Machine Learning Signal FilterIntroducing the "Machine Learning Signal Filter," an innovative trading indicator designed to leverage the power of machine learning to enhance trading strategies. This tool combines advanced data processing capabilities with user-friendly customization options, offering traders a sophisticated yet accessible means to optimize their market analysis and decision-making processes. Importantly, this indicator does not repaint, ensuring that signals remain consistent and reliable after they are generated.
Machine Learning Integration
The "Machine Learning Signal Filter" employs machine learning algorithms to analyze historical price data and identify patterns that may not be immediately apparent through traditional technical analysis. By utilizing techniques such as regression analysis and neural networks, the indicator continuously learns from new data, refining its predictive capabilities over time. This dynamic adaptability allows the indicator to adjust to changing market conditions, potentially improving the accuracy of trading signals.
Key Features and Benefits
Dynamic Signal Generation: The indicator uses machine learning to generate buy and sell signals based on complex data patterns. This approach enables it to adapt to evolving market trends, offering traders timely and relevant insights. Crucially, the indicator does not repaint, providing reliable signals that traders can trust.
Customizable Parameters: Users can fine-tune the indicator to suit their specific trading styles by adjusting settings such as the temporal synchronization and neural pulse rate. This flexibility ensures that the indicator can be tailored to different market environments.
Visual Clarity and Usability: The indicator provides clear visual cues on the chart, including color-coded signals and optional display of signal curves. Users can also customize the table's position and text size, enhancing readability and ease of use.
Comprehensive Performance Metrics: The indicator includes a detailed metrics table that displays key performance indicators such as return rates, trade counts, and win/loss ratios. This feature helps traders assess the effectiveness of their strategies and make data-driven decisions.
How It Works
The core of the "Machine Learning Signal Filter" is its ability to process and learn from large datasets. By applying machine learning models, the indicator identifies potential trading opportunities based on historical data patterns. It uses regression techniques to predict future price movements and neural networks to enhance pattern recognition. As new data is introduced, the indicator refines its algorithms, improving its accuracy and reliability over time.
Use Cases
Trend Following: Ideal for traders seeking to capitalize on market trends, the indicator helps identify the direction and strength of price movements.
Scalping: With its ability to provide quick signals, the indicator is suitable for scalpers aiming for rapid profits in volatile markets.
Risk Management: By offering insights into trade performance, the indicator aids in managing risk and optimizing trade setups.
In summary, the "Machine Learning Signal Filter" is a powerful tool that combines the analytical strength of machine learning with the practical needs of traders. Its ability to adapt and provide actionable insights makes it an invaluable asset for navigating the complexities of financial markets.
The "Machine Learning Signal Filter" is a tool designed to assist traders by providing insights based on historical data and machine learning techniques. It does not guarantee profitable trades and should be used as part of a comprehensive trading strategy. Users are encouraged to conduct their own research and consider their financial situation before making trading decisions. Trading involves significant risk, and it is possible to lose more than the initial investment. Always trade responsibly and be aware of the risks involved.
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Price & Volume Breakout Fibonacci Probability [TradeDots]📝 OVERVIEW
The "Price & Volume Breakout Fibonacci Probability" indicator is designed to detect the probability of the maximum run-up and drawdown of each breakout trade on an asset, assisting traders in optimizing their take profit and stop loss strategies.
🧮 CALCULATIONS
The algorithm detects price and volume breakouts to activate the Fibonacci levels displayed on the chart. It calculates these levels using the period pivot high and low, with the close price of the breakout bar as the reference price.
The indicator then forward-tests within an user-selected number of bars, detecting the maximum run-up and drawdown during that period. Consequently, it calculates the probability of the price hitting either side of the Fibonacci levels, showing the likelihood of reaching take profit and stop loss targets for each breakout trade.
📊 EXAMPLE
The above example shows two breakout trades, circled within the yellow rectangle zone.
The first trade has a maximum run-up above the +0.382 Fibonacci level zone and a maximum drawdown below the -0.618 Fibonacci level zone.
When the price reaches the maximum run-up, it only has a ~45% probability of moving further upward into the last two zones (25% + 19.44%). This indicates that setting a take profit at a higher level may have less than a 50% chance of success.
Conversely, when the price reaches its maximum drawdown, there is only an ~8% probability of moving further downward into the last drawdown zone. This could indicate a potential reversal.
⚙️ SETTINGS
Breakout Condition: Determines the type of breakout condition to track: "Price", "Volume", "Price & Volume".
Backtest Period: The maximum run-up and drawdown are detected within this bar period.
Price Breakout Period: Specifies the number of bars the price needs to break out from.
Volume Breakout Period: Specifies the number of bars the volume needs to break out from.
Trendline Confirmation: Confirms that the close price needs to be above the trendline.
📈 HOW TO USE
By understanding the probabilities of price movements to both the upside and downside, traders can set take profit and stop loss targets with greater accuracy.
For instance, placing a stop loss order below the zone with the highest probability minimizes the chances of being stopped out of a profitable trade. Conversely, setting a take profit target at the zone with the highest probability increases the win rate.
Additionally, if the price breaches multiple Fibonacci levels during the breakout period, it may indicate an abnormal state, signaling a potential reversal or pullback. This can help traders exit trades in a timely manner.
Traders can adjust their take profit and stop loss levels based on their individual risk tolerance.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Negroni Opening Range StrategyStrategy Summary:
This tool can be used to help identify breakouts from a range during a time-zone of your choosing. It plots a pre-market range, an opening range, it also includes moving average levels that can be used as confluence, as well as plotting previous day SESSION highs and lows.
There are several options on how you wish to close out the trades, all described in more detail below.
Back-testing Inputs:
You define your timezone.
You define how many trades to open on any given day.
You decide to go: long only, short only, or long & short (CAREFUL: "Long & Short" can open trades that effectively closes-out existing ones, for better AND worse!)
You define between which times the strategy will open trades.
You define when it closes any open trades (preventing overnight trades, or leaving trades open into US data times!!).
This hopefully helps make back-testing reflect YOUR trading hours.
NOTE: Renko or Heikin-Ashi charts
For ALL strategies, don’t use Renko or Heikin-Ashi charts unless you know EXACTLY the implications.
Specific to my strategy, using a renko chart can make this 85-90% profitable (I wish it was!!) Although they can be useful, renko charts don’t always capture real wicks, so the renko chart may show your trade up-only but your broker (who is not using renko!!) will have likely stopped you out on a wick somewhere along the line.
NOTE: TradingView ‘Deep backtesting’
For ALL strategies, be cynical of all backtesting (e.g. repainting issues etc) as well as ‘Deep backtesting’ results.
Specific to this strategy, the default settings here SHOULD BE OK, but unfortunately at the time of writing, we can’t see on the chart what exactly ‘deep backtesting’ is calculating. In the past I have noted a number of trades that were not closed at the end of the day, despite my ‘end of day’ trade closing being enabled, so there were big winners and losers that would not have materialized otherwise. As I say, this seems ok at these settings but just always be cynical!!
Opening Range Inputs
You define a pre-market range (example: 08:00 - 09:00).
You define an opening range (example: 09:00 - 09:30).
The strategy will give an update at the close of the opening range to let you know if the opening range has broken out the pre-market range (OR Breakout), or if it has remained inside (OR Inside). The label appears at the end of the opening range NOT at the bar that ‘broke-out’.
This is just a visual cue for you, it has no bearing on what the strategy will do.
The strategy default will trade off the pre-market range, but you can untick this if you prefer to trade off the opening range.
Opening Trades:
Strategy goes long when the bar (CLOSE) crosses-over the ‘pre-market’ high (not the ‘opening range’ high); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Strategy goes short when the bar (CLOSE) crosses-under the ‘pre-market’ low (not the ‘opening range low); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Remember, you can untick this if you prefer to trade off the opening range instead.
NOTES:
Using momentum indicators can help (RSI and MACD): especially to trade range plays in failed breakouts, when momentum shifts… but the strategy won’t do this for you!
Using an anchored vwap at the session open can also provide nice confluence, as well as take-profit levels at the upper/lower of 3x standard deviation.
CLOSING TRADES:
You have 6 take-profit (TP) options:
1) Full TP: uses ATR Multiplier - Full TP at the ATR parameters as defined in inputs.
2) Take Partial profits: ATR Multiplier - Takes partial profits based on parameters as defined in inputs (i.e close 40% of original trade at TP1, close another 40% of original trade at TP2, then the remainder at Full TP as set in option 1.).
3) Full TP: Trailing Stop - Applies a Trailing Stop at the number of points, as defined in inputs.
4) Full TP: MA cross - Takes profit when price crosses ‘Trend MA’ as defined in inputs.
5) Scalp: Points - closes at a set number of points, as defined in inputs.
6) Full TP: PMKT Multiplier - places a SL at opposite pre-market Hi/Low (we go long at a break-out of the pre-market high, 50% would place a SL at the pre-market range mid-point; 100% would place a SL at the pre-market low)'. This takes profit at the input set in option 1).
Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram
Certainly! Here’s an enhanced description of the Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram indicator with detailed usage instructions and explanations of why it's effective:
Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram
Description:
The Gabriel's Relative Unrealized Profit with Dynamic MVRV Histogram is an advanced trading indicator designed to offer in-depth insights into asset profitability and market valuation. By integrating Relative Unrealized Profit (RUP) and the Market Value to Realized Value (MVRV) Ratio, this indicator provides a nuanced view of an asset's performance and potential trading signals.
Key Components:
SMA Length and Volume Indicator:
SMA Length: Defines the period for the Simple Moving Average (SMA) used to calculate the entry price, defaulted to 14 periods. This smoothing technique helps estimate the average historical price at which the asset was acquired.
Volume Indicator: Allows selection between "volume" and "vwap" (Volume-Weighted Average Price) for calculating entry volume. The choice impacts the calculation of entry volume, either based on standard trading volume or a weighted average price.
Realized Price Calculation:
Computes the average price over a specified period (default of 30 periods) to establish the realized price. This serves as a benchmark for evaluating the cost basis of the asset.
MVRV Calculation:
Current Price: The most recent closing price of the asset, representing its market value.
Total Cost: Calculated as the product of the entry price and entry volume, reflecting the total investment made.
Unrealized Profit: The difference between the current price and the entry price, multiplied by entry volume, indicating profit or loss that has yet to be realized.
Relative Unrealized Profit: Expressed as a percentage of the total cost, showing how much profit or loss exists relative to the initial investment.
Market Value and Realized Value: Market Value is the current price multiplied by entry volume, while Realized Value is the realized price multiplied by entry volume. The MVRV Ratio is obtained by dividing Market Value by Realized Value.
Normalization:
Normalizes both Relative Unrealized Profit and MVRV Ratio to a standardized range of -100 to 100. This involves calculating the minimum and maximum values over a 100-period window to ensure comparability and relevance.
Histogram Calculation:
The histogram is derived from the difference between the normalized Relative Unrealized Profit and the normalized MVRV Ratio. It visually represents the disparity between the two metrics, highlighting potential trading signals.
Plotting and Alerts:
Plots:
Normalized Relative Unrealized Profit (Blue Line): Plotted in blue, this line shows the scaled measure of unrealized profit. Positive values indicate potential gains, while negative values suggest potential losses.
Normalized MVRV Ratio (Red Line): Plotted in red, this line represents the scaled MVRV Ratio. Higher values suggest that the asset’s market value significantly exceeds its realized value, indicating potential overvaluation, while lower values suggest potential undervaluation.
Histogram (Green Bars): Plotted in green, this histogram displays the difference between the normalized Relative Unrealized Profit and the normalized MVRV Ratio. Positive bars indicate that the asset’s profitability is exceeding its market valuation, while negative bars suggest the opposite.
Alerts:
High Histogram Alert: Activated when the histogram value exceeds 50. This condition signals a strong positive divergence, indicating that the asset's profitability is outperforming its market valuation. It may suggest a buying opportunity or indicate that the asset is undervalued relative to its potential profitability.
Low Histogram Alert: Triggered when the histogram value falls below -50. This condition signals a strong negative divergence, indicating that the asset's profitability is lagging behind its market valuation. It may suggest a selling opportunity or indicate that the asset is overvalued relative to its profitability.
How to Use the Indicator:
Setup: Customize the SMA Length, Volume Indicator, and Realized Price Length based on your trading strategy and asset volatility. These parameters allow you to tailor the indicator to different market conditions and asset types.
Interpretation:
Blue Line (Normalized Relative Unrealized Profit): Monitor this line to gauge the profitability of holding the asset. Significant positive values suggest that the asset is currently in a profitable position relative to its purchase price.
Red Line (Normalized MVRV Ratio): Use this line to assess whether the asset is trading at a premium or discount relative to its cost basis. Higher values may indicate overvaluation, while lower values suggest undervaluation.
Green Bars (Histogram): Observe the histogram for deviations between RUP and MVRV Ratio. Large positive bars indicate that the asset's profitability is strong relative to its valuation, signaling potential buying opportunities. Large negative bars suggest that the asset's profitability is weak relative to its valuation, signaling potential selling opportunities.
Trading Strategy:
Bullish Conditions: When the histogram shows large positive values, it suggests that the asset’s profitability is strong compared to its valuation. Consider this as a potential buying signal, especially if the histogram remains consistently positive.
Bearish Conditions: When the histogram displays large negative values, it indicates that the asset’s profitability is weak compared to its valuation. This may signal a potential selling opportunity or caution, particularly if the histogram remains consistently negative.
Why This Indicator is Effective:
Integrated Metrics: Combining Relative Unrealized Profit and MVRV Ratio provides a comprehensive view of asset performance. This integration allows traders to evaluate both profitability and market valuation in one cohesive tool.
-5% Rule Investment Method ＠Ray_SP500NISASigns are displayed on the chart when the price drops more than 5% from the previous week. Otherwise, the previous week's change is displayed in a smaller size.
Buy if it falls 5% or more from the previous week, and do not buy if it does not fall. The sign is for the sole purpose of making it easier to understand.
This method is expected to be more effective and profitable than this method alone when used in conjunction with accumulation investing.
Details of the 5% Rule Investment Method
It is basically designed to be applied to the S&P 500.
The sign to follow is a simple rule: buy only when the S&P 500 has fallen 5% or more from the previous week. This makes this investment method easy for beginners.
Combined with accumulation: This method, when used in conjunction with accumulation, can be expected to produce higher returns than when used alone.
As an added bonus, we also provide a sign when the market rises 10% or more from the previous week, which is something to keep in mind.
Supertrend with Extreme SignalsOriginality and Usefulness
The "Supertrend with Extreme Signals" indicator is an innovative tool I've developed to combine the strengths of the Supertrend indicator with the RSI (Relative Strength Index). This combination enhances the accuracy of entry and exit signals, making it more useful for traders looking to gain a comprehensive understanding of market conditions.
Justification for Mashup:
Supertrend: This is a trend-following indicator that identifies the current market trend and potential reversal points by adjusting dynamically based on market volatility.
RSI: A momentum oscillator that measures the speed and change of price movements. It helps pinpoint overbought and oversold conditions, adding an extra layer of confirmation to trend signals.
By merging these two indicators, the script filters out false signals and improves the precision of trade entries and exits. The Supertrend identifies the trend direction, while the RSI confirms the strength and potential reversals within that trend.
Description
Overview
The "Supertrend with Extreme Signals" indicator is a powerful hybrid tool that brings together the trend-following capability of the Supertrend and the momentum analysis of RSI. This integration provides clear buy and sell signals, helping traders make more informed decisions.
What It Does
Trend Identification: Utilizes the Supertrend to determine the prevailing market trend.
Signal Confirmation: Uses RSI to confirm signals by identifying overbought and oversold conditions.
Buy and Sell Signals: Generates buy signals when the price crosses above the Supertrend line and RSI indicates oversold conditions. Generates sell signals when the price crosses below the Supertrend line and RSI indicates overbought conditions.
How It Works
Supertrend Calculation:
Calculates the Average True Range (ATR) to assess market volatility.
Computes upper and lower levels based on the mid-price and ATR.
Determines trend direction by smoothing these levels over a specified period.
Dynamically adjusts the Supertrend value based on market conditions.
RSI Calculation:
Calculates the RSI over a defined period to measure price momentum.
Uses RSI levels to identify overbought (above 70) and oversold (below 30) conditions.
Signal Generation:
Buy Signal: Triggered when the price crosses above the Supertrend line and RSI is below the oversold threshold.
Sell Signal: Triggered when the price crosses below the Supertrend line and RSI is above the overbought threshold.
How to Use It
Trend Following: Use the Supertrend color to identify the current trend (green for uptrend, red for downtrend).
Entry Signals: Look for buy signals (green label) when the price crosses above the Supertrend line and RSI is in the oversold zone.
Exit Signals: Look for sell signals (red label) when the price crosses below the Supertrend line and RSI is in the overbought zone.
Visual Confirmation: The background color changes based on the trend direction, providing a quick visual cue for the current market state.
This script is especially useful for traders who combine trend-following strategies with momentum indicators. It helps filter out false signals and provides a robust framework for identifying profitable trading opportunities.
Concepts Underlying Calculations
ATR (Average True Range): Measures market volatility by calculating the average range of price movements over a specified period.
Supertrend: A trend-following indicator that adjusts dynamically based on market volatility.
RSI (Relative Strength Index): A momentum oscillator that measures the speed and change of price movements, helping to identify overbought and oversold conditions.
By combining these concepts, the "Supertrend with Extreme Signals" indicator offers a balanced approach to trading. It considers both trend direction and market momentum, making it a powerful tool for improving trading performance through informed market analysis.
Multi-Step Vegas SuperTrend - strategy [presentTrading]Long time no see! I am back : ) Please allow me to gain some warm-up.
█ Introduction and How it is Different
The "Vegas SuperTrend Strategy" is an enhanced trading strategy that leverages both the Vegas Channel and SuperTrend indicators to generate buy and sell signals.
What sets this strategy apart from others is its dynamic adjustment to market volatility and its multi-step take profit mechanism. Unlike traditional single-step profit-taking approaches, this strategy allows traders to systematically scale out of positions at predefined profit levels, thereby optimizing their risk-reward ratio and maximizing potential gains.
BTCUSD 6hr performance
█ Strategy, How it Works: Detailed Explanation
The Vegas SuperTrend Strategy combines the strengths of the Vegas Channel and SuperTrend indicators to identify market trends and generate trade signals. The following subsections delve into the details of how each component works and how they are integrated.
🔶 Vegas Channel Calculation
The Vegas Channel is based on a simple moving average (SMA) and the standard deviation (STD) of the closing prices over a specified period. The channel is defined by upper and lower bounds that are dynamically adjusted based on market volatility.
Simple Moving Average (SMA):
SMA_vegas = (1/N) * Σ(Close_i) for i = 0 to N-1
where N is the length of the Vegas Window.
Standard Deviation (STD):
STD_vegas = sqrt((1/N) * Σ(Close_i - SMA_vegas)^2) for i = 0 to N-1
Vegas Channel Upper and Lower Bounds:
VegasChannelUpper = SMA_vegas + STD_vegas
VegasChannelLower = SMA_vegas - STD_vegas
The details are here:
🔶 Trend Detection and Trade Signals
The strategy determines the current market trend based on the closing price relative to the SuperTrend bounds:
Market Trend:
MarketTrend = 1 if Close > SuperTrendPrevLower
-1 if Close < SuperTrendPrevUpper
Previous Trend otherwise
Trade signals are generated when there is a shift in the market trend:
Bullish Signal: When the market trend shifts from -1 to 1.
Bearish Signal: When the market trend shifts from 1 to -1.
🔶 Multi-Step Take Profit Mechanism
The strategy incorporates a multi-step take profit mechanism that allows for partial exits at predefined profit levels. This helps in locking in profits gradually and reducing exposure to market reversals.
Take Profit Levels:
The take profit levels are calculated as percentages of the entry price:
TakeProfitLevel_i = EntryPrice * (1 + TakeProfitPercent_i/100) for long positions
TakeProfitLevel_i = EntryPrice * (1 - TakeProfitPercent_i/100) for short positions
Multi-steps take profit local picture:
█ Trade Direction
The trade direction can be customized based on the user's preference:
Long: The strategy only takes long positions.
Short: The strategy only takes short positions.
Both: The strategy can take both long and short positions based on the market trend.
█ Usage
To use the Vegas SuperTrend Strategy, follow these steps:
Configure Input Settings:
- Set the ATR period, Vegas Window length, SuperTrend Multiplier, and Volatility Adjustment Factor.
- Choose the desired trade direction (Long, Short, Both).
- Enable or disable the take profit mechanism and set the take profit percentages and amounts for each step.
█ Default Settings
The default settings of the strategy are designed to provide a balanced approach to trading. Below is an explanation of each setting and its effect on the strategy's performance:
ATR Period (10): This setting determines the length of the ATR used in the SuperTrend calculation. A longer period smoothens the ATR, making the SuperTrend less sensitive to short-term volatility. A shorter period makes the SuperTrend more responsive to recent price movements.
Vegas Window Length (100): This setting defines the period for the Vegas Channel's moving average. A longer window provides a broader view of the market trend, while a shorter window makes the channel more responsive to recent price changes.
SuperTrend Multiplier (5): This base multiplier adjusts the sensitivity of the SuperTrend to the ATR. A higher multiplier makes the SuperTrend less sensitive, reducing the frequency of trade signals. A lower multiplier increases sensitivity, generating more signals.
Volatility Adjustment Factor (5): This factor dynamically adjusts the SuperTrend multiplier based on the width of the Vegas Channel. A higher factor increases the sensitivity of the SuperTrend to changes in market volatility, while a lower factor reduces it.
Take Profit Percentages (3.0%, 6.0%, 12.0%, 21.0%): These settings define the profit levels at which portions of the trade are exited. They help in locking in profits progressively as the trade moves in favor.
Take Profit Amounts (25%, 20%, 10%, 15%): These settings determine the percentage of the position to exit at each take profit level. They are distributed to ensure that significant portions of the trade are closed as the price reaches the set levels, reducing exposure to reversals.
Adjusting these settings can significantly impact the strategy's performance. For instance, increasing the ATR period or the SuperTrend multiplier can reduce the number of trades, potentially improving the win rate but also missing out on some profitable opportunities. Conversely, lowering these values can increase trade frequency, capturing more short-term movements but also increasing the risk of false signals.
MACD with SAR Indicator [CHE] MACD with SAR Indicator
Introduction
"The whole is greater than the sum of its parts. " The "MACD with SAR Indicator" is an innovative technical analysis tool that combines the strengths of the Moving Average Convergence Divergence (MACD) indicator with the Parabolic Stop and Reverse (SAR) indicator. This indicator provides traders with an enhanced method to detect trend changes and determine optimal entry and exit points in the market by using the SAR based on the MACD line to better identify reversal points. The combination generates clear trend reversal signals, which are visually represented through long (L) and short (S) signals on the chart.
Originality and Usefulness
This indicator differs from traditional MACD or SAR indicators by combining the trend-following calculations of the SAR with the trend strength and momentum calculations of the MACD. This enables a more precise identification of trend changes and provides clear buy and sell signals, which is particularly useful for manual traders.
Key Features and Functionality
1. Combination of MACD and SAR
- Why this Combination?: The MACD is known for its ability to measure the strength and direction of a trend, while the SAR is specifically designed to identify reversal points. By combining these two indicators, traders can better understand both the trend strength and potential turning points in the market.
- How Components Work Together: The MACD measures the difference between fast and slow moving averages, indicating market momentum. The SAR follows the MACD line instead of the price and marks potential reversal points more accurately. When the MACD signals a new trend and the SAR confirms it, the indicator provides reliable trading opportunities.
2. Adjustable Parameters
- MACD Settings: Users can adjust the lengths of the fast and slow moving averages (default: 28 and 38 periods) and the signal smoothing (default: 9 periods) to tailor the indicator to different market conditions.
- SAR Settings: Users can adjust the start value (default: 0.01), increment (default: 0.01), and maximum value (default: 0.18) of the SAR to control sensitivity and responsiveness.
3. Visual Representation and Signals
- Color-Coded Histograms: The histogram shows the difference between the MACD and signal line and is color-coded to highlight the direction of the trend.
- Signal Labels: The indicator automatically adds "L" (Long) and "S" (Short) labels on the chart to show the current positions to traders.
4. Alert Settings
- Custom Alerts: Alerts can be set to notify traders when the MACD and SAR experience significant state changes, such as when the histogram switches from rising to falling or vice versa.
5. Toggle Display
- Display Mode: Users can toggle the display of the MACD_SAR oscillator and MACD to focus on the information most relevant to their trading strategy.
Application and Benefits
- Versatility: This indicator can be used in various market conditions and for different trading strategies, including trend following and reversal trading.
- Ease of Interpretation: The clear visual representation and automatic signals make it easier for traders to identify trading opportunities and track trends.
- Customizability: With numerous settings options, the indicator can be tailored to individual preferences and specific market conditions.
Conclusion
The "MACD with SAR Indicator" is a valuable tool for traders seeking precise and reliable signals to identify market trends and make profitable trading decisions. With its extensive customization options, powerful features, and the ability to toggle displays, this indicator provides excellent support for technical analysis.
By emphasizing the synergy between the MACD and SAR indicators, highlighting the default settings, and clarifying that the SAR is based on the MACD line and generates clear trend reversal signals through long and short labels, this revised description should help users understand the functionalities and advantages of your indicator while meeting TradingView's publication requirements.
Best regards Chervolino
Harmonic Patterns Library [TradingFinder]🔵 Introduction
Harmonic patterns blend geometric shapes with Fibonacci numbers, making these numbers fundamental to understanding the patterns.
One person who has done a lot of research on harmonic patterns is Scott Carney.Scott Carney's research on harmonic patterns in technical analysis focuses on precise price structures based on Fibonacci ratios to identify market reversals.
Key patterns include the Gartley, Bat, Butterfly, and Crab, each with specific alignment criteria. These patterns help traders anticipate potential market turning points and make informed trading decisions, enhancing the predictability of technical analysis.
🟣 Understanding 5-Point Harmonic Patterns
In the current library version, you can easily draw and customize most XABCD patterns. These patterns often form M or W shapes, or a combination of both. By calculating the Fibonacci ratios between key points, you can estimate potential price movements.
All five-point patterns share a similar structure, differing only in line lengths and Fibonacci ratios. Learning one pattern simplifies understanding others.
🟣 Exploring the Gartley Pattern
The Gartley pattern appears in both bullish (M shape) and bearish (W shape) forms. In the bullish Gartley, point X is below point D, and point A surpasses point C. Point D marks the start of a strong upward trend, making it an optimal point to place a buy order.
The bearish Gartley mirrors the bullish pattern with inverted Fibonacci ratios. In this scenario, point D indicates the start of a significant price drop. Traders can place sell orders at this point and buy at lower prices for profit in two-way markets.
🟣 Analyzing the Butterfly Pattern
The Butterfly pattern also manifests in bullish (M shape) and bearish (W shape) forms. It resembles the Gartley pattern but with point D lower than point X in the bullish version.
The Butterfly pattern involves deeper price corrections than the Gartley, leading to more significant price fluctuations. Point D in the bullish Butterfly indicates the beginning of a sharp price rise, making it an entry point for buy orders.
The bearish Butterfly has inverted Fibonacci ratios, with point D marking the start of a sharp price decline, ideal for sell orders followed by buying at lower prices in two-way markets.
🟣 Insights into the Bat Pattern
The Bat pattern, appearing in bullish (M shape) and bearish (W shape) forms, is one of the most precise harmonic patterns. It closely resembles the Butterfly and Gartley patterns, differing mainly in Fibonacci levels.
The bearish Bat pattern shares the Fibonacci ratios with the bullish Bat, with an inverted structure. Point D in the bearish Bat marks the start of a significant price drop, suitable for sell orders followed by buying at lower prices for profit.
🟣 The Crab Pattern Explained
The Crab pattern, found in both bullish (M shape) and bearish (W shape) forms, is highly favored by analysts. Discovered in 2000, the Crab pattern features a larger final wave correction compared to other harmonic patterns.
The bearish Crab shares Fibonacci ratios with the bullish version but in an inverted form. Point D in the bearish Crab signifies the start of a sharp price decline, making it an ideal point for sell orders followed by buying at lower prices for profitable trades.
🟣 Understanding the Shark Pattern
The Shark pattern appears in bullish (M shape) and bearish (W shape) forms. It differs from previous patterns as point C in the bullish Shark surpasses point A, with unique level measurements.
The bearish Shark pattern mirrors the Fibonacci ratios of the bullish Shark but is inverted. Point D in the bearish Shark indicates the start of a sharp price drop, ideal for placing sell orders and buying at lower prices to capitalize on the pattern.
🟣 The Cypher Pattern Overview
The Cypher pattern is another that appears in both bullish (M shape) and bearish (W shape) forms. It resembles the Shark pattern, with point C in the bullish Cypher extending beyond point A, and point D forming within the XA line.
The bearish Cypher shares the Fibonacci ratios with the bullish Cypher but in an inverted structure. Point D in the bearish Cypher marks the start of a significant price drop, perfect for sell orders followed by buying at lower prices.
🟣 Introducing the Nen-Star Pattern
The Nen-Star pattern appears in both bullish (M shape) and bearish (W shape) forms. In the bullish Nen-Star, point C extends beyond point A, and point D, the final point, forms outside the XA line, making CD the longest wave.
The bearish Nen-Star has inverted Fibonacci ratios, with point D indicating the start of a significant price drop. Traders can place sell orders at point D and buy at lower prices to profit from this pattern in two-way markets.
The 5-point harmonic patterns, commonly referred to as XABCD patterns, are specific geometric price structures identified in financial markets. These patterns are used by traders to predict potential price movements based on historical price data and Fibonacci retracement levels.
Here are the main 5-point harmonic patterns :
Gartley Pattern
Anti-Gartley Pattern
Bat Pattern
Anti-Bat Pattern
Alternate Bat Pattern
Butterfly Pattern
Anti-Butterfly Pattern
Crab Pattern
Anti-Crab Pattern
Deep Crab Pattern
Shark Pattern
Anti- Shark Pattern
Anti Alternate Shark Pattern
Cypher Pattern
Anti-Cypher Pattern
🔵 How to Use
To add "Order Block Refiner Library", you must first add the following code to your script.
import TFlab/Harmonic_Chart_Pattern_Library_TradingFinder/1 as HP
🟣 Parameters
XABCD(Name, Type, Show, Color, LineWidth, LabelSize, ShVF, FLPC, FLPCPeriod, Pivot, ABXAmin, ABXAmax, BCABmin, BCABmax, CDBCmin, CDBCmax, CDXAmin, CDXAmax) =>
Parameters:
Name (string)
Type (string)
Show (bool)
Color (color)
LineWidth (int)
LabelSize (string)
ShVF (bool)
FLPC (bool)
FLPCPeriod (int)
Pivot (int)
ABXAmin (float)
ABXAmax (float)
BCABmin (float)
BCABmax (float)
CDBCmin (float)
CDBCmax (float)
CDXAmin (float)
CDXAmax (float)
🟣 Genaral Parameters
Name : The name of the pattern.
Type: Enter "Bullish" to draw a Bullish pattern and "Bearish" to draw an Bearish pattern.
Show : Enter "true" to display the template and "false" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Logical Parameters
ShVF : If this parameter is on "true" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "false" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
FLPC : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the lateest pattern seeing and a sharp reduction in reward to risk.
FLPCPeriod : Using this parameter you can determine that the last pivot is based on Pivot period.
Pivot : You need to determine the period of the zigzag indicator. This factor is the most important parameter in pattern recognition.
ABXAmin : Minimum retracement of "AB" line compared to "XA" line.
ABXAmax : Maximum retracement of "AB" line compared to "XA" line.
BCABmin : Minimum retracement of "BC" line compared to "AB" line.
BCABmax : Maximum retracement of "BC" line compared to "AB" line.
CDBCmin : Minimum retracement of "CD" line compared to "BC" line.
CDBCmax : Maximum retracement of "CD" line compared to "BC" line.
CDXAmin : Minimum retracement of "CD" line compared to "XA" line.
CDXAmax : Maximum retracement of "CD" line compared to "XA" line.
🟣 Function Outputs
This library has two outputs. The first output is related to the alert of the formation of a new pattern. And the second output is related to the formation of the candlestick pattern and you can draw it using the "plotshape" tool.
Candle Confirmation Logic :
Example :
import TFlab/Harmonic_Chart_Pattern_Library_TradingFinder/1 as HP
PP = input.int(3, 'ZigZag Pivot Period')
ShowBull = input.bool(true, 'Show Bullish Pattern')
ShowBear = input.bool(true, 'Show Bearish Pattern')
ColorBull = input.color(#0609bb, 'Color Bullish Pattern')
ColorBear = input.color(#0609bb, 'Color Bearish Pattern')
LineWidth = input.int(1 , 'Width Line')
LabelSize = input.string(size.small , 'Label size' , options = )
ShVF = input.bool(false , 'Show Valid Format')
FLPC = input.bool(false , 'Show Formation Last Pivot Confirm')
FLPCPeriod =input.int(2, 'Period of Formation Last Pivot')
//Call function
= HP.XABCD('Bullish Bat', 'Bullish', ShowBull, ColorBull , LineWidth, LabelSize ,ShVF, FLPC, FLPCPeriod, PP, 0.382, 0.50, 0.382, 0.886, 1.618, 2.618, 0.85, 0.9)
= HP.XABCD('Bearish Bat', 'Bearish', ShowBear, ColorBear , LineWidth, LabelSize ,ShVF, FLPC, FLPCPeriod, PP, 0.382, 0.50, 0.382, 0.886, 1.618, 2.618, 0.85, 0.9)
//Alert
if BearAlert
alert('Bearish Harmonic')
if BullAlert
alert('Bulish Harmonic')
//CandleStick Confirm
plotshape(BearCandleConfirm, style = shape.arrowdown, color = color.red)
plotshape(BullCandleConfirm, style = shape.arrowup, color = color.green, location = location.belowbar )
20-day High BreakoutOverview:
The 20-day High Breakout Indicator is a very simple yet powerful tool designed for traders seeking to capitalize on significant price movements in the stock market. This indicator identifies potential buy and sell signals based on a stock's 20-day high breakout levels, making it an essential addition to your trading strategy.
Key Features:
Swing Period Input: Customize the swing period to your preferred number of days, with a default of 20 days, allowing flexibility based on your trading style.
Trailing Stop Level: Automatically calculates the trailing stop level based on the highest high and lowest low within the defined swing period, helping to manage risk and lock in profits.
Buy and Sell Signals: Generates clear buy signals when the price crosses above the trailing stop level and sell signals when the price crosses below, enabling timely entries and exits.
Visual Indicators: Plots buy signals as green upward triangles below the bars and sell signals as red downward triangles above the bars, providing easy-to-interpret visual cues directly on the chart.
How It Works:
Resistance and Support Levels: The indicator calculates the highest high (resistance) and lowest low (support) over the defined swing period.
Swing Direction: It determines the market direction by comparing the current closing price to the previous resistance and support levels.
Trailing Stop Calculation: Depending on the market direction, the trailing stop level is set to either the support or resistance level.
Signal Generation: Buy and sell signals are generated based on the crossover of the closing price and the trailing stop level, filtered to ensure only valid signals are displayed.
Visual Representation: The trailing stop level is plotted as a line, and buy/sell signals are marked with respective shapes for easy identification.
Usage:
Trend Following: Ideal for traders looking to follow trends and catch significant breakouts in the stock price.
Risk Management: Helps in managing risk by providing a trailing stop level that adjusts with market movements.
Visual Clarity: The clear visual signals make it easy for traders to interpret and act upon the indicator's signals.
Add the 20-day High Breakout Indicator to your TradingView charts to enhance your trading strategy and gain an edge in identifying profitable trading opportunities.
Bitcoin Logarithmic Regression
This indicator displays logarithmic regression channels for Bitcoin. A logarithmic regression is a function that increases or decreases rapidly at first, but then steadily slows as time moves. The original version of this indicator/model was created as an open source script by a user called Owain but is not available on TradingView anymore. So I decided to update the code to the latest version of pinescript and fine tune some of the parameters.
How to read and use the logarithmic regression:
There are 3 different regression lines or channels visible:
Green Channel: These lines represent different levels of support derived from the logarithmic regression model.
Purpose: The green channel is used to identify potential support levels where the price might find a bottom or bounce back upwards.
Interpretation:
If the price is approaching or touching the lower green lines, it might indicate a buying opportunity or an area where the price is considered undervalued.
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Red Channel: These lines represent different levels of resistance derived from the logarithmic regression model.
Purpose: The red channel is used to identify potential resistance levels where the price might encounter selling pressure or face difficulty moving higher.
Interpretation:
If the price is approaching or touching the upper red lines, it might indicate a selling opportunity or an area where the price is considered overvalued.
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Purple Line This line represents to so-called "fair price" of Bitcoin according to the regression model.
Purpose: The purple line can be used to identify if the current price of Bitcoin is under- or overvalued.
Interpretation: A simple interpretation here would be that over time the price will have the tendency to always return to its "fair price", so starting to DCA more when price is under the line and less when it is over the line could be a suitable investment strategy.
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Practical Application:
You can use this regression channel to build your own, long term, trading strategies. Notice how Bitcoin seems to always act in kind of the same 4 year cycle:
- Price likes to trade around the purple line at the time of the halvings
- After the halvings we see an extended sideways range for up to 300 days
- After the sideways range Bitcoin goes into a bull market frenzy (the area between the green and red channel)
- The price tops out at the upper red channel and then enters a prolonged bear market.
Buying around the purple line or lower line of the green channel and selling once the price reaches the red channel can be a suitable and very profitable strategy.
Symbols Correlation, built for pair tradingOverview:
This script is designed for pairs trading. If you are not familiar with pairs trading, I suggest learning about it, as it can be a profitable strategy in neutral markets (or neutral trends between two assets). The correlation between two assets is the foundation of pairs trading, and without it, the chances of making a profit are low.
Correlation can be described in two opposite ways:
1: Absolute positive correlation (meaning the asset prices move together).
-1: Absolute negative correlation (meaning the asset prices move in opposite directions).
Any value between 1 and -1 indicates some degree of correlation, but generally, values higher than 0.7 or lower than -0.7 are considered significant.
Features:
Typically, correlation is measured using the closing prices. This script adds three more correlation studies based on open, high, and low prices. By using all four lines, we can get a better understanding of the pair's correlation.
How to Read This Indicator:
To use this indicator effectively, you need to input your pair as a ratio. For example, if your pair is TSN and ZBH, enter it in the symbol search as: TSN/ZBH
Gray Area : This area indicates "no high correlation" (default is between -0.8 and 0.8, adjustable in the settings).
Gray Line : This represents the close correlation within the "no high correlation" range.
Green Line : This represents the close correlation within the "high correlation" range.
Dot Lines : These represent the open, high, and low correlations.
Example Interpretations:
A : All four lines are close together & the line is green – very good correlation!
B : The line is gray, and the dot lines are apart – not a strong correlation.
C : When the close correlation remains green for a long time, it signals a strong correlation.
Application in Pairs Trading:
In pairs trading, aim for the highest possible correlation, and it is important to have a sustained correlation over a long period. Pairs that correlate only part of the year but not consistently are less reliable for pairs trading.
This is an example for good correlation for pairs trading:
This is an example for bad correlation for pairs trading:
Here is a view of my full indicators when doing pairs trading:
ICT KillZones + Pivot Points [TradingFinder] Support/Resistance 🟣 Introduction
Pivot Points are critical levels on a price chart where trading activity is notably high. These points are derived from the prior day's price data and serve as key reference markers for traders' decision-making processes.
Types of Pivot Points :
Floor
Woodie
Camarilla
Fibonacci
🔵 Floor Pivot Points
Widely utilized in technical analysis, floor pivot points are essential in identifying support and resistance levels. The central pivot point (PP) acts as the primary level, suggesting the trend's likely direction.
The additional resistance levels (R1, R2, R3) and support levels (S1, S2, S3) offer further insight into potential trend reversals or continuations.
🔵 Camarilla Pivot Points
Featuring eight distinct levels, Camarilla pivot points closely correspond with support and resistance, making them highly effective for setting stop-loss orders and profit targets.
🔵 Woodie Pivot Points
Similar to floor pivot points, Woodie pivot points differ by placing greater emphasis on the closing price, often resulting in different pivot levels compared to the floor method.
🔵 Fibonacci Pivot Points
Fibonacci pivot points combine the standard floor pivot points with Fibonacci retracement levels applied to the previous trading period's range. Common retracement levels used are 38.2%, 61.8%, and 100%.
🟣 Sessions
Financial markets are divided into specific time segments, known as sessions, each with unique characteristics and activity levels. These sessions are active at different times throughout the day.
The primary sessions in financial markets include :
Asian Session
European Session
New York Session
The timing of these major sessions in UTC is as follows :
Asian Session: 23:00 to 06:00
European Session: 07:00 to 14:25
New York Session: 14:30 to 22:55
🟣 Kill Zones
Kill zones are periods within a session marked by heightened trading activity. During these times, trading volume surges and price movements become more pronounced.
The timing of the major kill zones in UTC is :
Asian Kill Zone: 23:00 to 03:55
European Kill Zone: 07:00 to 09:55
New York Kill Zone: 14:30 to 16:55
Combining kill zones and pivot points in financial market analysis provides several advantages :
Enhanced Market Sentiment Analysis : Aligns key price levels with high-activity periods for a clearer market sentiment.
Improved Timing for Trade Entries and Exits : Helps better time trades based on when price movements are most likely.
Higher Probability of Successful Trades : Increases the accuracy of predicting market movements and placing profitable trades.
Strategic Stop-Loss and Profit Target Placement : Allows for precise risk management by strategically setting stop-loss and profit targets.
Versatility Across Different Time Frames : Effective in both short and long time frames, suitable for various trading strategies.
Enhanced Trend Identification and Confirmation : Confirms trends using both pivot levels and high-activity periods, ensuring stronger trend validation.
In essence, this integrated approach enhances decision-making, optimizes trading performance, and improves risk management.
🟣 How to Use
🔵 Two Approaches to Trading Pivot Points
There are two main strategies for trading pivot points: utilizing "pivot point breakouts" and "price reversals."
🔵 Pivot Point Breakout
When the price breaks through pivot lines, it signals a shift in market sentiment to the trader. In the case of an upward breakout, where the price crosses these pivot lines, a trader might enter a long position, placing their stop-loss just below the pivot point (P).
Conversely, if the price breaks downward, a short position can be initiated below the pivot point. When using the pivot point breakout strategy, the first and second support levels can serve as profit targets in an upward trend. In a downward trend, these roles are filled by the first and second resistance levels.
🔵 Price Reversal
An alternative method involves waiting for the price to reverse at the support and resistance levels. To implement this strategy, traders should take positions opposite to the prevailing trend as the price rebounds from the pivot point.
While this tool is commonly used in higher time frames, it tends to produce better results in shorter time frames, such as 1-hour, 30-minute, and 15-minute intervals.
Three Strategies for Trading the Kill Zone
There are three principal strategies for trading within the kill zone :
Kill Zone Hunt
Breakout and Pullback to Kill Zone
Trading in the Trend of the Kill Zone
🔵 Kill Zone Hunt
This strategy involves waiting until the kill zone concludes and its high and low lines are established. If the price reaches one of these lines within the same session and is strongly rejected, a trade can be executed.
🔵 Breakout and Pullback to Kill Zone
In this approach, once the kill zone ends and its high and low lines stabilize, a trade can be made if the price breaks one of these lines decisively within the same session and then pulls back to that level.
🔵 Trading in the Trend of the Kill Zone
Kill zones are characterized by high trading volumes and strong trends. Therefore, trades can be placed in the direction of the prevailing trend. For instance, if an upward trend dominates this area, a buy trade can be entered when the price reaches a demand order block.
Uptrick: Trend Confirmation IndicatorIf you buy this indicator/strategy the code will be provided so in order to access it you will need to go to Tradingview and at the bottom click 'Pine Editor'. Then click 'Open' and then click on 'New strategy'. Here you can then paste the code and save it. Make sure to first delete all the code that there is before pasting it inside.
Description:
The "Uptrick: Trend Confirmation Indicator" stands as an exceptional tool for traders seeking reliable confirmation of market trends. This indicator integrates multiple technical analysis components to provide clear signals for trend direction, aiding traders in making well-informed trading decisions with confidence.
EMA and MACD Analysis:
The indicator leverages the Exponential Moving Average (EMA) to capture the long-term trend direction of the market. The EMA is calculated over a customizable period, allowing traders to adapt the indicator to various timeframes and market conditions.
Additionally, the Moving Average Convergence Divergence (MACD) is employed to further confirm trend direction. By analyzing the difference between two moving averages and their smoothing, the MACD component helps identify potential shifts in market momentum.
Trend Confirmation Mechanism:
The indicator confirms a trend when the closing price is above the EMA, and the MACD line shows a positive change, indicating upward momentum. This combined signal enhances the reliability of trend confirmation, reducing false signals and noise in the market.
To filter out short-term fluctuations, the indicator requires trend confirmation over multiple bars, ensuring a more robust assessment of market direction.
Background Color and Visualization:
The background color dynamically adjusts based on the direction of the EMA, providing visual cues for trend directionality. A green background signifies an upward trend, while a red background indicates a downward trend.
This visual representation enhances the clarity of trend identification, allowing traders to quickly assess market conditions at a glance.
Signal Generation and Execution:
The indicator generates long signals when the EMA crosses above its previous value, indicating a potential bullish reversal. Conversely, short signals are generated when the EMA crosses below its previous value, signaling a potential bearish reversal.
These signals are executed through automated buy and sell orders, streamlining the trading process and minimizing human error.
Utility and Potential Usage:
The "Uptrick: Trend Confirmation Indicator" is an indispensable tool for traders across various experience levels, offering clear and reliable signals for trend confirmation.
Short-term traders can benefit from its ability to filter out noise and provide accurate trend signals, enhancing their intraday trading strategies.
Long-term investors can leverage its robust trend confirmation mechanism to identify favorable entry and exit points, optimizing their portfolio management and risk mitigation strategies.
In conclusion, the "Uptrick: Trend Confirmation Indicator" stands out as an excellent trading tool, empowering traders with the confidence to navigate the markets effectively and capitalize on profitable opportunities with precision and clarity.
Chande Kroll Trend Strategy (SPX, 1H) | PINEINDICATORSThe "Chande Kroll Stop Strategy" is designed to optimize trading on the SPX using a 1-hour timeframe. This strategy effectively combines the Chande Kroll Stop indicator with a Simple Moving Average (SMA) to create a robust method for identifying long entry and exit points. This detailed description will explain the components, rationale, and usage to ensure compliance with TradingView's guidelines and help traders understand the strategy's utility and application.
Objective
The primary goal of this strategy is to identify potential long trading opportunities in the SPX by leveraging volatility-adjusted stop levels and trend-following principles. It aims to capture upward price movements while managing risk through dynamically calculated stops.
Chande Kroll Stop Parameters:
Calculation Mode: Offers "Linear" and "Exponential" options for position size calculation. The default mode is "Exponential."
Risk Multiplier: An adjustable multiplier for risk management and position sizing, defaulting to 5.
ATR Period: Defines the period for calculating the Average True Range (ATR), with a default of 10.
ATR Multiplier: A multiplier applied to the ATR to set stop levels, defaulting to 3.
Stop Length: Period used to determine the highest high and lowest low for stop calculation, defaulting to 21.
SMA Length: Period for the Simple Moving Average, defaulting to 21.
Calculation Details:
ATR Calculation: ATR is calculated over the specified period to measure market volatility.
Chande Kroll Stop Calculation:
High Stop: The highest high over the stop length minus the ATR multiplied by the ATR multiplier.
Low Stop: The lowest low over the stop length plus the ATR multiplied by the ATR multiplier.
SMA Calculation: The 21-period SMA of the closing price is used as a trend filter.
Entry and Exit Conditions:
Long Entry: A long position is initiated when the closing price crosses over the low stop and is above the 21-period SMA. This condition ensures that the market is trending upward and that the entry is made in the direction of the prevailing trend.
Exit Long: The long position is exited when the closing price falls below the high stop, indicating potential downward movement and protecting against significant drawdowns.
Position Sizing:
The quantity of shares to trade is calculated based on the selected calculation mode (linear or exponential) and the risk multiplier. This ensures position size is adjusted dynamically based on current market conditions and user-defined risk tolerance.
Exponential Mode: Quantity is calculated using the formula: riskMultiplier / lowestClose * 1000 * strategy.equity / strategy.initial_capital.
Linear Mode: Quantity is calculated using the formula: riskMultiplier / lowestClose * 1000.
Execution:
When the long entry condition is met, the strategy triggers a buy signal, and a long position is entered with the calculated quantity. An alert is generated to notify the trader.
When the exit condition is met, the strategy closes the position and triggers a sell signal, accompanied by an alert.
Plotting:
Buy Signals: Indicated with an upward triangle below the bar.
Sell Signals: Indicated with a downward triangle above the bar.
Application
This strategy is particularly effective for trading the SPX on a 1-hour timeframe, capitalizing on price movements by adjusting stop levels dynamically based on market volatility and trend direction.
Default Setup
Initial Capital: $1,000
Risk Multiplier: 5
ATR Period: 10
ATR Multiplier: 3
Stop Length: 21
SMA Length: 21
Commission: 0.01
Slippage: 3 Ticks
Backtesting Results
Backtesting indicates that the "Chande Kroll Stop Strategy" performs optimally on the SPX when applied to the 1-hour timeframe. The strategy's dynamic adjustment of stop levels helps manage risk effectively while capturing significant upward price movements. Backtesting was conducted with a realistic initial capital of $1,000, and commissions and slippage were included to ensure the results are not misleading.
Risk Management
The strategy incorporates risk management through dynamically calculated stop levels based on the ATR and a user-defined risk multiplier. This approach ensures that position sizes are adjusted according to market volatility, helping to mitigate potential losses. Trades are sized to risk a sustainable amount of equity, adhering to the guideline of risking no more than 5-10% per trade.
Usage Notes
Customization: Users can adjust the ATR period, ATR multiplier, stop length, and SMA length to better suit their trading style and risk tolerance.
Alerts: The strategy includes alerts for buy and sell signals to keep traders informed of potential entry and exit points.
Pyramiding: Although possible, the strategy yields the best results without pyramiding.
Justification of Components
The Chande Kroll Stop indicator and the 21-period SMA are combined to provide a robust framework for identifying long trading opportunities in trending markets. Here is why they work well together:
Chande Kroll Stop Indicator: This indicator provides dynamic stop levels that adapt to market volatility, allowing traders to set logical stop-loss levels that account for current price movements. It is particularly useful in volatile markets where fixed stops can be easily hit by random price fluctuations. By using the ATR, the stop levels adjust based on recent market activity, ensuring they remain relevant in varying market conditions.
21-Period SMA: The 21-period SMA acts as a trend filter to ensure trades are taken in the direction of the prevailing market trend. By requiring the closing price to be above the SMA for long entries, the strategy aligns itself with the broader market trend, reducing the risk of entering trades against the overall market direction. This helps to avoid false signals and ensures that the trades are in line with the dominant market movement.
Combining these two components creates a balanced approach that captures trending price movements while protecting against significant drawdowns through adaptive stop levels. The Chande Kroll Stop ensures that the stops are placed at levels that reflect current volatility, while the SMA filter ensures that trades are only taken when the market is trending in the desired direction.
Concepts Underlying Calculations
ATR (Average True Range): Used to measure market volatility, which informs the stop levels.
SMA (Simple Moving Average): Used to filter trades, ensuring positions are taken in the direction of the trend.
Chande Kroll Stop: Combines high and low price levels with ATR to create dynamic stop levels that adapt to market conditions.
Risk Disclaimer
Trading involves substantial risk, and most day traders incur losses. The "Chande Kroll Stop Strategy" is provided for informational and educational purposes only. Past performance is not indicative of future results. Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and risk tolerance.
[InvestorUnknown] Performance MetricsOverview
The Performance Metrics indicator is a tool designed to help traders and investors understand and utilize key performance metrics in their strategies. This indicator is inspired by the Rolling Risk-Adjusted Performance Ratios created by @EliCobra, but it offers enhanced usability and additional features to provide a more user-friendly code for understanding the calculations.
Features
Rolling Lookback:
Dynamic Lookback Calculation: The indicator automatically calculates the number of bars from the start of the asset's price history, up to a maximum of 5000 bars due to TradingView platform restrictions.
Adjustable Lookback Period: Users can manually set a lookback period or choose to use the rolling lookback feature for dynamic calculations.
RollingLookback() =>
x = bar_index + 1
y = x > 4999 ? 5000 : x > 1 ? (x - 1) : x
y
Trend Analysis
The Trend Analysis section in this indicator helps traders identify the direction of the market trend based on the balance of positive and negative returns over time. This is achieved by calculating the sums of positive and negative returns and optionally smoothing these values to provide a clearer trend signal.
Configuration: Enable smoothing if you want to reduce noise in the trend analysis. Choose between EMA and SMA for smoothing. Set the length for smoothing according to your preference for sensitivity (shorter lengths are more sensitive to changes, longer lengths provide smoother signals).
Interpretation:
- A positive trend difference (filled with green) indicates a bullish trend, suggesting more positive returns.
- A negative trend difference (filled with red) indicates a bearish trend, suggesting more negative returns.
- Colored bars provide a quick visual cue on the trend direction, helping to make timely trading decisions.
// The Trend Analysis section calculates and optionally smooths the sums of positive and negative returns.
// This helps identify the trend direction based on the balance of positive and negative returns over time.
Ps = Smooth ? Smooth_type == "EMA" ? ta.ema(pos_sum, Smooth_len) : ta.sma(pos_sum, Smooth_len) : pos_sum
Ns = Smooth ? Smooth_type == "EMA" ? ta.ema(neg_sum, Smooth_len) : ta.sma(neg_sum, Smooth_len) : neg_sum
// Calculate the difference between smoothed positive and negative sums
dif = Ps + Ns
Performance Metrics Table
Visual Table Display: Option to display a table on the chart with calculated performance metrics. This table includes comprehensive metrics like Mean Return, Positive and Negative Mean Return, Standard Deviation, Sharpe Ratio, Sortino Ratio, and Omega Ratio.
Performance Metrics Calculated
Mean Return:
Description: The average return over the lookback period.
Purpose: Helps in understanding the overall performance of the asset by providing a simple average of returns.
Positive Mean Return:
Description: The average of all positive returns over the lookback period.
Purpose: Highlights the average gain during profitable periods, giving insight into the asset's potential upside.
Negative Mean Return:
Description: The average of all negative returns over the lookback period.
Purpose: Focuses on the average loss during unprofitable periods, helping to assess the downside risk.
Standard Deviation (STDEV):
Description: A measure of volatility that calculates the dispersion of returns from the mean.
Purpose: Indicates the risk associated with the asset. Higher standard deviation means higher volatility and risk.
Sharpe Ratio:
Description: A risk-adjusted return metric that divides the mean return by the standard deviation of returns. It can be annualized if selected.
Purpose: Provides a standardized way to compare the performance of different assets by considering both return and risk. A higher Sharpe Ratio indicates better risk-adjusted performance.
sharpe_ratio = mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1)
Sortino Ratio:
Description: Similar to the Sharpe Ratio but focuses only on downside volatility. It divides the mean return by the standard deviation of negative returns. It can be annualized if selected.
Purpose: Offers a better assessment of downside risk by ignoring upside volatility. A higher Sortino Ratio indicates a higher return per unit of downside risk.
sortino_ratio = mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1)
Omega Ratio:
Description: The ratio of the probability-weighted average of positive returns to the probability-weighted average of negative returns.
Purpose: Measures the overall likelihood of positive returns compared to negative returns. An Omega Ratio greater than 1 indicates more frequent and/or larger positive returns compared to negative returns.
omega_ratio = (prob_pos * mean_pos) / (prob_neg * -mean_neg)
By calculating and displaying these metrics, the indicator provides a comprehensive view of the asset's performance, enabling traders and investors to make informed decisions based on both returns and risk-adjusted metrics.
Use Cases:
Performance Evaluation: Assesses an asset's performance by analyzing both returns and risk factors, giving a clear picture of profitability and volatility.
Risk Comparison: Compares the risk-adjusted returns of different assets or portfolios, aiding in identifying investments with superior risk-reward trade-offs.
Risk Management: Helps manage risk exposure by evaluating downside risks and overall volatility, enabling more informed and strategic investment decisions.
Vwap Z-Score with Signals [UAlgo]The "VWAP Z-Score with Signals " is a technical analysis tool designed to help traders identify potential buy and sell signals based on the Volume Weighted Average Price (VWAP) and its Z-Score. This indicator calculates the VWAP Z-Score to show how far the current price deviates from the VWAP in terms of standard deviations. It highlights overbought and oversold conditions with visual signals, aiding in the identification of potential market reversals. The tool is customizable, allowing users to adjust parameters for their specific trading needs.
🔶 Features
VWAP Z-Score Calculation: Measures the deviation of the current price from the VWAP using standard deviations.
Customizable Parameters: Allows users to set the length of the VWAP Z-Score calculation and define thresholds for overbought and oversold levels.
Reversal Signals: Provides visual signals when the Z-Score crosses the specified thresholds, indicating potential buy or sell opportunities.
🔶 Usage
Extreme Z-Score values (both positive and negative) highlight significant deviations from the VWAP, useful for identifying potential reversal points.
The indicator provides visual signals when the Z-Score crosses predefined thresholds:
A buy signal (🔼) appears when the Z-Score crosses above the lower threshold, suggesting the price may be oversold and a potential upward reversal.
A sell signal (🔽) appears when the Z-Score crosses below the upper threshold, suggesting the price may be overbought and a potential downward reversal.
These signals can help you identify potential entry and exit points in your trading strategy.
🔶 Disclaimer
The "VWAP Z-Score with Signals " indicator is designed for educational purposes and to assist traders in their technical analysis. It does not guarantee profitable trades and should not be considered as financial advice.
Users should conduct their own research and use this indicator in conjunction with other tools and strategies.
Trading involves significant risk, and it is possible to lose more than your initial investment.
Entry Fragger - Strategy
For basic instructions please visit my other script "Entry Fragger".
The Signal Logic is explained there.
v1.4:
- Added advanced backtesting with fully customizable entries.
- Fully automated Buy Signals (profitable).
- Adjustable timeframes for signal logic. (requested)
Every setting affects the accuracy and profitability greatly now, based on settings applied.
The strategy performs best on high timeframes with larger capital and no leverage.
Useless for Forex, but absolutely smashes stocks and crypto on mid to high timeframes.
Please read through my other scripts description.
Set values as preferred and try your assets.
It does NOT work on low timeframes and forex!
Hint: BTC 4H, Custom Timeframe 1h, Moon Mode and Show Sell Signals enabled, R2R: 2.
Trailing Take Profit - Close Based📝 Description
This script demonstrates a new approach to the trailing take profit.
Trailing Take Profit is a price-following technique. When used, instead of setting a limit order for the take profit target exiting from your position at the specified price, a stop order is conditionally set when the take profit target is reached. Then, the stop price (a.k.a trailing price), is placed below the take profit target at a distance defined by the user percentagewise. On regular time intervals, the stop price gets updated by following the "Trail Barrier" price (high by default) upwards. When the current price hits the stop price you exit the trade. Check the chart for more details.
This script demonstrates how to implement the close-based Trailing Take Profit logic for long positions, but it can also be applied for short positions if the logic is "reversed".
📢 NOTE
To generate some entries and showcase the "Trailing Take Profit" technique, this script uses the crossing of two moving averages. Please keep in mind that you should not relate the Backtesting results you see in the "Strategy Tester" tab with the success of the technique itself.
This is not a complete strategy per se, and the backtest results are affected by many parameters that are outside of the scope of this publication. If you choose to use this new approach of the "Trailing Take Profit" in your logic you have to make sure that you are backtesting the whole strategy.
⚔️ Comparison
In contrast to my older "Trailing Take Profit" publication where the trailing take profit implementation was tick-based, this new approach is close-based, meaning that the update of the stop price occurs at the bar close instead of every tick.
While comparing the real-time results of the two implementations is like comparing apples to oranges, because they have different dynamic behavior, the new approach offers better consistency between the backtesting results and the real-time results.
By updating the stop price on every bar close, you do not rely on the backtester assumptions anymore (check the Reasoning section below for more info).
The new approach resembles the conditional "Trailing Exit" technique, where the condition is true when the current price crosses over the take profit target. Then, the stop order is placed at the trailing price and it gets updated on every bar close to "follow" the barrier price (high). On the other hand, the older tick-based approach had more "tight" dynamics since the trailing price gets updated on every tick leaving less room for price fluctuations by making it more probable to reach the trailing price.
🤔 Reasoning
This new close-based approach addresses several practical issues the older tick-based approach had. Those issues arise mainly from the technicalities of the TV Backtester. More specifically, due to the assumptions the Broker Emulator makes for the price action of the history bars, the backtesting results in the TV Backtester are exaggerated, and depending on the timeframe, the backtesting results look way better than they are in reality.
The effect above, and the inability to reason about the performance of a strategy separated people into two groups. Those who never use this feature, because they couldn't know for sure the actual effect it might have in their strategy, (even if it turned out to be more profitable) and those who abused this type of "repainting" behavior to show off, and hijack some boosts from the community by boasting about the "fake" results of their strategies.
Even if there are ways to evaluate the effectiveness of the tick-based approach that is applied in an existing strategy (this is out of the topic of this publication), it requires extra effort to do the analysis. Using this closed-based approach we can have more predictable results, without surprises.
⚠️ Caveats
Since this approach updates the trailing price on bar close, you must wait for at least one bar to close after the price crosses over the take profit target.
Moving Average Crossover Strategy by AI and Anton ThomasDescription:
Indicator Name: Moving Average Crossover Strategy
Overview:
The "Moving Average Crossover Strategy" is a technical analysis indicator that combines moving averages and the Relative Strength Index (RSI) to identify potential buy and sell signals. It aims to capture trend reversals and momentum shifts in the market.
Key Components:
Moving Averages:
The indicator calculates two moving averages:
Fast Moving Average (10-period SMA): This average reacts more quickly to price changes.
Slow Moving Average (30-period SMA): This average provides a smoother trend indication.
A bullish signal occurs when the fast moving average crosses above the slow moving average (golden cross), indicating a potential uptrend.
A bearish signal occurs when the fast moving average crosses below the slow moving average (death cross), indicating a potential downtrend.
Relative Strength Index (RSI):
The RSI measures the strength and momentum of price movements on a scale of 0 to 100.
A reading above 70 indicates overbought conditions, suggesting a potential reversal to the downside.
A reading below 30 indicates oversold conditions, suggesting a potential reversal to the upside.
Trading Signals:
Buy Signal:
Generated when the fast moving average crosses above the slow moving average (longCondition).
Additionally, a buy signal is identified when the RSI is oversold (below 30) and then crosses above the oversold threshold.
The indicator plots a green triangle above the bar to indicate the buy signal.
Sell Signal:
Generated when the fast moving average crosses below the slow moving average (shortCondition).
Additionally, a sell signal is identified when the RSI is overbought (above 70) and then crosses below the overbought threshold.
The indicator plots a red triangle below the bar to indicate the sell signal.
Additional Features:
Bullish Engulfing Pattern:
Detects bullish engulfing candlestick patterns, indicating potential bullish reversals.
Plots a green triangle below the bar to highlight the bullish engulfing pattern.
Bearish Engulfing Pattern:
Detects bearish engulfing candlestick patterns, indicating potential bearish reversals.
Plots a red triangle above the bar to highlight the bearish engulfing pattern.
Oversold and Overbought Levels:
Plots horizontal dashed lines at 30 (oversold) and 70 (overbought) on the RSI indicator.
Usage:
Traders can use this indicator to identify potential entry and exit points in the market based on moving average crossovers, RSI conditions, and candlestick patterns. It provides a comprehensive view of trend direction and momentum.
Considerations:
Always confirm signals with other technical analysis tools and market conditions.
Implement proper risk management strategies to minimize potential losses.
Example:
A buy signal is generated when the fast moving average crosses above the slow moving average, and the RSI is below 30 but crosses above it.
A sell signal is generated when the fast moving average crosses below the slow moving average, and the RSI is above 70 but crosses below it.
If you find this indicator profitable, please support by gifting some USDT (BSC NETWORK): 0x2c5c2dd39bbcc9453dd1428d881da37dacd9bf47
or just a thank you email at antonthomasfull(at)gmail.com
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
SVMKR_VIX_Based_LevelsThe "SVMKR_VIX_Based_Levels" script is a Pine Script indicator designed to assist intraday traders in identifying dynamic support and resistance levels based on the Volatility Index (VIX). Here's a breakdown of the script and its uses for intraday traders:
### Script Description:
1. **Data Retrieval**:
- The script fetches daily closing prices of the India VIX (volatility index) and a specified security using `request.security()`.
2. **Input Parameters**:
- Intraday traders can customize the indicator using input parameters such as the number of levels above and below the Pivot Day Close (PDC), line offset lengths, line extension options, and color and width settings for plotted lines.
3. **Plotting**:
- The script plots the PDC and VIX as hidden lines (`display=display.none`).
- Support and resistance levels are calculated based on the VIX and PDC, and plotted above and below the PDC with customizable colors and widths.
- Each level can be labeled with its corresponding price.
4. **Customization**:
- Intraday traders can choose to display or hide prices on the plotted lines.
- Colors and widths of plotted lines are customizable.
- Options to show minor and mild support levels provide additional flexibility.
5. **Labels**:
- Labels are added to indicate the PDC and the plotted levels, displaying corresponding prices if enabled.
### Uses for Intraday Traders:
1. **Dynamic Support and Resistance**: Intraday traders can benefit from dynamically adjusted support and resistance levels that respond to changes in market volatility, providing more accurate levels for trade planning.
2. **Market Sentiment Analysis**: By incorporating the VIX, a measure of market volatility and sentiment, the indicator provides insights into market sentiment, helping intraday traders gauge market mood and potential direction.
3. **Confirmation of Price Action**: The plotted support and resistance levels can serve as confirmation signals for intraday traders, helping validate trading decisions and enhance trading confidence.
4. **Adaptability to Changing Market Conditions**: Intraday traders often face rapidly changing market conditions. The indicator's ability to adapt to changes in volatility ensures that plotted levels remain relevant and responsive, aiding traders in adjusting their strategies accordingly.
5. **Trade Planning and Execution**: Intraday traders can use the plotted support and resistance levels to identify potential entry and exit points, set profit targets and stop-loss levels, and plan their trades more effectively.
Overall, the "SVMKR_VIX_Based_Levels" indicator provides intraday traders with a valuable tool for dynamic support and resistance identification, market sentiment analysis, confirmation of price action, and trade planning and execution, ultimately assisting them in making more informed and profitable trading decisions in the intraday timeframe.
Channels With NVI Strategy [TradeDots]The "Channels With NVI Strategy" is a trading strategy that identifies oversold market instances during a bullish trading market. Specifically, the strategy integrates two principal indicators to deliver profitable opportunities, anticipating potential uptrends.
2 MAIN COMPONENTS
1. Channel Indicators: This strategy gives users the flexibility to choose between Bollinger Band Channels or Keltner Channels. This selection can be made straight from the settings, allowing the traders to adjust the tool according to their preferences and strategies.
2. Negative Volume Indicator (NVI): An indicator that calculates today's price rate of change, but only when today's trading volume is less than the previous day's. This functionality enables users to detect potential shifts in the trading volume with time and price.
ENTRY CONDITION
First, the assets price must drop below the lower band of the channel indicator.
Second, NVI must ascend above the exponential moving average line, signifying a possible flood of 'smart money' (large institutional investors or savvy traders), indicating an imminent price rally.
EXIT CONDITION
Exit conditions can be customized based on individual trading styles and risk tolerance levels. Traders can define their ideal take profit or stop loss percentages.
Moreover, the strategy also employs an NVI-based exit policy. Specifically, if the NVI dips under the exponential moving average – suggestive of a fading trading momentum, the strategy grants an exit call.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
