Price Action Analyst [OmegaTools]Price Action Analyst (PAA) is an advanced trading tool designed to assist traders in identifying key price action structures such as order blocks, market structure shifts, liquidity grabs, and imbalances. With its fully customizable settings, the script offers both novice and experienced traders insights into potential market movements by visually highlighting premium/discount zones, breakout signals, and significant price levels.
This script utilizes complex logic to determine significant price action patterns and provides dynamic tools to spot strong market trends, liquidity pools, and imbalances across different timeframes. It also integrates an internal backtesting function to evaluate win rates based on price interactions with supply and demand zones.
The script combines multiple analysis techniques, including market structure shifts, order block detection, fair value gaps (FVG), and ICT bias detection, to provide a comprehensive and holistic market view.
Key Features:
Order Block Detection: Automatically detects order blocks based on price action and strength analysis, highlighting potential support/resistance zones.
Market Structure Analysis: Tracks internal and external market structure changes with gradient color-coded visuals.
Liquidity Grabs & Breakouts: Detects potential liquidity grab and breakout areas with volume confirmation.
Fair Value Gaps (FVG): Identifies bullish and bearish FVGs based on historical price action and threshold calculations.
ICT Bias: Integrates ICT bias analysis, dynamically adjusting based on higher-timeframe analysis.
Supply and Demand Zones: Highlights supply and demand zones using customizable colors and thresholds, adjusting dynamically based on market conditions.
Trend Lines: Automatically draws trend lines based on significant price pivots, extending them dynamically over time.
Backtesting: Internal backtesting engine to calculate the win rate of signals generated within supply and demand zones.
Percentile-Based Pricing: Plots key percentile price levels to visualize premium, fair, and discount pricing zones.
High Customizability: Offers extensive user input options for adjusting zone detection, color schemes, and structure analysis.
User Guide:
Order Blocks: Order blocks are significant support or resistance zones where strong buyers or sellers previously entered the market. These zones are detected based on pivot points and engulfing price action. The strength of each block is determined by momentum, volume, and liquidity confirmations.
Demand Zones: Displayed in shades of blue based on their strength. The darker the color, the stronger the zone.
Supply Zones: Displayed in shades of red based on their strength. These zones highlight potential resistance areas.
The zones will dynamically extend as long as they remain valid. Users can set a maximum number of order blocks to be displayed.
Market Structure: Market structure is classified into internal and external shifts. A bullish or bearish market structure break (MSB) occurs when the price moves past a previous high or low. This script tracks these breaks and plots them using a gradient color scheme:
Internal Structure: Short-term market structure, highlighting smaller movements.
External Structure: Long-term market shifts, typically more significant.
Users can choose how they want the structure to be visualized through the "Market Structure" setting, choosing from different visual methods.
Liquidity Grabs: The script identifies liquidity grabs (false breakouts designed to trap traders) by monitoring price action around highs and lows of previous bars. These are represented by diamond shapes:
Liquidity Buy: Displayed below bars when a liquidity grab occurs near a low.
Liquidity Sell: Displayed above bars when a liquidity grab occurs near a high.
Breakouts: Breakouts are detected based on strong price momentum beyond key levels:
Breakout Buy: Triggered when the price closes above the highest point of the past 20 bars with confirmation from volume and range expansion.
Breakout Sell: Triggered when the price closes below the lowest point of the past 20 bars, again with volume and range confirmation.
Fair Value Gaps (FVG): Fair value gaps (FVGs) are periods where the price moves too quickly, leaving an unbalanced market condition. The script identifies these gaps:
Bullish FVG: When there is a gap between the low of two previous bars and the high of a recent bar.
Bearish FVG: When a gap occurs between the high of two previous bars and the low of the recent bar.
FVGs are color-coded and can be filtered by their size to focus on more significant gaps.
ICT Bias: The script integrates the ICT methodology by offering an auto-calculated higher-timeframe bias:
Long Bias: Suggests the market is in an uptrend based on higher timeframe analysis.
Short Bias: Indicates a downtrend.
Neutral Bias: Suggests no clear directional bias.
Trend Lines: Automatic trend lines are drawn based on significant pivot highs and lows. These lines will dynamically adjust based on price movement. Users can control the number of trend lines displayed and extend them over time to track developing trends.
Percentile Pricing: The script also plots the 25th percentile (discount zone), 75th percentile (premium zone), and a fair value price. This helps identify whether the current price is overbought (premium) or oversold (discount).
Customization:
Zone Strength Filter: Users can set a minimum strength threshold for order blocks to be displayed.
Color Customization: Users can choose colors for demand and supply zones, market structure, breakouts, and FVGs.
Dynamic Zone Management: The script allows zones to be deleted after a certain number of bars or dynamically adjusts zones based on recent price action.
Max Zone Count: Limits the number of supply and demand zones shown on the chart to maintain clarity.
Backtesting & Win Rate: The script includes a backtesting engine to calculate the percentage of respect on the interaction between price and demand/supply zones. Results are displayed in a table at the bottom of the chart, showing the percentage rating for both long and short zones. Please note that this is not a win rate of a simulated strategy, it simply is a measure to understand if the current assets tends to respect more supply or demand zones.
How to Use:
Load the script onto your chart. The default settings are optimized for identifying key price action zones and structure on intraday charts of liquid assets.
Customize the settings according to your strategy. For example, adjust the "Max Orderblocks" and "Strength Filter" to focus on more significant price action areas.
Monitor the liquidity grabs, breakouts, and FVGs for potential trade opportunities.
Use the bias and market structure analysis to align your trades with the prevailing market trend.
Refer to the backtesting win rates to evaluate the effectiveness of the zones in your trading.
Terms & Conditions:
By using this script, you agree to the following terms:
Educational Purposes Only: This script is provided for informational and educational purposes and does not constitute financial advice. Use at your own risk.
No Warranty: The script is provided "as-is" without any guarantees or warranties regarding its accuracy or completeness. The creator is not responsible for any losses incurred from the use of this tool.
Open-Source License: This script is open-source and may be modified or redistributed in accordance with the TradingView open-source license. Proper credit to the original creator, OmegaTools, must be maintained in any derivative works.
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Statistics plot1. setting the price range
At the beginning of the script, set the price range (interval). Price ranges are used to divide prices into several groups (buckets) and record how many prices have been reached within each group. For example, setting the price range to “10” will divide the price into intervals 0-10, 10-20, 20-30, and so on.
The price range can also be set manually by the user or automatically calculated based on the initial price. This allows for flexibility in adjusting price ranges for different assets and different time frames.
2. aggregate the number of times a price is reached
Record how many times the price reached each price range (e.g., 100-110, 110-120, etc.). This aggregate data is stored in a data structure called an array.
Each element of the array corresponds to a price range, and when a price reaches that range, the corresponding array value is incremented by one. This process is performed in real time, tracking price movements.
3. initializing and extending price ranges
The first bar of the script (when the chart is first loaded) divides the price ranges into several groups and initializes a count of 0 for each range.
When a price reaches a new range, the array is expanded as needed to add the new price range. This allows the script to work with any price movement, even if the price range continues to grow.
4. visualize the number of price arrivals with a histogram
The aggregated number of arrivals per price range is visually displayed in the form of a histogram. This histogram is designed to allow the user to see at a glance which price range is being reached most frequently.
For example, if prices frequently reach the 100-110 range, the histogram bar corresponding to that range will appear higher than the other ranges. This allows you to visually identify price “dwell points” or support and resistance levels.
5. display of moving averages
A moving average (MA) of the number of times a price has been reached is drawn above the histogram. Moving averages are indicators that show a smooth trend for the number of price arrivals and are useful for understanding the overall direction of price movements.
The duration of the moving average (how many data points it is calculated based on) can be set by the user. This allows for flexible analysis of short or long term price trends. 6.
6. price range tracking and labeling
The script keeps track of which price range the current price is located in. Based on this, information related to the current price range is displayed on the chart as labels.
In particular, labels indicate the beginning and end points of the price range, including which range the price was in at the beginning and which range the price reached at the end. These labels are a useful feature to visually identify price ranges on the chart.
7. labeling of current price range
To confirm which price range the current price is in, when a price reaches a specific price range, a label corresponding to that price range is displayed. This label indicates the position of the price in real-time, allowing traders to visually track where the current price is in the area.
8. calculating the start and end points of the range
The script calculates the start and end points of a range with a non-zero number of price arrivals to find the minimum and maximum of the range. This calculation allows you to see where prices are concentrated within a range.
9. out-of-range price processing
When a price reaches outside the range, the script automatically adds the array element corresponding to that price range and inserts the data in the appropriate location for the count. This allows the script to follow the price as it moves unexpectedly.
VATICAN BANK CARTELVATICAN BANK CARTEL - Precision Signal Detection for Buyers.
The VATICAN BANK CARTEL indicator is a highly sophisticated tool designed specifically for buyers, helping them identify key market trends and generate actionable buy signals. Utilizing advanced algorithms, this indicator employs a multi-variable detection mechanism that dynamically adapts to price movements, offering real-time insights to assist in executing profitable buy trades. This indicator is optimized solely for identifying buying opportunities, ensuring that traders are equipped to make well-timed entries and exits, without signals for shorting or selling.
The recommended settings for VATICAN BANK CARTEL indicator is as follows:-
Depth Engine = 20,30,40,50,100.
Deviation Engine = 3,5,7,15,20.
Backstep Engine = 15,17,20,25.
NOTE:- But you can also use this indicator as per your setting, whichever setting gives you best results use that setting.
Key Features:
1.Adaptive Depth, Deviation, and Backstep Inputs:
The core of this indicator is its customizable Depth Engine, Deviation Engine, and Backstep Engine parameters. These inputs allow traders to adjust the sensitivity of the trend detection algorithm based on specific market conditions:
Depth: Defines how deep the indicator scans historical price data for potential trend reversals.
Deviation: Determines the minimum required price fluctuation to confirm a market movement.
Backstep: Sets the retracement level to filter false signals and maintain the accuracy of trend detection.
2. Visual Signal Representation:
The VATICAN BANK CARTEL plots highly visible labels on the chart to mark trend reversals. These labels are customizable in terms of size and transparency, ensuring clarity in various chart environments. Traders can quickly spot buying opportunities with green labels and potential square-off points with red labels, focusing exclusively on buy-side signals.
3.Real-Time Alerts:
The indicator is equipped with real-time alert conditions to notify traders of significant buy or square-off buy signals. These alerts, which are triggered based on the indicator’s internal signal logic, ensure that traders never miss a critical market movement on the buy side.
4.Custom Label Size and Transparency:
To enhance visual flexibility, the indicator allows the user to adjust label size (from small to large) and transparency levels. This feature provides a clean, adaptable view suited for different charting styles and timeframes.
How It Works:
The VATICAN BANK CARTEL analyzes the price action using a sophisticated algorithm that considers historical low and high points, dynamically detecting directional changes. When a change in market direction is detected, the indicator plots a label at the key reversal points, helping traders confirm potential entry points:
- Buy Signal (Green): Indicates potential buying opportunities based on a trend reversal.
- Square-Off Buy Signal (Red): Marks the exit point for open buy positions, allowing traders to take profits or protect capital from potential market reversals.
Note: This indicator is exclusively designed to provide signals for buyers. It does not generate sell or short signals, making it ideal for traders focused solely on identifying optimal buying opportunities in the market.
Customizable Parameters:
- Depth Engine: Fine-tunes the historical data analysis for signal generation.
- Deviation Engine: Adjusts the minimum price change required for detecting trends.
- Backstep Engine: Controls the indicator's sensitivity to retracements, minimizing false signals.
- Labels Transparency: Adjusts the opacity of the labels, ensuring they integrate seamlessly into any chart layout.
- Buy and Sell Colors: Customizable color options for buy and square-off buy labels to match your preferred color scheme.
- Label Size: Select between five different label sizes for optimal chart visibility.
Ideal For:
This indicator is ideal for both beginner and experienced traders looking to enhance their buying strategy with a highly reliable, visual, and alert-driven tool. The VATICAN BANK CARTEL adapts to various timeframes, making it suitable for day traders, swing traders, and long-term investors alike—focused exclusively on buying opportunities.
Benefits and Applications:
1.Intraday Trading: The VATICAN BANK CARTEL indicator is particularly well-suited for intraday trading, as it provides accurate and timely "buy" and "square-off buy" signals based on the current market dynamics.
2.Trend-following Strategies: Traders who employ trend-following strategies can leverage the indicator's ability to identify the overall market direction, allowing them to align their trades with the dominant trend.
3.Swing Trading: The dynamic price tracking and signal generation capabilities of the indicator can be beneficial for swing traders, who aim to capture medium-term price movements.
Security Measures:
1. The code includes a security notice at the beginning, indicating that it is subject to the Mozilla Public License 2.0, which is a reputable open-source license.
2. The code does not appear to contain any obvious security vulnerabilities or malicious content that could compromise user data or accounts.
NOTE:- This indicator is provided under the Mozilla Public License 2.0 and is subject to its terms and conditions.
Disclaimer: The usage of VATICAN BANK CARTEL indicator might or might not contribute to your trading capital(money) profits and losses and the author is not responsible for the same.
IMPORTANT NOTICE:
While the indicator aims to provide reliable "buy" and "square-off buy" signals, it is crucial to understand that the market can be influenced by unpredictable events, such as natural disasters, political unrest, changes in monetary policies, or economic crises. These unforeseen situations may occasionally lead to false signals generated by the VATICAN BANK CARTEL indicator.
Users should exercise caution and diligence when relying on the indicator's signals, as the market's behavior can be unpredictable, and external factors may impact the accuracy of the signals. It is recommended to thoroughly backtest the indicator's performance in various market conditions and to use it as one of the many tools in a comprehensive trading strategy, rather than solely relying on its output.
Ultimately, the success of the VATICAN BANK CARTEL indicator will depend on the user's ability to adapt it to their specific trading style, market conditions, and risk management approach. Continuous monitoring, analysis, and adjustment of the indicator's settings may be necessary to maintain its effectiveness in the ever-evolving financial markets.
DEVELOPER:- yashgode9
PineScript:- version:- 5
This indicator aims to enhance trading decision-making by combining DEPTH, DEVIATION, BACKSTEP with custom signal generation, offering a comprehensive tool for traders seeking clear "buy" and "square-off buy" signals on the TradingView platform.
Options Series - NonOverlay_Technical
⭐ 1. Purpose:
The script is designed to show technical indicators in a non-overlay form using candlestick representations. It combines multiple popular technical analysis tools to gauge the market's bullish or bearish conditions.
⭐ 2. Indicators:
The script uses several indicators across different timeframes: Exponential Moving Averages (EMA) for 5, 20, 50 periods. Simple Moving Average (SMA) for 200 periods. RSI (Relative Strength Index) for momentum. VWAP (Volume Weighted Average Price) for average price evaluation. PSAR (Parabolic SAR) for trend direction. Daily and multi-day (2-day and 3-day) data for broader market context.
⭐ 3. Candlestick Representation:
The script uses color-coded candlesticks to visually represent various indicators and their bullish/bearish states: Green candlesticks for bullish conditions. Red candlesticks for bearish conditions. Neutral/transparent for non-significant conditions.
⭐ 4. Important Conditions:
It calculates bullish and bearish conditions for each indicator: MA20: When the price is above or below the 20-period EMA. RSI: When RSI is above or below 50. VWAP: When the price is above or below the VWAP. PSAR: When the price is above or below the PSAR. 2-day and 3-day Moving Averages: Evaluating the broader trend.
⭐ 5. Bullish vs. Bearish Calculation:
The script sums up bullish and bearish signals to determine the overall market condition: Current_logical_bull: Counts the number of bullish indicators. Current_logical_bear: Counts the number of bearish indicators. The script compares these values to conclude whether the market is more bullish or bearish.
⭐ 6. Visual Plotting:
The script uses plotcandle to display the non-overlay signals at different levels for each condition, stacked vertically from MA20 to PSAR. Additionally, a master candle combines all indicators to show an overall market trend.
⭐ 7. Neon Effect on MA20:
It adds a neon-like effect to the MA20 line, making it visually prominent: A standard plot line with the base color. Two additional neon layers with increasing transparency to enhance the effect.
⭐ 8. Daily Timeframes and Lookahead:
The script fetches daily data using the lookahead feature to get a broader view of the market trend. It tracks the previous day’s and two days' data for comparison.
⭐ 9. Labels and Customization:
The script dynamically adds labels to the chart for the different plotted indicators at the last bar, making it easier to identify which indicator is being represented.
🚀 Conclusion:
The script combines multiple technical indicators, such as EMA, RSI, VWAP, PSAR, and multi-day moving averages, to visually assess bullish and bearish market conditions. It uses color-coded candlesticks to represent each indicator and sums up the signals to determine the overall trend.
Daksh RSI POINT to ShootHere are the key points and features of the Pine Script provided:
### 1. **Indicator Settings**:
- The indicator is named **"POINT and Shoot"** and is set for non-overlay (`overlay=false`) on the chart.
- `max_bars_back=4000` is defined, indicating the maximum number of bars that the script can reference.
### 2. **Input Parameters**:
- `Src` (Source): The price source, default is `close`.
- `rsilen` (RSI Length): The length for calculating RSI, default is 20.
- `linestylei`: Style for the trend lines (`Solid` or `Dashed`).
- `linewidth`: Width of the plotted lines, between 1 and 4.
- `showbroken`: Option to show broken trend lines.
- `extendlines`: Option to extend trend lines.
- `showpivot`: Show pivot points (highs and lows).
- `showema`: Show a weighted moving average (WMA) line.
- `len`: Length for calculating WMA, default is 9.
### 3. **RSI Calculation**:
- Calculates a custom RSI value using relative moving averages (`ta.rma`), and optionally uses On-Balance Volume (`ta.obv`) if `indi` is set differently.
- Plots RSI values as a green or red line depending on its position relative to the WMA.
### 4. **Pivot Points**:
- Utilizes the `ta.pivothigh` and `ta.pivotlow` functions to detect pivot highs and lows over the defined period.
- Stores up to 10 recent pivot points for highs and lows.
### 5. **Trend Line Drawing**:
- Lines are drawn based on pivot highs and lows.
- Calculates potential trend lines using linear interpolation and validates them by checking if subsequent bars break or respect the trend.
- If the trend is broken, and `showbroken` is enabled, it draws dotted lines to represent these broken trends.
### 6. **Line Management**:
- Initializes multiple lines (`l1` to `l20` and `t1` to `t20`) and uses these lines for drawing uptrend and downtrend lines.
- The maximum number of lines is set to 20 for uptrends and 20 for downtrends, due to a limit on the total number of lines that can be displayed on the chart.
### 7. **Line Style and Color**:
- Defines different colors for uptrend lines (`ulcolor = color.red`) and downtrend lines (`dlcolor = color.blue`).
- Line styles are determined by user input (`linestyle`) and use either solid or dashed patterns.
- Broken lines use a dotted style to indicate invalidated trends.
### 8. **Pivot Point Plotting**:
- Plots labels "H" and "L" for pivot highs and lows, respectively, to visually indicate turning points on the chart.
### 9. **Utility Functions**:
- Uses helper functions to get the values and positions of the last 10 pivot points, such as `getloval`, `getlopos`, `gethival`, and `gethipos`.
- The script uses custom logic for line placement based on whether the pivots are lower lows or higher highs, with lines adjusted dynamically based on price movement.
### 10. **Plotting and Visuals**:
- The main RSI line is plotted using a color gradient based on its position relative to the WMA.
- Horizontal lines (`hline1` and `hline2`) are used for visual reference at RSI levels of 60 and 40.
- Filled regions between these horizontal lines provide visual cues for potential overbought or oversold zones.
These are the main highlights of the script, which focuses on trend detection, visualization of pivot points, and dynamic line plotting based on price action.
Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
Bullish Gap Up DetectionThis indicator is designed to identify gap-up trading opportunities in real-time. A gap-up occurs when the opening price of a stock is higher than the previous day's high, signaling potential bullish momentum.
Key Features :
Gap Detection : The indicator detects when today’s open is above yesterday’s high and remains above that level throughout the trading session.
Visual Alerts : A triangle shape appears below the price bar when a gap-up condition is met, providing clear visual signals for traders to consider potential entry points.
EMA Analysis : The indicator incorporates two Exponential Moving Averages:
10-day EMA: Used to assess short-term price trends and help determine if the stock is currently in an upward momentum phase.
20-day EMA: Provides additional context for medium-term trends, ensuring that gaps are only considered when the stock is in a favorable trend.
The indicator confirms that the 10-day EMA is above the 20-day EMA, indicating bullish sentiment in the market.
This indicator can be used in various trading strategies to capitalize on momentum following gap-up openings. It’s suitable for day traders and swing traders looking for entry points in trending stocks.
Trend CCITrend CCI (TCCI) Indicator
Description:
The Trend CCI (TCCI) indicator is a unique combination of the Commodity Channel Index (CCI) and the Average True Range (ATR), designed to identify trends and market reversals with a refined sensitivity to price volatility. The indicator plots the CCI, adjusted by an ATR filter, and color-codes the trendline to signal uptrends and downtrends.
How It Works:
This indicator uses the CCI to measure price momentum and an ATR-based filter to smooth out market noise, making it easier to detect significant shifts in the market trend. Key parameters such as the ATR Period, ATR Multiplier, and CCI Period have been carefully chosen to optimize the indicator's performance:
1. ATR Period (default: 18)
The ATR Period determines the number of periods used to calculate the **Average True Range**, which reflects market volatility. In this case, an **ATR Period of 18** has been selected for several reasons:
Balance between responsiveness and noise reduction : A period of 18 strikes a balance between being responsive to recent price movements and filtering out minor fluctuations. Shorter ATR periods might be too reactive, creating false signals, while longer periods might miss shorter-term trends.
Adaptable to various market conditions : An 18-period ATR is suitable for both intraday and swing trading strategies, making it versatile across different time frames.
Standard industry practice : Many traders use ATR settings between 14 and 20 periods as a convention for detecting reliable volatility levels.
2. ATR Multiplier (default: 1.5)
The ATR Multiplier is applied to the ATR value to define how sensitive the indicator is to volatility. In this case, a multiplier of 1.5 has been chosen:
Avoiding whipsaws in low volatility markets: By setting the multiplier to 1.5, the indicator filters out smaller, less significant price movements, reducing the likelihood of whipsaw signals (i.e., false trend reversals during periods of low volatility).
Optimizing signal accuracy: A moderate multiplier like 1.5 ensures that the indicator only generates signals when the price moves a significant distance from the average range. Higher multipliers (e.g., 2.0) may ignore valid opportunities, while lower multipliers (e.g., 1.0) might create too many signals.
Enhancing trend clarity : The multiplier’s role in widening the range allows the indicator to respond more clearly during periods of strong trends, reducing signal noise and false positives.
3. CCI Period (default: 63)
The CCI Period defines the number of periods used to calculate the Commodity Channel Index. A 63-period CCI is selected based on the following considerations:
Smoothing the momentum calculation: A longer period, such as 63, is used to smooth out the CCI and reduce the effects of short-term price fluctuations. This period captures longer-term momentum, making it ideal for identifying more significant market trends.
-Filtering out short-term noise: While shorter CCI periods (e.g., 14 or 20) may be more reactive, they tend to produce more signals, some of which may be false. A 63-period CCI focuses on stronger and more sustained price movements, providing fewer but higher-quality signals.
Adapted to intermediate trading: A 63-period CCI aligns well with traders looking for medium-term trend-following strategies, striking a balance between long-term trend identification and responsiveness to significant price shifts.
How to Use:
Green Area: When the trendline turns green, it signals that the CCI is positive, reflecting upward momentum. This can be interpreted as a buy signal, indicating the potential for long positions or continuing bullish trades.
Red Area: When the trendline turns red, it signals that the CCI is negative, reflecting downward momentum. This can be interpreted as a sell signal, indicating potential short positions or bearish trades.
ATR Filter: The ATR helps reduce false signals by ignoring minor price movements. Traders can adjust the ATR Multiplier to make the indicator more or less sensitive based on market conditions. A lower multiplier (e.g., 1.2) may increase signal frequency, while a higher multiplier (e.g., 2.0) reduces it.
Originality:
The Trend CCI (TCCI) stands out due to its combination of the CCI and ATR. While many indicators simply plot raw CCI values, this script enhances the CCI’s effectiveness by incorporating an ATR-based volatility filter. This ensures that only significant trends trigger signals, making it a more reliable tool in volatile markets. The choice of the ATR period, multiplier, and CCI period ensures a refined balance between trend detection and noise reduction, distinguishing it as a powerful trend-following indicator.
Additionally, the visual aspect—using color-coded trendlines that dynamically shift between green and red—simplifies the interpretation of market trends, offering traders a clear and immediate understanding of trend direction and momentum strength.
Final Recommendations:
Use in Trending Markets The TCCI is most effective in trending markets, where its signals align with broader market momentum. In sideways or low-volatility markets, consider adjusting the ATR multiplier or using other complementary indicators to confirm the signals.
Risk Management: Always integrate robust risk management practices, such as using stop-loss orders and position sizing, to protect against sudden market reversals or periods of heightened volatility.
Adjust for Volatility: Consider the volatility of the asset being traded. In highly volatile assets, a higher ATR multiplier (e.g., 2.0) may be necessary to filter out noise, while in more stable assets, a lower multiplier (e.g., 1.2) might generate earlier signals.
By using the Trend CCI (TCCI) indicator with a deeper understanding of its key parameters, traders can better identify trends, reduce noise, and improve their overall decision-making in the markets.
Good Profits!
Post-Open Long Strategy with ATR-based Stop Loss and Take ProfitThe "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit
The "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Entry and Exit Conditions:
Long Entry:
The price breaks above the identified resistance.
The market is in a lateralization phase with low volatility.
The price is above the 10 and 200-period EMAs.
RSI is above 30, and ADX is above 10.
No short-term downtrend is detected.
The last two candles are not both bearish.
The current candle is a "panic candle" (negative close).
Order Execution: The order is executed at the close of the candle that meets all conditions.
Exit from Position:
Dynamic Stop Loss: Set at 2 times the ATR below the entry price.
Dynamic Take Profit: Set at 4 times the ATR above the entry price.
The position is automatically closed upon reaching the Stop Loss or Take Profit.
How to Use the Strategy:
Application on Volatile Instruments:
Ideal for financial instruments that show significant volatility during the target market opening hours, such as indices or major forex pairs.
Recommended Timeframes:
Intraday timeframes, such as 5 or 15 minutes, to capture significant post-open moves.
Parameter Customization:
The default parameters are optimized but can be adjusted based on individual preferences and the instrument analyzed.
Backtesting and Optimization:
Backtesting is recommended to evaluate performance and make adjustments if necessary.
Risk Management:
Ensure position sizing respects risk management rules, avoiding risking more than 1-2% of capital per trade.
Originality and Benefits of the Strategy:
Unique Combination of Indicators: Integrates various technical metrics to filter signals, reducing false positives.
Volatility Adaptability: The use of ATR for Stop Loss and Take Profit allows the strategy to adapt to real-time market conditions.
Focus on Post-Lateralization Breakout: Aims to capitalize on significant moves following consolidation periods, often associated with strong directional trends.
Important Notes:
Commissions and Slippage: Include commissions and slippage in settings for more realistic simulations.
Capital Size: Use a realistic trading capital for the average user.
Number of Trades: Ensure backtesting covers a sufficient number of trades to validate the strategy (ideally more than 100 trades).
Warning: Past results do not guarantee future performance. The strategy should be used as part of a comprehensive trading approach.
With this strategy, traders can identify and exploit specific market opportunities supported by a robust set of technical indicators and filters, potentially enhancing their trading decisions during key times of the day.
Multi-Sector Trend AnalysisThis script, titled "Multi-Sector Trend Analysis: Track Sector Momentum and Trends," is designed to assist traders and investors in monitoring multiple sectors of the stock market simultaneously. It leverages technical analysis by incorporating trend detection and momentum indicators like moving averages and the Relative Strength Index (RSI) to offer insights into the price action of various market sectors.
Core Features:
1. Sector-Based Analysis: The script covers 20 major sectors from the NSE (National Stock Exchange) such as Auto, Banking, Energy, FMCG, IT, Pharma, and others. Users can customize which sectors they wish to analyze using the available input fields.
Technical Indicators: The script uses two core technical indicators to detect trends and momentum:
2. Moving Averages: The script calculates both fast and slow exponential moving averages (EMAs). These are critical for identifying short- and long-term price trends and crossovers, helping detect shifts in momentum.
3. Relative Strength Index (RSI): A well-known momentum indicator that shows whether a stock is overbought or oversold. This script uses a 14-period RSI to gauge the strength of each sector.
4. Trend Detection: The script identifies whether the current market trend is "Up" or "Down" based on the relationship between the fast and slow EMAs (i.e., whether the fast EMA is above or below the slow EMA). It highlights this trend visually in a table format, allowing quick and easy trend recognition.
5. Gain/Loss Tracking: This feature calculates the percentage gain or loss since the last EMA crossover (a key point in trend change), giving users a sense of how much the price has moved since the trend shifted.
6. Customizable Table for Display: The script displays the analyzed data in a table format, where users can view each sector's:
Symbol
Trend (Up or Down)
RSI Value
Gain/Loss Since the Last EMA Crossover
This table is customizable in terms of size and color theme (dark or light), providing flexibility in presentation for different charting styles.
How It Works:
Sector Selection: Users can input up to 20 different sector symbols for analysis.
Moving Averages: Users can define the period lengths for both the fast and slow EMAs to suit their trading strategies.
Table Options: Choose between different table sizes and opt for a dark theme to enhance the visual appearance on charts.
How to Use:
Select the symbols (sectors) that you want to track. The script includes pre-configured symbols for major sectors on the NSE, but you can modify these to suit your needs.
Adjust the fast and slow EMA lengths to your preference. A common setting would be 3 for the fast EMA and 4 for the slow EMA, but more conservative traders might opt for higher values.
Customize the table size and theme based on your preference, whether you want a compact table or a larger one for easier readability.
Why Use This Script:
This script is ideal for traders looking to:
Monitor multiple market sectors simultaneously.
Identify key trends across sectors quickly.
Understand momentum and detect potential reversals through RSI and EMA crossovers.
Stay informed on sector performance using a clear visual table that tracks gains or losses.
By using this script, traders can gain better insights into sector-based trading strategies, improve their sector rotation tactics, and stay informed about the broader market environment. It provides a powerful yet easy-to-use tool for both beginner and advanced traders.
ADX & DI with dynamic threshold indicator
ADX and DI with Dynamic Threshold
This Pine Script indicator, "ADX & DI with Dynamic Threshold," helps traders detect trends, trend reversals, and trend strength using the Average Directional Index (ADX) and the Directional Indexes (DI+ and DI-). It incorporates a dynamic threshold calculated using the average ADX over a user-defined period, along with a fixed minimum threshold, making trend detection more flexible and adaptable.
ADX and Directional Indexes (DI+ and DI-)
ADX measures the strength of a trend, while DI+ and DI- measure the direction of the trend. High DI+ signals upward price strength, and high DI- signals downward price strength.
Dynamic Threshold
A threshold based on the average ADX over a certain number of periods, ensuring the indicator adapts to market conditions. The threshold is compared to DI+ and DI- to generate trend signals.
Fixed Minimum Threshold
A user-defined minimum threshold ensures that signals are only generated in markets with a certain level of trend strength, preventing false signals in low-trending markets.
Visual Highlights
The background color highlights:
Green for potential uptrend,
Red for potential downtrend, and
Orange when directional movement is strong but trend strength is weak, helping traders avoid false signals in sideways markets.
Customization
Several input parameters allow for complete customization of the indicator, ensuring it can adapt to different timeframes and assets.
How to Use
Length (len)
This is the smoothing period used to calculate the ADX and DI+/- values. Range: 5 to 50 (default: 14).
Threshold Period (th_period)
Determines the number of periods over which the dynamic ADX threshold is calculated. Range: 5 to 200 (default: 50).
Fixed Minimum Threshold (fixed_th)
The minimum ADX value that must be exceeded for the indicator to trigger signals. Range: 10 to 40 (default: 20).
Smoothing Method
Choose between SMA (Simple Moving Average) or EMA (Exponential Moving Average) for smoothing the true range and directional movement calculations.
DI+ (Green)
Indicates the strength of upward price movements.
DI- (Red)
Indicates the strength of downward price movements.
ADX (Navy)
Indicates the overall strength of the trend, regardless of direction.
Dynamic Threshold (Gray)
The dynamic threshold used for comparing ADX values.
Fixed Threshold Line
A dotted black line showing the user-defined minimum threshold for ADX.
Green Background
Indicates a potential uptrend when DI+ > DI- and ADX is above the threshold.
Red Background
Indicates a potential downtrend when DI- > DI+ and ADX is above the threshold.
Orange Background
Indicates that DI+ or DI- are strong, but ADX is weak, suggesting a lack of trend strength despite directional movement, which could lead to false signals.
Adjust the length (len) based on the volatility of the asset. A lower len (e.g., 10) may be suitable for faster timeframes (like 5-min charts), while a higher value (e.g., 20-30) may work better on longer timeframes.
Use the threshold period (th_period) to fine-tune the dynamic ADX threshold. A higher value smooths the dynamic threshold over a longer period, making it more resistant to sudden volatility.
Fixed Threshold (fixed_th) should be set based on the strength of trends you want to capture. A higher value (e.g., 30-40) is more conservative and will only trigger signals in very strong trends.
Example Usage
This indicator can be used to:
Identify trends: When the ADX crosses the threshold and DI+ or DI- is dominant, indicating an uptrend or downtrend.
Spot trend reversals: When DI+ and DI- cross each other with a strong ADX reading.
Avoid false signals: By recognizing when DI+ or DI- are strong, but the ADX is below the threshold (highlighted in orange).
Conclusion
The ADX and DI with Dynamic Threshold indicator is a versatile tool for trend-following strategies. It adapts to market conditions using dynamic and fixed thresholds and provides clear visual signals to help traders make informed decisions about market direction and trend strength.
By adjusting the various input parameters, this indicator can be tailored to any asset class or timeframe, making it suitable for all types of traders, from scalpers to swing traders.
Feel free to experiment with different settings and incorporate this indicator into your trading strategy for enhanced market analysis.
DP-OCR MTF & MA 2024This script developed is designed for multi-timeframe analysis of previous open, close, and range, with additional signal plots based on various percentage extension levels. It also incorporates EMA calculations for crossover strategies. Here's a quick breakdown of what the script does:
Key Features:
1. Timeframes:
o Two separate timeframes (TF1 and TF2), which can be set by the user (e.g., 15 mins, 30 mins, daily, etc.). The script computes price actions and extensions for both timeframes. For better analysis, use Daily in TF1 and Weekly in TF2
2. Extension Levels:
o Calculates and plots 10%, 21%, 31%, 51%, and 61% extensions (both positive and negative) for each timeframe.
o The most commonly used extension levels are 61%, 31%, -61%, and -21%.
o These extension levels can be turned on or off by the user.
3. Open/Close/Range:
o Tracks the high, low, open, and close for both timeframes.
o Highlights open/close gaps.
o Plots the previous high/low range for both timeframes with a fill and different colors based on price movement.
How to Use:
• You can toggle specific extension levels on or off in the script’s settings.
• For example, when price hits a +61% extension, it could signal a breakout, and when it hits a -61% extension, it may indicate a potential retracement.
• Use these levels in conjunction with your price action analysis to set entry/exit points or stop-loss levels.
4. Today’s Open:
o Plots today’s opening price for both timeframes.
How to Use:
• Use today’s open as a key reference point to determine the day’s price action.
• Compare today’s open with the previous high/low or extension levels to evaluate possible trends or reversals.
5. EMA Calculations:
o The script calculates 5, 15, and 20 period EMAs and plots them on the chart.
o Additional EMA crossover signals can be included for strategy optimization.
How to Use:
• Observe the EMAs for potential crossover signals. For example, a 5-period EMA crossing above a 15-period or 20-period EMA may signal a buy opportunity, while a crossover in the opposite direction may signal a sell.
• Combine the EMA crossovers with extension levels or previous price data to refine your entries and exits.
Customizations Available:
• Users can select whether to display extension levels for either timeframe.
• The script allows automatic adaptation to intraday, daily, weekly, or monthly timeframes based on the current chart settings.
Moreover, the extension levels are calculated based on the previous period’s range, with the most commonly usable extension levels being 61, 31, -61, and -21. These levels are often used for identifying potential price retracements, breakouts, or reversal points in technical analysis.
Bull/Bear Ratio By Month Table [MsF]Japanese below / 日本語説明は英文の後にあります。
-------------------------
This is an indicator that shows monthly bull-bear ratio in a table.
By specifying the start year and end year, the ratio will be calculated and showed based on the number of bullish and bearish lines in the monthly bar. It allows you to analyze the trend of each symbol and month (bullish / bearish). Up to 10 symbols can be specified.
You can take monthly bull-bear ratio for the past 10 or 20 years on the web, but with this indicator, you can narrow it down to the period in which you want to see the symbols you want to see. It is very convenient because you can take statistics at will.
Furthermore, if the specified ratio is exceeded, the font color can be changed to any color, making it very easy to read.
=== Parameter description ===
- From … Year of start of aggregation
- To … Year of end of aggregation
- Row Background Color … Row title background color
- Col Background Color … Column title background color
- Base Text Color … Text color
- Background Color … Background Color
- Border Color … Border Color
- Location … Location
- Text Size … Text Size
- Highlight Threshold … Ratio threshold, and color
- Display in counter? … Check if you want to show the number of times instead of the ratio
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月別陰陽確率をテーブル表示するインジケータです。
開始年から終了年を指定することで、月足における陽線数および陰線数を元に確率を計算して表示します。
この機能により各シンボルおよび各月の特徴（買われやすい／売られやすい）を認識することができアノマリー分析が可能です。
シンボルは10個まで指定可能です。
過去10年、20年の月別陰陽確率は、Web上でよく見かけますが、このインジケータでは見たいシンボルを見たい期間に絞って、
自由自在に統計を取ることができるため大変便利です。
なお、指定した確率を上回った場合、文字色を任意の色に変更することができるため、大変見やすくなっています。
=== パラメータの説明 ===
- From … 集計開始年
- To … 集計終了年
- Row Background Color … 行タイトルの背景色
- Col Background Color … 列タイトルの背景色
- Base Text Color … テキストカラー
- Background Color … 背景色
- Border Color … 区切り線の色
- Location … 配置
- Text Size … テキストサイズ
- Highlight Threshold … 色変更する確率の閾値、および色
- Display in counter? … 確率ではなく回数表示する場合はチェックする
Dynamic Jurik RSX w/ Fisher Transform█ Introduction
The Dynamic Jurik RSX with Fisher Transform is a powerful and adaptive momentum indicator designed for traders who seek a non-laggy view of price movements. This script is based on the classic Jurik RSX (Relative Strength Index). It also includes features such as the dynamic overbought and oversold limits, the Inverse Fisher Transform, trend display, slope calculations, and the ability to color extremes for better clarity.
█ Key Features:
• RSX: The Relative Strength Index (RSX) in this script is based on Jurik’s RSX, which is smoother than the traditional RSI and aims to reduce noise and lag. This script calculates the RSX using an exponential smoothing technique and adaptive adjustments.
• Inverse Fisher Transform: This script can optionally apply the Inverse Fisher Transform to the RSX, which helps to normalize the RSX values, compressing them between -1 and 1. The inverse transformation makes it easier to spot extreme values (overbought and oversold conditions) by enhancing the visual clarity of those extremes. It also smooths the curve over a user-defined period in hopes of providing a more consistent signal.
• Dynamic Limits: The dynamic overbought and oversold limits are calculated based on the RSX's recent high and low values. The limits adjust dynamically depending on market conditions, making them more relevant to current price action.
• Slope Display: The slope of the RSX is calculated as the rate of change between the current and previous RSX value. The slope is displayed as dots when the slope exceeds the threshold designated by the user, providing visual cues for momentum shifts.
• Trend Coloring: Optionally, the user can also enable a trend-based display. It is simply based on current value of RSX versus the previous one. If RSX is rising then the trend is bullish, if not, then the trend is bearish.
• Coloring Extremes: Users can configure the RSX to color the chart when prices enter extreme conditions, such as overbought or oversold zones, providing visual cues for market reversals.
█ Attached Chart Notes:
• Top Panel: Enabled dynamic limits, Trend display, standard Jurik RSX with 20 lookback period, and Slope display.
• Middle Panel: Enabled dynamic limits, Extremes display, and standard Jurik RSX with 20 lookback period.
• Bottom Panel: Enabled dynamic limits, Trend display, Inverse Fisher Transform with 14 lookback period and 9 smoothing period. and Slope display.
█ Credits:
Special thanks to Everget for providing the original script. The script was also slightly modified based on updates from outside sources.
█ Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research and consult a professional before making any trading decisions.
S&P500 Market Breadth /MA20Introduction
It calculates the percentage of assets trading above their 20-day moving average (MA20), providing a clear view of market breadth and highlighting the strength of an uptrend or downtrend.
Features
• Market Breadth Analysis: The MA20 Market Breadth Indicator tracks the number of assets trading above their 20-day moving average, offering an intuitive view of the proportion of rising versus falling assets. A high breadth suggests a strong uptrend, while low breadth indicates that most assets are in a downtrend.
• Trend Following: This indicator allows traders to easily identify whether the overall market trend is healthy and upward or potentially weakening and downward.
• Simple and Intuitive: The breadth is displayed as a percentage, enabling users to quickly assess market conditions and make informed decisions.
How to Use
1. Assess Market Sentiment: When the MA20 market breadth is above the 50% zone, it indicates that the market is in a broad uptrend, favoring long positions. When it falls below 50%, it signals downward pressure, making it a time for caution or short opportunities.
2. Spot Trend Reversals: Sudden changes in market breadth, such as a sharp decline from a high level, can indicate an upcoming market reversal or correction, signaling traders to adjust their positions.
3. Confirm Trends: Combine the MA20 market breadth with other indicators, such as momentum or volume, to further validate the overall direction of the market.
Applicable Markets
This indicator works across various markets and asset classes, including but not limited to:
• Stock markets (indices and individual stocks)
• Cryptocurrencies
• Forex markets
Conclusion
The MA20 Market Breadth Indicator provides traders with a clear picture of market health, helping to identify broader trends and confirm shifts in market sentiment. It’s an essential tool for traders of all types, particularly those focused on medium to short-term trend following and market reversals.
Disclaimer
This indicator is for educational purposes only. Please use it in conjunction with your own trading strategies and adjust according to your risk tolerance.
This introduction should work well for your TradingView release. You can adjust it as needed for specific features or updates in the indicator.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
IMI and MFI CombinedFor a strategy using the combined IMI (Intraday Momentum Index), MFI (Money Flow Index), and Bollinger Bands on a 1-minute chart of Bank NIFTY (Bank Nifty Index), here's how you can interpret the indicators and define a sell signal strategy:
Strategy Explanation:
IMI (Intraday Momentum Index):
IMI measures the ratio of upward price changes to downward price changes over a specified period, indicating momentum.
In the script, IMI is plotted with a range from 0 to 100. Levels above 75 are considered overbought, and levels below 25 are oversold.
Strategy Condition: A sell signal can be considered when IMI is above 75, indicating a potentially overbought market condition.
MFI (Money Flow Index):
MFI measures the strength of money flowing in and out of a security, using price and volume.
In the script, MFI is plotted with levels at 80 (overbought) and 20 (oversold).
Strategy Condition: A sell signal can be considered when MFI is above 80, suggesting an overbought condition in the market.
Bollinger Bands:
Bollinger Bands consist of a middle band (SMA) and upper/lower bands representing volatility levels around the price.
In the script, Bollinger Bands are plotted with a length of 20 and a standard deviation multiplier of 2.
Strategy Condition: While not explicitly used for generating sell signals in this script, Bollinger Bands can help confirm price volatility and potential reversals when combined with other indicators.
Sell Signal Criteria:
IMI Sell Signal: Look for instances where IMI rises above 75. This indicates that the recent upward price momentum may be reaching an unsustainable level, potentially signaling a reversal or a pullback in prices.
MFI Sell Signal: Look for MFI rising above 80. This suggests that the market has experienced strong buying pressure, possibly leading to an overbought condition where a price correction or reversal might occur.
Implementation Considerations:
Confirmation: Consider waiting for both IMI and MFI to confirm the overbought condition simultaneously before entering a sell trade. This can increase the reliability of the signal.
Risk Management: Use stop-loss orders to manage risk in case the market moves against the anticipated direction after the sell signal is triggered.
Timeframe: This strategy is tailored for a 1-minute chart, meaning signals should be interpreted and acted upon quickly due to the rapid nature of price movements in intraday trading.
By combining these indicators and interpreting their signals, you can develop a systematic approach to identifying potential sell opportunities in the Bank NIFTY index on a 1-minute timeframe. Adjustments to indicator parameters and additional technical analysis may further refine the strategy based on your trading preferences and risk tolerance.
Fibonacci Retracements & Trend Following Strategy V2This Pine Script strategy generates trading signals using Fibonacci levels and trend-following indicators.
1. Strategy Summary
This strategy analyzes price movements using a combination of Fibonacci levels and trend-following indicators, providing potential trading signals. The strategy includes Fibonacci levels as well as EMA (Exponential Moving Average) and ADX (Average Directional Index) indicators.
2. Indicators and Parameters
Fibonacci Levels
Fibonacci Level 1, Level 2, Level 3, Level 4: Used as Fibonacci retracement levels. These levels are typically set at 0.236, 0.382, 0.618, and 0.786. Users can adjust these values according to their preferences.
Trend-Following Indicator
Trend Length: The period for calculating the EMA used as the trend-following indicator. For example, if set to 20, the EMA will be calculated over 20 periods.
ADX (Average Directional Index)
ADX Length: The period for calculating the ADX. ADX measures the strength of the price trend and is usually set to 14 periods.
ADX Threshold: A threshold value for the ADX. This value determines when trading signals will be activated.
3. Usage Steps
Displaying the Indicator on the Chart:
On the TradingView platform, paste the code into the Pine Editor and click the "Add to Chart" button to add it to the chart.
Analyzing the Indicators:
Fibonacci Levels: Show retracement levels of price movements. When the price reaches one of these levels, potential reversals may occur.
Trend-Following Indicator: EMAs determine the direction of the trend. Green EMA represents an uptrend, while red EMA represents a downtrend.
ADX: Measures the strength of the trend. When ADX surpasses the threshold value, it indicates a strong trend.
Trading Signals:
Long Signal: Generated when the price is above the second Fibonacci level and the trend is upward. Additionally, the ADX value must be above the set threshold.
Short Signal: Generated when the price is below the second Fibonacci level and the trend is downward. Additionally, the ADX value must be above the set threshold.
Target Prices:
Long Targets: Determines upward targets based on Fibonacci levels. These targets indicate expected prices if the price reverses from Fibonacci levels.
Short Targets: Determines downward targets based on Fibonacci levels. These targets indicate expected prices if the price reverses from Fibonacci levels.
4. Chart Displays
Trend Up (Green Line): Shows the rising EMA.
Trend Down (Red Line): Shows the falling EMA.
Fibonacci Levels (Blue Lines): Shows Fibonacci retracement levels.
Long Targets (Green Circles): Shows targets for long positions.
Short Targets (Red Circles): Shows targets for short positions.
Long Signal (Green Label): Buy signal.
Short Signal (Red Label): Sell signal.
5. Important Notes
Retracement and Target Levels: Fibonacci levels can act as potential retracement or support/resistance levels. However, they should always be used in conjunction with other technical analysis tools.
Trend and ADX: ADX is used to determine the strength of the trend. Be aware that when ADX is low, trends may be weak.
6. Example Scenarios
Example 1: If the trend is upward (green EMA) and the price is above the second Fibonacci level, you may receive a long position signal. If the ADX value is above the threshold, the signal may be stronger.
Example 2: If the trend is downward (red EMA) and the price is below the second Fibonacci level, you may receive a short position signal. If the ADX value is above the threshold, the signal may be stronger.
This updated version contains significant improvements in both technical aspects and user experience. Innovations such as ADX calculations and dynamic Fibonacci levels make the strategy more robust and flexible. The code's readability and comprehensibility have been enhanced, and errors have been corrected.
This guide will help you understand the basic operation of the strategy. It is always recommended to conduct your own research and test the strategy before using it.
GOOD LUCK. // halilvarol
Artaking 2Components of the Indicator:
Moving Averages:
Short-Term Moving Average (MA): This is a 50-period Simple Moving Average (SMA) applied to the closing price. It is used to track the short-term trend of the market.
Long-Term Moving Average (MA): This is a 200-period SMA used to track the long-term trend.
Day Trading Moving Average: A 20-period SMA is used specifically for day trading signals, focusing on shorter-term price movements.
Purpose:
The crossing of these moving averages (short-term crossing above or below long-term) provides basic buy and sell signals, indicative of potential trend reversals or continuations.
ADX (Average Directional Index) for Trend Strength:
ADX Calculation: The ADX is calculated using a 14-period length with 14-period smoothing. The ADX value indicates the strength of a trend, regardless of direction.
Strong Trend Condition: The indicator considers a trend to be strong if the ADX value is above 25. This threshold helps filter out trades during weak or sideways markets.
Purpose:
To ensure that the strategy only generates signals when there is a strong trend, thus avoiding whipsaws in low volatility or range-bound conditions.
Support Levels:
Support Level Calculation: The indicator calculates the lowest close over the last 100 periods. This level is used to identify significant support zones where the price might find a floor.
Purpose:
Support levels are critical in identifying potential areas where the price might bounce, making them ideal for setting stop losses or identifying buy opportunities.
Volatility Spike (Proxy for News Trading):
ATR (Average True Range) Calculation: The indicator uses a 14-period ATR to measure market volatility. A volatility spike is identified when the ATR is greater than 1.5 times the 14-period SMA of the ATR.
Purpose:
This serves as a proxy for news events or other sudden market movements that could make the market unpredictable. The indicator avoids generating signals during these periods to reduce the risk of being caught in a volatile, potentially news-driven move.
Fibonacci Retracement Levels:
61.8% Fibonacci Level: Calculated from the highest high and lowest low over the long MA period, this retracement level is widely regarded as a significant support or resistance level.
Purpose:
Position traders often use Fibonacci levels to identify potential reversal points. The indicator incorporates the 61.8% level to fine-tune entries and exits.
Candlestick Patterns for Price Action Trading:
Bullish Engulfing Pattern: A bullish reversal pattern where a green candle fully engulfs the previous red candle.
Bearish Engulfing Pattern: A bearish reversal pattern where a red candle fully engulfs the previous green candle.
Purpose:
These patterns are classic signals used in price action trading to identify potential reversals at key levels, especially when they align with other conditions like support/resistance or Fibonacci levels.
Signal Generation:
The indicator generates buy and sell signals by combining the above elements:
Buy Signal:
A buy signal is triggered when:
The short-term MA crosses above the long-term MA (indicating a potential uptrend).
The trend is strong (ADX > 25).
The current price is near or below the 61.8% Fibonacci retracement level, suggesting a potential reversal.
No significant volatility spike is detected, ensuring the market isn’t reacting unpredictably to news.
Sell Signal:
A sell signal is triggered when:
The short-term MA crosses below the long-term MA (indicating a potential downtrend).
The trend is strong (ADX > 25).
The current price is near or above the 61.8% Fibonacci retracement level, suggesting potential resistance.
No significant volatility spike is detected.
Day Trading Signals:
Independent of the main trend signals, the indicator also generates intraday buy and sell signals when the price crosses above or below the 20-period day trading MA.
Price Action Signals:
The indicator can trigger buy or sell signals based purely on price action, such as the occurrence of bullish or bearish engulfing patterns. This is optional and can be enabled or disabled.
Alerts:
The indicator includes built-in alert conditions that notify the trader when a buy or sell signal is generated. This allows traders to act immediately without having to constantly monitor the charts.
Practical Application:
This indicator is versatile and can be used across various trading styles:
Position Trading: The long-term MA, Fibonacci retracement, and ADX provide a solid foundation for identifying long-term trends and potential entry/exit points.
Day Trading: The short-term MA and day trading MA offer quick signals for intraday trading.
Price Action: Candlestick pattern recognition allows for precise entry points based on market sentiment and behavior.
News Trading: The volatility spike filter helps avoid trading during periods of market instability, often driven by news events.
Conclusion:
The Comprehensive Trading Strategy Indicator is a robust tool designed to help traders navigate various market conditions by integrating multiple strategies into a single, coherent framework. It provides clear, actionable signals while filtering out potentially dangerous trades during volatile or weak market conditions. Whether you're a long-term trader, a day trader, or someone who relies on price action, this indicator can be a valuable addition to your trading toolkit.
Heartbeat Momentum Strategy BetaHeartbeat Momentum Strategy Beta
Overview
The Heartbeat Momentum Strategy is an innovative approach to market analysis that draws inspiration from the rhythmic patterns of a heartbeat. This strategy aims to identify significant momentum shifts in the market by comparing short-term and long-term moving averages, analogous to detecting irregularities in a heartbeat.
Key Concepts
Market Heartbeat: The difference between short-term and long-term moving averages, representing the market's current 'pulse'.
Heartbeat Volatility: Measured by the standard deviation of the market heartbeat.
Momentum Signals: Generated when the heartbeat deviates significantly from its normal range.
How It Works
Calculates a short-term moving average (default 5 periods) and a long-term moving average (default 20 periods) of the closing price.
Computes the 'heartbeat' by subtracting the long-term MA from the short-term MA.
Measures the volatility of the heartbeat using its standard deviation over the long-term period.
Generates buy signals when the heartbeat exceeds 2 standard deviations above its mean.
Generates sell signals when the heartbeat falls 2 standard deviations below its mean.
Indicator Components
Blue Line: Short-term moving average
Red Line: Long-term moving average
Green Triangles: Buy signals
Red Triangles: Sell signals
Background Color: Light green during buy signals, light red during sell signals
Strategy Parameters
Short MA Window: The period for the short-term moving average (default: 5)
Long MA Window: The period for the long-term moving average (default: 20)
Standard Deviation Threshold: The number of standard deviations to trigger a signal (default: 2.0)
Interpretation
Buy Signal: Indicates a potential strong upward momentum shift. Consider opening long positions or closing short positions.
Sell Signal: Suggests a potential strong downward momentum shift. Consider opening short positions or closing long positions.
No Signal: The market is moving within its normal rhythm. Maintain current positions or look for other entry opportunities.
Customization
Users can adjust the strategy parameters to suit different assets, timeframes, or trading styles:
Decrease the MA windows for more frequent signals (more suitable for shorter timeframes).
Increase the MA windows for fewer, potentially more significant signals (better for longer timeframes).
Adjust the Standard Deviation Threshold to fine-tune sensitivity (lower for more signals, higher for fewer but potentially stronger signals).
Risk Management
While this strategy can provide valuable insights into market momentum, it should not be used in isolation:
Always use stop-loss orders to manage potential losses.
Consider the overall market context and other technical/fundamental factors.
Be aware of potential false signals, especially in ranging or highly volatile markets.
Backtest and forward-test the strategy with different parameters before live trading.
Conclusion
The Heartbeat Momentum Strategy offers a unique perspective on market movements by treating price action like a heartbeat. By identifying significant deviations from the normal market rhythm, it aims to capture strong momentum shifts while filtering out market noise. As with any trading strategy, use it as part of a comprehensive trading plan and always practice sound risk management.
Support line based on RSIThis indicator builds a support line using the stock price and RSI.
Inputs:
1. Time window for the RSI:
the time window the RSI is calculated with, usually it's 14 but in here I recommend 30.
2. offset by percentage:
just adding or subtructing some percentage of the result, some stocks need a bit of offset to work
3. stability:
the higher it is the less the RSI effects the graph. for realy high stability the indicator the the stock price will be realy close.
formula: (close*(100-newRSI)/50)*(100+offset)/100
when:
newRSI = (RSI + (50 * stability1))/(stability+1)
recommended usage:
Usually, if the indicator becomes higher than the price, (the price lowers). the stock will go up again to around the last price where they met.
so, for example, if the stock price was 20 and going down. while the indicator was 18 and going up, then they met at 19 and later the indicator became 20 while the stock fell to 18. most chances are that the stock will come back to 19 where they met and at the same time the indicator will also get to 19.
In stocks that are unstable, like NVDA. this indicator can be used to see the trend and avoid the unstability of the stock.
Swing Trend AnalysisIntroducing the Swing Trend Analyzer: A Powerful Tool for Swing and Positional Trading
The Swing Trend Analyzer is a cutting-edge indicator designed to enhance your swing and positional trading by providing precise entry points based on volatility contraction patterns and other key technical signals. This versatile tool is packed with features that cater to traders of all timeframes, offering flexibility, clarity, and actionable insights.
Key Features:
1. Adaptive Moving Averages:
The Swing Trend Analyzer offers multiple moving averages tailored to the timeframe you are trading on. On the daily chart, you can select up to four different moving average lengths, while all other timeframes provide three moving averages. This flexibility allows you to fine-tune your analysis according to your trading strategy. Disabling a moving average is as simple as setting its value to zero, making it easy to customize the indicator to your needs.
2. Dynamic Moving Average Colors Based on Relative Strength:
This feature allows you to compare the performance of the current ticker against a major index or any symbol of your choice. The moving average will change color based on whether the ticker is outperforming or underperforming the selected index over the chosen period. For example, on a daily chart, if the 21-day moving average turns blue, it indicates that the ticker has outperformed the selected index over the last 21 days. This visual cue helps you quickly identify relative strength, a key factor in successful swing trading.
3. Visual Identification of Price Contractions:
The Swing Trend Analyzer changes the color of price bars to white (on a dark theme) or black (on a light theme) when a contraction in price is detected. Price contractions are highlighted when either of the following conditions is met: a) the current bar is an inside bar, or b) the price range of the current bar is less than the 14-period Average Daily Range (ADR). This feature makes it easier to spot price contractions across all timeframes, which is crucial for timing entries in swing trading.
4. Overhead Supply Detection with Automated Resistance Lines:
The indicator intelligently detects the presence of overhead supply and draws a single resistance line to avoid clutter on the chart. As price breaches the resistance line, the old line is automatically deleted, and a new resistance line is drawn at the appropriate level. This helps you focus on the most relevant resistance levels, reducing noise and improving decision-making.
5. Buyable Gap Up Marker: The indicator highlights bars in blue when a candle opens with a gap that remains unfilled. These bars are potential Buyable Gap Up (BGU) candidates, signaling opportunities for long-side entries.
6. Comprehensive Swing Trading Information Table:
The indicator includes a detailed table that provides essential data for swing trading:
a. Sector and Industry Information: Understand the sector and industry of the ticker to identify stocks within strong sectors.
b. Key Moving Averages Distances (10MA, 21MA, 50MA, 200MA): Quickly assess how far the current price is from key moving averages. The color coding indicates whether the price is near or far from these averages, offering vital visual cues.
c. Price Range Analysis: Compare the current bar's price range with the previous bar's range to spot contraction patterns.
d. ADR (20, 10, 5): Displays the Average Daily Range over the last 20, 10, and 5 periods, crucial for identifying contraction patterns. On the weekly chart, the ADR continues to provide daily chart information.
e. 52-Week High/Low Data: Shows how close the stock is to its 52-week high or low, with color coding to highlight proximity, aiding in the identification of potential breakout or breakdown candidates.
f. 3-Month Price Gain: See the price gain over the last three months, which helps identify stocks with recent momentum.
7. Pocket Pivot Detection with Visual Markers:
Pocket pivots are a powerful bullish signal, especially relevant for swing trading. Pocket pivots are crucial for swing trading and are effective across all timeframes. The indicator marks pocket pivots with circular markers below the price bar:
a. 10-Day Pocket Pivot: Identified when the volume exceeds the maximum selling volume of the last 10 days. These are marked with a blue circle.
b. 5-Day Pocket Pivot: Identified when the volume exceeds the maximum selling volume of the last 5 days. These are marked with a green circle.
The Swing Trend Analyzer is designed to provide traders with the tools they need to succeed in swing and positional trading. Whether you're looking for precise entry points, analyzing relative strength, or identifying key price contractions, this indicator has you covered. Experience the power of advanced technical analysis with the Swing Trend Analyzer and take your trading to the next level.
MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe between 30 min and 4 hours and chart (optimal performance observed on 45 min BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
