner - Advanced trading system combining MACD, momentum and volume analysis
// @author AviPro
// @license MIT
//
// This indicator helps identify high-quality trading opportunities by analyzing:
// 1. MACD momentum and crossovers
// 2. Trend strength and direction
// 3. Volume patterns and breakouts
//
// The system provides:
// - Total score (0-100)
// - Visual signals on chart
// - Information panel with key metrics
// - Customizable parameters
//
// IMPORTANT: This indicator is for educational and informational purposes only.
// Always conduct your own analysis and use proper risk management.
//
// If you find this indicator helpful, please consider leaving a like and comment!
// Feedback and suggestions for improvement are always welcome.
Probability System v1.0 [AstroHub]The Probability System is an indicator designed to assess the likelihood of a market trend change based on the analysis of previous candles. The system calculates the probability of price increasing (up) or decreasing (down) based on the count of bullish (up) and bearish (down) candles over a selected period. The script generates buy and sell signals based on these probabilities and displays visual elements that help traders gauge the strength of the trend across different timeframes.
How it works:
Probability Calculation:
The script analyzes the open and close prices of candles over the chosen period (default is 20).
Using this data, the script calculates the probability of price increasing Up Probability or decreasing Down Probability as percentages.
Signal Generation:
A Green signal is generated when the upProbability exceeds a set threshold.
A Red signal is generated when the downProbability exceeds a threshold.
Multi-Level Visualization:
For both up and down probabilities, four levels are defined: 50%, 60%, 70%, and 80%. Each level is represented by circles with varying intensity (color opacity):
Green circles below the price represent up probabilities, with increasing intensity indicating a stronger bullish trend.
Red circles above the price represent down probabilities, with increasing intensity showing stronger bearish signals.
Alerts:
Alerts are set up for each probability level, notifying traders in real-time when specific thresholds are met.
The alerts provide the exact percentage of the probability, allowing traders to act on changes in the market conditions promptly.
How to Use:
Set the desired analysis period (default is 20) and the probability threshold (e.g., 80%) for buy or sell signals.
The script will automatically display signals on the chart, as well as color-coded circles to indicate the probability strength.
Enable real-time notifications for each probability level to keep track of changes in the market trend.
This script is suitable for all types of traders, whether using short-term or long-term strategies.
Unique Features:
Multi-Level Probability Visualization: Four distinct probability levels (50%, 60%, 70%, 80%) are displayed with varying color intensities, providing a clearer understanding of market conditions.
Flexible Settings: Users can customize the analysis period and probability threshold according to their trading style and market conditions.
Real-Time Alerts: Alerts for different probability levels help traders respond swiftly to changes in the market.
Dynamic Signals Based on Statistics: The indicator doesn't rely on fixed data but rather uses the actual statistics of past candles, offering more accurate and timely signals for traders.
Suitable for All Trading Styles: Whether you trade short-term or follow longer-term strategies, this system is versatile and valuable for both types of traders.
Who it’s for:
This indicator is ideal for traders who use technical analysis and are looking for accurate signals based on the probability of trend changes. It’s useful for both beginner and experienced traders who want to improve the precision of their market decisions.
Trend Battery [Phantom]Trend Battery
Visualize Trend Strength with a Dynamic EMA Power Gauge
OVERVIEW
The Trend Battery indicator offers a clear, visual representation of trend strength based on the alignment of multiple Exponential Moving Averages (EMAs). It assigns a color-coded score to each bar, helping traders quickly assess the prevailing trend's power and direction.
CONCEPT
• Trend Strength Using EMAs: The indicator analyzes the alignment of 20 EMAs (8 to 200 periods) to gauge trend strength. The more EMAs align, the stronger the trend.
• Gradient-Based Visualization: Scores are mapped to a color gradient, transitioning from green (bullish) to purple (bearish), providing an intuitive visual representation of trend momentum.
HOW IT WORKS
Trend Battery calculates 20 EMAs and evaluates their alignment. When EMAs align in a strong trend, the bar colors change (as displayed in battery color key on chart) displaying a spectrum of colors from bright green (strong uptrend) to deep purple (strong downtrend).
• Dynamic Bar Colors:
o Green hues: Strong bullish trends.
o Purple hues: Strong bearish trends.
o Red hues: Weaker trends or potential transitions.
FEATURES
• Dynamic Color Coding: Easy-to-read and instantly assess trend.
• Customizable Transparency: Adjust bar color opacity to your preference.
• Optional EMA Display: Toggle individual EMA lines on/off for additional context.
• Compact Battery View: Quick reference table displaying the gradient color mapping.
SETTINGS
• Transparency: Controls the opacity of bar colors.
• Show EMAs on Chart: Enables/disables plotting of EMA lines.
USAGE
• Identify trend strength and direction.
• Confirm trend reversals or continuations.
• Complement other indicators and strategies.
• Monitor multi-timeframe trends.
TRADE IDEAS:
• For larger timeframes purple hues can be used for accumulating and green hues for distribution.
• For smaller timeframes, color transitions could be a signal for trend reversal, or corrections.
• It is a good idea to use larger timeframes for overall trend directions, and smaller timeframes for entries.
LIMITATIONS
• Lagging Indicator: As the Trend Battery relies on Exponential Moving Averages (EMAs), it is inherently a lagging indicator. This means it reflects past price action and may not always provide timely signals for rapid market changes or sudden reversals.
• False Signals in Sideways Markets: In ranging or consolidating markets, the indicator may produce mixed signals (frequent color changes) as EMAs intertwine without a clear trend. This can lead to false interpretations if not considered alongside other market context indicators.
• Not a Standalone System: The Trend Battery is designed to be a visual aid and should not be used as the sole basis for trading decisions. It's most effective when combined with other technical analysis tools, such as oscillators, support/resistance levels, and fundamental analysis.
DISCLAIMER
Use the Trend Battery indicator in conjunction with other forms of analysis and risk management. Past performance is not indicative of future results.
EMA Squeeze RythmHere's a description of this indicator and its purpose:
This indicator is based on the concept of price consolidation and volatility contraction using multiple Exponential Moving Averages (EMAs). It primarily looks for "squeeze" conditions where the EMAs converge, indicating potential market consolidation and subsequent breakout opportunities.
Key Features:
1. Uses 8 EMAs (20-55 period) to measure price compression
2. Measures the distance between fastest (20) and slowest (55) EMAs in ATR units
3. Identifies four distinct states:
- PRE-SQZE: Initial convergence of EMAs
- SQZE: Tighter convergence
- EXT-SQZE: Extreme convergence (highest probability of breakout)
- RELEASE: EMAs begin to expand (potential breakout in progress)
Best Used For:
- Identifying potential breakout setups
- Finding periods of low volatility before explosive moves
- Confirming trend strength using higher timeframe analysis
- Trading mean reversion strategies during squeeze states
- Catching momentum moves during release states
The indicator works well on any timeframe but is particularly effective on 15M to 4H charts for most liquid markets. It includes higher timeframe analysis to help confirm the broader market context.
Duong_Sideway ZoneThis indicator is designed to identify sideway (ranging) zones on the price chart. It uses a Moving Average (MA) and criteria such as the number of price crosses over the MA, as well as breakout checks, to determine whether the market is in a sideway state. When a sideway zone is detected, it is highlighted with a yellow background on the chart.
Key Features:
MA Line: Uses a Moving Average (MA) as the basis for trend identification.
Sideway Threshold: Based on the number of price crosses over the MA within a specific period.
Breakout Check: Excludes zones from being considered sideway if a breakout occurs beyond the ATR threshold.
Visual Highlighting: Highlights sideway zones with a yellow background for easy identification.
This indicator is ideal for traders looking to identify ranging market phases to adjust their trading strategies accordingly.
For example, if within the last 20 candles, the number of times the closing price crosses the MA5 is greater than 4, it is considered a sideway zone, except in cases where the closing price of a recent candle has broken out of the highest/ lowest price of the previous 20 candles.
Long Position with 1:3 Risk Reward and 20EMA CrossoverThe provided Pine Script code implements a strategy to identify long entry signals based on a 20-EMA crossover on a 5-minute timeframe. Once a buy signal is triggered, it calculates and plots the following:
Entry Price: The price at which the buy signal is generated.
Stop Loss: The low of the previous candle, acting as a risk management tool.
Take Profit: The price level calculated based on a 1:3 risk-reward ratio.
Key Points:
Buy Signal: A buy signal is generated when the current 5-minute candle closes above the 20-EMA.
Risk Management: The stop-loss is set below the entry candle to limit potential losses.
Profit Target: The take-profit is calculated based on a 1:3 risk-reward ratio, aiming for a potential profit three times the size of the risk.
Visualization: The script plots the entry price, stop-loss, and take-profit levels on the chart for visual clarity.
Remember:
Backtesting: It's crucial to backtest this strategy on historical data to evaluate its performance and optimize parameters.
Risk Management: Always use appropriate risk management techniques, such as stop-loss orders and position sizing, to protect your capital.
Market Conditions: Market conditions can change, and strategies that worked in the past may not perform as well in the future. Continuously monitor and adapt your strategy.
By understanding the core components of this script and applying sound risk management principles, you can effectively use it to identify potential long entry opportunities in the market.
Prediction Based on Linreg & Atr
We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈.
How Does the Linreg & ATR Prediction Work?
1. Trend Calculation and Signals:
o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script).
o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉.
2. Predicting Future Prices:
o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮.
o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍.
3. Adjusting the Prediction:
o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍.
4. Visualization:
o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈.
5. EMA Cross Signals:
o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉.
6. Additional Considerations:
o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented).
Confidence Interpretation:
• High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥.
• Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️.
Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀.
Español
Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈.
¿Cómo Funciona la Predicción con Linreg & ATR?
Cálculo de Tendencias y Señales:
Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script).
Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉.
Predicción de Precios Futuros:
Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮.
Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍.
Ajuste de la Predicción:
El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍.
Visualización:
Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈.
Señales de Cruce de EMAs:
Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉.
Consideraciones Adicionales:
Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente).
Interpretación de la Confianza:
Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥.
Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️.
La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Volume Spike DetectorVolume Spike Detector
This script is designed to identify significant spikes in trading volume and visually represent them on the chart. It calculates the 20-period simple moving average (SMA) of the trading volume and multiplies it by a user-defined threshold to determine the spike threshold. When the current volume exceeds this threshold, the script detects and highlights a volume spike.
Key Features:
Dynamic Spike Threshold:
The script calculates the spike threshold dynamically based on the average trading volume. Users can customize the threshold multiplier using an input setting.
Example: A threshold multiplier of 2.0 means the current volume must be twice the 20-period SMA to trigger a detection.
Visual Representation:
The current volume is plotted in blue bars.
The spike threshold is plotted as a red line, making it easy to visually identify when the volume crosses the threshold.
Alert Notification:
When a volume spike is detected, an alert is triggered to notify the user.
This feature is useful for real-time monitoring and spotting potential trading opportunities.
Use Case:
Traders can use this tool to identify sudden increases in trading activity, which may indicate a significant market move or event. It’s suitable for all markets, including cryptocurrencies, stocks, and forex.
Ichimoku by FarmerBTCLegal Disclaimer
This strategy, "Ichimoku by FarmerBTC," is provided for educational and informational purposes only. It does not constitute financial advice and should not be relied upon as such. Trading and investing involve substantial risk, including the potential for losing more than your initial investment. Past performance is not indicative of future results. Always consult with a qualified financial advisor before making trading or investment decisions. The author of this strategy is not responsible for any financial losses incurred through its use.
Overview
The "Ichimoku by FarmerBTC" strategy is a trend-following system built on the Ichimoku Cloud indicator, enhanced with volume analysis and a high-timeframe Simple Moving Average (HTF SMA) condition. It is designed to identify long-only trade opportunities and performs optimally on higher timeframes, such as the daily chart or above.
Core Components
1. Ichimoku Cloud
The Ichimoku Cloud is a comprehensive trend-following indicator that helps identify the overall market direction and momentum. It consists of:
Conversion Line (Tenkan-Sen): Measures short-term momentum.
Base Line (Kijun-Sen): Filters medium-term trends.
Leading Span A: The average of the Conversion and Base Lines, forming one cloud boundary.
Leading Span B: The midpoint of the highest high and lowest low over a longer period, forming the other cloud boundary.
Key Ichimoku Rules Applied:
The strategy identifies bullish trends when:
The price is above the cloud.
The cloud is bullish (Leading Span A > Leading Span B).
2. High-Timeframe Simple Moving Average (HTF SMA)
This condition ensures alignment with the broader trend:
Default SMA Length: 13 periods.
Default Timeframe: 1 day.
HTF SMA Rule:
Trades are allowed only when the price is above the HTF SMA, ensuring alignment with the larger trend.
3. Volume Analysis
The strategy uses volume to validate trade setups:
Volume MA: A 20-period moving average of volume is calculated.
Trades are allowed only when the current volume is at least 1.5x the Volume MA, indicating strong market participation.
Entry and Exit Rules
Entry Condition (Long Only):
Price above the Ichimoku Cloud: Confirms a bullish trend.
Bullish Cloud: Leading Span A > Leading Span B indicates upward momentum.
Price above the HTF SMA: Ensures alignment with the broader trend.
Volume exceeds threshold: Confirms strong market participation.
Exit Condition:
The strategy exits the position when the price moves below the Ichimoku Cloud, signaling a potential trend reversal.
Best Timeframes
This strategy is optimized for daily (1D) or higher timeframes (e.g., weekly 1W). Using it on lower timeframes may produce false signals due to increased noise in price and volume data.
Default Settings
Ichimoku Settings:
Conversion Line Period: 10
Base Line Period: 30
Lagging Span Period: 53
Displacement: 26
HTF SMA Settings:
SMA Length: 13
Timeframe: 1 Day
Volume Settings:
Volume MA Length: 20
Volume Multiplier: 1.5x
Visualization
Ichimoku Cloud:
Dynamic cloud coloring (green for bullish, red for bearish) helps identify the current trend.
HTF SMA:
A purple line overlays the chart, providing a clear representation of the high-timeframe trend.
Volume Panel:
An optional panel displays volume (blue histogram) and the Volume Moving Average (orange line) to analyze market participation.
Advantages of This Strategy
High Accuracy on Higher Timeframes:
Filtering trades using the Ichimoku Cloud, HTF SMA, and volume ensures robust trend alignment, reducing false signals.
Volume Confirmation:
Incorporates volume as a validation metric to enter trades only during strong market participation.
Easy Customization:
Parameters like Ichimoku periods, SMA length, timeframe, and volume thresholds can be adjusted to suit different assets or trading styles.
Limitations
Not Suitable for Low Timeframes:
Lower timeframes can produce excessive noise, leading to false signals.
Long-Only:
The strategy is designed only for bullish markets and does not support short trades.
Lagging Nature of Indicators:
Both the Ichimoku Cloud and SMA are lagging indicators, meaning they react to past price movements.
Conclusion
The "Ichimoku by FarmerBTC" strategy is an excellent tool for trend-following on daily or higher timeframes. Its combination of Ichimoku Cloud, high-timeframe SMA, and volume ensures a robust framework for identifying high-probability long trades in trending markets. However, users are advised to test the strategy thoroughly and manage their risk appropriately. Always consult with a financial professional before making trading decisions.
DNSE VN301!, SMA & EMA Cross StrategyDiscover the tailored Pinescript to trade VN30F1M Future Contracts intraday, the strategy focuses on SMA & EMA crosses to identify potential entry/exit points. The script closes all positions by 14:25 to avoid holding any contracts overnight.
HNX:VN301!
www.tradingview.com
Setting & Backtest result:
1-minute chart, initial capital of VND 100 million, entering 4 contracts per time, backtest result from Jan-2024 to Nov-2024 yielded a return over 40%, executed over 1,000 trades (average of 4 trades/day), winning trades rate ~ 30% with a profit factor of 1.10.
The default setting of the script:
A decent optimization is reached when SMA and EMA periods are set to 60 and 15 respectively while the Long/Short stop-loss level is set to 20 ticks (2 points) from the entry price.
Entry & Exit conditions:
Long signals are generated when ema(15) crosses over sma(60) while Short signals happen when ema(15) crosses under sma(60). Long orders are closed when ema(15) crosses under sma(60) while Short orders are closed when ema(15) crosses over sma(60).
Exit conditions happen when (whichever came first):
Another Long/Short signal is generated
The Stop-loss level is reached
The Cut-off time is reached (14:25 every day)
*Disclaimers:
Futures Contracts Trading are subjected to a high degree of risk and price movements can fluctuate significantly. This script functions as a reference source and should be used after users have clearly understood how futures trading works, accessed their risk tolerance level, and are knowledgeable of the functioning logic behind the script.
Users are solely responsible for their investment decisions, and DNSE is not responsible for any potential losses from applying such a strategy to real-life trading activities. Past performance is not indicative/guarantee of future results, kindly reach out to us should you have specific questions about this script.
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Khám phá Pinescript được thiết kế riêng để giao dịch Hợp đồng tương lai VN30F1M trong ngày, chiến lược tập trung vào các đường SMA & EMA cắt nhau để xác định các điểm vào/ra tiềm năng. Chiến lược sẽ đóng tất cả các vị thế trước 14:25 để tránh giữ bất kỳ hợp đồng nào qua đêm.
Thiết lập & Kết quả backtest:
Chart 1 phút, vốn ban đầu là 100 triệu đồng, vào 4 hợp đồng mỗi lần, kết quả backtest từ tháng 1/2024 tới tháng 11/2024 mang lại lợi nhuận trên 40%, thực hiện hơn 1.000 giao dịch (trung bình 4 giao dịch/ngày), tỷ lệ giao dịch thắng ~ 30% với hệ số lợi nhuận là 1,10.
Thiết lập mặc định của chiến lược:
Đạt được một mức tối ưu ổn khi SMA và EMA periods được đặt lần lượt là 60 và 15 trong khi mức cắt lỗ được đặt thành 20 tick (2 điểm) từ giá vào.
Điều kiện Mở và Đóng vị thế:
Tín hiệu Long được tạo ra khi ema(15) cắt trên sma(60) trong khi tín hiệu Short xảy ra khi ema(15) cắt dưới sma(60). Lệnh Long được đóng khi ema(15) cắt dưới sma(60) trong khi lệnh Short được đóng khi ema(15) cắt lên sma(60).
Điều kiện đóng vị thể xảy ra khi (tùy điều kiện nào đến trước):
Một tín hiệu Long/Short khác được tạo ra
Giá chạm mức cắt lỗ
Lệnh chưa đóng nhưng tới giờ cut-off (14:25 hàng ngày)
*Tuyên bố miễn trừ trách nhiệm:
Giao dịch hợp đồng tương lai có mức rủi ro cao và giá có thể dao động đáng kể. Chiến lược này hoạt động như một nguồn tham khảo và nên được sử dụng sau khi người dùng đã hiểu rõ cách thức giao dịch hợp đồng tương lai, đã đánh giá mức độ chấp nhận rủi ro của bản thân và hiểu rõ về logic vận hành của chiến lược này.
Người dùng hoàn toàn chịu trách nhiệm về các quyết định đầu tư của mình và DNSE không chịu trách nhiệm về bất kỳ khoản lỗ tiềm ẩn nào khi áp dụng chiến lược này vào các hoạt động giao dịch thực tế. Hiệu suất trong quá khứ không chỉ ra/cam kết kết quả trong tương lai, vui lòng liên hệ với chúng tôi nếu bạn có thắc mắc cụ thể về chiến lược giao dịch này.
Futures Correlation VisualizerOVERVIEW
This indicator plots the normalized price changes of commonly traded futures. Visualizing data in this way makes studying and understanding market participation and sentiment easier.
Note:
Only 20 symbols can be plotted. The "request" functions are limited to 40 calls , 1 timeframe counts as a call, and 2 timeframes are used per symbol. Normalized values are derived by dividing the charts timeframe by 1D data. A runtime error will occur when more than 20 symbols are enabled. This limitation is unavoidable.
INPUTS
You can configure:
Colors and color scheme
Symbols to plot (most common futures)
Norm. source (todays open / yesterdays close)
Measurement type (%, ‱, Δ)
Label, zone, and zero options
Edwin K Stochastic Candle ColorsThe Stochastic Candle Colors indicator highlights price action using candle colors based on signals from the stochastic oscillator. Here's how to use it:
1. Indicator Purpose
This indicator overlays on your price chart and changes candle colors based on stochastic oscillator signals:
Green candles: Indicate a bullish signal when the %K line crosses above the %D line in an oversold area (below 20).
Red candles: Indicate a bearish signal when the %K line crosses below the %D line in an overbought area (above 80).
2. How to Use the Inputs
K (periodK): The lookback period for calculating the %K line of the stochastic oscillator. A smaller value makes the indicator more sensitive to price changes.
D (periodD): The period for smoothing the %K line to get the %D line. A larger value creates smoother signals but may result in delays.
Smooth (smoothK): The additional smoothing applied to the %K line before calculating the %D line. This helps reduce noise.
3. How to Interpret the Candle Colors
Green Candle:
Occurs when the %K line crosses above the %D line in the oversold zone (below 20).
Signals a potential bullish reversal.
Red Candle:
Occurs when the %K line crosses below the %D line in the overbought zone (above 80).
Signals a potential bearish reversal.
No Color:
No crossover occurs, or the crossover doesn't happen in overbought/oversold zones.
4. Application in Trading
Entry Points:
Buy when you see a green candle and confirm with other indicators or chart patterns.
Sell when you see a red candle and confirm with additional signals.
Trend Context:
Combine this indicator with trend-following tools like moving averages or support/resistance levels to improve accuracy.
Stop Loss/Take Profit:
Use nearby swing highs/lows for stop-loss placement.
Set profit targets based on risk-reward ratios or key levels.
5. Customization
Adjust the input parameters (K, D, and Smooth) to align the indicator's sensitivity with your trading style:
Short-term traders might prefer lower values for quicker signals.
Long-term traders might opt for higher values for smoother, more reliable signals.
6. Limitations
Signals in isolation might not be reliable. Always use this indicator in conjunction with other tools.
Avoid using during low volatility or sideways markets as stochastic oscillators can produce false signals.
Detrended Price Oscillator [NexusSignals]Detrended Price Oscillator (DPO) is a detrended price oscillator, used in technical analysis, strips out price trends in an effort to estimate the length of price cycles from peak to peak or trough to trough.
DPO is not a momentum indicator, instead highlights peaks and troughs in price, which are used to estimate buy and sell points in line with the historical cycle. (cf. to investopedia)
DPO indicator made by NexusSignals components :
a filled area that allow users to see easy the trend of an asset;
a sma moving average on chart (default length is 20)
a 20 sma on oscillator, both ma's are color coded to show uptrend / downtrend
a donchian channel applied to the dpo to show breakouts, breakdowns and resistances/support, reversals
few alerts for price crossing above ma, cross above the 0 dpo line, and for cross above and below the donchian channels top and bottom
How you can use DPO indicator ?
The detrended price oscillator (DPO) can be used for measuring the distance between peaks and troughs in the indicator that may help traders to make future decisions as they can locate the most recent trough and determine when the next one may occur in the meassured distance on oscillator between peaks and troughs.
You can use the indicator to find the potential price reversals, for example when the price of an asset is in a bearish trend and the dpo is bouncing from the donchian channel bottom, that may be a potential swing low for that asset, same thing in a bullish trend when the dpo rejecting at top of donchian channel may be a trend reversal, a pullback or swing high.
When DPO is above the 0 trend is in an uptrend and when dpo is below the zero the asset is possible to move into a downtrend.
Also crosses of DPO above and below the DPO moving average may signalising a trend change.
Indicator DashboardThis script creates an 'Indicator Dashboard' designed to assist you in analyzing financial markets and making informed decisions. The indicator provides a summary of current market conditions by presenting various technical analysis indicators in a table format. The dashboard evaluates popular indicators such as Moving Averages, RSI, MACD, and Stochastic RSI. Below, we'll explain each part of this script in detail and its purpose:
### Overview of Indicators
1. **Moving Averages (MA)**:
- This indicator calculates Simple Moving Averages (“SMA”) for 5, 14, 20, 50, 100, and 200 periods. These averages provide a visual summary of price movements. Depending on whether the price is above or below the moving average, it determines the market direction as either “Bullish” or “Bearish.”
2. **RSI (Relative Strength Index)**:
- The RSI helps identify overbought or oversold market conditions. Here, the RSI is calculated for a 14-period window, and this value is displayed in the table. Additionally, the 14-period moving average of the RSI is also included.
3. **MACD (Moving Average Convergence Divergence)**:
- The MACD indicator is used to determine trend strength and potential reversals. This script calculates the MACD line, signal line, and histogram. The MACD condition (“Bullish,” “Bearish,” or “Neutral”) is displayed alongside the MACD and signal line values.
4. **Stochastic RSI**:
- Stochastic RSI is used to identify momentum changes in the market. The %K and %D lines are calculated to determine the market condition (“Bullish” or “Bearish”), which is displayed along with the calculated values for %K and %D.
### Table Layout and Presentation
The dashboard is presented in a vertical table format in the top-right corner of the chart. The table contains two columns: “Indicator” and “Status,” summarizing the condition of each technical indicator.
- **Indicator Column**: Lists each of the indicators being tracked, such as SMA values, RSI, MACD, etc.
- **Status Column**: Displays the current status of each indicator, such as “Bullish,” “Bearish,” or specific values like the RSI or MACD.
The table also includes rounded indicator values for easier interpretation. This helps traders quickly assess market conditions and make informed decisions based on multiple indicators presented in a single location.
### Detailed Indicator Status Calculations
1. **SMA Status**: For each moving average (5, 14, 20, 50, 100, 200), the script checks if the current price is above or below the SMA. The status is determined as “Bullish” if the price is above the SMA and “Bearish” if below, with the value of the SMA also displayed.
2. **RSI and RSI Average**: The RSI value for a 14-period is displayed along with its 14-period SMA, which provides an average reading of the RSI to smooth out volatility.
3. **MACD Indicator**: The MACD line, signal line, and histogram are calculated using standard parameters (12, 26, 9). The status is shown as “Bullish” when the MACD line is above the signal line, and “Bearish” when it is below. The exact values for the MACD line, signal line, and histogram are also included.
4. **Stochastic RSI**: The %K and %D lines of the Stochastic RSI are used to determine the trend condition. If %K is greater than %D, the condition is “Bullish,” otherwise it is “Bearish.” The actual values of %K and %D are also displayed.
### Conclusion
The 'Indicator Dashboard' provides a comprehensive overview of multiple technical indicators in a single, easy-to-read table. This allows traders to quickly gauge market conditions and make more informed decisions. By consolidating key indicators like Moving Averages, RSI, MACD, and Stochastic RSI into one dashboard, it saves time and enhances the efficiency of technical analysis.
This script is particularly useful for traders who prefer a clean and organized overview of their favorite indicators without needing to plot each one individually on the chart. Instead, all the crucial information is available at a glance in a consolidated format.
Wick Detection (1 and 0) - AYNETDetailed Scientific Explanation
1. Wick Detection Logic
Definition of a Wick:
A wick, also known as a shadow, represents the price action outside the range of a candlestick's body (the region between open and close).
Upper Wick: Occurs when the high value exceeds the greater of open and close.
Lower Wick: Occurs when the low value is lower than the smaller of open and close.
Upper Wick Detection:
pinescript
Kodu kopyala
bool has_upper_wick = high > math.max(open, close)
This checks if the high price of the candle is greater than the maximum of the open and close prices. If true, an upper wick exists.
Lower Wick Detection:
pinescript
Kodu kopyala
bool has_lower_wick = low < math.min(open, close)
This checks if the low price of the candle is less than the minimum of the open and close prices. If true, a lower wick exists.
2. Binary Representation
The presence of a wick is encoded as a binary value for simplicity and computational analysis:
Upper Wick: Represented as 1 if present, otherwise 0.
pinescript
Kodu kopyala
float upper_wick_binary = has_upper_wick ? 1 : 0
Lower Wick: Represented as 1 if present, otherwise 0. This value is inverted (-1) for visualization purposes.
pinescript
Kodu kopyala
float lower_wick_binary = has_lower_wick ? 1 : 0
3. Visualization with Histograms
The plot function is used to create histograms for visualizing the binary wick data:
Upper Wicks: Plotted as positive values with green columns:
pinescript
Kodu kopyala
plot(upper_wick_binary, title="Upper Wick", color=color.new(color.green, 0), style=plot.style_columns, linewidth=2)
Lower Wicks: Plotted as negative values with red columns:
pinescript
Kodu kopyala
plot(lower_wick_binary * -1, title="Lower Wick", color=color.new(color.red, 0), style=plot.style_columns, linewidth=2)
Features and Applications
1. Wick Visualization:
Upper wicks are displayed as positive green columns.
Lower wicks are displayed as negative red columns.
This provides a clear visual representation of wick presence in historical data.
2. Technical Analysis:
Wick formations often indicate market sentiment:
Upper Wicks: Sellers pushed the price lower after buyers drove it higher, signaling rejection at the top.
Lower Wicks: Buyers pushed the price higher after sellers drove it lower, signaling rejection at the bottom.
3. Signal Generation:
Traders can use wick detection to build strategies, such as identifying key price levels or market reversals.
Enhancements and Future Improvements
1. Wick Length Measurement
Instead of binary detection, measure the actual length of the wick:
pinescript
Kodu kopyala
float upper_wick_length = high - math.max(open, close)
float lower_wick_length = math.min(open, close) - low
This approach allows for thresholds to identify significant wicks:
pinescript
Kodu kopyala
bool significant_upper_wick = upper_wick_length > 10 // For wicks longer than 10 units.
bool significant_lower_wick = lower_wick_length > 10
2. Alerts for Long Wicks
Trigger alerts when significant wicks are detected:
pinescript
Kodu kopyala
alertcondition(significant_upper_wick, title="Long Upper Wick", message="A significant upper wick has been detected.")
alertcondition(significant_lower_wick, title="Long Lower Wick", message="A significant lower wick has been detected.")
3. Combined Wick Analysis
Analyze both upper and lower wicks to assess volatility:
pinescript
Kodu kopyala
float total_wick_length = upper_wick_length + lower_wick_length
bool high_volatility = total_wick_length > 20 // Combined wick length exceeds 20 units.
Conclusion
This script provides a compact and computationally efficient way to detect candlestick wicks and represent them as binary data. By visualizing the data with histograms, traders can easily identify wick formations and use them for technical analysis, signal generation, and volatility assessment. The approach can be extended further to measure wick length, detect significant wicks, and integrate these insights into automated trading systems.
Trend & Volume Dynamics Indicator (Color identifying the Trend)Benefits
1. Trend Identification:
o The script calculates a 20-period Weighted Moving Average (WMA) of the closing prices. This helps in smoothing out price data to identify the underlying trend.
o The color of the WMA line changes based on the price position relative to the WMA:
Green: When the current price is above the WMA, indicating a potential uptrend.
Red: When the current price is below the WMA, indicating a potential downtrend.
Blue: When the price is exactly at the WMA, indicating no clear trend.
2. Volume Dynamics:
o The script also plots the volume with a color-coding mechanism:
Green: When the current volume is higher than the previous period's volume, indicating increasing trading activity.
Red: When the current volume is lower than the previous period's volume, indicating decreasing trading activity.
o The volume bars are plotted with 90% transparency, making them less visually dominant but still informative.
Usage
• Overlay: The indicator is set to overlay=true, meaning it will be plotted directly on the price chart, allowing users to see the WMA and volume dynamics in the context of the price movements.
• WMA Length: The length of the WMA is set to 20 periods, which is a common setting for short to medium-term trend analysis.
• Visual Cues: The color changes in both the WMA and volume bars provide immediate visual cues about the trend and volume dynamics, helping traders make quicker decisions.
Detailed Explanation of the Script
1. Indicator Declaration:
o Declares the indicator with a descriptive name and specifies that it should be overlaid on the price chart.
2. WMA Calculation:
o Defines the length of the WMA and calculates it using the closing prices.
3. Plotting the WMA:
o Plots the WMA with full brightness (0 transparency).
4. Color-Coding the WMA:
o Changes the color of the WMA line based on the price's position relative to the WMA.
5. Volume Indicator:
o Plots the volume bars with color-coding based on the volume change from the previous period and with 90% transparency.
Conclusion
One of the most best combinations of Volume and Moving average and works on any given timeframe and charts
