Double CCI Confirmed Hull Moving Average Reversal StrategyOverview
The Double CCI Confirmed Hull Moving Average Strategy utilizes hull moving average (HMA) in conjunction with two commodity channel index (CCI) indicators: the slow and fast to increase the probability of entering when the short and mid-term uptrend confirmed. The main idea is to wait until the price breaks the HMA while both CCI are showing that the uptrend has likely been already started. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Double trade setup confirmation: Strategy utilizes two different period CCI indicators to confirm the breakouts of HMA.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Short-term period CCI indicator shall be above 0.
Long-term period CCI indicator shall be above 0.
Price shall cross the HMA and candle close above it with the same candle
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 25, used for calculation short term period CCI
CCI Slow Length (by default = 50, used for calculation long term period CCI)
Hull MA Length (by default = 34, period of HMA, which shall be broken to open trade)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI and HMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator used in trading to measure a security's price relative to its average price over a given period. Developed by Donald Lambert in 1980, the CCI is primarily used to identify cyclical trends in a security, helping traders to spot potential buying or selling opportunities.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Hull Moving Average (HMA) is a type of moving average that was developed by Alan Hull to improve upon the traditional moving averages by reducing lag while maintaining smoothness. The goal of the HMA is to create an indicator that is both quick to respond to price changes and less prone to whipsaws (false signals).
How the Hull Moving Average is Calculated?
The Hull Moving Average is calculated using the following steps:
Weighted Moving Average (WMA): The HMA starts by calculating the Weighted Moving Average (WMA) of the price data over a period square root of n (sqrt(n))
Speed Adjustment: A WMA is then calculated for half of the period n/2, and this is multiplied by 2 to give more weight to recent prices.
Lag Reduction: The WMA of the full period n is subtracted from the doubled n/2 WMA.
Final Smoothing: To smooth the result and reduce noise, a WMA is calculated for the square root of the period n.
The formula can be represented as:
HMA(n) = WMA(WMA(n/2) × 2 − WMA(n), sqrt(n))
The Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes than a Simple Moving Average (SMA). In a WMA, each data point within the selected period is multiplied by a weight, with the most recent data receiving the highest weight. The sum of these weighted values is then divided by the sum of the weights to produce the WMA.
This strategy leverages HMA of user given period as a critical level which shall be broken to say that probability of trend change to the upside increased. HMA reacts faster than EMA or SMA to the price change, that’s why it increases chances to enter new trade earlier. Long-term period CCI helps to have an approximation of mid-term trend. If it’s above 0 the probability of uptrend increases. Short-period CCI allows to have an approximation of short-term trend reversal from down to uptrend. This approach increases chances to have a long trade setup in the direction of mid-term trend when the short-term trend starts to reverse.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses HMA to enter the trade, but for trailing it leverages EMA. It’s used because EMA has no such fast reaction to price move which increases probability not to be stopped out from any significant uptrend move.
Backtest Results
Operating window: Date range of backtests is 2022.07.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 100%
Maximum Single Position Loss: -4.67%
Maximum Single Profit: +19.66%
Net Profit: +14897.94 USDT (+148.98%)
Total Trades: 104 (36.54% win rate)
Profit Factor: 2.312
Maximum Accumulated Loss: 1302.66 USDT (-9.58%)
Average Profit per Trade: 143.25 USDT (+0.96%)
Average Trade Duration: 34 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
ATR
Trend Strength | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Trend Strength indicator! Latest trends and their strengths play an important role for traders. This indicator aims to make trend and strength detection much easier by coloring candlesticks based on the current strength of trend. More info about the process in the "How Does It Work" section.
Features of the new Trend Strength Indicator :
3 Trend Detection Algorithms Combined (RSI, Supertrend & EMA Cross)
Fully Customizable Algorithm
Strength Labels
Customizable Colors For Bullish, Neutral & Bearish Trends
📌 HOW DOES IT WORK ?
This indicator uses three different methods of trend detection and combines them all into one value. First, the RSI is calculated. The RSI outputs a value between 0 & 100, which this indicator maps into -100 <-> 100. Let this value be named RSI. Then, the Supertrend is calculated. Let SPR be -1 if the calculated Supertrend is bearish, and 1 if it's bullish. After that, latest EMA Cross is calculated. This is done by checking the distance between the two EMA's adjusted by the user. Let EMADiff = EMA1 - EMA2. Then EMADiff is mapped from -ATR * 2 <-> ATR * 2 to -100 <-> 100.
Then a Total Strength (TS) is calculated by given formula : RSI * 0.5 + SPR * 0.2 + EMADiff * 0.3
The TS value is between -100 <-> 100, -100 being fully bearish, 0 being true neutral and 100 being fully bullish.
Then the Total Strength is converted into a color adjusted by the user. The candlesticks in the chart will be presented with the calculated color.
If the Labels setting is enabled, each time the trend changes direction a label will appear indicating the new direction. The latest candlestick will always show the current trend with a label.
EMA = Exponential Moving Average
RSI = Relative Strength Index
ATR = Average True Range
🚩 UNIQUENESS
The main point that differentiates this indicator from others is it's simplicity and customization options. The indicator interprets trend and strength detection in it's own way, combining 3 different well-known trend detection methods: RSI, Supertrend & EMA Cross into one simple method. The algorithm is fully customizable and all styling options are adjustable for the user's liking.
⚙️ SETTINGS
1. General Configuration
Detection Length -> This setting determines the amount of candlesticks the indicator will look for trend detection. Higher settings may help the indicator find longer trends, while lower settings will help with finding smaller trends.
Smoothing -> Higher settings will result in longer periods of time required for trend to change direction from bullish to bearish and vice versa.
EMA Lengths -> You can enter two EMA Lengths here, the second one must be longer than the first one. When the shorter one crosses under the longer one, this will be a bearish sign, and if it crosses above it will be a bullish sign for the indicator.
Labels -> Enables / Disables trend strength labels.
Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Volumetric Volatility Blocks [UAlgo]The Volumetric Volatility Blocks indicator is designed to identify significant volatility blocks based on price and volume data. It utilizes a combination of the Average True Range (ATR) and Simple Moving Average (SMA) to determine the volatility level and identify periods of heightened market activity. The indicator highlights these volatility blocks, providing traders with visual cues for potential trading opportunities. It differentiates between bullish and bearish volatility by analyzing price movement and volume, offering a nuanced view of market sentiment. This tool is particularly useful for traders looking to capitalize on periods of high volatility and momentum shifts.
🔶 Key Features
Volatility Measurement Length: Controls the period used to calculate the ATR.
Smooth Length of Volatility: Defines the period for the SMA used to smooth the ATR.
Multiplier of SMA: Sets the minimum threshold for the ATR to be considered a "high volatility" block.
Show Last X Volatility Blocks: Determines how many of the most recent volatility blocks are displayed on the chart.
Mitigation Method: Choose between "Close" or "Wick" price to filter volatility blocks based on price action. This helps avoid highlighting blocks broken by the chosen price level.
Volume Info: Displaying the volume associated with each block.
Up/Down Block Color: Sets the color for bullish and bearish volatility blocks.
🔶 Usage
The Volumetric Volatility Blocks indicator visually represents periods of high volatility with blocks on the chart. Green blocks indicate bullish volatility, while red blocks indicate bearish volatility.
Bullish Volatility Blocks: When the ATR surpasses the smoothed ATR multiplied by the set multiplier, and the price closes higher than it opened, a bullish block is formed. These blocks are generally used to identify potential buying opportunities as they indicate upward momentum.
Bearish Volatility Blocks: Conversely, bearish blocks form under the same conditions, but when the price closes lower than it opened. These blocks can signal potential selling opportunities as they highlight downward momentum.
Volume Information: Each block can display volume data, providing insight into the strength of the market movement. The percentage shown on the block indicates the relative volume contribution of that block, helping traders assess the significance of the volatility.
The volume percentages in the Volumetric Volatility Blocks indicator are calculated based on the total volume of the most recent volatility blocks. For each of the most recent volatility blocks, the percentage of the total volume is calculated by dividing the block's volume by the total volume:
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Market Cycle Phases IndicatorOverview
The Market Cycle Phases Indicator is a powerful tool designed to help traders identify and visualize the different phases of market cycles. By distinguishing between Accumulation, Uptrend, Distribution, and Downtrend phases, this indicator provides a clear and color-coded representation of market conditions, aiding in better decision-making and strategy development. It is especially useful for long-term investors to observe and understand market cycles over extended periods. The phases are color-coded for easy identification: Green for Accumulation, Blue for Uptrend, Yellow for Distribution, and Red for Downtrend.
Key Features
Identifies four key market phases: Accumulation, Uptrend, Distribution, and Downtrend
Uses a combination of moving averages and volatility measures
Color-coded background for easy visualization of market phases
Adjustable parameters for moving average length, volatility length, and volatility threshold
Plots the moving average and Average True Range (ATR) for reference
Suitable for both short-term trading and long-term investing
Concepts Underlying the Calculations
The calculations behind the Market Cycle Phases Indicator are straightforward, combining the principles of moving averages and volatility measures:
Moving Average (MA): A simple moving average is used to determine the overall trend direction.
Average True Range (ATR): This measures market volatility over a specified period.
Volatility Threshold: A multiplier is applied to the ATR to distinguish between high and low volatility conditions.
How It Works
The indicator first calculates a moving average (MA) of the closing prices and the Average True Range (ATR) to measure market volatility. Based on the position of the price relative to the MA and the current volatility level, the indicator determines the current market phase:
Accumulation Phase: Price is below the MA, and volatility is low (Green background). This phase often indicates a period of consolidation and potential buying interest before an uptrend.
Uptrend Phase: Price is above the MA, and volatility is high (Blue background). This phase represents a strong upward movement in price, often driven by increased buying activity.
Distribution Phase: Price is above the MA, and volatility is low (Yellow background). This phase suggests a period of consolidation at the top of an uptrend, where selling interest may start to increase.
Downtrend Phase: Price is below the MA, and volatility is high (Red background). This phase indicates a strong downward movement in price, often driven by increased selling activity.
How Traders Can Use It
Traders can use the Market Cycle Phases Indicator to:
Identify potential entry and exit points based on market phase transitions.
Confirm trends and avoid false signals by considering both trend direction and volatility.
Develop and refine trading strategies tailored to specific market conditions.
Enhance risk management by recognizing periods of high and low volatility.
Observe long-term market cycles to make informed investment decisions.
Example Usage Instructions
Add the Market Cycle Phases Indicator to your chart.
Adjust the input parameters as needed:
Base Length: Default is 50.
Volatility Length: Default is 14.
Volatility Threshold: Default is 1.5.
Observe the color-coded background to identify the current market phase
Use the identified phases to inform your trading decisions:
Consider buying during the Accumulation or Uptrend phases.
Consider selling or shorting during the Distribution or Downtrend phases.
Combine with other indicators and analysis techniques for comprehensive market insights.
By incorporating the Market Cycle Phases Indicator into your trading toolkit, you can gain a clearer understanding of market dynamics and enhance your ability to navigate different market conditions, making it a valuable asset for long-term investing.
Multi-Regression StrategyIntroducing the "Multi-Regression Strategy" (MRS) , an advanced technical analysis tool designed to provide flexible and robust market analysis across various financial instruments.
This strategy offers users the ability to select from multiple regression techniques and risk management measures, allowing for customized analysis tailored to specific market conditions and trading styles.
Core Components:
Regression Techniques:
Users can choose one of three regression methods:
1 - Linear Regression: Provides a straightforward trend line, suitable for steady markets.
2 - Ridge Regression: Offers a more stable trend estimation in volatile markets by introducing a regularization parameter (lambda).
3 - LOESS (Locally Estimated Scatterplot Smoothing): Adapts to non-linear trends, useful for complex market behaviors.
Each regression method calculates a trend line that serves as the basis for trading decisions.
Risk Management Measures:
The strategy includes nine different volatility and trend strength measures. Users select one to define the trading bands:
1 - ATR (Average True Range)
2 - Standard Deviation
3 - Bollinger Bands Width
4 - Keltner Channel Width
5 - Chaikin Volatility
6 - Historical Volatility
7 - Ulcer Index
8 - ATRP (ATR Percentage)
9 - KAMA Efficiency Ratio
The chosen measure determines the width of the bands around the regression line, adapting to market volatility.
How It Works:
Regression Calculation:
The selected regression method (Linear, Ridge, or LOESS) calculates the main trend line.
For Ridge Regression, users can adjust the lambda parameter for regularization.
LOESS allows customization of the point span, adaptiveness, and exponent for local weighting.
Risk Band Calculation:
The chosen risk measure is calculated and normalized.
A user-defined risk multiplier is applied to adjust the sensitivity.
Upper and lower bounds are created around the regression line based on this risk measure.
Trading Signals:
Long entries are triggered when the price crosses above the regression line.
Short entries occur when the price crosses below the regression line.
Optional stop-loss and take-profit mechanisms use the calculated risk bands.
Customization and Flexibility:
Users can switch between regression methods to adapt to different market trends (linear, regularized, or non-linear).
The choice of risk measure allows adaptation to various market volatility conditions.
Adjustable parameters (e.g., regression length, risk multiplier) enable fine-tuning of the strategy.
Unique Aspects:
Comprehensive Regression Options:
Unlike many indicators that rely on a single regression method, MRS offers three distinct techniques, each suitable for different market conditions.
Diverse Risk Measures: The strategy incorporates a wide range of volatility and trend strength measures, going beyond traditional indicators to provide a more nuanced view of market dynamics.
Unified Framework:
By combining advanced regression techniques with various risk measures, MRS offers a cohesive approach to trend identification and risk management.
Adaptability:
The strategy can be easily adjusted to suit different trading styles, timeframes, and market conditions through its various input options.
How to Use:
Select a regression method based on your analysis of the current market trend (linear, need for regularization, or non-linear).
Choose a risk measure that aligns with your trading style and the market's current volatility characteristics.
Adjust the length parameter to match your preferred timeframe for analysis.
Fine-tune the risk multiplier to set the desired sensitivity of the trading bands.
Optionally enable stop-loss and take-profit mechanisms using the calculated risk bands.
Monitor the regression line for potential trend changes and the risk bands for entry/exit signals.
By offering this level of customization within a unified framework, the Multi-Regression Strategy provides traders with a powerful tool for market analysis and trading decision support. It combines the robustness of regression analysis with the adaptability of various risk measures, allowing for a more comprehensive and flexible approach to technical trading.
Market Structure Break Targets [UAlgo]The "Market Structure Break Targets " indicator is designed to identify and visualize key market structure points such as Market Structure Breaks (MSBs) and Break of Structures (BoS). These points are crucial for understanding market trends and potential reversal zones. By plotting these structures on the chart, traders can easily spot significant support and resistance levels, as well as potential entry and exit points.
This indicator uses a combination of swing highs and lows to determine market structures and calculates targets based on user-defined percentages or Average True Range (ATR) multipliers. It provides visual cues in the form of lines, labels, and boxes to help traders quickly interpret market conditions.
🔶 Key Features
Customizable Swing Length: Users can set the swing length to identify the pivot highs and lows, which are crucial for determining market structure.
Target Duration Bars: Defines the maximum duration (in bars) for which the targets will be considered valid.
Target Calculation Methods: The target levels are crucial for setting potential price objectives. The calculation can be based on a percentage move from the identified pivot or using the ATR to factor in market volatility. These targets help in setting realistic profit-taking levels or identifying stop-loss placements.
Bullish and Bearish Market Structure Break (MSB): Detects and highlights bullish and bearish market structure breaks with customizable colors and target percentages.
Bullish MSB
When the price closes above a significant pivot high, a bullish MSB is identified. The indicator will draw a line at this level and calculate a target based on the chosen method (percentage or ATR). The target is visualized with a dotted line, and a label "MSB" is displayed. Additionally, an order block is created at the level of the bullish MSB. This order block is highlighted with a semi-transparent box, representing a potential area where price might find support in the future.
Bearish MSB
Conversely, when the price closes below a significant pivot low, a bearish MSB is marked. Similar to bullish MSBs, targets are calculated and displayed on the chart. An order block is also generated at the level of the bearish MSB, visualized with a semi-transparent box. This box highlights a potential resistance area where price might face selling pressure.
Bullish and Bearish Break of Structure (BoS): Identifies break of structures for both bullish and bearish scenarios, providing additional target levels.
Bullish BoS
If the price continues to rise and breaks another significant level, a bullish BoS is detected. This break is also marked with lines and labels, providing additional target levels for traders. An order block is created at the BoS level, serving as a potential support zone.
Bearish BoS
If the price falls further after a bearish MSB, a bearish BoS is identified and visualized similarly. The indicator creates an order block at the BoS level, which acts as a potential resistance zone.
🔶 Disclaimer:
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Custom ATR Trailing StopThis Script creates a custom ATR (Average True Range) trailing stop. It allows traders to set up automated stop-loss levels based on the ATR, which adjusts dynamically to market volatility. The script is designed to support both long and short trades, offering flexibility and precision in trade management.
When loading the indicator to your chart, simply click to set the trade begining time, confirm various settings and you are set.
Check tooltips for more details in the input settigns menu.
User Inputs
Trade Setup: Allows users to set the trade direction (Long or Short), the signal source for entries, and the specific bar time for the trade setup.
ATR Settings: Configurable ATR lookback period, ATR smoothing period, initial ATR multiplier for setting the stop-loss, breakeven ATR multiplier, and a manual breakeven level.
ATR Calculations
Computes the ATR and its moving average.
Determines initial and breakeven stop levels based on the ATR.
Signal Validation
Validates long or short trade signals based on the specified bar time and trade direction.
Triggers alerts when a valid trade signal is detected.
Trailing Stop Logic
For long trades, adjusts the stop-loss level dynamically based on the ATR.
For short trades, performs similar adjustments in the opposite direction.
Updates the trailing stop level to ensure it follows the price, moving closer as the price moves favorably.
Resets the trade state when the stop-loss is hit, triggering an alert.
Plotting
Plots the trailing stop levels on the chart.
Uses green for stop levels indicating profit and red for stop levels indicating a loss.
Fair Value Gap (FVG) Oscillator [UAlgo]The "Fair Value Gap (FVG) Oscillator " is designed to identify and visualize Fair Value Gaps (FVG) within a given lookback period on a trading chart. This indicator helps traders by highlighting areas where price gaps may signify potential trading opportunities, specifically bullish and bearish patterns. By leveraging volume and Average True Range (ATR) data, the FVG Oscillator aims to enhance the accuracy of pattern recognition and provide more reliable signals for trading decisions.
🔶 Identification of Fair Value Gap (FVG)
Fair Value Gaps (FVG) are specific price areas where gaps occur, and they are often considered significant in technical analysis. These gaps can indicate potential future price movements as the market may return to fill these gaps. This indicator identifies two types of FVGs:
Bullish FVG: Occurs when the current low price is higher than the high price two periods ago. This condition suggests a potential upward price movement.
Obtains with:
low > high
Bearish FVG: Occurs when the current high price is lower than the low price two periods ago. This condition suggests a potential downward price movement.
Obtains with:
high < low
The FVG Oscillator not only identifies these gaps but also verifies them using volume and ATR conditions to ensure more reliable trading signals.
🔶 Key Features
Lookback Period: Users can set the lookback period to determine how far back the indicator should search for FVG patterns.
ATR Multiplier: The ATR Multiplier is used to adjust the sensitivity of the ATR-based conditions for verifying FVG patterns.
Volume SMA Period: This setting determines the period for the Simple Moving Average (SMA) of the volume, which helps in identifying high volume conditions.
Why ATR and Volume are Used?
ATR (Average True Range) and volume are integrated into the Fair Value Gap (FVG) Oscillator to enhance the accuracy and reliability of the identified patterns. ATR measures market volatility, helping to filter out insignificant price gaps and focus on impactful ones, ensuring that the signals are relevant and strong. Volume, on the other hand, confirms the strength of price movements. High volume often indicates the sustainability of these movements, reducing the likelihood of false signals. Together, ATR and volume ensure that the detected FVGs are both significant and supported by market activity, providing more trustworthy trading signals.
Normalized Values: The FVG counts are normalized to enhance the visual representation and interpretation of the patterns on the chart.
Visual Customization and Plotting: Users can customize the colors for positive (bullish) and negative (bearish) areas, and choose whether to display these areas on the chart, also plots the bullish and bearish FVG counts, a zero line, and the net value of FVG counts. Additionally, it uses histograms to display the width of verified bullish and bearish patterns.
🔶 Disclaimer:
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Filtered MACD with Backtest [UAlgo]The "Filtered MACD with Backtest " indicator is an advanced trading tool designed for the TradingView platform. It combines the Moving Average Convergence Divergence (MACD) with additional filters such as Moving Average (MA) and Average Directional Index (ADX) to enhance trading signals. This indicator aims to provide more reliable entry and exit points by filtering out noise and confirming trends. Additionally, it includes a comprehensive backtesting module to simulate trading strategies and assess their performance based on historical data. The visual backtest module allows traders to see potential trades directly on the chart, making it easier to evaluate the effectiveness of the strategy.
🔶 Customizable Parameters :
Price Source Selection: Users can choose their preferred price source for calculations, providing flexibility in analysis.
Filter Parameters:
MA Filter: Option to use a Moving Average filter with types such as EMA, SMA, WMA, RMA, and VWMA, and a customizable length.
ADX Filter: Option to use an ADX filter with adjustable length and threshold to determine trend strength.
MACD Parameters: Customizable fast length, slow length, and signal smoothing for the MACD indicator.
Backtest Module:
Entry Type: Supports "Buy and Sell", "Buy", and "Sell" strategies.
Stop Loss Types: Choose from ATR-based, fixed point, or X bar high/low stop loss methods.
Reward to Risk Ratio: Set the desired take profit level relative to the stop loss.
Backtest Visuals: Display entry, stop loss, and take profit levels directly on the chart with
colored backgrounds.
Alerts: Configurable alerts for buy and sell signals.
🔶 Filtered MACD : Understanding How Filters Work with ADX and MA
ADX Filter:
The Average Directional Index (ADX) measures the strength of a trend. The script calculates ADX using the user-defined length and applies a threshold value.
Trading Signals with ADX Filter:
Buy Signal: A regular MACD buy signal (crossover of MACD line above the signal line) is only considered valid if the ADX is above the set threshold. This suggests a stronger uptrend to potentially capitalize on.
Sell Signal: Conversely, a regular MACD sell signal (crossunder of MACD line below the signal line) is only considered valid if the ADX is above the threshold, indicating a stronger downtrend for potential shorting opportunities.
Benefits: The ADX filter helps avoid whipsaws or false signals that might occur during choppy market conditions with weak trends.
MA Filter:
You can choose from various Moving Average (MA) types (EMA, SMA, WMA, RMA, VWMA) for the filter. The script calculates the chosen MA based on the user-defined length.
Trading Signals with MA Filter:
Buy Signal: A regular MACD buy signal is only considered valid if the closing price is above the MA value. This suggests a potential uptrend confirmed by the price action staying above the moving average.
Sell Signal: Conversely, a regular MACD sell signal is only considered valid if the closing price is below the MA value. This suggests a potential downtrend confirmed by the price action staying below the moving average.
Benefits: The MA filter helps identify potential trend continuation opportunities by ensuring the price aligns with the chosen moving average direction.
Combining Filters:
You can choose to use either the ADX filter, the MA filter, or both depending on your strategy preference. Using both filters adds an extra layer of confirmation for your signals.
🔶 Backtesting Module
The backtesting module in this script allows you to visually assess how the filtered MACD strategy would have performed on historical data. Here's a deeper dive into its features:
Backtesting Type: You can choose to backtest for buy signals only, sell signals only, or both. This allows you to analyze the strategy's effectiveness in different market conditions.
Stop-Loss Types: You can define how stop-loss orders are placed:
ATR (Average True Range): This uses a volatility measure (ATR) multiplied by a user-defined factor to set the stop-loss level.
Fixed Point: This allows you to specify a fixed dollar amount or percentage value as the stop-loss.
X bar High/Low: This sets the stop-loss at a certain number of bars (defined by the user) above/below the bar's high (for long positions) or low (for short positions).
Reward-to-Risk Ratio: Define the desired ratio between your potential profit and potential loss on each trade. The backtesting module will calculate take-profit levels based on this ratio and the stop-loss placement.
🔶 Disclaimer:
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
RSI Trail [UAlgo]The RSI Trail indicator is a technical analysis tool designed to assist traders in making informed decisions by utilizing the Relative Strength Index (RSI) and various moving average calculations. This indicator dynamically plots support and resistance levels based on RSI values, providing visual cues for potential bullish and bearish signals. The inclusion of a trailing stop mechanism allows traders to adapt to market volatility, ensuring optimal entry and exit points.
🔶 Key Features
Multiple Moving Average Types: Choose from Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), Running Moving Average (RMA), and McGinley Dynamic for diverse analytical approaches.
Configurable RSI Bounds: Tailor the RSI lower and upper bounds to your specific trading preferences, with default settings at 40 and 60.
Signals: The indicator determines bullish and bearish market states and plots corresponding signals on the chart.
Customizable Visualization: Options to display the midline and color candles based on market state enhance visual analysis.
Alerts: Integrated alert conditions notify you of bullish and bearish signals.
🔶 Calculations
The RSI Trail indicator calculates dynamic support and resistance levels using a combination of moving averages and the Relative Strength Index (RSI). It starts by computing a chosen moving average (SMA, EMA, WMA, RMA, or McGinley) over a period of 27 using the typical price (ohlc4).
The indicator then defines upper and lower bounds based on customizable RSI levels (default 40 and 60) and adjusts these bounds using the Average True Range (ATR) to account for market volatility. The upper bound is calculated by adding a volatility-adjusted value to the moving average, while the lower bound is found by subtracting this value. Bullish signals occur when the price crosses above the upper bound, and bearish signals when it falls below the lower bound.
The RSI Trail indicator also can be used to identify pullback opportunities. When the price high/low crosses above/below the calculated upper/lower bound, it indicates a potential pullback, suggesting a favorable point to enter a trade during a pullback.
🔶 Disclaimer
This indicator is for informational purposes only and should not be considered financial advice.
Always conduct your own research and due diligence before making any trading decisions. Past performance is not necessarily indicative of future results.
ATR Gerchik LightAverage True Range ( ATR ) is a technical analysis indicator that measures volatility in the market. ATR is a moving average of the true range over a period of time.
ATR calculation procedure:
1. Determine the true maximum - this is the highest of the current maximum and yesterday's closing price of the day.
2. Determine the true minimum - this is the smallest of the current minimum and yesterday's closing price.
3. Determine the true range - this is the distance between the true maximum and minimum.
4. We exclude extremely large candles (> x2 ATR) and extremely small ones (< 0.5 ATR) from the obtained true ranges.
5. We calculate the average for the selected period based on the remaining range.
6. We calculate the percentage of the current True Range relative to the average ATR value for the previous period.
Description:
If you analyze it yourself, you will see that 75-80% of the time, the instrument moves only 1 ATR per day. You must understand that if an instrument has, for example, moved 80% of its daily range, it is not advisable to purchase it. This is comparable to a car's fuel tank: if the tank is almost empty, the car won't go far. Most indicators that calculate ATR include anomalous candles, which give unreliable results and lead to incorrect decisions. Because of this, many traders prefer to calculate ATR on their own.
However, the Gerchik ATR indicator accounts for anomalous candles and filters out extremely large candles (> 2x ATR) and extremely small ones (< 0.5x ATR). Additionally, this indicator immediately shows the consumed “fuel” of the instrument as a percentage, so you don't have to calculate the distance traveled yourself. This allows you to make quick, informed decisions. If we see that the tank is almost empty, it is logical not to get into that car today. When building any strategy, you must rely on the average movement.
Key Features:
Anomalous Candle Filtering: Excludes extremely large and small candles to provide more reliable ATR values.
Consumed Fuel Indicator: Shows the percentage of the ATR consumed, helping traders quickly assess the remaining potential movement.
Daily Timeframe Focus: Designed specifically for use on daily charts for accurate long-term analysis.
Practical Applications:
Entry and Exit Points: Use the ATR to determine optimal entry and exit points by assessing market volatility and potential price movement.
Stop-Loss Placement: Calculate stop-loss levels based on ATR to ensure they are placed at appropriate distances, accounting for current market volatility.
Trend Confirmation: Use the percentage of ATR consumed to confirm the strength of a trend and decide whether to enter or exit trades.
Examples of Use:
Trend Following: During strong trends, ATR helps identify periods of increased volatility, signaling potential breakouts or reversals.
Range Trading: In ranging markets, ATR can highlight periods of low volatility, indicating consolidation and potential breakout zones.
Note: The indicator is displayed and works only on the daily timeframe!
The indicator was created according to the instructions, description of the functionality, and strategy of Mr. Gerchik. Thank you so much, Chief!
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Average True Range ( ATR , средний истинный диапазон) – это индикатор технического анализа, который измеряет волатильность на рынке. ATR представляет собой скользящее среднее истинного диапазона за определенный период времени.
Порядок расчета ATR:
1. Определяем истинный максимум – это наивысшее из текущего максимума и вчерашней цены закрытия дня.
2. Определяем истинный минимум – это наименьшее из текущего минимума и вчерашней цены закрытия.
3. Определяем истинный диапазон – это расстояние между истинным максимумом и минимумом.
4. Исключаем из полученных истинных диапазонов экстремально большие свечи (> x2 ATR) и экстремально маленькие (< 0.5 ATR).
5. Рассчитываем среднее за выбранный период исходя из оставшегося диапазона.
6 . Рассчитываем процент текущего истинного диапазона (True Range) относительно среднего значения ATR за предыдущий период.
Описание:
Если вы сами проанализируете, то увидите, что 75-80% времени инструмент ходит только 1 ATR. И вы должны понимать, что если инструмент внутри дня прошел, к примеру, 80% своего движения, то этот инструмент больше нельзя покупать. Это можно сравнить с баком машины: если бак почти пустой, машина далеко не уедет. Большинство индикаторов, которые рассчитывают ATR, производят расчет с паранормальными свечами. Это дает недостоверный результат и приводит к неверным решениям. Многие трейдеры из-за этого не используют готовые индикаторы и предпочитают считать ATR самостоятельно. Но индикатор ATR Gerchik учитывает паранормальные свечи и фильтрует экстремально большие свечи (> x2 ATR) и экстремально маленькие (< 0.5 ATR). Также этот индикатор сразу показывает израсходованный "бензин" инструмента в процентах. И вам не надо самостоятельно высчитывать пройденный путь. Вы можете быстро принимать правильные решения. Если мы видим, что бак почти пустой, логично не садиться в эту машину сегодня. Когда вы строите какую-то стратегию, вы должны обязательно полагаться на среднестатистическое движение.
Существует много стратегий, завязанных на ATR, которые учитывают волатильность инструмента, запас хода, точки разворота, места выставления стоп-лоссов (SL) и тейк-профитов (TP) и другие факторы. Я не буду останавливаться на них, так как каждый может найти описание этих стратегий и использовать их на свой выбор.
Индикатор отображается и работает только на дневном таймфрейме!
Индикатор создан по наставлениям, описанию функционала и стратегии господина Герчика. Огромное спасибо, Шеф!
Performance IndicatorsDescription:
The Performance Indicators tool provides traders with a comprehensive overview of both fundamental and technical performance metrics of a security. This dual approach helps traders make informed decisions by evaluating the security's intrinsic value as well as its market behavior.
Fundamental Performance Indicators:
EPS Year Over Year % Growth : Measures the percentage growth in earnings per share (EPS) compared to the same quarter in the previous year. This helps in understanding the company's profitability trends.
EPS 3 Quarters Year Over Year % Growth : Analyzes the percentage growth in EPS over the last three quarters compared to the same quarters in the previous year, providing insight into the company's recent earnings performance.
Sales Year Over Year % Growth : Tracks the percentage growth in sales compared to the same quarter in the previous year, offering a view of the company's revenue trends.
Sales 3 Quarters Year Over Year % Growth : Evaluates the percentage growth in sales over the last three quarters compared to the same quarters in the previous year, helping to assess the company's recent revenue performance.
Return On Equity (ROE) : Measures the company's profitability by comparing net income to shareholder equity. This indicates how effectively the company is using its equity base to generate profits.
Market Capitalization : Represents the total market value of the company's outstanding shares, providing a sense of the company's size and market presence.
Float Shares Outstanding : Refers to the number of shares available for trading by the public, excluding restricted shares. This metric helps in understanding the liquidity and volatility of the stock.
Technical Performance Indicators:
Average Daily Range (ADR) %: Calculates the average range between the high and low prices over a specific period, expressed as a percentage. This helps in understanding the stock's daily volatility.
Average True Range (ATR) $ : Measures market volatility by calculating the average range between the high and low prices, taking into account any gaps in the price. It is expressed in dollar terms.
% Off 52-Week High : Indicates how far the current price is from the highest price achieved over the last 52 weeks, helping to assess the stock's current performance relative to its yearly peak.
Relative Price Strength (RPS) : Compares the stock's price performance to a benchmark index, helping to identify how the stock is performing relative to the broader market.
How it Works:
The fundamental performance indicators provide insights into the company's financial health and growth trends by analyzing key metrics such as EPS, sales growth, ROE, market capitalization, and float shares outstanding.
The technical performance indicators offer a view of the stock's market behavior and volatility through metrics like ADR, ATR, % off 52-week high, and RPS.
By combining these fundamental and technical metrics, traders can gain a well-rounded perspective on the security's overall performance.
How to Use:
Add the Performance Indicators tool to your chart.
Evaluate the fundamental indicators to assess the company's financial health and growth trends.
Analyze the technical indicators to understand the stock's market behavior and volatility.
Use the combined insights from both fundamental and technical indicators to make informed trading decisions.
This tool is particularly useful for traders who want to integrate both fundamental analysis and technical analysis into their trading strategy, providing a holistic view of a security's performance.
Fractal Breakout Trend Following StrategyOverview
The Fractal Breakout Trend Following Strategy is a trend-following system which utilizes the Willams Fractals and Alligator to execute the long trades on the fractal's breakouts which have a high probability to be the new uptrend phase beginning. This system also uses the normalized Average True Range indicator to filter trades after a large moves, because it's more likely to see the trend continuation after a consolidation period. Strategy can execute only long trades.
Unique Features
Trend and volatility filtering system: Strategy uses Williams Alligator to filter the counter-trend fractals breakouts and normalized Average True Range to avoid the trades after large moves, when volatility is high
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Flexible Risk Management: Users can choose the stop-loss percent (by default = 3%) for trades, but strategy also has the dynamic stop-loss level using down fractals.
Methodology
The strategy places stop order at the last valid fractal breakout level. Validity of this fractal is defined by the Williams Alligator indicator. If at the moment of time when price breaking the last fractal price is higher than Alligator's teeth line (8 period SMA shifted 5 bars in the future) this is a valid breakout. Moreover strategy has the additional volatility filtering system using normalized ATR. It calculates the average normalized ATR for last user-defined number of bars and if this value lower than the user-defined threshold value the long trade is executed.
When trade is opened, script places the stop loss at the price higher of two levels: user defined stop-loss from the position entry price or down fractal validation level. The down fractal is valid with the rule, opposite as the up fractal validation. Price shall break to the downside the last down fractal below the Willians Alligator's teeth line.
Strategy has no fixed take profit. Exit level changes with the down fractal validation level. If price is in strong uptrend trade is going to be active until last down fractal is not valid. Strategy closes trade when price hits the down fractal validation level.
Risk Management
The strategy employs a combined approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined stop-loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 3% drop from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Williams Fractals to open long trade when price has broken the key resistance level to the upside. This resistance level is the last up fractal and is shall be broken above the Williams Alligator's teeth line to be qualified as the valid breakout according to this strategy. The Alligator filtering increases the probability to avoid the false breakouts against the current trend.
Moreover strategy has an additional filter using Average True Range(ATR) indicator. If average value of ATR for the last user-defined number of bars is lower than user-defined threshold strategy can open the long trade according to open trade condition above. The logic here is following: we want to open trades after period of price consolidation inside the range because before and after a big move price is more likely to be in sideways, but we need a trend move to have a profit.
Another one important feature is how the exit condition is defined. On the one hand, strategy has the user-defined stop-loss (3% below the entry price by default). It's made to give users the opportunity to restrict their losses according to their risk-tolerance. On the other hand, strategy utilizes the dynamic exit level which is defined by down fractal activation. If we assume the breaking up fractal is the beginning of the uptrend, breaking down fractal can be the start of downtrend phase. We don't want to be in long trade if there is a high probability of reversal to the downside. This approach helps to not keep open trade if trend is not developing and hold it if price continues going up.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -3.19%
Maximum Single Profit: +24.97%
Net Profit: +3036.90 USDT (+30.37%)
Total Trades: 83 (28.92% win rate)
Profit Factor: 1.953
Maximum Accumulated Loss: 963.98 USDT (-8.29%)
Average Profit per Trade: 36.59 USDT (+1.12%)
Average Trade Duration: 72 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h and higher time frames and the BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
ATR (Average True Range) mit relative/absolute Zahlen GERMAN:
Schnelle Zusammenfassung:
Dieses Skript basiert auf dem ATR-Indikator und wurde so angepasst, dass sowohl relative (%) als auch absolute Zahlen angezeigt werden. Es bietet eine Darstellung des ATR in absoluten und prozentualen Werten sowie multipliziert mit den Faktoren x2, x2.5 und x3. Diese Darstellung erleichtert die Festlegung von Stop-Kursen, insbesondere für Trailing Stops und Trailing Abstände.
Periode:
Die Periode ist einstellbar und definiert die Länge der Berechnung des ATR (Standardwert: 14).
Glättung: Es stehen verschiedene Methoden zur Auswahl, um die Daten zu glätten (RMA, SMA, EMA, WMA).
Berechnungen:
ATR (Absolute Zahl): Berechnung der durchschnittlichen wahren Reichweite (ATR) unter Verwendung der ausgewählten Glättungsmethode und Periode.
ATR (Prozentualer Wert): Berechnung des ATR als Prozentsatz des aktuellen Schlusskurses.
Multiplikation des ATR: Berechnung des ATR multipliziert mit den Faktoren 2, 2.5 und 3 zur Einschätzung verschiedener Handelsszenarien.
Darstellung:
Absoluter ATR-Wert: Darstellung der absoluten ATR-Werte in Blau.
Relative ATR-Werte (%): Darstellung der prozentualen ATR-Werte, ohne Linie in der Grafik (transparent).
Multiplizierte ATR-Werte (x2, x2.5, x3): Darstellung der multiplizierten ATR-Werte in den Farben Grün (x2), Orange (x2.5) und Lila (x3).
Textbeschriftungen: Für jeden absoluten ATR-Wert und seine Multiplikationen werden Textbeschriftungen links im Chart angezeigt.
Verwendung des Indikators:
Dieser Indikator unterstützt Trader und Analysten dabei, die durchschnittliche wahre Reichweite (ATR) eines Finanzinstruments zu verstehen und zu visualisieren. Die verschiedenen Multiplikationen des ATR ermöglichen es, potenzielle Preisbewegungen zu analysieren und Handelsstrategien zu entwickeln, die auf der Volatilität basieren.
Hinweis:
Dies ist meine persönliche Meinung und Einstellung. Dieses Skript stellt keine Bankberatung oder Anlageempfehlung dar. Die Nutzung erfolgt auf eigenes Risiko und Verantwortung des Nutzers.
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ENGLISH:
Quick Summary:
This script is based on the ATR (Average True Range) indicator and has been modified to display both relative (%) and absolute values. It provides a representation of ATR in absolute and percentage terms, as well as multiplied by factors x2, x2.5, and x3. This visualization aids in setting stop-loss levels, especially for trailing stops and trailing distances.
Period:
The period is adjustable and defines the length of the ATR calculation (default: 14).
Smoothing: Various methods are available to smooth the data (RMA, SMA, EMA, WMA).
Calculations:
ATR (Absolute Value): Computes the Average True Range using the selected smoothing method and period.
ATR (Percentage Value): Calculates the ATR as a percentage of the current closing price.
Multiplication of ATR: Computes the ATR multiplied by factors 2, 2.5, and 3 to assess different trading scenarios.
Visualization:
Absolute ATR Value: Displays the absolute ATR values in blue.
Relative ATR Values (%): Shows the ATR values as percentages, without lines in the chart (transparent).
Multiplied ATR Values (x2, x2.5, x3): Presents the multiplied ATR values in green (x2), orange (x2.5), and purple (x3).
Text Labels: Text labels are shown on the left side of the chart for each absolute ATR value and its multiples.
Use of the Indicator:
This indicator helps traders and analysts understand and visualize the Average True Range (ATR) of a financial instrument. The different multipliers of ATR allow for the analysis of potential price movements and the development of trading strategies based on volatility.
Disclaimer:
This represents my personal opinion and viewpoint. This script does not constitute bank advice or investment recommendations. Use it at your own risk and responsibility.
ACD Indicator [TradingFinder] M Fisher Pivots Methodology Signal🔵 Introduction
The book "The Logical Trader" begins with a comprehensive review of the ACD Methodology principles, which include identifying specific price points related to the opening range.
This method allows you to set reference points for trading and use points "A" and "C" for trade entry. You will also learn about the "Pivot Range" and how to combine them with the ACD method to maximize position size and minimize risk.
In this indicator, the strategy is implemented to make it easier to use.
🔵 How to Use
The "ACD" strategy can be applied to various markets such as stocks, commodities, or forex, providing buy and sell signals that allow you to set your price targets and stop losses.
This strategy is based on the assumption that the opening range of trades is statistically significant each day, meaning the initial market fluctuations influence the market until the end of the day.
The ACD trading strategy is known as a breakout strategy and performs best in volatile or strongly trending markets, such as crude oil and stocks.
Some of the rules for using the ACD strategy include the following :
Consider points A and C as reference points and continuously pay attention to these points during trades. These points serve as entry and exit points for trades.
Examine daily and multi-day pivot ranges to analyze market trends. If the price is above the pivots, the trend is upward, and if below the pivots, the trend is downward.
Trading with the ACD strategy in forex is possible using the ACD indicator. This indicator is a technical tool used to measure the balance between supply and demand in the market. By analyzing trading volume and price, this indicator helps traders identify trend strength and suitable entry and exit points.
To use the ACD indicator, consider the following :
Identifying strong trends: The ACD indicator can help you identify strong and stable trends in the market.
Determining entry and exit points: ACD provides buy and sell signals to enter or exit trades at the best possible time.
Bullish Setup :
When the "A up" line is broken, it is advisable to wait for some time to ensure that this is not a "Fake Breakout" and that the price stabilizes above this line.
After entering the trade, the best stop loss you can choose is below the "A down" line. However, it is recommended to test this in backtests to achieve the best results. The suitable reward-to-risk ratio for this strategy is 1, which should also be backtested.
Bearish Setup :
When the "A down" line is broken, it is advisable to wait for some time to ensure that this is not a "Fake Breakout" and that the price stabilizes below this line.
After entering the trade, the best stop loss you can choose is above the "A up" line. However, it is recommended to test this in backtests to achieve the best results. The suitable reward-to-risk ratio for this strategy is 1, which should also be backtested.
🔵 Setting
NDay Pivot Range Period : Using this entry you can specify the number of days to calculate NDay Pivot Range.
Show Daily Pivot Range : Set the Daily Pivot color and displayed or not.
Show NDay Pivot Range : Set the NDay Pivot color and displayed or not.
ATR Period Levels : Determining the period of the ATR indicator, which is used to determine the A and C levels.
Show Tokyo ACD Setup : Set the Tokyo ACD Setup color and displayed or not.
Tokyo Opening Range Time : The amount of time taken to determine the opening range. You can set this number between 5 and 60 minutes.
Tokyo Session : Market start and end time.
A Level Multiplier : The coefficient that is multiplied by ATR to determine the distance of line A up and A down.
C Level Multiplier : The coefficient that is multiplied by ATR to determine the distance of line C up and C down.
The same settings exist for the London and New York sessions.
ATR by Time [QuantVue]"ATR by Time" incorporates time-specific volatility patterns by calculating the Average True Range (ATR) over a customizable period and comparing it to historical ATR values
at specific times of the day.
The Average True Range (ATR) is a popular technical indicator that measures market volatility by decomposing the entire range of an asset price for that period.
By taking the ATR at certain times of the day and comparing it to the current bar's ATR, traders can gain several potential advantages:
Volatility Pattern Recognition: Different times of the trading day often exhibit different levels of volatility. For instance, markets might be more volatile at the open and close compared to midday. By tracking ATR at specific times, traders can recognize these patterns and better predict periods of high or low volatility.
Risk Management: Understanding volatility trends throughout the day helps in better risk management. During periods of high expected volatility (indicated by higher ATR compared to the historical average), traders can adjust their stop-loss levels and position sizes accordingly to protect their capital.
Trend Confirmation and Divergence: This indicator can help confirm trends or identify potential reversals. For example, if the current ATR consistently exceeds the average ATR at specific times, it may confirm a strong trend. Conversely, if the current ATR falls below the historical average, it could signal a potential slowdown or reversal.
This indicator will work on all markets on all time frames. User can customize ATR length as well as the lookback period.
This script utilizes TradingView's RelativeValue library and averageAtTime function, which is used to compare a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
Trade Exit Calculator [MarketSignalsPro]█ OVERVIEW
This Pine Script calculates a Stop Loss and Take Profit order suggestion based on the Average True Range (ATR). This provides a market generated visual reference for the user to better gauge risk and profit potential for their trades. This is not a trade signal system, it is a tool best used in conjunction with an existing system.
█ FEATURES
Inputs:
stopLossMultiplier and takeProfitMultiplier : These are input parameters that allow the user to adjust the multiplier for calculating stop loss and take profit levels.
longIndicator : This input parameter determines whether the script is calculating levels for a long setup (buy) or a short setup (sell).
Variable Initialization:
Various variables are initialized to manage labels, lines, and calculated stop loss and take profit levels.
ATR (Average True Range) is calculated using a period of 14.
Calculation of Stop Loss and Take Profit:
Depending on the value of longIndicator stop loss and take profit levels are not calculated the same way.
For long setups, stop loss is calculated below the closing price and take profit above, while for short setups, it's the opposite.
The calculation involves multiplying the ATR value by the user-defined multipliers and adding or subtracting from the closing price accordingly.
Plotting Lines:
Lines representing the calculated stop loss, take profit, and entry price are plotted on the chart.
Displaying Labels:
Labels displaying the calculated stop loss, take profit, and entry price are shown on the chart alongside the respective lines.
Updating and Deleting Objects:
Existing lines and labels are updated or deleted to ensure only the most recent levels are displayed on the chart.
Final Output:
The script outputs visual representations of stop loss, take profit, and entry price levels on the chart, providing traders with guidance for risk management and profit-taking strategies based on the volatility of the market.
█ CONCLUSION
In summary, this Pine Script enhances trading strategies by calculating and illustrating stop loss and take profit levels based on the Average True Range indicator, offering traders a structured way to manage risk and profit potential.
█ THANKS
Special thanks to Cryptosnagger for taking the time to build this Pine Script and share it freely with the community.
Fourier Adjusted Average True Range [BackQuant]Fourier Adjusted Average True Range
1. Conceptual Foundation and Innovation
The FA-ATR leverages the principles of Fourier analysis to dissect market prices into their constituent cyclical components. By applying Fourier Transform to the price data, the FA-ATR captures the dominant cycles and trends which are often obscured in noisy market data. This integration allows the FA-ATR to adapt its readings based on underlying market dynamics, offering a refined view of volatility that is sensitive to both market direction and momentum.
2. Technical Composition and Calculation
The core of the FA-ATR involves calculating the traditional ATR, which measures market volatility by decomposing the entire range of price movements. The FA-ATR extends this by incorporating a Fourier Transform of price data to assess cyclical patterns over a user-defined period 'N'. This process synthesizes both the magnitude of price changes and their rhythmic occurrences, resulting in a more comprehensive volatility indicator.
Fourier Transform Application: The Fourier series is calculated using price data to identify the fundamental frequency of market movements. This frequency helps in adjusting the ATR to reflect more accurately the current market conditions.
Dynamic Adjustment: The ATR is then adjusted by the magnitude of the dominant cycle from the Fourier analysis, enhancing or reducing the ATR value based on the intensity and phase of market cycles.
3. Features and User Inputs
Customizability: Traders can modify the Fourier period, ATR period, and the multiplication factor to suit different trading styles and market environments.
Visualization : The FA-ATR can be plotted directly on the chart, providing a visual representation of volatility. Additionally, the option to paint candles according to the trend direction enhances the usability and interpretative ease of the indicator.
Confluence with Moving Averages: Optionally, a moving average of the FA-ATR can be displayed, serving as a confluence factor for confirming trends or potential reversals.
4. Practical Applications
The FA-ATR is particularly useful in markets characterized by periodic fluctuations or those that exhibit strong cyclical trends. Traders can utilize this indicator to:
Adjust Stop-Loss Orders: More accurately set stop-loss orders based on a volatility measure that accounts for cyclical market changes.
Trend Confirmation: Use the FA-ATR to confirm trend strength and sustainability, helping to avoid false signals often encountered in volatile markets.
Strategic Entry and Exit: The indicator's responsiveness to changing market dynamics makes it an excellent tool for planning entries and exits in a trend-following or a breakout trading strategy.
5. Advantages and Strategic Value
By integrating Fourier analysis, the FA-ATR provides a volatility measure that is both adaptive and anticipatory, giving traders a forward-looking tool that adjusts to changes before they become apparent through traditional indicators. This anticipatory feature makes it an invaluable asset for traders looking to gain an edge in fast-paced and rapidly changing market conditions.
6. Summary and Usage Tips
The Fourier Adjusted Average True Range is a cutting-edge development in technical analysis, offering traders an enhanced tool for assessing market volatility with increased accuracy and responsiveness. Its ability to adapt to the market's cyclical nature makes it particularly useful for those trading in highly volatile or cyclically influenced markets.
Traders are encouraged to integrate the FA-ATR into their trading systems as a supplementary tool to improve risk management and decision-making accuracy, thereby potentially increasing the effectiveness of their trading strategies.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Volatility ATR Support and Resistance Bands [Quantigenics]Volatility ATR Support and Resistance Bands
The “Volatility ATR Support and Resistance Bands” is a trend visualization tool that uses Average True Range (ATR) to create a dynamic channel around price action, adapting to changes in volatility and offering clear trend indicators. The band direction can indicate trend and the lines can indicate support and resistance levels.
The script works by calculating a series of moving averages from the highest and lowest prices, then applies an ATR-based multiplier to generate a set of bands. These bands expand and contract with the market’s volatility, providing a visual guide to the strength and potential direction of price movements.
How to Trade with Volatility ATR Band:
Identify Trend Direction: When the bands slope upwards, the market is trending upwards, which may be a good opportunity to consider a long position. When the bands slope downward, the market is trending downwards, which could be a sign to sell or short.
Volatility Awareness: The wider the bands, the higher the market volatility. Narrow bands suggest a quieter market, which might indicate consolidation or a potential breakout/breakdown.
Confirm Entries and Exits: Use the bands as dynamic support and resistance; entering trades as the price bounces off the bands and considering exits as it reaches the opposite side or breaches the bands.
Hope you enjoy this script!
Happy trading!
AminioLibraryLibrary "AminioLibrary"
: this is my personal library that is being used in different indicators and strategies
calculateMA(source, len, maType)
This fuction returns a moving average value based on the type
Parameters:
source (float) : Is the time series source to calculate average from
len (simple int) : The length of the moving average, this should be integer
maType (string) : The type of moving average, acceptable types are : SMA, HMA, EMA, RMA, WMA, VWMA
Returns: value of moving average
atr(source, len)
This fuction returns atr value for a given source
Parameters:
source (float) : Is the time series source to calculate atr from
len (simple int) : The length of the atr, this should be integer
Returns: value of atr from source
superTrend(source, factor, len)
This fuction returns value of super trend indicator and the trend direction as a tupple
Parameters:
source (float) : Is the time series source to calculate super trend from
factor (simple float) : The multiplication factor for upper and lower band calcualtion, this can be a float
len (simple int) : The length of the super trend, this should be integer
Returns: value of atr from source
halfTrend(am, chdev)
This fuction returns a hTrend type carrying different values for half trend indicator
Parameters:
am (int) : This is the amplitude used for calcucating the half trend, use integers
chdev (float) : This is the Channel Deviation value used for calculating upper and lower atr channel boundaries, you can use floats
Returns: hTrend data type
hTrend
Fields:
halfTrend (series__float)
trend (series__integer)
atrHigh (series__float)
atrLow (series__float)
arrowUp (series__float)
arrowDown (series__float)
RSI and ATR Trend Reversal SL/TPQuick History:
I was frustrated with a standard fixed percent TP/SL as they often were not receptive to quick market rallies/reversals. I developed this TP/SL and eventually made it into a full fledge strategy and found it did well enough to publish. This strategy can be used as a standalone or tacked onto another strategy as a TP/SL. It does function as both with a single line. This strategy has been tested with TSLA , AAPL, NVDA, on the 15 minutes timeframe.
HOW IT WORKS:
Inputs:
Length: Simple enough, it determines the length of the RSI and ATR used.
Multiplier: This multiplies the RSI and ATR calculation, more on this later.
Delay to prevent Idealization: TradingView will use the open of the bar the strategy triggers on when calculating the backtest. This can produce unrealistic results depending on the source. If your source is open, set to 0, if anything else, set to 1.
Minimum Difference: This is essentially a traditional SL/TP, it is borderline unnecessary, but if the other parameters are wacky this can be used to ensure the SL/TP. It multiplies the source by the percent, so if it is set to 10, the SL/TP is initialized at src +- 10%.
Source input: Self Explanatory, be sure to update the Delay if you use open.
CALCULATION:
Parameters Initialization:
The strategy uses Heikinashi values for calculations, this is not toggleable in parameters, but can be easily changed by changing hclose to equal src.
FUNCTION INITIALIZATION:
highest_custom and lowest_custom do the same thing as ta.highest and ta.lowest, however the built in ta library does not allow for var int input, so I had to create my own functions to be used here. I actually developed these years ago and have used them in almost every strategy since. Feel especially free to use these in your own scripts.
The rsilev is where the magic happens.
SL/TP min/max are initially calculated to be used later.
Then we begin by establishing variables.
BullGuy is used to determine the length since the last crossup or crossdown, until one happens, it returns na, breaking the function. BearGuy is used in all the calculations, and is the same as BullGuy, unless BullGuy is na, where BearGuy counts up from 1 on each bar from 0.
We create our rsi and have to modify the second one to suit the function. In the case of the upper band, we mirror the lower one. So if the RSI is 80, we want it to be 20 on the upper band.
the upper band and lower band are calculated the exact same way, but mirrored. For the purpose of writing, I'm going to talk about the lower band. Assume everything is mirrored for the upper one. It finds the highest source since the last crossup or crossdown. It then multiplies from 1 / the RSI, this means that a rapid RSI increase will increase the band dramatically, so it is able to capture quick rally/reversals. We add this to the atr to source ratio, as the general volatility is a massive factor to be included. We then multiply this number by our chosen amount, and subtract it from the highest source, creating the band.
We do this same process but mirrored with both bands and compared it to the source. If the source is above the lower band, it suggests an uptrend, so the lower band is outputted, and vice versa for the upper one.
PLOTTING:
We also determine the line color in the same manner as we do the trend direction.
STRATEGY:
We then use the source again, and if it crosses up or down relative to the selected band, we enter a long or short respectively.
This may not be the most superb independent strategy, but it can be very useful as a TP/SL for your chosen entry conditions, especially in volatile markets or tickers.
Thank you for taking the time to read, and please enjoy.
UT Bot Stochastic RSIUT Bot Stochastic RSI is a powerful trading tool designed to help traders identify potential buy and sell signals in the market. This indicator combines the Stochastic and RSI (Relative Strength Index) oscillators, two of the most popular and effective technical analysis tools, to provide a comprehensive view of market conditions.
The Stochastic oscillator is a momentum indicator that compares a security's closing price to its price range over a given time period. The RSI, on the other hand, is a momentum oscillator that measures the speed and change of price movements. By combining these two indicators, the UT Bot Stochastic RSI can help traders identify overbought and oversold conditions, as well as potential trend reversals.
The UT Bot Stochastic RSI also includes an ATR (Average True Range) trailing stop, which can be used to set stop-loss levels and manage risk. This feature is particularly useful in volatile markets, where price movements can be large and unpredictable.
In addition to its powerful technical analysis tools, the UT Bot Stochastic RSI also includes a backtesting feature, allowing traders to test their strategies on historical data. This can help traders identify the most effective settings for the indicator and improve their trading performance.
Overall, the UT Bot Stochastic RSI is a versatile and effective tool for traders of all levels, providing valuable insights into market conditions and helping to improve trading decisions
