Power Root SuperTrend [AlgoAlpha]📈🚀 Power Root SuperTrend by AlgoAlpha - Elevate Your Trading Strategy! 🌟
Introducing the Power Root SuperTrend by AlgoAlpha, an advanced trading indicator that enhances the traditional SuperTrend by incorporating Root-Mean-Square (RMS) calculations for a more responsive and adaptive trend detection. This innovative tool is designed to help traders identify trend directions, potential take-profit levels, and optimize entry and exit points with greater accuracy, making it an excellent addition to your trading arsenal.
Key Features:
🔹 Root-Mean-Square SuperTrend Calculation : Utilizes the RMS of closing prices to create a smoother and more sensitive SuperTrend line that adapts quickly to market changes.
🔸 Multiple Take-Profit Levels : Automatically calculates and plots up to seven take-profit levels (TP1 to TP7) based on market volatility and the change in SuperTrend values.
🟢 Dynamic Trend Coloring : Visually distinguish between bullish and bearish trends with customizable colors for clearer market visualization.
📊 RSI-Based Take-Profit Signals : Incorporates the Relative Strength Index (RSI) of the distance between the price and the SuperTrend line to generate additional take-profit signals.
🔔 Customizable Alerts : Set alerts for trend direction changes, achievement of take-profit levels, and RSI-based take-profit conditions to stay informed without constant chart monitoring.
How to Use:
Add the Indicator : Add the indicator to favorites by pressing the ⭐ icon or search for "Power Root SuperTrend " in the TradingView indicators library and add it to your chart. Adjust parameters such as the ATR multiplier, ATR length, RMS length, and RSI take-profit length to suit your trading style and the specific asset you are analyzing.
Analyze the Chart : Observe the SuperTrend line and the plotted take-profit levels. The color changes indicate trend directions—green for bullish and red for bearish trends.
Set Alerts : Utilize the built-in alert conditions to receive notifications when the trend direction changes, when each TP level is drawn, or when RSI-based take-profit conditions are met.
How It Works:
The Power Root SuperTrend indicator enhances traditional SuperTrend calculations by applying a Root-Mean-Square (RMS) function to the closing prices, resulting in a more responsive trend line that better reflects recent price movements. It calculates the Average True Range (ATR) to determine the volatility and sets the upper and lower SuperTrend bands accordingly. When a trend direction change is detected—signified by the SuperTrend line switching from above to below the price or vice versa—the indicator calculates the change in the SuperTrend value. This change is then used to establish multiple take-profit levels (TP1 to TP7), each representing incremental targets based on market volatility. Additionally, the indicator computes the RSI of the distance between the current price and the SuperTrend line to generate extra take-profit signals when the RSI crosses under a specific threshold. The combination of RMS calculations, multiple TP levels, dynamic coloring, and RSI signals provides traders with a comprehensive tool for identifying trends and optimizing trade exits. Customizable alerts ensure that traders can stay updated on important market developments without needing to constantly watch the charts.
Elevate your trading strategy with the Power Root SuperTrend indicator and gain a smarter edge in the markets! 🚀✨
Indicators and strategies
Stoch RSI & RSI Buy/Sell Signals with MACD Trend FilterThis indicator combines multiple technical analysis tools and conditions to generate precise buy and sell signals. It utilizes the Stochastic RSI and RSI for overbought/oversold signals, a MACD trend filter, and candle color confirmation to avoid false signals. Key conditions include:
Buy Signal:
Conditions Met on Previous Candle:
Stochastic RSI (%K) is below the user-defined oversold level.
RSI is either below the neutral level or within the oversold range.
MACD line is in a bearish trend, confirmed by three consecutive downward bars.
Current Candle Requirement: Closes in green to confirm a buy.
Sell Signal:
Conditions Met on Previous Candle:
Stochastic RSI (%K) is above the user-defined overbought level.
RSI is either above the neutral level or within the overbought range.
MACD line is in a bullish trend, confirmed by three consecutive upward bars.
Current Candle Requirement: Closes in red to confirm a sell.
This indicator also includes custom color settings based on RSI levels and can be toggled to display buy/sell signals visually on the chart.
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IQ Zones [TradingIQ]Hey Traders!
Introducing "IQ Zones".
"IQ Zones" is an indicator that combines support and resistance identification with volume, the "value area" of a candlestick to be exact. IQ Zones identifies turning points in the market; however, the candlestick high or low that formed the key turning point is not necessarily distinguished as the support/resistance area. Instead, the script looks into the bar at lower timeframes and calculates the value area of the candlestick that formed the support or resistance level. Therefore, any lines protruding from a candlestick reflect the value area of that candlestick. These levels (value area high and value area low) are marked on the candlestick as a support/resistance level. If the level formed on high volume it's marked as an "IQ Zone".
Additionally, IQ Zones presents a heat map to show volume intensity at nearby price areas. The heatmap is a product of the Volume Profile (IQ Profile) located on the right of the chart.
The IQ Profile is a segmented volume profile. Recent price is split into fifths (customizable), and individual volume profiles are calculated for all segmented price areas. Price is split into more than one segment to avoid a situation where volume in a ranging price zone far surpasses all other recent price areas - creating an "unusable" volume profile that doesn't offer helpful insights. If desired, you can set the segmenting option to "1" to calculate one unified volume profile for the entire price range.
The image above shows IQ Zones in action!
Core Features of IQ Zones
Value Area Support and Resistance Levels
Segmented volume profile for the recent trading period
Volume intensity heatmap
Support and resistance levels in high volume intensity may be more significant as price stoppers
The image above explains the labels marked along the y-axis of the IQ Profile.
The "more green" a price area/label is, the higher the volume intensity at the marked support/resistance area.
The image above further explains line lines protruding from the IQ Profile.
For this example, the value area of the candlestick (where most trading action occurred) is quite far from the high price of the candlestick that formed a resistance level! Using the value area of a candlestick that marks a key turning point to draw support/resistance offers insight into where the majority of trading action took place when the support/resistance level was forming!
Additionally, you can hover your mouse over the IQ Zone labels (triangles pointing up or down) to see the prices of the value area for the support/resistance level, including the total buying volume and total selling volume at the price area!
The image above further explains the IQ Profile!
You can segment the recent price area anywhere from 1 - 15 times.
The image above further explains IQ Zones and the IQ Profile!
That will be all for this indicator - a fun project to share with the community.
Thank you!
Linear Regression Channel UltimateKey Features and Benefits
Logarithmic scale option for improved analysis of long-term trends and volatile markets
Activity-based profiling using either touch count or volume data
Customizable channel width and number of profile fills
Adjustable number of most active levels displayed
Highly configurable visual settings for optimal chart readability
Why Logarithmic Scale Matters
The logarithmic scale option is a game-changer for analyzing assets with exponential growth or high volatility. Unlike linear scales, log scales represent percentage changes consistently across the price range. This allows for:
Better visualization of long-term trends
More accurate comparison of price movements across different price levels
Improved analysis of volatile assets or markets experiencing rapid growth
How It Works
The indicator calculates a linear regression line based on the specified period
Upper and lower channel lines are drawn at a customizable distance from the regression line
The space between the channel lines is divided into a user-defined number of levels
For each level, the indicator tracks either:
- The number of times price touches the level (touch count method)
- The total volume traded when price is at the level (volume method)
The most active levels are highlighted based on this activity data
Understanding Touch Count vs Volume
Touch count method: Useful for identifying key support/resistance levels based on price action alone
Volume method: Provides insight into levels where the most trading activity occurs, potentially indicating stronger support/resistance
Practical Applications
Trend identification and strength assessment
Support and resistance level discovery
Entry and exit point optimization
Volume profile analysis for improved market structure understanding
This Linear Regression Channel indicator combines powerful statistical analysis with flexible visualization options, making it an invaluable tool for traders and analysts across various timeframes and markets. Its unique features, especially the logarithmic scale and activity profiling, provide deeper insights into market behavior and potential turning points.
PDF Smoothed Moving Average [BackQuant]PDF Smoothed Moving Average
Introducing BackQuant’s PDF Smoothed Moving Average (PDF-MA) — an innovative trading indicator that applies Probability Density Function (PDF) weighting to moving averages, creating a unique, trend-following tool that offers adaptive smoothing to price movements. This advanced indicator gives traders an edge by blending PDF-weighted values with conventional moving averages, helping to capture trend shifts with enhanced clarity.
Core Concept: Probability Density Function (PDF) Smoothing
The Probability Density Function (PDF) provides a mathematical approach to applying adaptive weighting to data points based on a specified variance and mean. In the PDF-MA indicator, the PDF function is used to weight price data, adding a layer of probabilistic smoothing that enhances the detection of trend strength while reducing noise.
The PDF weights are controlled by two key parameters:
Variance: Determines the spread of the weights, where higher values spread out the weighting effect, providing broader smoothing.
Mean : Centers the weights around a particular price value, influencing the trend’s directionality and sensitivity.
These PDF weights are applied to each price point over the chosen period, creating an adaptive and smooth moving average that more closely reflects the underlying price trend.
Blending PDF with Standard Moving Averages
To further improve the PDF-MA, this indicator combines the PDF-weighted average with a traditional moving average, selected by the user as either an Exponential Moving Average (EMA) or Simple Moving Average (SMA). This blended approach leverages the strengths of each method: the responsiveness of PDF smoothing and the robustness of conventional moving averages.
Smoothing Method: Traders can choose between EMA and SMA for the additional moving average layer. The EMA is more responsive to recent prices, while the SMA provides a consistent average across the selected period.
Smoothing Period: Controls the length of the lookback period, affecting how sensitive the average is to price changes.
The result is a PDF-MA that provides a reliable trend line, reflecting both the PDF weighting and traditional moving average values, ideal for use in trend-following and momentum-based strategies.
Trend Detection and Candle Coloring
The PDF-MA includes a built-in trend detection feature that dynamically colors candles based on the direction of the smoothed moving average:
Uptrend: When the PDF-MA value is increasing, the trend is considered bullish, and candles are colored green, indicating potential buying conditions.
Downtrend: When the PDF-MA value is decreasing, the trend is considered bearish, and candles are colored red, signaling potential selling or shorting conditions.
These color-coded candles provide a quick visual reference for the trend direction, helping traders make real-time decisions based on the current market trend.
Customization and Visualization Options
This indicator offers a range of customization options, allowing traders to tailor it to their specific preferences and trading environment:
Price Source : Choose the price data for calculation, with options like close, open, high, low, or HLC3.
Variance and Mean : Fine-tune the PDF weighting parameters to control the indicator’s sensitivity and responsiveness to price data.
Smoothing Method : Select either EMA or SMA to customize the conventional moving average layer used in conjunction with the PDF.
Smoothing Period : Set the lookback period for the moving average, with a longer period providing more stability and a shorter period offering greater sensitivity.
Candle Coloring : Enable or disable candle coloring based on trend direction, providing additional clarity in identifying bullish and bearish phases.
Trading Applications
The PDF Smoothed Moving Average can be applied across various trading strategies and timeframes:
Trend Following : By smoothing price data with PDF weighting, this indicator helps traders identify long-term trends while filtering out short-term noise.
Reversal Trading : The PDF-MA’s trend coloring feature can help pinpoint potential reversal points by showing shifts in the trend direction, allowing traders to enter or exit positions at optimal moments.
Swing Trading : The PDF-MA provides a clear trend line that swing traders can use to capture intermediate price moves, following the trend direction until it shifts.
Final Thoughts
The PDF Smoothed Moving Average is a highly adaptable indicator that combines probabilistic smoothing with traditional moving averages, providing a nuanced view of market trends. By integrating PDF-based weighting with the flexibility of EMA or SMA smoothing, this indicator offers traders an advanced tool for trend analysis that adapts to changing market conditions with reduced lag and increased accuracy.
Whether you’re trading trends, reversals, or swings, the PDF-MA offers valuable insights into the direction and strength of price movements, making it a versatile addition to any trading strategy.
Advanced Klinger OscillatorAdvanced Klinger Oscillator
The Advanced Klinger Oscillator is an enhanced version of the traditional Klinger Oscillator, which measures the difference between two exponential moving averages (EMAs) of volume flow. This tool helps traders identify momentum shifts and potential trading opportunities.
Key Features:
Dual EMA Calculation: The oscillator calculates the difference between a short-term and a long-term EMA of volume flow, smoothing out price fluctuations for clearer trend analysis.
Signal Line: A signal line, which is an EMA of the Klinger Oscillator, generates buy and sell signals. A crossover above the signal line indicates a potential buy, while a crossover below suggests a sell.
Volume Confirmation: Signals are only generated when trading volume exceeds a specified threshold, ensuring that price movements are supported by sufficient market activity.
Trend Lines: Upper and lower trend lines are plotted above the oscillator, helping traders visualize momentum strength and identify bullish or bearish trends.
Background Color Coding: The indicator uses color changes in the background to indicate positive (green) and negative (red) momentum, allowing for quick assessment of market conditions.
Usage:
Traders can utilize the Advanced Klinger Oscillator to:
Identify entry and exit points based on oscillator and signal line crossovers.
Confirm trends by observing the relationship between the oscillator and its trend lines.
Make informed trading decisions by considering volume alongside price movements.
The Advanced Klinger Oscillator is a valuable addition to any trader's toolkit, combining price momentum, volume analysis, and visual cues for effective trading strategies.
Equilibrium Candles + Pattern [Honestcowboy]The Equilibrium Candles is a very simple trend continuation or reversal strategy depending on your settings.
How an Equilibrium Candle is created:
We calculate the equilibrium by measuring the mid point between highest and lowest point over X amount of bars back.
This now is the opening price for each bar and will be considered a green bar if price closes above equilibrium.
Bars get shaded by checking if regular candle close is higher than open etc. So you still see what the normal candles are doing.
Why are they useful?
The equilibrium is calculated the same as Baseline in Ichimoku Cloud. Which provides a point where price is very likely to retrace to. This script visualises the distance between close and equilibrium using candles. To provide a clear visual of how price relates to this equilibrium point.
This also makes it more straightforward to develop strategies based on this simple concept and makes the trader purely focus on this relationship and not think of any Ichimoku Cloud theories.
Script uses a very simple pattern to enter trades:
It will count how many candles have been one directional (above or below equilibrium)
Based on user input after X candles (7 by default) script shows we are in a trend (bg colors)
On the first pullback (candle closes on other side of equilibrium) it will look to enter a trade.
Places a stop order at the high of the candle if bullish trend or reverse if bearish trend.
If based on user input after X opposite candles (2 by default) order is not filled will cancel it and look for a new trend.
Use Reverse Logic:
There is a use reverse logic in the settings which on default is turned on. It will turn long orders into short orders making the stop orders become limit orders. It will use the normal long SL as target for the short. And TP as stop for the short. This to provide a means to reverse equity curve in case your pair is mean reverting by nature instead of trending.
ATR Calculation:
Averaged ATR, which is using ta.percentile_nearest_rank of 60% of a normal ATR (14 period) over the last 200 bars. This in simple words finds a value slightly above the mean ATR value over that period.
Big Candle Exit Logic:
Using Averaged ATR the script will check if a candle closes X times that ATR from the equilibrium point. This is then considered an overextension and all trades are closed.
This is also based on user input.
Simple trade management logic:
Checks if the user has selected to use TP and SL, or/and big candle exit.
Places a TP and SL based on averaged ATR at a multiplier based on user Input.
Closes trade if there is a Big Candle Exit or an opposite direction signal from indicator.
Script can be fully automated to MT5
There are risk settings in % and symbol settings provided at the bottom of the indicator. The script will send alert to MT5 broker trying to mimic the execution that happens on tradingview. There are always delays when using a bridge to MT5 broker and there could be errors so be mindful of that. This script sends alerts in format so they can be read by tradingview.to which is a bridge between the platforms.
Use the all alert function calls feature when setting up alerts and make sure you provide the right webhook if you want to use this approach.
There is also a simple buy and sell alert feature if you don't want to fully automate but still get alerts. These are available in the dropdown when creating an alert.
Almost every setting in this indicator has a tooltip added to it. So if any setting is not clear hover over the (?) icon on the right of the setting.
The backtest uses a 4% exposure per trade and a 10 point slippage. I did not include a commission cause I'm not personaly aware what the commissions are on most forex brokers. I'm only aware of minimal slippage to use in a backtest. Trading conditions vary per broker you use so always pay close attention to trading costs on your own broker. Use a full automation at your own risk and discretion and do proper backtesting.
ol1ls scalp proHello, I’m Omar.
In the world of trading, it is essential to simplify the buying and selling process to reduce complexities and increase opportunities for profit. Therefore, I have developed an effective strategy based on analyzing price movements using price channels.
Strategy Conditions: This strategy operates when the price touches one of the channel’s edges, as this touch indicates a strong trading opportunity. When the price touches the upper boundary of the channel, it signals a selling opportunity, while a touch at the lower boundary indicates a buying opportunity.
By using this approach, traders can make more confident decisions, making it easier for them to achieve profits.
العربية:
مرحبًا، أنا عمر.
في عالم التداول، من الضروري تبسيط عملية البيع والشراء لتقليل التعقيدات وزيادة الفرص لتحقيق الأرباح. لذلك، قمت بتطوير استراتيجية فعّالة تعتمد على تحليل حركة السعر باستخدام قنوات الأسعار.
شروط الاستراتيجية: تعمل هذه الاستراتيجية عندما يلمس السعر أحد طرفي القناة، حيث تشير هذه اللمسة إلى فرصة قوية للتداول. عندما يلامس السعر الحد العلوي للقناة، يكون ذلك إشارة للبيع، بينما يشير اللمس عند الحد السفلي إلى فرصة للشراء.
باستخدام هذه الطريقة، يمكن للمتداولين اتخاذ قرارات أكثر ثقة، مما يسهل عليهم تحقيق الأرباح.
TechniTrend: Volume and Momentum Analysis (Weighted)Description:
The TechniTrend: Volume and Momentum Analysis indicator combines volume analysis with multiple momentum indicators to provide a holistic view of market conditions. By integrating Weighted Relative Strength Index (RSI), Rate of Change (ROC), and Stochastic Oscillator (%K and %D), this indicator offers a comprehensive, blended signal that responds to both price momentum and volume trends. Ideal for identifying potential reversal zones, overbought/oversold conditions, and divergence patterns.
Features:
Volume and Momentum Analysis:
The core of this indicator is a "Combined Analysis Line" that integrates various momentum indicators, each weighted according to user-defined preferences. This line allows for dynamic responsiveness based on selected weightings for RSI, ROC, and Stochastic, making it highly customizable.
High Volume Area Highlight:
Periods of high trading volume (above the threshold defined by Volume Threshold Factor) are highlighted on the chart's background. This feature aids in identifying volume-driven price actions, especially when combined with overbought/oversold signals from the Combined Analysis Line.
Divergence Detection System:
Regular bullish and bearish divergence patterns are automatically detected and marked on the chart. The indicator uses a pivot-based approach with user-adjustable lookback periods to identify divergence patterns, helping traders spot potential reversal points.
Overbought/Oversold Zones:
The indicator displays overbought and oversold zones with gradient fills based on user-defined thresholds, enhancing visibility and helping to gauge market momentum.
Alert System:
Built-in alerts notify the trader when a regular bullish or bearish divergence is detected. This feature is especially useful for monitoring the market passively and receiving timely alerts for potential trend changes.
Settings:
Volume MA Length: Defines the length of the moving average used to smooth out volume data.
Momentum Length: Length for calculating the momentum indicators (e.g., RSI).
Volume Threshold Factor: Multiplier for determining high-volume levels, setting the bar for significant volume.
Weight Parameters: Assign weight percentages to each momentum indicator for precise calibration of the Combined Analysis Line.
Overbought/Oversold Thresholds: Adjusts the levels at which overbought and oversold conditions are displayed, providing custom sensitivity to market extremes.
Divergence Settings: Adjustable lookback periods for detecting divergence patterns, along with upper and lower ranges, which fine-tune the search for divergence points.
This indicator is highly configurable and offers a nuanced view of market conditions by combining volume and momentum signals. Designed to assist in identifying potential entry and exit points, the TechniTrend: Volume and Momentum Analysis is a powerful tool for both short-term and long-term traders.
SuperATR 7-Step Profit - Strategy [presentTrading] Long time no see!
█ Introduction and How It Is Different
The SuperATR 7-Step Profit Strategy is a multi-layered trading approach that integrates adaptive Average True Range (ATR) calculations with momentum-based trend detection. What sets this strategy apart is its sophisticated 7-step take-profit mechanism, which combines four ATR-based exit levels and three fixed percentage levels. This hybrid approach allows traders to dynamically adjust to market volatility while systematically capturing profits in both long and short market positions.
Traditional trading strategies often rely on static indicators or single-layered exit strategies, which may not adapt well to changing market conditions. The SuperATR 7-Step Profit Strategy addresses this limitation by:
- Using Adaptive ATR: Enhances the standard ATR by making it responsive to current market momentum.
- Incorporating Momentum-Based Trend Detection: Identifies stronger trends with higher probability of continuation.
- Employing a Multi-Step Take-Profit System: Allows for gradual profit-taking at predetermined levels, optimizing returns while minimizing risk.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy revolves around detecting strong market trends and capitalizing on them using an adaptive ATR and momentum indicators. Below is a detailed breakdown of each component of the strategy.
🔶 1. True Range Calculation with Enhanced Volatility Detection
The True Range (TR) measures market volatility by considering the most significant price movements. The enhanced TR is calculated as:
TR = Max
Where:
High and Low are the current bar's high and low prices.
Previous Close is the closing price of the previous bar.
Abs denotes the absolute value.
Max selects the maximum value among the three calculations.
🔶 2. Momentum Factor Calculation
To make the ATR adaptive, the strategy incorporates a Momentum Factor (MF), which adjusts the ATR based on recent price movements.
Momentum = Close - Close
Stdev_Close = Standard Deviation of Close over n periods
Normalized_Momentum = Momentum / Stdev_Close (if Stdev_Close ≠ 0)
Momentum_Factor = Abs(Normalized_Momentum)
Where:
Close is the current closing price.
n is the momentum_period, a user-defined input (default is 7).
Standard Deviation measures the dispersion of closing prices over n periods.
Abs ensures the momentum factor is always positive.
🔶 3. Adaptive ATR Calculation
The Adaptive ATR (AATR) adjusts the traditional ATR based on the Momentum Factor, making it more responsive during volatile periods and smoother during consolidation.
Short_ATR = SMA(True Range, short_period)
Long_ATR = SMA(True Range, long_period)
Adaptive_ATR = /
Where:
SMA is the Simple Moving Average.
short_period and long_period are user-defined inputs (defaults are 3 and 7, respectively).
🔶 4. Trend Strength Calculation
The strategy quantifies the strength of the trend to filter out weak signals.
Price_Change = Close - Close
ATR_Multiple = Price_Change / Adaptive_ATR (if Adaptive_ATR ≠ 0)
Trend_Strength = SMA(ATR_Multiple, n)
🔶 5. Trend Signal Determination
If (Short_MA > Long_MA) AND (Trend_Strength > Trend_Strength_Threshold):
Trend_Signal = 1 (Strong Uptrend)
Elif (Short_MA < Long_MA) AND (Trend_Strength < -Trend_Strength_Threshold):
Trend_Signal = -1 (Strong Downtrend)
Else:
Trend_Signal = 0 (No Clear Trend)
🔶 6. Trend Confirmation with Price Action
Adaptive_ATR_SMA = SMA(Adaptive_ATR, atr_sma_period)
If (Trend_Signal == 1) AND (Close > Short_MA) AND (Adaptive_ATR > Adaptive_ATR_SMA):
Trend_Confirmed = True
Elif (Trend_Signal == -1) AND (Close < Short_MA) AND (Adaptive_ATR > Adaptive_ATR_SMA):
Trend_Confirmed = True
Else:
Trend_Confirmed = False
Local Performance
🔶 7. Multi-Step Take-Profit Mechanism
The strategy employs a 7-step take-profit system
█ Trade Direction
The SuperATR 7-Step Profit Strategy is designed to work in both long and short market conditions. By identifying strong uptrends and downtrends, it allows traders to capitalize on price movements in either direction.
Long Trades: Initiated when the market shows strong upward momentum and the trend is confirmed.
Short Trades: Initiated when the market exhibits strong downward momentum and the trend is confirmed.
█ Usage
To implement the SuperATR 7-Step Profit Strategy:
1. Configure the Strategy Parameters:
- Adjust the short_period, long_period, and momentum_period to match the desired sensitivity.
- Set the trend_strength_threshold to control how strong a trend must be before acting.
2. Set Up the Multi-Step Take-Profit Levels:
- Define ATR multipliers and fixed percentage levels according to risk tolerance and profit goals.
- Specify the percentage of the position to close at each level.
3. Apply the Strategy to a Chart:
- Use the strategy on instruments and timeframes where it has been tested and optimized.
- Monitor the positions and adjust parameters as needed based on performance.
4. Backtest and Optimize:
- Utilize TradingView's backtesting features to evaluate historical performance.
- Adjust the default settings to optimize for different market conditions.
█ Default Settings
Understanding default settings is crucial for optimal performance.
Short Period (3): Affects the responsiveness of the short-term MA.
Effect: Lower values increase sensitivity but may produce more false signals.
Long Period (7): Determines the trend baseline.
Effect: Higher values reduce noise but may delay signals.
Momentum Period (7): Influences adaptive ATR and trend strength.
Effect: Shorter periods react quicker to price changes.
Trend Strength Threshold (0.5): Filters out weaker trends.
Effect: Higher thresholds yield fewer but stronger signals.
ATR Multipliers: Set distances for ATR-based exits.
Effect: Larger multipliers aim for bigger moves but may reduce hit rate.
Fixed TP Levels (%): Control profit-taking on smaller moves.
Effect: Adjusting these levels affects how quickly profits are realized.
Exit Percentages: Determine how much of the position is closed at each TP level.
Effect: Higher percentages reduce exposure faster, affecting risk and reward.
Adjusting these variables allows you to tailor the strategy to different market conditions and personal risk preferences.
By integrating adaptive indicators and a multi-tiered exit strategy, the SuperATR 7-Step Profit Strategy offers a versatile tool for traders seeking to navigate varying market conditions effectively. Understanding and adjusting the key parameters enables traders to harness the full potential of this strategy.
Demand and Supply with Price actionThis indicator is made by "Dawn Forex Academy". I have added price action, demand and supply with FVG. This indicator may help us to identify the potential buy and sell zone after its breakout.
TCM OverboughtRelative Strength Index (RSI) + Stochastic Oscillator: combined
RSI-70+
Stochastic Oscillator-80+
Produces flag
Open Interest - Nifty, BankNifty, SensexDescription: The Open Interest - Multi-Index Analysis indicator provides a powerful tool for traders seeking to gain deeper insights into market sentiment by analyzing Open Interest (OI) across multiple indices simultaneously. This script combines the OI data from Nifty, Bank Index, and Sensex, allowing users to monitor shifts in volume and open interest, which are essential indicators of market activity, accumulation, and distribution phases. The script is designed with flexibility in mind, enabling traders to fine-tune the display to meet their specific analytical needs.
Key Features and Customizations
Versatile Display Options :
Open Interest : View OI data in a traditional format to track absolute levels of open interest.
Open Interest Delta : Displays the change in OI from one bar to the next, helping to identify increases or decreases in market participation.
OI Delta x Relative Volume : Provides a hybrid metric by multiplying the OI delta with relative volume, useful for spotting significant OI shifts that coincide with volume spikes.
Open Interest RSI : Visualize OI using a Relative Strength Index (RSI) to track the strength or weakness of open interest trends, which may signal overbought or oversold conditions.
Customizable Data Sources :
Enable or disable OI data from Nifty, Bank Index, and Sensex independently to create an aggregate view or focus on specific indices.
This flexibility allows traders to focus on the markets most relevant to their trading strategies.
Threshold-Based Highlights for Large OI Changes :
Threshold Multiplier : Define a multiplier to adjust the sensitivity for identifying large OI increases or decreases.
Visual Highlights : Choose fluorescent colors (green for increases and red for decreases) to quickly spot substantial changes in OI that may indicate strong buying or selling pressure.
Threshold Lines : Optionally display threshold lines on the chart to set visual benchmarks for significant OI changes, helping to filter out noise and focus on meaningful movements.
Additional Technical Analysis Tools :
Exponential Moving Average (EMA) : Plot an EMA line for the adjusted OI values, allowing traders to track trends and potential reversals. The EMA length and color are customizable to fit individual preferences.
Open Interest RSI : Optionally plot an RSI based on the OI values, with customizable period length and color, offering a view of the relative strength of OI. Horizontal lines at 30, 50, and 70 levels provide benchmarks for oversold, neutral, and overbought conditions.
OHLC Values for Multi-Index Open Interest :
Combines OHLC values from selected indices (Nifty, BankNifty, Sensex) to create an aggregated OI candle view, which can be adjusted based on quote currency (INR or Index).
This unique aggregation allows a multi-dimensional look at OI trends, helping traders to interpret the collective behavior of these key indices.
Dynamic Color Coding :
The indicator uses conditional coloring based on large OI changes and open-close price dynamics to make trends easily recognizable.
Up-trend and down-trend colors are customizable, so traders can visually distinguish between positive and negative movements quickly.
How to Use
Monitor Market Sentiment : By observing the changes in Open Interest across multiple indices, traders can gain insights into market sentiment and identify potential breakout or breakdown scenarios.
Spot Potential Reversals : The inclusion of EMA and RSI lines helps identify trend reversals and overbought/oversold conditions, providing an additional layer for decision-making.
Identify High-Volume Movements : The OI Delta x Relative Volume option is particularly useful for spotting large moves that are backed by volume, which may indicate the beginning of a new trend or an imminent reversal.
This indicator is ideal for advanced traders and analysts looking to enhance their market analysis by combining Open Interest data with technical indicators and customizable display options. Tailor the settings to align with your trading strategy, and use the highlighted OI thresholds to focus on critical market shifts. Whether you’re monitoring the general market trend or looking for high-probability entries and exits, this multi-index OI indicator provides a robust tool for making informed trading decisions.
Quick scan for cycles🙏🏻
The followup for
As I told before, ML based algorading is all about detecting any kind of non-randomness & exploiting it (cuz allegedly u cant trade randomness), and cycles are legit patterns that can be leveraged
But bro would u really apply Fourier / Wavelets / 'whatever else heavy' on every update of thousands of datasets, esp in real time on HFT / nearly HFT data? That's why this metric. It works much faster & eats hell of a less electicity, will do initial rough filtering of time series that might contain any kind of cyclic behaviour. And then, only on these filtered datasets u gonna put Periodograms / Autocorrelograms and see what's going there for real. Better to do it 10x times less a day on 10x less datasets, right?
I ended up with 2 methods / formulas, I called em 'type 0' and 'type 1':
- type 0: takes sum of abs deviations from drift line, scales it by max abs deviation from the same drift line;
- type 1: takes sum of abs deviations from drift line, scales it by range of non-abs deviations from the same drift line.
Finnaly I've chosen type 0 , both logically (sum of abs dev divided by max abs dev makes more sense) and experimentally. About that actually, here are both formulas put on sine waves with uniform noise:
^^ generated sine wave with uniform noise
^^ both formulas on that wave
^^ both formulas on real data
As you can see type 0 is less affected by noise and shows higher values on synthetic data, but I decided to put type 1 inside as well, in case my analysis was not complete and on real data type 1 can actually be better since it has a lil higher info gain / info content (still not sure). But I can assure u that out of all other ways I've designed & tested for quite a time I tell you, these 2 are really the only ones who got there.
Now about dem thresholds and how to use it.
Both type 0 and type 1 can be modelled with Beta distribution, and based on it and on some obvious & tho non mainstream statistical modelling techniques, I got these thresholds, so these are not optimized overfitted values, but natural ones. Each type has 3 thresholds (from lowest to highest):
- typical value (turned off by default). aka basis ;
- typical deviation from typical value, aka deviation ;
- maximum modelled deviation from typical value (idk whow to call it properly for now, this is my own R&D), aka extension .
So when the metric is above one of these thresholds (which one is up to you, you'll read about it in a sec), it means that there might be a strong enough periodic signal inside the data, and the data got to be put through proper spectral analysis tools to confirm / deny it.
If you look at the pictures above again, you'll see gray signal, that's uniform noise. Take a look at it and see where does it sit comparing to the thresholds. Now you just undertand that picking up a threshold is all about the amount of false positives you care to withstand.
If you take basis as threshold, you'll get tons of false positives (that's why it's even turned off by default), but you'll almost never miss a true positive. If you take deviation as threshold, it's gonna be kinda balanced approach. If you take extension as threshold, you gonna miss some cycles, and gonna get only the strongest ones.
More true positives -> more false positives, less false positives -> less true positives, can't go around that mane
Just to be clear again, I am not completely sure yet, but I def lean towards type 0 as metric, and deviation as threshold.
Live Long and Prosper
P.S.: That was actually the main R&D of the last month, that script I've released earlier came out as derivative.
P.S.: These 2 are the first R&Ds made completely in " art-space", St. Petersburg. Come and see me, say wassup🤘🏻
Buy/Sell Signals: 1-minute Low Crosses Above/Below 5-Bar MA 2LCKSome creativity done while bored. Message me if you like this :) IG zekecollects
Pine Execution MapPine Script Execution Map
Overview:
This is an educational script for Pine Script developers. The script includes data structure, functions/methods, and process to capture and print Pine Script execution map of functions called while pine script execution.
Map of execution is produced for last/latest candle execution.
The script also has example code to call execution map methods and generate Pine Execution map.
Use cases:
Pine script developers can get view of how the functions are called
This can also be used while debugging the code and know which functions are called vs what developer expect code to do
One can use this while using any of the open source published script and understand how public script is organized and how functions of the script are called.
Code components:
User defined type
type EMAP
string group
string sub_group
int level
array emap = array.new()
method called internally by other methods to generate level of function being executed
method id(string tag) =>
if(str.startswith(tag, "MAIN"))
exe_level.set(0, 0)
else if(str.startswith(tag, "END"))
exe_level.set(0, exe_level.get(0) - 1)
else
exe_level.set(0, exe_level.get(0) + 1)
exe_level.get(0)
Method called from main/global scope to record execution of main scope code. There should be only one call to this method at the start of global scope.
method main(string tag) =>
this = EMAP.new()
this.group := "MAIN"
this.sub_group := tag
this.level := "MAIN".id()
emap.push(this)
Method called from main/global scope to record end of execution of main scope code. There should be only one call to this method at the end of global scope.
method end_main(string tag) =>
this = EMAP.new()
this.group := "END_MAIN"
this.sub_group := tag
this.level := 0
emap.push(this)
Method called from start of each function to record execution of function code
method call(string tag) =>
this = EMAP.new()
this.group := "SUB"
this.sub_group := tag
this.level := "SUB".id()
emap.push(this)
Method called from end of each function to record end of execution of function code
method end_call(string tag) =>
this = EMAP.new()
this.group := "END_SUB"
this.sub_group := tag
this.level := "END_SUB".id()
emap.push(this)
Pine code which generates execution map and show it as a label tooltip.
if(barstate.islast)
for rec in emap
if(not str.startswith(rec.group, "END"))
lvl_tab = str.repeat("", rec.level+1, "\t")
txt = str.format("=> {0} {1}> {2}", lvl_tab, rec.level, rec.sub_group)
debug.log(txt)
debug.lastr()
Snapshot 1:
This is the output of the script and can be viewed by hovering mouse pointer over the blue color diamond shaped label
Snapshot 2:
How to read the Pine execution map
O Piá Das Criptos - Super RSI BASED!Estrutura Geral do Código:
O código é um indicador de análise técnica que combina o Índice de Força Relativa (RSI) e a Média Móvel Exponencial (EMA) do RSI do Bitcoin (BTC). O objetivo é ajudar os traders a identificar condições de sobrecompra e sobrevenda, assim como a força relativa do ativo em comparação ao Bitcoin.
Youtube: O Piá das Criptos!
Definições Iniciais:
- RSI, EMA e SMMA: O código permite que o usuário defina os períodos para o RSI (padrão de 14), EMA do RSI e SMMA (Média Móvel Suavizada) do RSI. Os valores padrão são 14 para o RSI e 9 para a EMA do RSI do BTC.
Cálculo do RSI:
- RSI do Ativo Atual: Calcula o RSI do ativo que está sendo analisado com base no fechamento das velas.
- RSI do Bitcoin: Usa a função request.security para buscar o RSI do Bitcoin, permitindo comparações entre o ativo e o BTC.
Cores das Linhas do RSI
Linha do RSI do Ativo:
-Cor Azul: Quando o RSI do ativo está acima do RSI do Bitcoin.
-Cor Verde: Quando o RSI do ativo está acima de 70 (zona de sobrecompra).
-Cor Vermelha: Quando o RSI do ativo está abaixo de 30 (zona de sobrevenda).
- Branca: Cor padrão quando o ativo não está em uma condição extrema.
- Quando o RSI do Bitcoin está acima de 70, indicando que o Bitcoin está sobrecomprado. Essa linha pode ficar mais transparente se estiver abaixo do nível de sobrecompra, o que a torna menos proeminente visualmente (vermelho).
Linha do RSI do Bitcoin:
-Cor Vermelha: Quando o RSI do Bitcoin está acima de 70 (zona de sobrecompra).
-Cor Vermelha com Transparência: Quando o RSI do Bitcoin está abaixo de 70.
Cálculo das Médias Móveis:
- EMA do RSI do Bitcoin: Calcula a média móvel exponencial do RSI do Bitcoin com base no período definido (9).
- SMMA do RSI do Ativo: Calcula a média móvel suavizada do RSI do ativo, usando o período definido (14).
Linhas de Sobrecompra e Sobrevenda
Linhas Horizontais:
-Sobrecompra (70): Linha pontilhada verde.
-Sobrevenda (30): Linha pontilhada vermelha.
-Linha do Meio (50): Linha pontilhada cinza.
Preenchimento:
-Área acima de 70 é preenchida em verde (zona de sobrecompra).
-Área abaixo de 30 é preenchida em vermelho (zona de sobrevenda).
Cálculo do Delta BTC:
- O Delta BTC é calculado em múltiplos timeframes (1 minuto, 5 minutos, 15 minutos, 1 hora, 4 horas e 1 dia) usando o RSI do ativo e comparando com a EMA do RSI do Bitcoin.
Cor das Velas
Candle de Compra:
- Azul, se o fechamento da vela for maior que a abertura e se o ativo estiver acima do BTC.
Candle de Venda:
- Laranja, se o fechamento da vela for menor que a abertura e se o ativo estiver acima do BTC.
Alertas
Configura alertas para notificar o usuário quando:
- O ativo ultrapassa a linha de sobrecompra.
- O ativo cai abaixo da linha de sobrevenda.
Etiquetas:
- As etiquetas são criadas para mostrar os valores atuais do RSI do ativo, do RSI do Bitcoin, da EMA do RSI do Bitcoin e da SMMA do RSI do ativo. Elas são adicionadas ao gráfico, e etiquetas antigas são removidas para evitar confusão.
Bolinhas no Gráfico
-As bolinhas servem como indicadores visuais para várias condições
Cruzamento da EMA:
- Bolinhas Verdes: Quando a EMA do RSI do Bitcoin cruza para cima.
- Bolinhas Vermelhas: Quando a EMA do RSI do Bitcoin cruza para baixo.
Condições do RSI do Ativo:
- Bolinhas Azuis: Quando o RSI do ativo está acima de 50, acima da EMA do RSI do BTC e acima do próprio RSI do Bitcoin.
Cruzamento do RSI do Ativo com o RSI do Bitcoin:
-Bolinhas Brancas: Quando o RSI do ativo cruza o RSI do Bitcoin.
Cruzamento do RSI do Ativo com a EMA do RSI do Bitcoin:
-"X" Verdes: Quando o RSI do ativo cruza para cima a EMA do RSI do Bitcoin.
-"X" Vermelhos: Quando o RSI do ativo cruza para baixo a EMA do RSI do Bitcoin
RSI Bollinger Volume StrategyThe RSI Bollinger Volume Reversal Strategy is designed to capture potential reversal points by combining RSI-based Bollinger Bands, volume analysis, and momentum shifts. This strategy is effective for identifying entry and exit points in markets where reversals frequently occur after high volatility or extreme momentum.
Gap Fill IndicatorPlots the gap and half gap fill based on the 4:00PM UTC-4 cash close or the 4:14PM UTC-4 RTH close.
It also marked the 10. 20. and 30 handle moves that correlate with our gap fill statistics,
the daily on intraday Pivot Point Level and the opening price.
To learn how to use it in your trading visit eminiaddict.com
Red Line = Gap Fill Price
Yellow Line = Half Gap Fill Price
Blue Line = Session Open Price
White line = Daily or Intraday Pivot Line
[TrendHunterTeo] L1 Sell after Pump Detectorindicatör gerçekten çok kullanışlı tüm zaman dilimlerinde repaint yapmadan bu kadar net sinyaller almak muazzam herkese bol kazançlar