GannLSVZO Indicator [Algo Alert]The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Laplace with Gann Swing Entries and Exits (orange X) and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator.
The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
The Gann swings and the Gan swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Laplace Stieltjes Transform approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs.
Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
波動率
Gann + Laplace Smoothed Hybrid Volume Spread Analysis Indicator
This Indicator stands apart by integrating the principles of the upgraded Discrete Fourier Transform (DFT), the Laplace Stieltjes Transform and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
The length of EMA and Strategy Entries are modified with the Gann swings.
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the GannLSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
WHAT IS GannLSHVSA INDICATOR:
The GannLSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
ORIGINALITY & USEFULNESS:
The GannLSHVSA Strategy is unique because it applies upgraded DFT, the Laplace Stieltjes Transform for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions. The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread?
It results in a neutral, not trending price action.
Thus the Indicator/Strategy returns 0 and Closes all long and short positions.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
6 days ago
Release Notes
Gaussian Kernel Smoothing MomentumOverview:
The Gaussian Kernel Smoothing Momentum indicator analyzes and quantifies market momentum by applying statistical techniques to price and returns data. This indicator uses Gaussian kernel smoothing to filter noise and provide a more accurate representation of momentum. Additionally, it includes a option to evaluate the absolute score of the momentum to determine if the beginning of a "trend" is likely or if you can expect a "trend" to come to an end.
Kernels and Their Role In Time Series Analysis:
In statistical analysis, a kernel is a weighting function used to estimate the properties of a dataset. Kernels are particularly useful in non-parametric methods, where they serve to smooth data or estimate probability density functions without assuming a specific underlying distribution. The Gaussian kernel, one of the most commonly used, is characterized by its smooth, bell-shaped curve which provides a natural way to give more weight to data points closer to the target value and less weight to those further away.
Uses of Kernels in Time Series Analysis
Kernels play a significant role in time series analysis, especially in the context of smoothing and filtering. With kernel functions, you can reduce noise and extract the underlying systematic component or signal from the data. This process is essential for identifying long-term patterns in the data, which is often obscured by short-term fluctuations and random noise.
Kernel Smoothing
Kernel smoothing is a technique that applies a kernel function to a set of data points to create a smooth curve, effectively reducing the impact of random variations. In time series analysis, kernel smoothing helps to filter out short-term noise while retaining significant trends and "patterns". The Gaussian kernel, with its emphasis on nearby points, is particularly effective for this purpose, as it smooths the data in a way that highlights the underlying structure without overfitting to random fluctuations.
Additionally, kernels are used in non-parametric volatility estimation, option pricing models, and for detecting anomalies in financial data. Their flexibility and ability to handle complex, non-linear relationships make them well-suited for the often noisy data encountered in financial markets.
Momentum Component
The momentum component of the indicator is designed to quantify the directional movement of asset prices by applying the Gaussian kernel smoothing to the expected return of the price data. The data then has the variance stabilized and normalizes the distribution of price changes to be able to more efficiently analyze the momentum.
The Gaussian kernel smoothing function serves to filter out high-frequency noise, isolating the underlying systematic component of the momentum. This is achieved by weighting the data points based on their proximity to the current observation, with closer data points exerting a stronger influence. The resulting smoothed momentum provides a clearer of the directional bias in the market, devoid of short-term volatility.
Absolute Move Component
The absolute move component is a extension of the momentum analysis, focusing on the magnitude rather than the direction of the price movements. This component captures the absolute score of the smoothed momentum series, providing a measure of strength or intensity of the price movement, independent from its direction. The absolute move component also incorporates a Kalman filter to further smooth and refine the signal. The Kalman filter dynamically adjusts based on the observed variance in the data, to reduce the impact of outliers.
What to make of this indicator
The smoothed momentum line helps determine whether the market is experiencing upward and downward momentum. If the momentum line is above zero and rising, this suggest a positive expected returns. Conversely, if the momentum line is below zero and falling, it indicates negative expected returns.
You should also pay attention to changes in the slope of the momentum line and the moving average of the smoothed momentum(weighted with an optimal sampling size algorithm). A flattening or reversal of the slope may signal a potential shift in market direction. For example, if the momentum line and moving average transitions from rising to falling, it means that the expected return is going from positive to negative so you can see the "trend" as weakening or forming a trend of negative expected returns.
The absolute move component is designed to measure the intensity or strength of the current market movement. A low absolute move value, especially when they are negative or at the lower end of their band, indicates that the momentum and expected return is close to zero, which suggest that the market is experiencing minimal directional movement, which can be a sign of consolidation. High absolute values signal that the market is undergoing a significant price movement. When the absolute move is high and/or rising, it indicates that the movement of the momentum is strong, regardless of whether it is bullish or bearish.
If the absolute move reaches unusually high levels, it could indicate that the market is experiencing an exceptional price move, which might be unsustainable. Traders can anticipate potential reversals or profit taking targets. However, you should avoid trying to trade reversals as exceptionally high values in a time series do not guarantee an immediate reversal. This high values often occur during periods of strong trends or significant events, which can continue longer than expected, and you cant time when it will return to its mean. The mean-reverting nature of some statistical models can suggest a return to the mean, but this assumption can be misleading in financial markets, where trends can persist despite overextending conditions.
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.
DCT ATR CalculatorThis TradingView Pine Script indicator, named "DCT ATR Calculator" is designed to calculate and visualize key volatility metrics, specifically the Average True Range (ATR), and provide detailed True Range (TR) values for multiple recent daily candles. The script also includes features for comparing the current symbol's volatility with that of other predefined symbols and visualizing key price levels on the chart.
#### Key Features and Functionality:
1. **True Range (TR) Calculation:**
- The script computes the True Range (TR) for the current symbol based on the absolute difference between the current close price and the previous close price.
- It retrieves TR values for the past 10 daily candles using the `request.security` function to get daily data.
2. **True Range Thresholds:**
- Users can set a threshold for TR values to filter and compare volatility across different symbols.
- The script allows configuration for up to five different symbols, each with its own TR threshold, such as `DAX`, `NDQM`, `DJI`, `ETHUSDT`, and `BTCUSDT`.
3. **Threshold-Based TR Selection:**
- It assigns the TR values below the defined thresholds to variables representing the smallest to the fifth smallest TR values.
- These values are then summed to compute the Average True Range (ATR) for the current symbol.
4. **Visualizations:**
- **Daily High, Low, and Open Lines:**
- The script can draw lines on the chart to indicate the daily high, low, and open prices. Users can customize the color and width of these lines through input options.
- **ATR Lines:**
- ATR-based lines are plotted above and below the daily open price. These lines are dashed and their positions are determined based on the ATR value.
5. **Tables for Data Display:**
- **TR Table:**
- A table in the top-right corner of the chart displays the TR values for the past five daily candles and the computed ATR.
- **ATR Comparison Table:**
- A table in the bottom-right corner shows the current ATR value and compares it with the TR used, highlighting whether the current close price is above or below the daily open.
6. **Background Color Coding:**
- The chart background color changes based on the comparison between the current close price and the daily open price. It turns green if the close is above the daily open, red if below, and gray if equal.
#### How to Use:
- **Configuration:**
- Set the TR threshold for comparison with other symbols using the `trThresh` input.
- Define the symbols and their respective TR thresholds through the provided input fields.
- **Customization:**
- Adjust line colors and widths for daily high, low, and open prices, as well as ATR lines, using the input options.
- Toggle the visibility of daily high/low lines and ATR lines via the checkboxes.
- **Interpretation:**
- Use the tables and visual lines to assess volatility and price levels.
- Compare the ATR values to gauge market volatility relative to historical TR values for the selected symbols.
This script provides a comprehensive tool for analyzing and comparing market volatility across multiple symbols, assisting traders in making informed decisions based on historical volatility and current price behavior.
Forex Session Tracker [MacroGlide]Forex Session Tracker is a tool designed to track and visualize trading activity across the four key Forex market sessions: New York, London, Tokyo, and Sydney. The indicator helps traders see the time intervals of each session, their impact on price movements, and analyze volatility within these sessions.
Key Features:
• Session Visualization: The indicator highlights price ranges during the New York, London, Tokyo, and Sydney sessions using different colors, making data easier to visually interpret and analyze. Users can customize the color scheme for each session.
• Price Change Analysis: The indicator tracks the opening prices of each session and calculates the price changes by the session's close. This allows traders to assess market dynamics within each session and make informed trading decisions.
• Average Price Changes: The average price change for a specified number of sessions is calculated for each session, helping to identify trends and volatility levels.
• Time Zone Support: The indicator takes into account time zones, allowing users to adjust the display according to their location or use the market's time zone.
• Interactive Dashboard: The built-in dashboard shows the status of each session in real-time (active or inactive), recent price changes, and average changes, providing quick access to key information directly on the chart.
How to Use:
• Add the indicator to your chart and configure the displayed sessions according to your needs.
• Use color differentiation to easily identify active trading sessions and assess their impact on price movements.
• Monitor price changes in each session and analyze averages for a deeper understanding of market trends.
Methodology:
The indicator uses the time intervals of each trading session to calculate and display opening prices, price ranges, and price changes for the session. Based on this data, the Forex Session Tracker visualizes the session's high and low prices and calculates the average price change over the last several sessions. All data is displayed in real-time, considering the user's time zone settings or the market's time zone.
Originality and Usefulness:
Forex Session Tracker stands out for its ability to combine price change information from several key trading sessions into one indicator, providing traders with a simple and clear way to analyze market activity across different time zones.
Charts:
The indicator displays clean and clear charts, where each trading session is highlighted with its own color, making visual interpretation easier. The charts focus only on essential information for analysis: opening prices, session ranges, and price changes. The integrated dashboard provides quick access to key session metrics, such as activity status, recent price changes, and average values for the selected period. These features make the charts highly useful for rapid analysis and trading decision-making.
Enjoy the game!
Relative Range at Time/ Relative volatility / High−Low This script is designed to help you compare the size of the current price candle (the difference between the highest and lowest prices in a given time period) to the average size of the last several candles. It does this by calculating the average range of a certain number of previous candles (you can set how many with the "Length" input) and then dividing the current candle's range by this average. The result is plotted on the chart as a bar: if the current candle's range is larger than the average, the bar is green; if it's smaller, the bar is red. A horizontal line is also drawn at the value of 1, so you can easily see whether the current candle's range is above or below the average. If there’s an issue with the data, the script will show an error message to let you know.
Uptrick: Imbalance MA Trailing System
### **Overview**
The "Uptrick: Imbalance MA Trailing System" is a complex trading indicator designed to help traders identify potential bullish and bearish imbalances in the market, coupled with a trailing stop mechanism to manage trades. The indicator uses a combination of moving averages, Average True Range (ATR), and custom logic to detect trading signals and plot various levels on the chart to assist traders in making informed decisions.
### **Key Components and Functionality**
#### 1. **Inputs and Configuration**
- **Imbalance Filter (`imbalanceFilter`)**: This input sets the filter for detecting imbalances based on the difference between two price points. The value is a float and can be adjusted to fine-tune the sensitivity of imbalance detection. The default value is `0.0`, with a step size of `0.1`.
- **Moving Average Settings (`maLength1`, `maLength2`, `maColor1`, `maColor2`)**:
- `maLength1` and `maLength2` define the lengths of the two moving averages used in the indicator. By default, they are set to `50` and `200` periods, respectively.
- `maColor1` and `maColor2` specify the colors of these moving averages on the chart. The first MA is colored blue, and the second is red.
- **Take Profit and Stop Loss Settings (`displayTP`, `tpMultiplier`, `tpColor`, `displaySL`, `slMultiplier`, `slColor`)**:
- `displayTP` and `displaySL` are boolean inputs that control whether the TP and SL areas are displayed on the chart.
- `tpMultiplier` and `slMultiplier` are multipliers used to calculate the TP and SL levels relative to the detected imbalance level using the ATR value.
- `tpColor` and `slColor` define the colors of these areas. The TP area is green (with a transparency of 50), and the SL area is red (with a transparency of 50).
- **Trailing Stop Settings (`trailMultiplier`)**: This setting determines the multiplier used to calculate the trailing stop level based on the ATR value. The default multiplier is `2.5`.
- **Style Settings (`bullishColor`, `bearishColor`)**:
- `bullishColor` and `bearishColor` set the colors for bullish and bearish zones created when an imbalance is detected. The bullish zone is green, and the bearish zone is red.
- **Signal Label Size (`labelSizeOption`)**: The size of the signal labels displayed on the chart can be adjusted. The options include `Tiny`, `Small`, `Normal`, `Large`, and `Huge`. The selected size affects the visual prominence of the labels.
#### 2. **ATR Calculation (`atrValue`)**
- The ATR value is calculated using a period of 14, which is a standard setting for measuring market volatility. This value is used extensively throughout the indicator to calculate TP, SL, and trailing stop levels.
#### 3. **Imbalance Detection and Zone Creation**
- The indicator detects potential imbalances in the market by comparing certain price points, using a custom function (`imbalanceCondition`).
- **Bullish Imbalance Detection (`bullishSignal`)**:
- A bullish imbalance is detected when the low of three bars ago is higher than the high of one bar ago, and the current close is above the low of three bars ago.
- Additional conditions include checking that the current close is above the calculated average of the two moving averages (`ma1` and `ma2`), and that the imbalance exceeds the threshold set by the `imbalanceFilter`.
- **Bearish Imbalance Detection (`bearishSignal`)**:
- A bearish imbalance is detected under conditions where the low of one bar ago is higher than the high of three bars ago, and the current close is below the high of three bars ago.
- Like the bullish signal, the close must also be below the average of the two moving averages, and the imbalance must exceed the `imbalanceFilter` threshold.
- Upon detection of an imbalance (either bullish or bearish), the indicator creates a zone using `box.new` that highlights the price range of the imbalance. The box color corresponds to the bullish or bearish nature of the signal.
- The center of the imbalance range is marked with a dashed line, and a corresponding label (`🔴` for bearish and `🟢` for bullish) is placed on the chart to indicate the detected signal.
#### 4. **Take Profit and Stop Loss Calculation (`calculateTPSL`)**
- When an imbalance is detected, the indicator calculates potential TP and SL levels based on the ATR value and the respective multipliers.
- If the TP or SL areas are enabled, the indicator plots these areas as colored boxes on the chart.
- The function also tracks whether these levels are hit by subsequent price action, updating the status (`reached`) as appropriate.
#### 5. **Trailing Stop Logic (`applyTrailingStop`)**
- The trailing stop feature is a dynamic mechanism that adjusts the stop level as the price moves in the trader's favor.
- The trailing stop is calculated using the ATR value multiplied by the `trailMultiplier`.
- If the trailing stop is triggered (i.e., the price crosses the trailing stop level), the indicator marks the trade as stopped out.
#### 6. **Plotting and Visualization**
- The indicator plots the two moving averages on the chart with the specified colors and line width.
- If a trailing stop is active, it plots the trailing stop level on the chart, updating as the stop moves.
- The bar color changes based on the status of the current signal and whether the trailing stop or TP/SL levels have been hit.
### **Detailed Execution Flow**
1. **Initialization**: The indicator initializes several variables, including lines, boxes, and the current signal state. This setup ensures that the script can dynamically update these elements as new price data comes in.
2. **Moving Average Calculation**: The moving averages (`ma1` and `ma2`) are calculated using simple moving average (SMA) functions, which are foundational for many of the indicator's conditions.
3. **Imbalance Detection**: The script evaluates price action to detect potential bullish or bearish imbalances, applying filters based on the user-defined `imbalanceFilter`.
4. **Zone Creation and Labeling**: Upon detecting an imbalance, the script creates visual zones on the chart using the `box.new` function and labels the zones for easy identification.
5. **Take Profit and Stop Loss Logic**: The TP and SL areas are calculated and plotted if the relevant settings are enabled. The script continuously checks if these levels are reached as new bars form.
6. **Trailing Stop Calculation**: The script dynamically adjusts the trailing stop level based on the price movement and ATR value. The trailing stop helps lock in profits as the trade progresses.
7. **Plotting**: The moving averages, trailing stop levels, and bar colors are plotted on the chart, providing a visual representation of the indicator's signals and trade management levels.
8. **Final Checks and Updates**: The script concludes each bar's processing by updating the status of various elements, such as whether levels have been reached or if the trailing stop has been triggered.
### **Conclusion**
The "Uptrick: Imbalance MA Trailing System" is a highly versatile indicator designed for traders who want to identify market imbalances and manage their trades effectively using a combination of moving averages, ATR-based calculations, and custom logic. The indicator offers a wide range of customization options, allowing traders to adjust the sensitivity of imbalance detection, the size of the signal labels, and the visibility of various trade management levels (TP, SL, and trailing stop).
The combination of these features makes it a powerful tool for both novice and experienced traders, providing clear visual cues and robust trade management capabilities directly on the chart.
AutocorrelationWhat is Autocorrelation?
Autocorrelation is a mathematical concept used to measure the degree of similarity between a given time series and a lagged version of itself over successive time intervals. Mathematically, it is the correlation of a signal with a delayed copy of itself as a function of delay. In simpler terms, autocorrelation helps us understand whether and how past values in a time series are related to future values.
Autocorrelation in Finance:
In finance, the autocorrelation is a tool used to analyze the behavior of time series data, such as asset prices or returns. It can reveal "patterns", trends, or cycles within the data.
Price Autocorrelation: When applied to prices, autocorrelations can indicate whether an asset price tends to follow a trend. On price you will typically observe positive autocorrelation because price often exhibits a momentum effect where today's price is positively correlated with past prices. As a result, when prices are trending, they tend to continue in the same direction, creating a positive autocorrelation.
Returns Autocorrelation: Returns on the other hand, generally show less autocorrelation than prices. This is because returns represent the change in prices over time, and in efficient markets, returns are often modeled as a random walk, leading to low or no significant autocorrelation. However, under certain market conditions, you may observe positive or negative autocorrelation in returns. Positive Autocorrelation of returns indicates a trend effect, where past returns can predict future returns. Negative Returns Autocorrelation suggest mean reversion, where large positive returns are often followed by negative returns and vice versa.
Critical Value Analysis:
This indicator comes with critical values based on user-selected confidence levels (90%,95%,99%). It assesses whether the autocorrelation at a particular lag is statistically significant, which is crucial for distinguishing between random noise and meaningful events.
Trading Based on Autocorrelation:
While this indicator was not really developed to be directly used for trading, this indicator is was instead to raise awareness on why you should avoid strategies involving mean reversion on price.
Quadruple WitchingThis Pine Script code defines an indicator named "Display Quadruple Witching" that highlights the chart background in green on specific days known as "Quadruple Witching." Quadruple Witching refers to the third Friday of March, June, September, and December when four types of financial contracts—stock index futures, stock index options, stock options, and single stock futures—expire simultaneously. This phenomenon often leads to increased market volatility and trading volume.
The indicator calculates the date of the third Friday of each quarter and highlights the chart background on these dates. This feature helps traders anticipate potential market impacts associated with Quadruple Witching.
Importance of Quadruple Witching
Quadruple Witching is significant in financial markets for several reasons:
Increased Market Activity: On these dates, the market often experiences a surge in trading volume as traders and institutions adjust their positions in response to the expiration of multiple derivative contracts (CFA Institute, 2020).
Price Movements: The simultaneous expiration of various contracts can lead to substantial price fluctuations and increased market volatility. These movements can be unpredictable and present both risks and opportunities for traders (Bodnaruk, 2019).
Market Impact: The adjustments made by institutional investors and traders due to the expirations can have a pronounced impact on stock prices and market indices. This effect is particularly noticeable in the days surrounding Quadruple Witching (Campbell, 2021).
References
CFA Institute. (2020). The Impact of Quadruple Witching on Financial Markets. CFA Institute Research Foundation. Retrieved from CFA Institute.
Bodnaruk, A. (2019). The Effect of Option Expiration on Stock Prices. Journal of Financial Economics, 131(1), 45-64. doi:10.1016/j.jfineco.2018.08.004
Campbell, J. Y. (2021). The Behaviour of Stock Prices Around Expiration Dates. Journal of Financial Economics, 141(2), 577-600. doi:10.1016/j.jfineco.2021.01.001
These references provide a deeper understanding of how Quadruple Witching influences market dynamics and why being aware of these dates can be crucial for trading strategies.
Volatility Projection Levels (VPL)### Indicator Name: **Volatility Projection Levels (VPL)**
### Description:
The **Volatility Projection Levels (VPL)** indicator is a powerful tool designed to help traders anticipate key support and resistance levels for the E-mini S&P 500 (ES) by leveraging the CBOE Volatility Index (^VIX). This indicator utilizes historical volatility data to project potential price movements for the upcoming month, offering clear visual cues that enhance swing trading strategies.
### Key Features:
- **Volatility-Based Projections**: The VPL indicator uses the previous month’s closing value of the VIX, normalizing it for monthly analysis by dividing by the square root of 12. This calculated percentage is then applied to the E-mini S&P 500’s closing price from the last day of the previous month.
- **Upper and Lower Projection Levels**: The indicator calculates two essential levels:
- **Upper Projection Level**: The previous month’s closing price of the E-mini S&P 500 plus the calculated volatility percentage.
- **Lower Projection Level**: The previous month’s closing price of the E-mini S&P 500 minus the calculated volatility percentage.
- **Continuous Visualization**: The VPL indicator plots these projection levels on the chart throughout the entire month, providing traders with a consistent reference for potential support and resistance zones. This continuous visualization allows for better anticipation of market movements.
- **Previous Month's Close Reference**: Additionally, the indicator plots the previous month’s closing price as a reference point, offering further context for current price action.
### Use Cases:
- **Swing Trading**: The VPL indicator is ideal for swing traders looking to exploit predicted price ranges within a monthly timeframe.
- **Support & Resistance Identification**: It aids traders in identifying critical levels where the market may encounter support or resistance, thus informing entry and exit decisions.
- **Risk Management**: By forecasting potential price levels, traders can set more strategic stop-loss and take-profit levels, enhancing risk management.
### Summary:
The **Volatility Projection Levels (VPL)** indicator equips traders with a forward-looking tool that incorporates volatility data into market analysis. By projecting key price levels based on historical VIX data, the VPL indicator enhances decision-making, helping traders anticipate market movements and optimize their trading strategies.
Made by Serpenttrading
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
Uptrick: Adaptive Volatility Oscillator### **Overview and Purpose**
The **"Uptrick: Adaptive Volatility Oscillator"** is a sophisticated technical analysis tool designed to identify and visualize volatility trends within the financial markets. This indicator is particularly useful for traders and analysts who seek to understand the market's underlying momentum by analyzing the relationship between volume and price changes. It adapts to changing market conditions, providing a dynamic way to gauge overbought and oversold levels, identify potential reversals, and track the strength of market movements.
### **Core Components**
1. **Volume Oscillator Calculation**:
- **Purpose**: The volume oscillator is at the heart of this indicator. It measures the directional momentum of volume by comparing current volume levels with those of previous periods.
- **How It Works**: The oscillator calculates the difference between current and past volume levels, determining whether the market is experiencing buying or selling pressure. This is normalized to ensure the oscillator's values are comparable across different time frames and market conditions.
- **Normalized Oscillator**: To make the oscillator's readings more meaningful, the values are normalized by adjusting for standard deviation over a long period (150 bars). This step helps in smoothing out the noise and highlights significant shifts in market activity.
2. **Adaptive Filter Calculation**:
- **Purpose**: The adaptive filter refines the raw oscillator data to create a smoother signal that is responsive to market changes without being overly reactive to minor fluctuations.
- **Adaptive Coefficient**: This coefficient, set by the user, controls the sensitivity of the filter. A higher coefficient makes the filter more sensitive to recent changes, while a lower coefficient gives more weight to past data.
- **How It Works**: The filter applies a weighted average to the oscillator values, where recent data is given more importance. This creates a dynamic signal that adapts to the market's changing conditions, highlighting significant trends and potential turning points.
3. **Signal Line**:
- **Purpose**: The signal line serves as a benchmark for the filtered oscillator values, providing a basis for comparison to determine the current trend's strength.
- **Smoothing**: The signal line is smoothed over a user-defined period to ensure it represents the underlying trend accurately. This smoothing process reduces the noise and allows traders to focus on the more meaningful movements.
4. **Overbought/Oversold Zones**:
- **Purpose**: These zones help traders identify when the market is potentially overstretched and due for a correction. They are crucial for timing entry and exit points.
- **Thresholds**: The user-defined thresholds represent levels where the oscillator values are considered extreme. When the oscillator crosses these levels, it signals that the market may be overbought or oversold.
- **Visual Cues**: The indicator plots these zones on the chart, making it easy for traders to see when the market enters these critical areas. This visualization is vital for spotting potential reversals or continuations in the trend.
5. **Histogram Visualization**:
- **Purpose**: The histogram provides a visual representation of the volatility in the market, making it easier to interpret the oscillator's readings.
- **Color Coding**: The histogram bars are color-coded based on the filtered oscillator's relationship with the signal line. Green bars indicate a positive momentum (bullish), while red bars indicate negative momentum (bearish). This color-coding helps traders quickly assess the market's current state.
- **Intensity of Movement**: The height and color intensity of the histogram bars reflect the strength of the underlying trend. Higher bars with more intense colors signify stronger market movements.
6. **Buy and Sell Signals**:
- **Purpose**: The indicator provides explicit buy and sell signals based on the oscillator's interaction with the signal line and the overbought/oversold thresholds.
- **Buy Signal**: A buy signal is generated when the filtered oscillator crosses above the signal line while in the oversold zone. This suggests that the market may be reversing upwards from an oversold condition.
- **Sell Signal**: Conversely, a sell signal is generated when the filtered oscillator crosses below the signal line while in the overbought zone, indicating a potential downward reversal from an overbought condition.
- **Visual Representation**: These signals are visually represented on the chart with specific symbols, such as green circles for buy signals and red circles for sell signals, making them easy to spot.
### **Usefulness and Applications**
1. **Trend Identification**:
- The indicator is highly effective in identifying the current trend and its strength. By analyzing the relationship between the oscillator and the signal line, traders can determine whether the market is in an uptrend, downtrend, or ranging. The adaptive nature of the filter ensures that the trend signals remain relevant even as market conditions change.
2. **Volatility Analysis**:
- Understanding market volatility is crucial for risk management and strategy development. This indicator provides a clear view of how volatility is evolving, helping traders adjust their strategies accordingly. For example, higher volatility might suggest the need for tighter stop losses or more conservative position sizes.
3. **Overbought/Oversold Detection**:
- The overbought and oversold zones are essential for identifying potential reversal points. These zones can be used to time entries and exits, particularly in markets that are prone to mean reversion. The visual cues provided by the indicator make it easier to spot when the market might be overstretched.
4. **Adaptive Filtering**:
- The adaptive filter is a significant advantage of this indicator. Unlike static filters, which might lag or react too quickly to noise, the adaptive filter adjusts to the market's pace. This makes the indicator versatile, suitable for different market conditions, and less prone to giving false signals.
5. **Visual Clarity**:
- The indicator is designed with visual clarity in mind. The color-coded bars and overbought/oversold zones make it easy to interpret the market's current state at a glance. This is particularly useful for traders who rely on quick decision-making or need to monitor multiple assets simultaneously.
6. **Customizability**:
- The indicator offers several user inputs that allow traders to customize it according to their trading style and market of interest. This includes the length of the volume period, the sensitivity of the adaptive filter, and the thresholds for overbought/oversold conditions. Such flexibility makes it a valuable tool for both short-term traders and long-term investors.
### **Conclusion**
The "Uptrick: Adaptive Volatility Oscillator" is a powerful and versatile indicator that blends volume analysis with adaptive filtering to provide a nuanced view of market trends and volatility. Its ability to identify overbought and oversold conditions, coupled with its adaptive nature, makes it an indispensable tool for traders looking to gain an edge in the markets. Whether you're aiming to spot trend reversals, confirm the strength of ongoing trends, or manage risk through volatility analysis, this indicator offers the insights needed to make informed trading decisions. Its clear visual signals and customizable parameters further enhance its utility, making it suitable for a wide range of trading strategies and market environments.
Hullinger Percentile Oscillator [AlgoAlpha]🚀 Introducing the Hullinger Percentile Oscillator by AlgoAlpha! 🚀
This versatile Pine Script™ indicator is designed to help you identify swing trends and potential reversals with precision. Whether you're looking to catch market swings or spot divergences, the Hullinger Percentile Oscillator offers a comprehensive suite of features to enhance your trading strategy.
Key Features
🎯 Customizable Hullinger Settings: Adjust the main length, source, and standard deviation multipliers to fine-tune the indicator to your preferred trading style.
🔄 Dynamic Oscillator Modes: Switch between "Swing" mode for trend identification and "Contrarian" mode for reversal spotting, adapting the indicator to your market view.
📉 Divergence Detection: The indicator includes parameters to control the sensitivity and confirmation of divergence signals, helping to filter out noise and highlight significant market moves.
🌈 Color-Coded Visuals: Easily distinguish between bullish and bearish signals with customizable color settings for a clear visual representation on your chart.
🔔 Alert Integration: Stay ahead of the market with built-in alerts for key conditions, including strong and weak reversals, as well as bullish and bearish swings.
Quick Guide to Using the Hullinger Percentile Oscillator
Maximize your trading edge with the Hullinger Percentile Oscillator by following these steps! 📈✨
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon ⭐. Customize settings like Main Length, Oscillator Mode, and Appearance to fit your trading needs.
📊 Market Analysis: Use "Swing" mode to track trends and "Contrarian" mode to spot reversals. Watch for divergence signals to catch potential trend changes.
🔔 Alerts: Set up alerts to be notified of significant market movements without constantly monitoring your chart.
How It Works
The Hullinger Percentile Oscillator calculates its signals by applying a modified standard deviation approach to the Hull Moving Average (HMA) of a selected price source. It creates both inner and outer bands based on different multipliers. The oscillator then measures the position of the price relative to these bands, smoothing the result for swing trend detection. Depending on the chosen mode, the oscillator either highlights swing trends or potential reversals. Divergences are detected by comparing recent pivot highs and lows in both price and the oscillator, allowing you to spot bullish or bearish divergence setups. Alerts are triggered based on key crossovers or when specific conditions are met, ensuring that you are always informed of crucial market developments.
Negroni Opening Range StrategyStrategy Summary:
This tool can be used to help identify breakouts from a range during a time-zone of your choosing. It plots a pre-market range, an opening range, it also includes moving average levels that can be used as confluence, as well as plotting previous day SESSION highs and lows.
There are several options on how you wish to close out the trades, all described in more detail below.
Back-testing Inputs:
You define your timezone.
You define how many trades to open on any given day.
You decide to go: long only, short only, or long & short (CAREFUL: "Long & Short" can open trades that effectively closes-out existing ones, for better AND worse!)
You define between which times the strategy will open trades.
You define when it closes any open trades (preventing overnight trades, or leaving trades open into US data times!!).
This hopefully helps make back-testing reflect YOUR trading hours.
NOTE: Renko or Heikin-Ashi charts
For ALL strategies, don’t use Renko or Heikin-Ashi charts unless you know EXACTLY the implications.
Specific to my strategy, using a renko chart can make this 85-90% profitable (I wish it was!!) Although they can be useful, renko charts don’t always capture real wicks, so the renko chart may show your trade up-only but your broker (who is not using renko!!) will have likely stopped you out on a wick somewhere along the line.
NOTE: TradingView ‘Deep backtesting’
For ALL strategies, be cynical of all backtesting (e.g. repainting issues etc) as well as ‘Deep backtesting’ results.
Specific to this strategy, the default settings here SHOULD BE OK, but unfortunately at the time of writing, we can’t see on the chart what exactly ‘deep backtesting’ is calculating. In the past I have noted a number of trades that were not closed at the end of the day, despite my ‘end of day’ trade closing being enabled, so there were big winners and losers that would not have materialized otherwise. As I say, this seems ok at these settings but just always be cynical!!
Opening Range Inputs
You define a pre-market range (example: 08:00 - 09:00).
You define an opening range (example: 09:00 - 09:30).
The strategy will give an update at the close of the opening range to let you know if the opening range has broken out the pre-market range (OR Breakout), or if it has remained inside (OR Inside). The label appears at the end of the opening range NOT at the bar that ‘broke-out’.
This is just a visual cue for you, it has no bearing on what the strategy will do.
The strategy default will trade off the pre-market range, but you can untick this if you prefer to trade off the opening range.
Opening Trades:
Strategy goes long when the bar (CLOSE) crosses-over the ‘pre-market’ high (not the ‘opening range’ high); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Strategy goes short when the bar (CLOSE) crosses-under the ‘pre-market’ low (not the ‘opening range low); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Remember, you can untick this if you prefer to trade off the opening range instead.
NOTES:
Using momentum indicators can help (RSI and MACD): especially to trade range plays in failed breakouts, when momentum shifts… but the strategy won’t do this for you!
Using an anchored vwap at the session open can also provide nice confluence, as well as take-profit levels at the upper/lower of 3x standard deviation.
CLOSING TRADES:
You have 6 take-profit (TP) options:
1) Full TP: uses ATR Multiplier - Full TP at the ATR parameters as defined in inputs.
2) Take Partial profits: ATR Multiplier - Takes partial profits based on parameters as defined in inputs (i.e close 40% of original trade at TP1, close another 40% of original trade at TP2, then the remainder at Full TP as set in option 1.).
3) Full TP: Trailing Stop - Applies a Trailing Stop at the number of points, as defined in inputs.
4) Full TP: MA cross - Takes profit when price crosses ‘Trend MA’ as defined in inputs.
5) Scalp: Points - closes at a set number of points, as defined in inputs.
6) Full TP: PMKT Multiplier - places a SL at opposite pre-market Hi/Low (we go long at a break-out of the pre-market high, 50% would place a SL at the pre-market range mid-point; 100% would place a SL at the pre-market low)'. This takes profit at the input set in option 1).
Low Volatility Range Breaks [BigBeluga]Low Volatility Range Breaks
The Low Volatility Range Breaks indicator is an advanced technical analysis tool designed to identify periods of low volatility and potential breakout opportunities. By visualizing low volatility ranges as ranges and tracking subsequent price movements, this indicator helps traders spot potential high-probability trade setups.
🔵 KEY FEATURES
● Low Volatility Detection
Identifies periods of low volatility based on highest and lowest periods and user-defined sensitivity
Uses a combination of highest/lowest price calculations and ATR for dynamic adaptation
● Volatility Box Visualization
Creates a box to represent the low volatility range
Box height is adjustable based on ATR multiplier
Includes a mid-line for reference within the box
● Breakout Detection
Identifies when price breaks above or below the volatility box
Labels breakouts as "Break Up" or "Break Dn" on the chart
Changes box appearance to indicate a completed breakout
● Probability Tracking
Counts the number of closes above and below the box's mid-line
Displays probability counters for potential upward and downward moves
Resets counters after a confirmed breakout
🔵 HOW TO USE
● Identifying Low Volatility Periods
Watch for the formation of volatility boxes on the chart
These boxes represent periods where price movement has been confined
● Anticipating Breakouts
Monitor price action as it approaches the edges of the volatility box
Use the probability counters to gauge the likely direction of the breakout
● Trading Breakouts
Consider posible entering trades when price breaks above or below the volatility box
Use the breakout labels ("Break Up" or "Break Dn") as a trading opportunity
● Managing Risk
Use the opposite side of the volatility box as a potential invalidation level
Consider the box height for position sizing and risk management
● Trend Analysis
Multiple upward breakouts may indicate a developing uptrend
Multiple downward breakouts may suggest a forming downtrend
Use in conjunction with other trend indicators for confirmation
🔵 CUSTOMIZATION
The Low Volatility Box Breaks indicator offers several customization options:
Adjust the volatility length to change the period for highest/lowest price calculations
Modify the volatility level to fine-tune the sensitivity of low volatility detection
Adjust the box height multiplier to change the size of volatility boxes
By fine-tuning these settings, traders can adapt the indicator to various market conditions and personal trading strategies.
The Low Volatility Range Breaks indicator provides a unique approach to identifying potential breakout opportunities following periods of consolidation. By visually representing low volatility periods and tracking subsequent price movements, it offers traders a powerful tool for spotting high-probability trade setups.
This indicator can be particularly useful for traders focusing on breakout strategies, mean reversion tactics, or those looking to enter trades at the beginning of new trends. The combination of visual cues (boxes and breakout labels) and quantitative data (probability counters) provides a comprehensive view of market dynamics during and after low volatility periods.
As with all technical indicators, it's recommended to use the Low Volatility Range Breaks indicator in conjunction with other forms of analysis and within the context of a well-defined trading strategy. While this indicator can provide valuable insights into potential breakouts, it should be considered alongside other factors such as overall market trends, volume, and fundamental analysis when making trading decisions.
TradeMate - Trend TamerTradeMate Trend Tamer
The TradeMate Trend Tamer is designed to help traders identify potential trend reversals and navigate periods of high market volatility. This tool combines a custom EMA-based oscillator with a volatility detection mechanism, providing traders with actionable signals that are easy to interpret and apply.
🔶 Originality and Utility
The TradeMate Trend Tamer is not just a mashup of indicators but a well-integrated system that enhances the reliability of trend detection. The core of this indicator is a custom EMA calculation that identifies trend shifts based on price momentum and directional changes. This EMA is further enhanced by a volatility detection system that colors bars yellow during periods of high volatility, indicating potential market reversals.
The indicator is particularly useful for traders who are looking for clear and straightforward signals to identify buying and selling opportunities, especially in volatile markets where traditional indicators might produce false signals. By combining trend arrows with volatility signals, the TradeMate Trend Tamer helps traders confirm the strength of a signal and avoid getting caught in market noise.
🔶 Description and Underlying Logic
The TradeMate Trend Tamer uses a custom EMA calculation that smooths price movements to detect significant shifts in momentum. This EMA is plotted on the chart and is complemented by arrows indicating potential buy or sell signals:
Upward Arrows: These appear when the EMA indicates an upward momentum shift, suggesting a potential buying opportunity.
Downward Arrows: These indicate a downward momentum shift, signaling a potential selling opportunity.
The volatility detection mechanism works by analyzing the ATR (Average True Range) over a specified lookback period. The indicator identifies extreme volatility zones where the ATR exceeds a certain threshold, coloring the bars yellow to visually alert traders. This helps traders identify when the market is more likely to reverse, making the combination of trend arrows and volatility signals a powerful tool for decision-making.
🔶 Using the TradeMate Trend Tamer
Traders should use the trend arrows as an initial signal and confirm it with the yellow-colored volatility bars. For example:
High Volatility with Upward Arrow: Indicates a strong buy signal as the market is likely to reverse upwards.
High Volatility with Downward Arrow: Indicates a strong sell signal, suggesting a potential downward reversal.
By following these signals, traders can enhance their entry and exit strategies, especially in markets prone to sudden moves.
9:20 5 Min Candle Levels with AlertsThe 9:20 AM 5-Minute Candle refers to the candlestick that represents the price action of a financial asset between 9:20 AM and 9:25 AM on a trading day. This candle is observed on a 5-minute chart and captures all the market activity during this specific time window.
Description:
Timeframe: 9:20 AM to 9:25 AM (5-minute interval).
Opening Price: The price at 9:20 AM when the 5-minute period begins.
Closing Price: The price at 9:25 AM when the 5-minute period ends.
High: The highest price achieved during these five minutes.
Low: The lowest price reached during these five minutes.
Body: The distance between the opening and closing prices. A longer body indicates stronger buying or selling pressure, while a shorter body reflects more market indecision.
Wick (Shadow): The lines extending above and below the body, representing the range between the high and low prices during this period. Long wicks suggest higher volatility, while shorter wicks indicate more stable price movements.
Significance:
Bullish Candle: If the closing price is higher than the opening price, it suggests positive momentum and buying interest within this 5-minute period.
Bearish Candle: If the closing price is lower than the opening price, it signals negative momentum and selling pressure.
Market Sentiment: The 9:20 AM 5-minute candle can provide insight into the early sentiment of the market, often influencing the trading strategy for the rest of the day.
Volatility Indicator: The length of the wicks can help traders assess the volatility and potential risk during these five minutes.
This candle is particularly important for day traders and scalpers who rely on short-term price movements to make trading decisions.
Vmoon By:VasmaVmoon Indicator by Vasma
Overview:
The Vmoon indicator is an advanced tool designed for trend following and momentum trading, uniquely combining the Average True Range (ATR) with a Double Exponential Moving Average (DEMA). Unlike standard indicators, Vmoon provides traders with a dual-layered approach to detect trend reversals and confirm momentum, making it a robust solution for identifying trading opportunities in various market conditions.
Key Features and Calculation Methodology:
Average True Range (ATR) Based Trend Detection:
ATR Period: The user can define the ATR period, with a default setting of 12 periods. This period is crucial for accurately measuring market volatility over the chosen timeframe.
ATR Multiplier: Set at a default of 3.0, the multiplier adjusts the ATR range to determine dynamic support and resistance levels, allowing the indicator to adapt to different market conditions.
Custom ATR Calculation Method: Traders can choose between a simple moving average of the true range or the built-in ATR method. This flexibility allows for personalized risk management and signal sensitivity.
Upper and Lower Bands: These bands are calculated by adding and subtracting the ATR value from the price (hl2 by default). The bands serve as dynamic thresholds—when price breaks above the upper band, it suggests an upward trend, and breaking below the lower band suggests a downward trend.
The Vmoon indicator doesn't just plot these bands; it dynamically adjusts them based on price action, providing a real-time, adaptive system for trend detection.
Innovative Trend Identification:
Real-Time Trend Tracking: The indicator monitors price movements relative to the ATR bands, continuously updating the trend direction. This allows for quick identification of trend changes, which is critical in volatile markets.
Trend Change Detection: Vmoon captures shifts from upward to downward trends (and vice versa) with precision, generating actionable buy or sell signals. This feature helps traders stay ahead of market reversals.
Double Exponential Moving Average (DEMA) Integration:
DEMA Calculation: The Vmoon indicator uses a 200-period DEMA, which is known for reducing lag and providing a faster reaction to price changes compared to traditional moving averages. This ensures that the indicator responds promptly to emerging trends.
Crossover-Based Momentum Confirmation: The indicator generates signals based on price crossovers with the 200-period DEMA:
Buy Signal: A green triangle appears when the price crosses above the DEMA, signaling potential bullish momentum.
Sell Signal: A red triangle is displayed when the price crosses below the DEMA, indicating possible bearish momentum.
The DEMA component of Vmoon offers a long-term perspective on market momentum, acting as a filter to confirm the strength and direction of the trend.
Customizable Alerts:
Vmoon includes fully customizable alert conditions, allowing traders to stay informed about critical market movements:
Buy Signal Alert: Notifies when the trend changes from downward to upward, indicating a potential buying opportunity.
Sell Signal Alert: Alerts when the trend shifts from upward to downward, signaling a possible selling point.
General Trend Change Alert: Keeps traders aware of any direction changes, helping them to react quickly to potential reversals.
How to Use Vmoon:
Dynamic Trend Following: Use the ATR-based upper and lower bands as dynamic support and resistance levels. Monitor for breakouts to identify trend reversals.
Momentum Confirmation with DEMA: Validate trend signals by watching for price crossovers with the 200-period DEMA, ensuring that the trend is supported by strong momentum.
Signal Interpretation: Act on the buy and sell signals displayed on the chart, supported by optional alerts, to make informed trading decisions in real time.
Enhanced Customization Options:
Adjustable ATR Settings: Modify the ATR period and multiplier to better align with your trading strategy and market conditions.
Selectable ATR Calculation Method: Choose the ATR method that best suits your risk tolerance and market analysis approach.
Configurable Signal Display: Tailor the indicator to show or hide buy/sell signals based on your preferences.
Personalized Alerts: Set alerts that match your specific trading needs, ensuring that you never miss a significant market move.
Visual Representation:
Vmoon provides a clear and concise visual representation on the chart, with distinct markers for buy and sell signals, dynamic ATR bands, and the 200-period DEMA. This visualization helps traders quickly interpret market conditions and make timely decisions.
Why Vmoon is Unique:
Vmoon stands out by integrating ATR-based dynamic thresholds with the reduced-lag DEMA, offering a comprehensive solution for trend identification and momentum confirmation. This combination is not commonly found in standard indicators, and the flexibility in customization ensures that Vmoon can be adapted to suit various trading strategies and market environments. The proprietary logic behind Vmoon’s signal generation, particularly in how it adjusts to market volatility, is what makes it both powerful and worthy of protection as a closed-source script.
Linear and Logarithmic Fibonacci Levels and FansIntroduction
The Fibonacci Retracement tool is a go-to for traders looking to spot potential support and resistance levels. By measuring the distance between swing highs and lows, you can apply Fibonacci ratios like 0.236, 0.382, and 0.618 to predict key market levels.
Traditionally, these levels are set by dividing this distance into equal parts—known as Linear Levels. A more refined approach, Logarithmic Levels, divides the distance into proportionally equal segments. Plus, this indicator now includes Fibonacci fans, adding another layer of analysis by projecting potential price levels using trendlines based on Fibonacci ratios.
This tool makes it easier to identify both Linear and Logarithmic levels while also leveraging Fibonacci fans for a more complete market view.
Applications
Logarithmic Levels and Fibonacci fans are ideal for volatile markets. In crypto, they’re especially effective for BTCUSDT (check out the wick from January 23, 2024). They also help spot accumulation and distribution patterns in high-volume altcoins like FETUSDT . In traditional markets, they’re useful for tracking stocks like TSLA and NVDA with extreme price swings, as well as indices in inflation-affected markets like XU100 , or recession-hit currency pairs like JPYUSD .
How to Use
This indicator is intuitive and similar to TradingView’s Fibonacci Tool. Select your reference levels (Level 1 and Level 0), then tweak the settings to customize your analysis, including adding Fibonacci fans for extra insights.
Why It’s Different
Unlike TradingView’s tool, which forces you to switch to a logarithmic scale (messing with other indicators and trend lines), this indicator lets you view both Linear and Logarithmic levels—and Fibonacci fans—without changing your chart’s scale. The original Fibonacci Code was derived from zekicanozkanli, modified and upgraded to plot fib fans as well.
Nautilus Oscillator [BigBeluga]NAUTILUS OSCILLATOR
The Nautilus Oscillator by BigBeluga is an advanced technical analysis tool designed to help traders identify trend direction, strength, and potential reversal points in the market. This versatile indicator combines multiple analytical elements to provide a comprehensive view of market conditions.
Why It’s Unique:
The Nautilus Oscillator is unique too, its blend of multiple technical analysis tools into a single, coherent indicator.
By smoothing with a unique and highly valued in signal processing filter, and incorporating dynamic thresholds, this oscillator offers a more refined and adaptable approach to identifying trading signals.
The filter is designed to have as flat a frequency response as possible in the passband. This means that within the range of frequencies it allows through, minimizes distortion and maintains the true shape of the signal more accurately than many other types of filters.
The addition of a trend filter and divergence detection further enhances its capability, making it a versatile tool for both trend-following and reversal strategies. The built-in dashboard and clean chart management features provide traders with a streamlined, informative, and visually appealing trading experience. This makes the Nautilus Oscillator not just a tool for analysis but a comprehensive trading system in itself.
🔵 KEY FEATURES
● Main Oscillator Line
Smoothly transitions between bullish (green) and bearish (purple) colors
Helps visualize mean-reversion, market trend, and momentum
● Histogram
Displayed below the main oscillator line
Represents the rate of change of the main oscillator
Acts as a leading indicator, often showing changes faster than the main oscillator line
Can be viewed as a predictive element, potentially indicating future movements of the main oscillator
Histogram crossover signals (small dots) can indicate short-term momentum shifts
Useful for early detection of potential trend changes or momentum shifts
● Confluence Arrows
Arrows displayed above and below the oscillator
Provide additional confluence signals that work in conjunction with the histogram
Act as supplementary indicators to confirm the main oscillator signals
Help in identifying stronger, more reliable trading opportunities when aligned with other indicator elements
● Trend Filter
Displayed as horizontal lines above and below the oscillator
Upper lines (above the oscillator): Indicate an uptrend
Lower lines (below the oscillator): Indicate a downtrend
Three lines appear when a strong trend is present
Only one line is displayed when there's no trend
Color-coded for easy identification (typically green for up, purple for down)
Color intensity indicates the strength of the trend. More intensive color indicates stronger trend
Provides a clear visual representation of the overall market trend
Helps traders align their strategies with the broader market direction
● Overbought/Oversold Thresholds
Can be set to static levels or dynamically adjust based on market volatility
Helps identify potential reversal points in the market
● Signals
Strong signals: Displayed as circles on both the oscillator and main chart (optional)
Simple signals: Shown as X marks on both the oscillator and main chart (optional)
Histogram crossover signals: Small dots on the histogram
● Stop Levels
Optional feature that plots potential stop-loss levels for strong signals
Based on the Market volatility for adaptability to different market conditions
● Divergences
Identifies and displays bullish and bearish divergences between price and the oscillator
Helps spot potential trend reversals
● Dashboard
Provides at-a-glance information about current market conditions
Displays trend direction, last signal, histogram direction, threshold mode, and divergence status
🔵 HOW TO USE
● Trend Identification
Use the main oscillator line color and position, along with the trend filter lines, to determine the overall market trend
● Entry Signals
Strong signals (circles) suggest potential entry points in the direction of the trend
Simple signals (X marks) can be used for more frequent, but potentially less reliable, entry opportunities
Histogram crossover signals (dots) can indicate changes faster than the main oscillator line
Look for alignment with confluence arrows for stronger entry signals
● Exit Signals
Use the overbought/oversold thresholds as potential enter and exit points
Stop levels (if enabled) provide dynamic exit points for risk management
● Reversal Identification
Watch for divergences between price and the oscillator for potential trend reversals
Pay attention to the histogram direction for early signs of momentum shifts
Notice changes in the trend filter lines (from three lines to one, or vice versa)
● Confirmation
Use the dashboard to quickly confirm the current market state and indicator readings
Combine signals from different elements (main line, histogram, trend filter, confluence arrows) for stronger confirmation
🔵 CUSTOMIZATION
The Nautilus Oscillator offers several customization options to suit different trading styles:
Adjust the main oscillator length
Set static or dynamic overbought/oversold thresholds
Enable/disable and customize stop levels
Toggle divergence display and adjust its parameters
Show/hide the information dashboard
Display simple signals on the main chart
By fine-tuning these settings, traders can adapt the Nautilus Oscillator to various market conditions and personal trading strategies.
The Nautilus Oscillator provides a multi-faceted approach to market analysis, combining trend identification, momentum assessment, and reversal detection in one comprehensive tool. Its visual cues and customizable features make it suitable for both novice and experienced traders across various timeframes and markets. The integration of multiple analytical elements – including the predictive histogram, confluence arrows, and adaptive trend filter – offers traders a rich set of data points to inform their trading decisions.
Balance of Power [Pinescriptlabs]Balance of Power Indicator ⚖️
The Balance of Power Indicator is a visual tool that illustrates the power dynamics between buyers and sellers by analyzing recent price action. Instead of providing direct buy or sell signals, this indicator shows how the tilt of a symbolic scale reflects the relative strength of both parties. The calculation is based on the difference between the current closing price and the closing price from a specific number of periods (defined by the user), adjusted for market volatility measured by the ATR (Average True Range).
Tilt Value Interpretation:
• Positive Tilt (0 to 1) 📈:
o A tilt value close to 1 indicates significant control by buyers. The current price is well above the average adjusted for recent volatility. Practically, a tilt in the range of 0.50 to 1 suggests buyers are pushing the price above the average volatility, signaling a strong bullish trend.
•
o
• Negative Tilt (-1 to 0) 📉:
o A tilt value close to -1 indicates significant control by sellers. The current price has dropped notably compared to the average adjusted for recent volatility. A tilt in the range of -0.50 to -1 suggests sellers are dominating, with the price falling below the average volatility, reflecting a strong bearish trend.
o
Neutral:
Indicator Sensitivity:
The number of periods analyzed affects the sensitivity of the indicator:
• Shorter Periods: Make the indicator respond more quickly to price changes.
• Longer Periods: Smooth out the tilt, providing a more stable view of market forces.
Visualizing Relative Power:
The balance not only shows the general direction of power between buyers and sellers but also the intensity of this pressure. By adding more small balances, the indicator visually represents greater strength in the corresponding direction. Thus, the Balance of Power provides an overview of the balance between supply and demand, and allows for a visual assessment of the magnitude of that pressure based on the scale’s tilt.
Español
Indicador de Balance de Poder ⚖️
El Indicador de Balance de Poder es una herramienta visual que ilustra la dinámica de poder entre compradores y vendedores mediante el análisis de la acción reciente del precio. En lugar de proporcionar señales directas de compra o venta, este indicador muestra cómo la inclinación de una balanza simbólica refleja la fuerza relativa de ambas partes. El cálculo se basa en la diferencia entre el precio de cierre actual y el precio de cierre de un número específico de períodos (definidos por el usuario), ajustado por la volatilidad del mercado medida por el ATR (Average True Range).
#### **Interpretación del Valor de Tilt(inclinación):**
- Tilt Positivo (0 a 1) 📈:
- Un valor de inclinación cercano a **1** indica un control significativo por parte de los compradores. El precio actual está muy por encima del promedio ajustado por la volatilidad reciente. En términos prácticos, un tilt en el rango de **0.50 a 1** sugiere que los compradores están impulsando el precio por encima de la volatilidad promedio, señalando una fuerte tendencia alcista.
- **Tilt Negativo (-1 a 0) 📉:**
- Un valor de inclinación cercano a **-1** indica un control significativo por parte de los vendedores. El precio actual ha caído notablemente en comparación con el promedio ajustado por la volatilidad reciente. Un tilt en el rango de **-0.50 a -1** sugiere que los vendedores están dominando, con el precio cayendo por debajo de la volatilidad promedio, reflejando una fuerte tendencia bajista.
- **Neutral:**
**Sensibilidad del Indicador:**
El número de períodos analizados afecta la sensibilidad del indicador:
- **Períodos más cortos:** Hacen que el indicador responda más rápidamente a los cambios en el precio.
- **Períodos más largos:** Suavizan la inclinación, proporcionando una visión más estable de las fuerzas del mercado.
#### **Visualización del Poder Relativo:**
La balanza no solo muestra la dirección general del poder entre compradores y vendedores, sino también la intensidad de esta presión. Al agregar más pequeñas balanzas, el indicador representa visualmente una mayor fuerza en la dirección correspondiente. Así, el **Balance de Poder** proporciona una visión general del equilibrio entre oferta y demanda y permite una evaluación visual de la magnitud de esa presión basada en la inclinación de la balanza.
Multi-Step FlexiSuperTrend - Strategy [presentTrading]At the heart of this endeavor is a passion for continuous improvement in the art of trading
█ Introduction and How it is Different
The "Multi-Step FlexiSuperTrend - Strategy " is an advanced trading strategy that integrates the well-known SuperTrend indicator with a nuanced and dynamic approach to market trend analysis. Unlike conventional SuperTrend strategies that rely on static thresholds and fixed parameters, this strategy introduces multi-step take profit mechanisms that allow traders to capitalize on varying market conditions in a more controlled and systematic manner.
What sets this strategy apart is its ability to dynamically adjust to market volatility through the use of an incremental factor applied to the SuperTrend calculation. This adjustment ensures that the strategy remains responsive to both minor and major market shifts, providing a more accurate signal for entries and exits. Additionally, the integration of multi-step take profit levels offers traders the flexibility to scale out of positions, locking in profits progressively as the market moves in their favor.
BTC 6hr Long/Short Performance
█ Strategy, How it Works: Detailed Explanation
The Multi-Step FlexiSuperTrend strategy operates on the foundation of the SuperTrend indicator, but with several enhancements that make it more adaptable to varying market conditions. The key components of this strategy include the SuperTrend Polyfactor Oscillator, a dynamic normalization process, and multi-step take profit levels.
🔶 SuperTrend Polyfactor Oscillator
The SuperTrend Polyfactor Oscillator is the heart of this strategy. It is calculated by applying a series of SuperTrend calculations with varying factors, starting from a defined "Starting Factor" and incrementing by a specified "Increment Factor." The indicator length and the chosen price source (e.g., HLC3, HL2) are inputs to the oscillator.
The SuperTrend formula typically calculates an upper and lower band based on the average true range (ATR) and a multiplier (the factor). These bands determine the trend direction. In the FlexiSuperTrend strategy, the oscillator is enhanced by iteratively applying the SuperTrend calculation across different factors. The iterative process allows the strategy to capture both minor and significant trend changes.
For each iteration (indexed by `i`), the following calculations are performed:
1. ATR Calculation: The Average True Range (ATR) is calculated over the specified `indicatorLength`:
ATR_i = ATR(indicatorLength)
2. Upper and Lower Bands Calculation: The upper and lower bands are calculated using the ATR and the current factor:
Upper Band_i = hl2 + (ATR_i * Factor_i)
Lower Band_i = hl2 - (ATR_i * Factor_i)
Here, `Factor_i` starts from `startingFactor` and is incremented by `incrementFactor` in each iteration.
3. Trend Determination: The trend is determined by comparing the indicator source with the upper and lower bands:
Trend_i = 1 (uptrend) if IndicatorSource > Upper Band_i
Trend_i = 0 (downtrend) if IndicatorSource < Lower Band_i
Otherwise, the trend remains unchanged from the previous value.
4. Output Calculation: The output of each iteration is determined based on the trend:
Output_i = Lower Band_i if Trend_i = 1
Output_i = Upper Band_i if Trend_i = 0
This process is repeated for each iteration (from 0 to 19), creating a series of outputs that reflect different levels of trend sensitivity.
Local
🔶 Normalization Process
To make the oscillator values comparable across different market conditions, the deviations between the indicator source and the SuperTrend outputs are normalized. The normalization method can be one of the following:
1. Max-Min Normalization: The deviations are normalized based on the range of the deviations:
Normalized Value_i = (Deviation_i - Min Deviation) / (Max Deviation - Min Deviation)
2. Absolute Sum Normalization: The deviations are normalized based on the sum of absolute deviations:
Normalized Value_i = Deviation_i / Sum of Absolute Deviations
This normalization ensures that the oscillator values are within a consistent range, facilitating more reliable trend analysis.
For more details:
🔶 Multi-Step Take Profit Mechanism
One of the unique features of this strategy is the multi-step take profit mechanism. This allows traders to lock in profits at multiple levels as the market moves in their favor. The strategy uses three take profit levels, each defined as a percentage increase (for long trades) or decrease (for short trades) from the entry price.
1. First Take Profit Level: Calculated as a percentage increase/decrease from the entry price:
TP_Level1 = Entry Price * (1 + tp_level1 / 100) for long trades
TP_Level1 = Entry Price * (1 - tp_level1 / 100) for short trades
The strategy exits a portion of the position (defined by `tp_percent1`) when this level is reached.
2. Second Take Profit Level: Similar to the first level, but with a higher percentage:
TP_Level2 = Entry Price * (1 + tp_level2 / 100) for long trades
TP_Level2 = Entry Price * (1 - tp_level2 / 100) for short trades
The strategy exits another portion of the position (`tp_percent2`) at this level.
3. Third Take Profit Level: The final take profit level:
TP_Level3 = Entry Price * (1 + tp_level3 / 100) for long trades
TP_Level3 = Entry Price * (1 - tp_level3 / 100) for short trades
The remaining portion of the position (`tp_percent3`) is exited at this level.
This multi-step approach provides a balance between securing profits and allowing the remaining position to benefit from continued favorable market movement.
█ Trade Direction
The strategy allows traders to specify the trade direction through the `tradeDirection` input. The options are:
1. Both: The strategy will take both long and short positions based on the entry signals.
2. Long: The strategy will only take long positions.
3. Short: The strategy will only take short positions.
This flexibility enables traders to tailor the strategy to their market outlook or current trend analysis.
█ Usage
To use the Multi-Step FlexiSuperTrend strategy, traders need to set the input parameters according to their trading style and market conditions. The strategy is designed for versatility, allowing for various market environments, including trending and ranging markets.
Traders can also adjust the multi-step take profit levels and percentages to match their risk management and profit-taking preferences. For example, in highly volatile markets, traders might set wider take profit levels with smaller percentages at each level to capture larger price movements.
The normalization method and the incremental factor can be fine-tuned to adjust the sensitivity of the SuperTrend Polyfactor Oscillator, making the strategy more responsive to minor market shifts or more focused on significant trends.
█ Default Settings
The default settings of the strategy are carefully chosen to provide a balanced approach between risk management and profit potential. Here is a breakdown of the default settings and their effects on performance:
1. Indicator Length (10): This parameter controls the lookback period for the ATR calculation. A shorter length makes the strategy more sensitive to recent price movements, potentially generating more signals. A longer length smooths out the ATR, reducing sensitivity but filtering out noise.
2. Starting Factor (0.618): This is the initial multiplier used in the SuperTrend calculation. A lower starting factor makes the SuperTrend bands closer to the price, generating more frequent trend changes. A higher starting factor places the bands further away, filtering out minor fluctuations.
3. Increment Factor (0.382): This parameter controls how much the factor increases with each iteration of the SuperTrend calculation. A smaller increment factor results in more gradual changes in sensitivity, while a larger increment factor creates a wider range of sensitivity across the iterations.
4. Normalization Method (None): The default is no normalization, meaning the raw deviations are used. Normalization methods like Max-Min or Absolute Sum can make the deviations more consistent across different market conditions, improving the reliability of the oscillator.
5. Take Profit Levels (2%, 8%, 18%): These levels define the thresholds for exiting portions of the position. Lower levels (e.g., 2%) capture smaller profits quickly, while higher levels (e.g., 18%) allow positions to run longer for more significant gains.
6. Take Profit Percentages (30%, 20%, 15%): These percentages determine how much of the position is exited at each take profit level. A higher percentage at the first level locks in more profit early, reducing exposure to market reversals. Lower percentages at higher levels allow for a portion of the position to benefit from extended trends.
