Hinton Map█ HINTON MAP
This script displays a Hinton Map visualization of market data for user-defined tickers and timeframes. It uses color gradients to represent the magnitude and direction of price change, RSI, and a combination of both.
This is one example. You can modify and try other values as you wish, but do keep the incoming values between -1 and 1.
In the Example Usage:
Users can input up to 5 symbols and 5 timeframes. For each ticker/timeframe combination:
The box size represents the relative magnitude of the 2-bar percentage change.
The box fill color represents the direction and magnitude of the 2-bar percentage change.
The box border color and thickness represent the RSI deviation from 50.
The inner box color represents a combination of price change magnitude and RSI deviation from 50.
Hovering over each box displays a tooltip with the ticker, timeframe, percentage change, and RSI.
Inputs:
• Unit Size (bars):
The size of each Hinton unit in bars.
Type: int
Default Value: 10
• Border Width:
The base width of the inner box border.
Type: int
Default Value: 3
• Negative Hue (0-360):
The hue value for negative price changes (0-360).
Type: float
Default Value: 100
• Positive Hue (0-360):
The hue value for positive price changes (0-360).
Type: float
Default Value: 180
• Ticker 1-5:
The tickers to display on the Hinton map.
Type: string
Default Value: AAPL
• Timeframes (comma separated):
The timeframes to display on the Hinton map (comma-separated).
Type: string
Default Value: 1, 5, 60, 1D, 1W
(Fun Note: My Home town is named `Hinton`)
Pine utilities
DYNAMIC USD MOMENTUM INDICATOR
Hello traders,
Welcome to my script, an indicator helping you to quickly see the performance of USD in constant daily comparison to other currencies.
This script requests price data from other charts but displays overbought and oversold labels on any selected chart currency pair.
See attached images to spot high probability reversal days when USD is in extremes against multiple other currencies. The output labels represent the currency traded against USD and reaching overbought and oversold zoned on a dynamic RSI scale.
Suggested pairs with higher co relation to stronger or weaker dollar:
AUD/USD, CAD/USD, EUR/USD, GBP/USD, NZD/USD
CHF/USD and JPY/USD require more in depth analysis of individual performance of JPY AND CHF
Mars Signals - SSL Trend AnalyzerIntroduction
The "Mars Signals - Precision Trend Analyzer with SSL Baseline & Price Action Zones" is a comprehensive technical analysis tool designed for traders seeking to enhance their market analysis and trading strategies. This indicator integrates multiple advanced trading concepts, including dynamic moving averages, trend detection algorithms, momentum indicators, volume analysis, higher timeframe confirmation, candlestick pattern recognition, and precise price action zones. By combining these elements, the indicator aims to provide clear and actionable buy and sell signals, helping traders to make informed decisions in various market conditions.
Core Components and Functionality
1.Dynamic Baseline Calculation
Moving Average Types: The indicator allows users to select from a variety of moving average types for the baseline calculation, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Hull Moving Average (HMA), Weighted Moving Average (WMA), Double EMA (DEMA), Triple EMA (TEMA), Least Squares Moving Average (LSMA), Triangular Moving Average (TMA), Kijun (from Ichimoku Kinko Hyo), and McGinley's Dynamic.
Baseline Length: Users can customize the length of the moving average, providing flexibility to adjust the sensitivity of the baseline to market movements.
Signal Line Generation: The indicator computes a dynamic signal line based on the relationship between the close price and the moving averages of the high and low prices. This signal line adapts to market volatility and trend changes.
2.SSL Baseline Integration
SSL Baseline: In addition to the primary baseline, the indicator incorporates an SSL (Semaphore Signal Level) Baseline, which further refines trend detection by considering the highs and lows over a specified period.
Dual Confirmation: The combination of the primary baseline and the SSL baseline enhances the reliability of the trend signals by requiring agreement between both baselines before generating a signal.
3.Momentum and Trend Filters
Relative Strength Index (RSI): The indicator uses the RSI to assess the momentum of price movements, filtering out signals that occur during overbought or oversold conditions.
Moving Average Convergence Divergence (MACD): The MACD is employed to identify the direction and strength of the trend, adding another layer of confirmation to the signals.
Average Directional Index (ADX): The ADX measures the strength of the trend, ensuring that signals are generated only when the market shows significant directional movement.
4.Volume Analysis
Volume Filter: An optional volume filter compares the current volume to its moving average, allowing traders to focus on signals that occur during periods of higher market activity.
5.Higher Timeframe Confirmation
Multi-Timeframe Analysis: The indicator can incorporate data from a higher timeframe, comparing the current price to the higher timeframe's baseline and signal line. This feature helps traders align their trades with the broader market trend.
6.Candlestick Pattern Recognition
Bullish Patterns: The indicator detects bullish patterns such as Bullish Engulfing, Piercing Line, Hammer, and Doji.
Bearish Patterns: It also identifies bearish patterns like Bearish Engulfing, Dark Cloud Cover, Shooting Star, and Doji.
Pattern Prioritization: The patterns are prioritized to highlight the most significant formations, which can serve as additional confirmation for trade entries and exits.
7.Price Action Zones
Support and Resistance Levels: The indicator automatically identifies pivot highs and lows to establish dynamic support and resistance levels.
Zone Visualization: It draws shaded rectangles on the chart to represent these zones, providing a clear visual aid for potential reversal or breakout areas.
ATR-Based Zone Width: The zones' thickness is dynamically calculated using the Average True Range (ATR), adjusting to the current market volatility.
Background Coloring: The chart background changes color when the price is above the maximum resistance or below the minimum support, alerting traders to significant price movements.
Interpreting the Signals
1.Buy Signals
Conditions:
Price crosses above the signal line.
RSI is below 70 (not overbought).
MACD line is above the signal line (indicating bullish momentum).
ADX is above the user-defined threshold (default is 20), confirming a strong trend.
(Optional) Volume is above its moving average if the volume filter is enabled.
(Optional) Price is above the higher timeframe baseline and signal line if the higher timeframe filter is enabled.
(Optional) A bullish candlestick pattern is detected if the candlestick pattern filter is enabled.
Visual Indicators:
An upward-pointing label with the text "BUY" appears below the price bar.
The baseline and SSL baseline lines turn to colors indicating bullish conditions.
2.Sell Signals
Conditions:
Price crosses below the signal line.
RSI is above 30 (not oversold).
MACD line is below the signal line (indicating bearish momentum).
ADX is above the user-defined threshold, confirming a strong trend.
(Optional) Volume is above its moving average if the volume filter is enabled.
(Optional) Price is below the higher timeframe baseline and signal line if the higher timeframe filter is enabled.
(Optional) A bearish candlestick pattern is detected if the candlestick pattern filter is enabled.
Visual Indicators:
A downward-pointing label with the text "SELL" appears above the price bar.
The baseline and SSL baseline lines turn to colors indicating bearish conditions.
3.Support and Resistance Zones
Interpretation:
Resistance Zones: Represent areas where the price may face selling pressure. A break above these zones can signal a strong bullish move.
Support Zones: Represent areas where the price may find buying interest. A break below these zones can signal a strong bearish move.
Background Color:
The background turns red when the price is above the maximum resistance, indicating potential overextension.
The background turns green when the price is below the minimum support, indicating potential undervaluation.
Effective Usage Strategies
1.Customization
Adjusting Baseline and SSL Settings: Traders should experiment with different moving average types and lengths to match their trading style and the specific characteristics of the asset being analyzed.
Filtering Parameters: Modify RSI, MACD, and ADX settings to fine-tune the sensitivity of the signals.
Volume and Higher Timeframe Filters: Enable these filters to add robustness to the signals, especially in volatile markets or when trading higher timeframes.
2.Combining with Other Analysis
Fundamental Analysis: Use the indicator in conjunction with fundamental insights to validate technical signals.
Risk Management: Always apply proper risk management techniques, such as setting stop-loss and take-profit levels based on the support and resistance zones provided by the indicator.
3.Backtesting
Historical Analysis: Utilize the indicator's settings to backtest trading strategies on historical data, helping to identify the most effective configurations before applying them in live trading.
4.Monitoring Market Conditions
Volatility Awareness: Pay attention to the ATR and ADX readings to understand market volatility and trend strength, adjusting strategies accordingly.
Event Considerations: Be cautious around major economic announcements or events that may impact market behavior beyond technical indications.
Indicator Inputs and Customization Options
Baseline Type and Length: Select from multiple moving average types and specify the period length.
ADX Settings: Adjust the length, smoothing, and threshold for trend strength confirmation.
Volume Filter: Enable or disable the volume confirmation filter.
Higher Timeframe Filter: Choose to incorporate higher timeframe analysis and specify the desired timeframe.
Candlestick Patterns: Enable or disable the detection of candlestick patterns for additional signal confirmation.
SSL Baseline Type and Length: Customize the SSL baseline settings separately from the primary baseline.
Price Action Zones Settings:
Zone Thickness: Adjust the visual thickness of the support and resistance zones.
Lookback Period: Define how far back the indicator looks for pivot points.
ATR Multiplier for Zone Width: Set the multiplier for ATR to determine the dynamic width of the zones.
Maximum Number of Zones: Limit the number of support and resistance zones displayed.
Pivot Bars: Customize the number of bars to the left and right used for identifying pivot highs and lows.
Conclusion
The "Mars Signals - Precision Trend Analyzer with SSL Baseline & Price Action Zones" is a versatile and powerful tool that amalgamates essential technical analysis techniques into a single, user-friendly indicator. By providing clear visual signals and incorporating multiple layers of confirmation, it assists traders in identifying high-probability trading opportunities. Whether you are a day trader, swing trader, or long-term investor, this indicator can be tailored to suit your trading style and enhance your decision-making process.
To maximize the benefits of this indicator:
Understand Each Component: Familiarize yourself with how each part of the indicator contributes to the overall signal generation.
Customize Thoughtfully: Adjust the settings based on the asset class, market conditions, and your risk tolerance.
Practice Diligently: Use demo accounts or paper trading to practice and refine your strategy before deploying it in live markets.
Stay Informed: Continuously educate yourself on technical analysis and market dynamics to make the most informed decisions.
Disclaimer
Trading financial markets involves risk, and past performance is not indicative of future results. This indicator is a tool to aid in analysis and should not be the sole basis for any trading decision. Always conduct your own research and consider consulting with a licensed financial advisor.
Vektorkerzen HighlightThe indicator highlights candles when:
The volume is at least twice the 20-period moving average.
The range (difference between high and low prices) is at least twice the 20-period average range.
[MAD MBS] L3 Float Operations & ML-NormalizersFirst of all:
This indicator is not a standalone tool ; it relies on other script series for its inputs.
This script is an indicator designed for multi-path float operations with integrated machine learning normalizers.
It supports up to four distinct paths, each customizable with multiple sources, factors, and operations.
Users can perform various mathematical operations on price data, including addition, subtraction, multiplication, division, and percentage changes, as well as more advanced tasks like double and triple moving averages or power operations.
The script also integrates several normalization methods (e.g., Min-Max, Z-Score, Robust) to standardize data—an important step for machine learning models.
Each path supports multiple smoothing techniques (e.g., EMA, SMA, and specialized Ehlers smoothers) to further refine the output.
Designed to handle multiple data inputs simultaneously, this tool is especially useful for traders looking to analyze and normalize data from different price sources.
The combination of advanced mathematical operations, normalization techniques, and smoothing enhances data management, aiding in more effective trading decisions.
Here you can see a single path, out of the four possible:
Details to the screenshot:
First Series
Second Series
Option to override the second series with a custom constant (or when normalizing, use the length instead)
The first selection box sets the mathematical operation or activates the normalizer.
The second selection box sets the normalization method.
The third selection box sets the final smoothing technique, followed by parameters for smoothing length.
These settings are repeated identically for Paths 2–4.
At the bottom of the setup, there's a general offset option (add the 'close' price for overlay purposes).
Additionally, there's an option to display a line at zero for centered results.
Martingale with MACD+KDJ opening conditionsStrategy Overview:
This strategy is based on a Martingale trading approach, incorporating MACD and KDJ indicators. It features pyramiding, trailing stops, and dynamic profit-taking mechanisms, suitable for both long and short trades. The strategy increases position size progressively using a Multiplier, a key feature of Martingale systems.
Key Concepts:
Martingale Strategy: A trading system where positions are doubled or increased after a loss to recover previous losses with a single successful trade. In this script, the position size is incremented using a Multiplier for each addition.
Pyramiding: Allows adding to existing trades when market conditions are favorable, enhancing profitability during trends.
Settings:
Basic Inputs:
Initial Order: Defines the starting size of the position.
Default: 150.0
MACD Settings: Customize the fast, slow, and signal smoothing lengths.
Default: Fast Length: 9, Slow Length: 26, Signal Smoothing: 9
KDJ Settings: Customize the length and smoothing parameters for KDJ.
Default: Length: 14, Smooth K: 3, Smooth D: 3
Max Additions: Sets the number of additional positions (pyramiding).
Default: 5 (Min: 1, Max: 10)
Position Sizing: Percent to add to positions on favorable conditions.
Default: 1.0%
Martingale Multiplier:
Add Multiplier: This value controls the scaling of additional positions according to the Martingale principle. After each loss, a new position is added, and its size is increased by the Multiplier factor. For example, with a multiplier of 2, each new addition will be twice as large as the previous one, accelerating recovery if the price moves favorably.
Default: 1.0 (no multiplication)
Can be adjusted up to 10x to aggressively increase position size after losses.
Trade Execution:
Long Trades:
Entry Condition: A long position is opened when the MACD line crosses over the signal line, and the KDJ’s %K crosses above %D.
Additions (Martingale): After the initial long position, new positions are added if the price drops by the defined percentage, and each new addition is increased using the Multiplier. This continues up to the set Max Additions.
Short Trades:
Entry Condition: A short position is opened when the MACD line crosses under the signal line, and the KDJ’s %K crosses below %D.
Additions (Martingale): After the initial short position, new positions are added if the price rises by the defined percentage, and each new addition is increased using the Multiplier.
Exit Conditions:
Take Profit: Exits are triggered when the price reaches the take-profit threshold.
Stop Loss: If the price moves unfavorably, the position will be closed at the set stop-loss level.
Trailing Stop: Adjusts dynamically as the price moves in favor of the trade to lock in profits.
On-Chart Visuals:
Long Signals: Blue triangles below the bars indicate long entries, and green triangles mark additional long positions.
Short Signals: Red triangles above the bars indicate short entries, and orange triangles mark additional short positions.
Information Table:
The strategy displays a table with key metrics:
Open Price: The entry price of the trade.
Average Price: The average price of the current position.
Additions: The number of additional positions taken.
Next Add Price: The price level for the next position.
Take Profit: The price at which profits will be taken.
Stop Loss: The stop-loss level to minimize risk.
Usage Instructions:
Adjust the parameters to your trading style using the input settings.
The Multiplier amplifies your position size after each addition, so use it cautiously, especially in volatile markets.
Monitor the signals and table on the chart for entry/exit decisions and trade management.
RSI Crossover Strategy with Compounding (Monthly)Explanation of the Code:
Initial Setup:
The strategy initializes with a capital of 100,000.
Variables track the capital and the amount invested in the current trade.
RSI Calculation:
The RSI and its SMA are calculated on the monthly timeframe using request.security().
Entry and Exit Conditions:
Entry: A long position is initiated when the RSI is above its SMA and there’s no existing position. The quantity is based on available capital.
Exit: The position is closed when the RSI falls below its SMA. The capital is updated based on the net profit from the trade.
Capital Management:
After closing a trade, the capital is updated with the net profit plus the initial investment.
Plotting:
The RSI and its SMA are plotted for visualization on the chart.
A label displays the current capital.
Notes:
Test the strategy on different instruments and historical data to see how it performs.
Adjust parameters as needed for your specific trading preferences.
This script is a basic framework, and you might want to enhance it with risk management, stop-loss, or take-profit features as per your trading strategy.
Feel free to modify it further based on your needs!
Point and Figure Displacement IndicatorThe PnF Displacement indicator is my custom script for TradingView, designed to analyze Point and Figure (PnF) charts with displacement features.
Key components of the script include:
User Inputs:
Require FVG: A boolean input to determine if a Fair Value Gap (FVG) is required for displacement calculations.
Displacement Type: Allows users to choose between "Open to Close" and "High to Low" for column range calculations.
Displacement Length: Defines how far back to look for calculating the standard deviation of the column range.
Displacement Strength: Multiplier for the standard deviation to adjust sensitivity.
Box Size: Sets the size of each box in the PnF chart.
Number of Boxes for Minimum Displacement: Specifies how many boxes to consider for calculating the minimum displacement.
Displacement Logic:
The script calculates the column range based on the selected displacement type.
It computes a standard deviation of the candle range and determines a minimum displacement based on user-defined box size and count.
The displacement condition combines the FVG check and the column range against the calculated minimum.
Visual Representation:
The bars are colored based on displacement conditions, enhancing visual analysis on the chart.
This indicator aids traders in identifying significant price movements in PnF charts while incorporating user customization options for better analysis.
PnF Fibonacci Levels with AlertsMy Pine Script indicator, "PnF Fibonacci Levels with Alerts," overlays on a trading chart to generate alerts based on Fibonacci levels in Point and Figure (PnF) charts.
Key Features:
Inputs and Initialization:
It uses a customizable Fibonacci level (set at 0.236) and initializes variables for tracking the high and low of O and X columns.
O Column Logic:
When the current column is identified as an O column (when the close is less than the open), it calculates the Fibonacci level based on the high and low of that column, drawing a line on the chart.
Buy Alert:
If the closing price of the previous bar is above the Fibonacci level of the O column, a buy alert is triggered.
X Column Logic:
If the current column is an X column and the close is above the previous O column's low, it captures the current high and low, calculates the Fibonacci level, and draws it on the chart.
Sell Alert:
A sell alert is triggered if the closing price of the X column is at or below the specified Fibonacci level.
This indicator aids traders by highlighting critical Fibonacci levels and providing timely alerts for potential buy and sell opportunities.
PnF Bullish & Bearish Trend Line Indicator with Proximity AlertThis Pine Script indicator, "PnF Bullish and Bearish Trend line Proximity Alert," overlays on a trading chart to monitor and alert users about interactions with bullish and bearish trend lines derived from Point and Figure (PnF) charting.
Key Features:
Inputs: Users can set parameters such as box size, bullish and bearish angles (in degrees), and a proximity threshold for detecting touches.
Slope Calculation: The script calculates the slopes for bullish and bearish trendlines using the tangent of the specified angles.
Trendline Management:
It initializes and updates trend lines based on price interactions, adjusting their starting points and positions as conditions change.
Proximity Detection: The indicator checks if the current price is close enough to the trend lines and sets conditions for alerts.
Alerts: Users receive alerts when both trend lines are touched, enhancing decision-making for trading strategies.
Visual Feedback: It highlights areas where both trend lines are touched and plots the trend lines in distinct colors for clarity.
This indicator provides an effective way to track key price levels and potential trend reversals in the market.
ADX + Volume Strategy### Strategy Description: ADX and Volume-Based Trading Strategy
This strategy is designed to identify strong market trends using the **Average Directional Index (ADX)** and confirm trading signals with **Volume**. The idea behind the strategy is to enter trades only when the market shows a strong trend (as indicated by ADX) and when the price movement is supported by high trading volume. This combination helps filter out weaker signals and provides more reliable entries into positions.
### Key Indicators:
1. **ADX (Average Directional Index)**:
- **Purpose**: ADX is a technical indicator that measures the strength of a trend, regardless of its direction (up or down).
- **Usage**: The strategy uses ADX to determine whether the market is trending strongly. If ADX is above a certain threshold (default is 25), it indicates that a strong trend is present.
- **Directional Indicators**:
- **DI+ (Directional Indicator Plus)**: Indicates the strength of the upward price movement.
- **DI- (Directional Indicator Minus)**: Indicates the strength of the downward price movement.
- ADX does not indicate the direction of the trend but confirms that a trend exists. DI+ and DI- are used to determine the direction.
2. **Volume**:
- **Purpose**: Volume is a key indicator for confirming the strength of a price movement. High volume suggests that a large number of market participants are supporting the movement, making it more likely to continue.
- **Usage**: The strategy compares the current volume to the 20-period moving average of the volume. The trade signal is confirmed if the current volume is greater than the average volume by a specified **Volume Multiplier** (default multiplier is 1.5). This ensures that the trade is supported by strong market participation.
### Strategy Logic:
#### **Entry Conditions:**
1. **Long Position** (Buy):
- **ADX** is above the threshold (default is 25), indicating a strong trend.
- **DI+ > DI-**, signaling that the market is trending upward.
- The **current volume** is greater than the 20-period average volume multiplied by the **Volume Multiplier** (e.g., 1.5), indicating that the upward price movement is backed by sufficient market activity.
2. **Short Position** (Sell):
- **ADX** is above the threshold (default is 25), indicating a strong trend.
- **DI- > DI+**, signaling that the market is trending downward.
- The **current volume** is greater than the 20-period average volume multiplied by the **Volume Multiplier** (e.g., 1.5), indicating that the downward price movement is backed by strong selling activity.
#### **Exit Conditions**:
- Positions are closed when the opposite signal appears:
- **For long positions**: Close when the short conditions are met (ADX still above the threshold, DI- > DI+, and the volume condition holds).
- **For short positions**: Close when the long conditions are met (ADX still above the threshold, DI+ > DI-, and the volume condition holds).
### Parameters:
- **ADX Period**: The period used to calculate ADX (default is 14). This controls how sensitive the ADX is to price movements.
- **ADX Threshold**: The minimum ADX value required for the strategy to consider the market trend as strong (default is 25). Higher values focus on stronger trends.
- **Volume Multiplier**: This parameter adjusts how much higher the current volume needs to be compared to the 20-period moving average for the signal to be valid. A value of 1.5 means the current volume must be 50% higher than the average volume.
### Example Trade Flow:
1. **Long Trade Example**:
- ADX > 25, confirming a strong trend.
- DI+ > DI-, confirming that the trend direction is upward.
- The current volume is 50% higher than the 20-period average volume (multiplied by 1.5).
- **Action**: Enter a long position.
2. **Short Trade Example**:
- ADX > 25, confirming a strong trend.
- DI- > DI+, confirming that the trend direction is downward.
- The current volume is 50% higher than the 20-period average volume.
- **Action**: Enter a short position.
### Strengths of the Strategy:
- **Trend Filtering**: The strategy ensures that trades are only taken when the market is trending strongly (confirmed by ADX) and that the price movement is supported by high volume, reducing the likelihood of false signals.
- **Volume Confirmation**: Using volume as confirmation provides an additional layer of reliability, as volume spikes often accompany sustained price moves.
- **Dual Signal Confirmation**: Both trend strength (ADX) and volume conditions must be met for a trade, making the strategy more robust.
### Weaknesses of the Strategy:
- **Limited Effectiveness in Range-Bound Markets**: Since the strategy relies on strong trends, it may underperform in sideways or non-trending markets where ADX stays below the threshold.
- **Lagging Nature of ADX**: ADX is a lagging indicator, which means that it may confirm the trend after it has already begun, potentially leading to late entries.
- **Volume Requirement**: In low-volume markets, the volume multiplier condition may not be met often, leading to fewer trade opportunities.
### Customization:
- **Adjust the ADX Threshold**: You can raise the threshold if you want to focus only on very strong trends, or lower it to capture moderate trends.
- **Adjust the Volume Multiplier**: You can change the multiplier to be more or less strict. A higher multiplier (e.g., 2.0) will require a stronger volume spike to confirm the signal, while a lower multiplier (e.g., 1.2) will allow more trades with weaker volume confirmation.
### Summary:
This ADX and Volume strategy is ideal for traders who want to follow strong trends while ensuring that the trend is supported by high trading volume. By combining a trend strength filter (ADX) and volume confirmation, the strategy aims to increase the probability of entering profitable trades while reducing the number of false signals. However, it may underperform in range-bound markets or in markets with low volume.
bar_index inspectorThis is a tool for developers who are working with index based plots and find themselves adding the bar_index to their indicators on a regular basis during development and debugging.
What it does:
shows the bar_index in the status line and data window.
plots optional labels (bar index + time) into the chart every 10 bars
Crossover CounterExplanation:
Crossover Detection: We detect the crossover of the 20-period and 50-period moving averages using ta.crossover().
Tracking Price Movement: After the crossover, we start tracking the price to check if it moves up or down by 2%. If an up movement occurs before a down movement, we increment the positive counter. If a down movement occurs first, we increment the negative counter.
Reset Condition: Once either a 2% up or down move is detected, we stop tracking until the next crossover.
Table Display: A table shows the counts of positive and negative events.
High/Low Breakout Statistical Analysis StrategyThis Pine Script strategy is designed to assist in the statistical analysis of breakout systems on a monthly, weekly, or daily timeframe. It allows the user to select whether to open a long or short position when the price breaks above or below the respective high or low for the chosen timeframe. The user can also define the holding period for each position in terms of bars.
Core Functionality:
Breakout Logic:
The strategy triggers trades based on price crossing over (for long positions) or crossing under (for short positions) the high or low of the selected period (daily, weekly, or monthly).
Timeframe Selection:
A dropdown menu enables the user to switch between the desired timeframe (monthly, weekly, or daily).
Trade Direction:
Another dropdown allows the user to select the type of trade (long or short) depending on whether the breakout occurs at the high or low of the timeframe.
Holding Period:
Once a trade is opened, it is automatically closed after a user-defined number of bars, making it useful for analyzing how breakout signals perform over short-term periods.
This strategy is intended exclusively for research and statistical purposes rather than real-time trading, helping users to assess the behavior of breakouts over different timeframes.
Relevance of Breakout Systems:
Breakout trading systems, where trades are executed when the price moves beyond a significant price level such as the high or low of a given period, have been extensively studied in financial literature for their potential predictive power.
Momentum and Trend Following:
Breakout strategies are a form of momentum-based trading, exploiting the tendency of prices to continue moving in the direction of a strong initial movement after breaching a critical support or resistance level. According to academic research, momentum strategies, including breakouts, can produce returns above average market returns when applied consistently. For example, Jegadeesh and Titman (1993) demonstrated that stocks that performed well in the past 3-12 months continued to outperform in the subsequent months, suggesting that price continuation patterns, like breakouts, hold value .
Market Efficiency Hypothesis:
While the Efficient Market Hypothesis (EMH) posits that markets are generally efficient, and it is difficult to outperform the market through technical strategies, some studies show that in less liquid markets or during specific times of market stress, breakout systems can capitalize on temporary inefficiencies. Taylor (2005) and other researchers have found instances where breakout systems can outperform the market under certain conditions.
Volatility and Breakouts:
Breakouts are often linked to periods of increased volatility, which can generate trading opportunities. Coval and Shumway (2001) found that periods of heightened volatility can make breakouts more significant, increasing the likelihood that price trends will follow the breakout direction. This correlation between volatility and breakout reliability makes it essential to study breakouts across different timeframes to assess their potential profitability .
In summary, this breakout strategy offers an empirical way to study price behavior around key support and resistance levels. It is useful for researchers and traders aiming to statistically evaluate the effectiveness and consistency of breakout signals across different timeframes, contributing to broader research on momentum and market behavior.
References:
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Fama, E. F., & French, K. R. (1996). Multifactor Explanations of Asset Pricing Anomalies. Journal of Finance, 51(1), 55-84.
Taylor, S. J. (2005). Asset Price Dynamics, Volatility, and Prediction. Princeton University Press.
Coval, J. D., & Shumway, T. (2001). Expected Option Returns. Journal of Finance, 56(3), 983-1009.
Shifted Symbol Overlay with OffsetThe Shifted Symbol Overlay Indicator is a custom TradingView indicator designed to overlay the price data of one stock or asset over another, allowing for direct visual comparison. This is particularly useful for comparing the performance of two assets over different time periods. The indicator enables you to shift the data from one asset either forward or backward in time, making it easier to compare historical data from one stock with more recent data from another. The indicator supports shifting both to the right (future periods) and to the left (earlier periods), helping traders and analysts explore correlations or divergences between two financial instruments.
The indicator also includes a normalization option that adjusts the scale of the two assets, so you can compare them even if they have vastly different price levels. This is useful when you're interested in relative performance rather than the absolute price values.
Simplified Gap Strategy with SMA FilterThe Simplified Gap Strategy leverages price gaps as a trading signal, focusing on their significance in market behavior. Gaps occur when the opening price of a security differs significantly from the previous closing price, often signaling potential continuation or reversal patterns.
Key Features:
Gap Threshold:
This strategy requires a minimum percentage gap (defined by the user) to qualify for trading signals.
Directional Trading:
Users can select from various gap types, including "Long Up Gap" and "Short Down Gap," allowing for tailored trading approaches.
SMA Filter:
An optional Simple Moving Average (SMA) filter helps refine trade entries based on trend direction, increasing the probability of successful trades.
Hold Duration:
Positions can be held for a user-defined duration, providing flexibility in trade management.
Statistical Significance of Gaps:
Research has shown that gaps can provide insights into future price movements. According to studies such as those by Hutton and Jiang (2008), price gaps are often followed by momentum in the direction of the gap, indicating that they can serve as reliable indicators for traders. The "Gap Theory" suggests that gaps are filled approximately 90% of the time, emphasizing their relevance in market dynamics (Nikkinen, Sahlström, & Kinnunen, 2006).
Important Note:
This strategy is designed solely for statistical analysis and should not be construed as financial advice. Users are encouraged to conduct their own research and analysis before applying this strategy in live trading scenarios.
By understanding the underlying mechanisms of price gaps and their statistical significance, traders can enhance their decision-making processes and potentially improve trading outcomes.
References:
Hutton, A. W., & Jiang, W. (2008). "Price Gaps: A Guide to Trading Gaps."
Nikkinen, J., Sahlström, P., & Kinnunen, J. (2006). "The Gaps in Financial Markets: An Empirical Study."
This description provides an overview of the strategy while emphasizing its analytical purpose and backing it with relevant academic insights.
Streak-Based Trading StrategyThe strategy outlined in the provided script is a streak-based trading strategy that focuses on analyzing winning and losing streaks. It’s important to emphasize that this strategy is not intended for actual trading but rather for statistical analysis of streak series.
How the Strategy Works
1. Parameter Definition:
• Trade Direction: Users can choose between “Long” (buy) and “Short” (sell).
• Streak Threshold: Defines how many consecutive wins or losses are needed to trigger a trade.
• Hold Duration: Specifies how many periods the position will be held.
• Doji Threshold: Determines the sensitivity for Doji candles, which indicate market uncertainty.
2. Streak Calculation:
• The script identifies Doji candles and counts winning and losing streaks based on the closing price compared to the previous closing price.
• Streak counting occurs only when no position is currently held.
3. Trade Conditions:
• If the loss streak reaches the defined threshold and the trade direction is “Long,” a buy position is opened.
• If the win streak is met and the trade direction is “Short,” a sell position is opened.
• The position is held for the specified duration.
4. Visualization:
• Winning and losing streaks are plotted as histograms to facilitate analysis.
Scientific Basis
The concept of analyzing streaks in financial markets is well-documented in behavioral economics and finance. Studies have shown that markets often exhibit momentum and trend-following behavior, meaning the likelihood of consecutive winning or losing periods can be higher than what random statistics would suggest (see, for example, “The Behavior of Stock-Market Prices” by Eugene Fama).
Additionally, empirical research indicates that investors often make decisions based on psychological factors influenced by streaks. This can lead to irrational behavior, as they may focus on past wins or losses (see “Behavioral Finance: Psychology, Decision-Making, and Markets” by R. M. F. F. Thaler).
Overall, this strategy serves as a tool for statistical analysis of streak series, providing deeper insights into market behavior and trends rather than being directly used for trading decisions.
Price Movement > Custom Points with Day of WeekThe code is a TradingView Pine Script indicator designed to track and visualize price movements in a financial market (like stocks or cryptocurrencies) based on a specific point threshold. Here’s a breakdown of its functionality:
Purpose of the Code:
Price Movement Calculation: It calculates the difference between the closing price and the opening price of each bar (or candle) to determine if the price has moved significantly.
Threshold Input: The user can set a threshold (e.g., 500 points) to determine what constitutes a significant movement.
Movement Conditions:
Positive Movement: If the price movement is greater than the threshold, it’s marked as a positive movement.
Negative Movement: If the price movement is less than the negative threshold (i.e., below -500 points), it’s marked as a negative movement.
Day of the Week Identification: The script identifies the day of the week for each bar (Monday through Sunday).
Visual Output:
It plots shapes (like labels) on the chart:
For positive movements, it shows "YES" in green, indicating the movement exceeded the threshold for that day.
For negative movements, it shows "YES" in red, indicating the movement fell below the negative threshold for that day.
Use Cases:
Traders: It helps traders quickly identify days where significant price movements occurred, allowing them to analyze trends and make informed trading decisions.
Market Analysis: The indicator can be used for backtesting strategies based on significant price movements.
Overall, this code serves as a visual tool for analyzing price volatility in a market based on user-defined thresholds and day-based observations. If you have any specific questions or need further clarification about any part of it, feel free to ask!
Currency Futures StatisticsThe "Currency Futures Statistics" indicator provides comprehensive insights into the performance and characteristics of various currency futures. This indicator is crucial for portfolio management as it combines multiple metrics that are instrumental in evaluating currency futures' risk and return profiles.
Metrics Included:
Historical Volatility:
Definition: Historical volatility measures the standard deviation of returns over a specified period, scaled to an annual basis.
Importance: High volatility indicates greater price fluctuations, which translates to higher risk. Investors and portfolio managers use volatility to gauge the stability of a currency future and to make informed decisions about risk management and position sizing (Hull, J. C. (2017). Options, Futures, and Other Derivatives).
Open Interest:
Definition: Open interest represents the total number of outstanding futures contracts that are held by market participants.
Importance: High open interest often signifies liquidity in the market, meaning that entering and exiting positions is less likely to impact the price significantly. It also reflects market sentiment and the degree of participation in the futures market (Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities).
Year-over-Year (YoY) Performance:
Definition: YoY performance calculates the percentage change in the futures contract's price compared to the same week from the previous year.
Importance: This metric provides insight into the long-term trend and relative performance of a currency future. Positive YoY performance suggests strengthening trends, while negative values indicate weakening trends (Fama, E. F. (1991). Efficient Capital Markets: II).
200-Day Simple Moving Average (SMA) Position:
Definition: This metric indicates whether the current price of the currency future is above or below its 200-day simple moving average.
Importance: The 200-day SMA is a widely used trend indicator. If the price is above the SMA, it suggests a bullish trend, while being below indicates a bearish trend. This information is vital for trend-following strategies and can help in making buy or sell decisions (Bollinger, J. (2001). Bollinger on Bollinger Bands).
Why These Metrics are Important for Portfolio Management:
Risk Assessment: Historical volatility and open interest provide essential information for assessing the risk associated with currency futures. Understanding the volatility helps in estimating potential price swings, which is crucial for managing risk and setting appropriate stop-loss levels.
Liquidity and Market Participation: Open interest is a critical indicator of market liquidity. Higher open interest usually means tighter bid-ask spreads and better liquidity, which facilitates smoother trading and better execution of trades.
Trend Analysis: YoY performance and the SMA position help in analyzing long-term trends. This analysis is crucial for making strategic investment decisions and adjusting the portfolio based on changing market conditions.
Informed Decision-Making: Combining these metrics allows for a holistic view of the currency futures market. This comprehensive view helps in making informed decisions, balancing risks and returns, and optimizing the portfolio to align with investment goals.
In summary, the "Currency Futures Statistics" indicator equips investors and portfolio managers with valuable data points that are essential for effective risk management, liquidity assessment, trend analysis, and overall portfolio optimization.
Pseudo-Renko Stabilized (Val)█ CALCULATE PSEUDO-RENKO VALUE
Calculates and returns the Pseudo-Renko Stabilized value (or close price) based on a given input value, along with the direction of the current Renko brick. This function adapts the traditional Renko brick size dynamically based on the volatility of the input value using a combination of SMA and EMA calculations. The calculated price represents the closing price of the most recent Pseudo-Renko brick, while the direction indicates the trend ( 1 for uptrend, -1 for downtrend).
Parameters:
* `val` :
* Type: ` float `
* Description: The input value upon which the Pseudo-Renko calculations are performed. You can use any price series or custom value as input.
* `sensitivity` :
* Type: ` float `
* Default Value: ` 1.0 `
* Description: Controls the sensitivity of the brick size to the volatility of the `val`. Higher values lead to larger bricks, resulting in a smoother Renko chart. Lower values produce smaller bricks, leading to a more reactive chart.
* Possible Values: Any positive float.
* `length` :
* Type: ` int `
* Default Value: ` 7 `
* Description: The length used for calculating the EMA and SMA in the dynamic brick size calculation. It influences how quickly the brick size adapts to changing volatility of the `val`.
* Possible Values: Any positive integer.
Return Values:
* `lastRenkoClose` :
* Type: ` float `
* Description: The closing price of the last completed Pseudo-Renko brick based on the `val`.
* `renkoDirection` :
* Type: ` int `
* Description: The direction of the current Pseudo-Renko brick based on the `val`:
* ` 1 `: Uptrend
* ` -1 `: Downtrend
* ` 0 `: No change (initially, or no brick change since the previous bar)
Example Usage:
//@version=5
indicator("Pseudo-Renko Stabilized (Val)", overlay=true)
// Get user inputs
sensitivityInput = input.float(0.1, "Sensitivity",0.01,step=0.01)
lengthInput = input.int(5, "Length",2)
// Example usage with the 'close' price as the input value
= pseudo_renko(math.avg(close,open), sensitivityInput, lengthInput)
// Plot the Renko close price
plot(renkoClose, "Renko Close", renkoDirection>0?color.aqua:color.orange,2)
// You can also use other values as input, such as:
// = pseudo_renko(high, sensitivityInput, lengthInput)
// = pseudo_renko(low, sensitivityInput, lengthInput)
This example demonstrates how to use the `pseudo_renko` function within an indicator. It takes user inputs for `sensitivity` and `length`, then calculates the Pseudo-Renko values using the average of the `close` and `open` prices as the `val`. The resulting `renkoClose` price is plotted on the chart, with a color change based on the `renkoDirection`. It also illustrates how you can use other values, like `high` and `low`, as input to the function.
Note: The Pseudo-Renko algorithm is based on adapting the Renko brick size dynamically based on the input `val`. This provides more flexibility compared to the normal, but is experimental. The `sensitivity` and `length` parameters, along with the choice of the `val`, offer further customization to tune the algorithm's behavior to your preference and trading style.
Sinc MAKaiser Windowed Sinc Moving Average Indicator
The Kaiser Windowed Sinc Moving Average is an advanced technical indicator that combines the sinc function with the Kaiser window to create a highly customizable finite impulse response (FIR) filter for financial time series analysis.
Sinc Function: The Ideal Low-Pass Filter
At the core of this indicator is the sinc function, which represents the impulse response of an ideal low-pass filter. In signal processing and technical analysis, the sinc function is crucial because it allows for the creation of filters with precise frequency cutoff characteristics. When applied to financial data, this means the ability to separate long-term trends from short-term fluctuations with remarkable accuracy.
The primary advantage of using a sinc-based filter is the independent control over two critical parameters: the cutoff frequency and the number of samples used. The cutoff frequency, analogous to the "length" in traditional moving averages, determines which price movements are considered significant (low frequency) and which are treated as noise (high frequency). By adjusting the cutoff, analysts can fine-tune the filter to respond to specific market cycles or timeframes of interest.
The number of samples used in the filter doesn't affect the cutoff frequency but instead influences the filter's accuracy and steepness. Increasing the sample size results in a better approximation of the ideal low-pass filter, leading to sharper transitions between passed and attenuated frequencies. This allows for more precise trend identification and noise reduction without changing the fundamental frequency response characteristics.
Kaiser Window: Optimizing the Sinc Filter
While the sinc function provides excellent frequency domain characteristics, it has infinite length in the time domain, which is impractical for real-world applications. This is where the Kaiser window comes into play. By applying the Kaiser window to the sinc function, we create a finite-length filter that approximates the ideal response while minimizing unwanted oscillations (known as the Gibbs phenomenon) in the frequency domain.
The Kaiser window introduces an additional parameter, alpha, which controls the trade-off between the main-lobe width and side-lobe levels in the frequency response. This parameter allows users to fine-tune the filter's behavior, balancing between sharp cutoffs and minimal ripple effects.
Customizable Parameters
The Kaiser Windowed Sinc Moving Average offers several key parameters for customization:
Cutoff: Controls the filter's cutoff frequency, determining the divide between trends and noise.
Length: Sets the number of samples used in the FIR filter calculation, affecting the filter's accuracy and computational complexity.
Alpha: Influences the shape of the Kaiser window, allowing for fine-tuning of the filter's frequency response characteristics.
Centered and Non-Centered Modes
The indicator provides two operational modes:
Non-Centered (Real-time) Mode: Uses half of the windowed sinc function, suitable for real-time analysis and current market conditions.
Centered Mode: Utilizes the full windowed sinc function, resulting in a zero-phase filter. This mode introduces a delay but offers the most accurate trend identification for historical analysis.
Visualization Features
To enhance the analytical value of the indicator, several visualization options are included:
Gradient Coloring: Offers a range of color schemes to represent trend direction and strength.
Glow Effect: An optional visual enhancement for improved line visibility.
Background Fill: Highlights the area between the moving average and price, aiding in trend visualization.
Applications in Technical Analysis
The Kaiser Windowed Sinc Moving Average is particularly useful for precise trend identification, cycle analysis, and noise reduction in financial time series. Its ability to create custom low-pass filters with independent control over cutoff and filter accuracy makes it a powerful tool for analyzing various market conditions and timeframes.
Compared to traditional moving averages, this indicator offers superior frequency response characteristics and reduced lag in trend identification when properly tuned. It provides greater flexibility in filter design, allowing analysts to create moving averages tailored to specific trading strategies or market behaviors.
Conclusion
The Kaiser Windowed Sinc Moving Average represents an advanced approach to price smoothing and trend identification in technical analysis. By making the ideal low-pass filter characteristics of the sinc function practically applicable through Kaiser windowing, this indicator provides traders and analysts with a sophisticated tool for examining price trends and cycles.
Its implementation in Pine Script contributes to the TradingView community by making advanced signal processing techniques accessible for experimentation and further development in technical analysis. This indicator serves not only as a practical tool for market analysis but also as an educational resource for those interested in the intersection of signal processing and financial markets.
Related script:
Thai Gold 96.5%Gold 96.5% Price Display (Test Version)
This Pine Script indicator is a test version designed to display the current price of Thai gold (96.5%) in a customizable table on your TradingView chart. The script calculates the gold price using the latest values for XAU/USD and USD/THB, reflecting the price of gold in Thai Baht (THB) with a purity adjustment.
Features:
- Price Calculation: Computes the Thai gold price by multiplying the XAU/USD price with USD/THB and adjusting for gold purity (0.49 * 0.965).
- Customizable Display: Adjust text size, text color, background color, and table position (Top Right, Top Left, Bottom Right, Bottom Left).
- Formatted Output: Gold price is formatted with commas for better readability.
Inputs:
- Text Size: Choose from tiny, small, normal, large, or huge.
- Text Color: Customize the text color.
- Background Color: Select a background color for the table.
- Table Position: Choose the table position on the chart.
Usage:
Add this test script to your TradingView chart to see the current Thai gold price displayed in a table format. This version is for testing purposes and may be updated based on feedback.
Feel free to test and customize the script further!
Kaiser Window MAKaiser Window Moving Average Indicator
The Kaiser Window Moving Average is a technical indicator that implements the Kaiser window function in the context of a moving average. This indicator serves as an example of applying the Kaiser window and the modified Bessel function of the first kind in technical analysis, providing an open-source implementation of these functions in the TradingView Pine Script ecosystem.
Key Components
Kaiser Window Implementation
This indicator incorporates the Kaiser window, a parameterized window function with certain frequency response characteristics. By making this implementation available in Pine Script, it allows for exploration and experimentation with the Kaiser window in the context of financial time series analysis.
Modified Bessel Function of the First Kind
The indicator includes an implementation of the modified Bessel function of the first kind, which is integral to the Kaiser window calculation. This mathematical function is now accessible within TradingView, potentially useful for other custom indicators or studies.
Customizable Alpha Parameter
The indicator features an adjustable alpha parameter, which directly influences the shape of the Kaiser window. This parameter allows for experimentation with the indicator's behavior:
Lower alpha values: The indicator's behavior approaches that of a Simple Moving Average (SMA)
Moderate alpha values: The behavior becomes more similar to a Weighted Moving Average (WMA)
Higher alpha values: Increases the weight of more recent data points
In signal processing terms, the alpha parameter affects the trade-off between main-lobe width and side lobe level in the frequency domain.
Centered and Non-Centered Modes
The indicator offers two operational modes:
Non-Centered (Real-time) Mode: Uses half of the Kaiser window, starting from the peak. This mode operates similarly to traditional moving averages, suitable for real-time analysis.
Centered Mode: Utilizes the full Kaiser window, resulting in a phase-correct filter. This mode introduces a delay equal to half the window size, with the plot automatically offset to align with the correct time points.
Visualization Options
The indicator includes several visualization features to aid in analysis:
Gradient Coloring: Offers three gradient options:
• Three-color gradient: Includes a neutral color
• Two-color gradient: Traditional up/down color scheme
• Solid color: For a uniform appearance
Glow Effect: An optional visual enhancement for the moving average line.
Background Fill: An option to fill the area between the moving average and the price.
Use Cases
The Kaiser Window Moving Average can be applied similarly to other moving averages. Its primary value lies in providing an example implementation of the Kaiser window and modified Bessel function in TradingView. It serves as a starting point for traders and analysts interested in exploring these mathematical concepts in the context of technical analysis.
Conclusion
The Kaiser Window Moving Average indicator demonstrates the application of the Kaiser window function in a moving average calculation. By providing open-source implementations of the Kaiser window and the modified Bessel function of the first kind, this indicator contributes to the expansion of available mathematical tools in the TradingView Pine Script environment, potentially facilitating further experimentation and development in technical analysis.
