ICT Single Candle Order Block (SCOB) [UAlgo]The "ICT Single Candle Order Block (SCOB) " designed for traders who utilize the concept of Order Blocks in their trading strategy. Order Blocks are significant price levels where institutions or smart money have placed their trades, leading to potential future price reactions when these levels are revisited. This indicator focuses on identifying and highlighting Single Candle Order Blocks (SCOBs), allowing traders to visually analyze key price levels on their charts.
🔶 What is Single Candle Order Block (SCOB) ?
A Single Candle Order Block (SCOB) is a specific type of Order Block that is identified based on a single candlestick pattern. These patterns indicate potential areas where significant buying or selling interest has occurred, often leading to a notable price reaction when revisited. In the context of this indicator, a bullish SCOB is identified when a specific bullish candlestick pattern is met, and a bearish SCOB is identified based on a bearish candlestick pattern.
Bullish SCOB: Detected when the open price of two bars ago is higher than its close, the close price of the previous bar is higher than its open, the current close price is higher than the open, the low of the previous bar is lower than the low of two bars ago, and the current close is higher than the high of the previous bar.
Bearish SCOB: Detected when the open price of two bars ago is lower than its close, the close price of the previous bar is lower than its open, the current close price is lower than the open, the high of the previous bar is higher than the high of two bars ago, and the current close is lower than the low of the previous bar.
🔶 Key Features
Show Single Candle Order Block (SCOB): Toggle the visibility of the Single Candle Order Blocks on the chart.
Mitigation Method: Choose between "Close" and "Wick" methods for determining whether a SCOB has been mitigated (price has interacted with the block).
Show Last X SCOBs: Control the number of most recent SCOBs displayed on the chart, allowing you to focus on the most relevant price levels.
Volatility Filter: Enable or disable the volatility filter, which uses the Average True Range (ATR) to filter out less significant SCOBs. When enabled, only SCOBs with an ATR above the mean value of the ATR are displayed.
Customizable Colors: Configure the colors for bullish and bearish SCOBs to enhance visual clarity. The indicator uses cooler RGB values to ensure the blocks are distinct and easily noticeable.
🔶 Disclaimer
The "ICT Single Candle Order Block (SCOB) " indicator is provided for educational and informational purposes only. Trading involves significant risk and may not be suitable for all investors.
Past performance is not indicative of future results. Users should use this indicator in conjunction with their own research and trading strategy.
Volatility
VWAP Bands [UAlgo]The "VWAP Bands " indicator is designed to provide traders with valuable insights into market trends and potential support/resistance levels using Volume Weighted Average Price (VWAP) bands. This indicator integrates the core concepts of VWAP with additional trend analysis features, making it a versatile tool for both range trading and trend-following strategies.
The VWAP bands are plotted based on the standard deviation multipliers, creating upper and lower bands around the VWAP. These bands serve as dynamic support and resistance levels. When the price approaches these bands, traders can anticipate potential reversals or continuations of the current trend. Additionally, the indicator provides visual cues for trend strength and potential trend changes, helping traders make informed decisions in various market conditions.
🔶 Settings
Source (Data Source): The data source for VWAP calculations. The default setting is the typical price (HLC3), which is the average of the high, low, and close prices.
Length: The number of bars used in the VWAP calculation. This determines the lookback period for the indicator.
Standard Deviation Multiplier: The multiplier applied to the standard deviation to create the primary upper and lower VWAP bands. This setting controls the distance of the bands from the VWAP.
Secondary Standard Deviation Multiplier: The multiplier applied to the standard deviation to create the secondary upper and lower VWAP bands, providing additional levels of support and resistance.
Display Trend: A toggle to enable or disable the display of the trend analysis feature. When enabled, the indicator highlights trend strength and potential trend changes.
Display Trend Crossovers: A toggle to enable or disable the display of trend crossover signals. When enabled, the indicator plots shapes to indicate where trend switches are likely occurring.
🔶 Calculations
The calculations behind the "VWAP Bands " indicator begin with determining the Volume Weighted Average Price (VWAP), which provides a comprehensive view of the average price of an asset, weighted by trading volume. This gives a more accurate representation of the asset's true average price over a specified period.
The first step in this process involves summing the trading volume over a chosen period, typically represented by the length parameter. Simultaneously, the product of the price (usually an average of the high, low, and close prices) and the trading volume is calculated and summed. By dividing this cumulative price-volume product by the total volume, we obtain the VWAP value. This VWAP serves as the central anchor around which the price action oscillates.
To enhance the utility of VWAP, we introduce standard deviation calculations. Standard deviation measures the extent of price dispersion from the VWAP, providing insight into price volatility. By calculating the variance (which involves the squared deviations of price) and then taking its square root, we derive the standard deviation. This helps in understanding how far prices typically stray from the VWAP.
With the VWAP and standard deviation in hand, we then establish upper and lower bands by adding and subtracting multiples of the standard deviation from the VWAP. These bands act as dynamic support and resistance levels, adapting to changes in market volatility. The primary bands, set by the first standard deviation multiplier, are augmented by secondary bands defined by a larger multiplier, offering additional layers of potential support and resistance.
It also integrates trend analysis, highlighting areas where the price action suggests a strong or weak trend. This is achieved by overlaying colored zones above and below the bands, indicating the strength and direction of the trend. When the price crosses these bands, it signals potential trend changes, aiding traders in making timely decisions.
🔶 Disclaimer
The "VWAP Bands " indicator is provided for educational and informational purposes only. It is not intended as financial advice and should not be construed as such.
Trading involves significant risk and may not be suitable for all investors. Before using this indicator or making any investment decisions, it is important to conduct thorough research and consider your financial situation.
Supports & Resistances [UAlgo]The "Supports & Resistances " indicator is designed to identify and visualize key support and resistance levels on the price chart. It utilizes the Average True Range (ATR) and Pivot Points to define the boundaries of S & R zones and considers historical price action to assess the strength of these zones.
🔶 How to Obtain Zones
The script continuously analyzes the price action and identifies potential support and resistance zones based on the following criteria:
Zone Creation: For swing highs, a zone is created with the high price at the zone length as the top and the top minus the Average True Range (ATR) as the bottom. Conversely, for swing lows, the zone is created with the low price at the zone length as the bottom and the low plus the ATR as the top.
Zone Strength Calculation: The script iterates through historical bars within the zone and counts how many times the price (low for support, high for resistance) touched but failed to break entirely through the zone. This count is assigned as the zone's "strength".
Zone Display and Removal: It identifying zones by assigning a "strength" value based on how many times the price has approached but failed to break the zone. This helps prioritize stronger potential support/resistance levels. Only zones exceeding the defined "strength threshold" are visually displayed on the chart. Weaker zones or those broken by price are automatically removed.
🔶 Parameters
Zone Length: Traders can adjust S & R detection sensitivity, length to be used to find pivot points.
Strength Threshold: Set the minimum number of times the price needs to touch but fail to break a zone for it to be considered "strong" and displayed.
Visual Settings: Tailor the appearance of the support/resistance zones by defining separate colors and text size for borders, backgrounds, and zone text.
🔶 Disclaimer
The "Supports & Resistances " indicator is provided for educational and informational purposes only.
It should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
The use of this indicator involves inherent risks, and users should employ their own judgment and conduct their own research before making any trading decisions. Past performance is not indicative of future results.
🔷 Related Scripts
Support and Resistance with Signals
ATR Based Support and Resistance Zones
Matt Liq LinesIndicator Overview
The "Matt Liq Lines" indicator is designed to help traders identify significant price levels where high-volume trading occurred. These levels are often referred to as liquidation levels and can act as support or resistance in the market. The indicator plots horizontal lines on the chart at these identified levels, helping traders make informed decisions based on volume spikes.
Key Features
Volume Multiplier: A user-defined threshold to identify high-volume candles. If a candle's volume is greater than the average volume multiplied by this multiplier, it is considered a high-volume candle.
Lookback Period: The period over which the average volume is calculated. This helps in smoothing out volume data to identify significant spikes.
Max Levels: The maximum number of liquidation levels to display on the chart. This helps in keeping the chart clean and focuses on the most relevant levels.
Indicator Components
Average Volume Calculation:
avgVolume = ta.sma(volume, lookbackPeriod)
Calculates the simple moving average (SMA) of the volume over the specified lookback period.
High Volume Identification:
highVolume = volume > (avgVolume * volumeMultiplier)
Identifies if the current candle's volume is greater than the average volume multiplied by the volume multiplier.
Liquidation Levels Storage:
Uses arrays to store the levels, their corresponding bar indices, and volumes.
Adding Liquidation Levels:
When a high-volume candle is identified, its open price is added as a liquidation level. If the maximum number of levels is exceeded, the oldest level is removed to make room for the new one.
Cleaning Levels:
A function f_clean_levels removes crossed levels (where the price has already moved above and below the level) and keeps the levels with the highest volumes.
Plotting Liquidation Lines:
Horizontal lines are drawn at the identified liquidation levels. These lines extend to the right and help traders visualize important price levels.
How to Use the Indicator
Set the Volume Multiplier: Adjust the volume multiplier to filter out minor volume spikes and focus on significant ones.
Adjust the Lookback Period: Set a lookback period that reflects the typical trading volume for the asset you are analyzing.
Configure Max Levels: Decide the number of levels you want to display on the chart to avoid clutter.
Interpret the Lines: Use the plotted lines as potential support or resistance levels. These lines indicate where significant trading activity has occurred, which could influence future price movements.
By following these steps and understanding the indicator's components, traders can effectively use the "Matt Liq Lines" indicator to identify key price levels influenced by high trading volumes, aiding in better decision-making
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
Volume-Adjusted Bollinger BandsThe Volume-Adjusted Bollinger Bands (VABB) indicator is an advanced technical analysis tool that enhances the traditional Bollinger Bands by incorporating volume data. This integration allows the bands to dynamically adjust based on market volume, providing a more nuanced view of price movements and volatility. The key qualities of the VABB indicator include:
1. Dynamic Adjustment with Volume: Traditional Bollinger Bands are based solely on price data and standard deviations. The VABB indicator adjusts the width of the bands based on the volume ratio, making them more responsive to changes in market activity. This means that during periods of high volume, the bands will expand, and during periods of low volume, they will contract. This adjustment helps to reinforce the significance of price movements relative to the central line (VWMA).
2. Volume-Weighted Moving Average (VWMA): Instead of using a simple moving average (SMA) as the central line, the VABB uses the VWMA, which weights prices by volume. This provides a more accurate representation of the average price level, considering the trading volume.
3. Enhanced Signal Reliability: By incorporating volume, the VABB can filter out false signals that might occur in low-volume conditions. This makes the indicator particularly useful for identifying significant price movements that are supported by strong trading activity.
How to Use and Interpret the VABB Indicator
To use the VABB indicator, you need to set it up on your trading platform with the following parameters:
1. BB Length: The number of periods for calculating the Bollinger Bands (default is 20).
2. BB Multiplier: The multiplier for the standard deviation to set the width of the Bollinger Bands (default is 2.0).
3. Volume MA Length: The number of periods for calculating the moving average of the volume (default is 14).
Volume Ratio Smoothing Length: The number of periods for smoothing the volume ratio (default is 5).
Interpretation
1.Trend Identification: The VWMA serves as the central line. When the price is above the VWMA, it indicates an uptrend, and when it is below, it indicates a downtrend. The direction of the VWMA itself can also signal the trend's strength.
2. Volatility and Volume Analysis: The width of the VABB bands reflects both volatility and volume. Wider bands indicate high volatility and/or high volume, suggesting significant price movements. Narrower bands indicate low volatility and/or low volume, suggesting consolidation.
3. Trading Signals:
Breakouts: A price move outside the adjusted upper or lower bands can signal a potential breakout. High volume during such moves reinforces the breakout's validity.
Reversals: When the price touches or crosses the adjusted upper band, it may indicate overbought conditions, while touching or crossing the adjusted lower band may indicate oversold conditions. These conditions can signal potential reversals, especially if confirmed by other indicators or volume patterns.
Volume Confirmation: The volume ratio component helps confirm the strength of price movements. For instance, a breakout accompanied by a high volume ratio is more likely to be sustained than one with a low volume ratio.
Practical Example
Bullish Scenario: If the price crosses above the adjusted upper band with a high volume ratio, it suggests a strong bullish breakout. Traders might consider entering a long position, setting a stop-loss just below the VWMA or the lower band.
Bearish Scenario: Conversely, if the price crosses below the adjusted lower band with a high volume ratio, it suggests a strong bearish breakout. Traders might consider entering a short position, setting a stop-loss just above the VWMA or the upper band.
Conclusion
The Volume-Adjusted Bollinger Bands (VABB) indicator is a powerful tool that enhances traditional Bollinger Bands by incorporating volume data. This dynamic adjustment helps traders better understand market conditions and make more informed trading decisions. By using the VABB indicator, traders can identify significant price movements supported by volume, improving the reliability of their trading signals.
The Volume-Adjusted Bollinger Bands (VABB) indicator is provided for educational and informational purposes only. It is not financial advice and should not be construed as a recommendation to buy, sell, or hold any financial instrument. Trading involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results.
ADX with Donchian Channels
The "ADX with Donchian Channels" indicator combines the Average Directional Index (ADX) with Donchian Channels to provide traders with a powerful tool for identifying trends and potential breakouts.
Features:
Average Directional Index (ADX):
The ADX is used to quantify the strength of a trend. It helps traders determine whether a market is trending or ranging.
Adjustable parameters for ADX smoothing and DI length allow traders to fine-tune the sensitivity of the trend strength measurement.
Donchian Channels on ADX:
Donchian Channels are applied directly to the ADX values to highlight the highest high and lowest low of the ADX over a specified period.
The upper and lower Donchian Channels can signal potential trend breakouts when the ADX value moves outside these bounds.
The middle Donchian Channel provides a reference for the average trend strength.
Visualization:
The indicator plots the ADX line in red to clearly display the trend strength.
The upper and lower Donchian Channels are plotted in blue, with a green middle line to represent the average.
The area between the upper and lower Donchian Channels is filled with a blue shade to visually emphasize the range of ADX values.
Default Settings for Scalping:
Donchian Channel Length: 10
Standard Deviation Multiplier: 1.58
ADX Length: 2
ADX Smoothing Length: 2
These default settings are optimized for scalping, offering a quick response to changes in trend strength and potential breakout signals. However, traders can adjust these settings to suit different trading styles and market conditions.
How to Use:
Trend Strength Identification: Use the ADX line to identify the strength of the current trend. Higher ADX values indicate stronger trends.
Breakout Signals: Monitor the ADX value in relation to the Donchian Channels. A breakout above the upper channel or below the lower channel can signal a potential trend continuation or reversal.
Range Identification: The filled area between the Donchian Channels provides a visual representation of the ADX range, helping traders identify when the market is ranging or trending.
This indicator is designed to enhance your trading strategy by combining trend strength measurement with breakout signals, making it a versatile tool for various market conditions.
[MAD] Custom Session VWAP BandsOverview
This indicator helps visualize the Volume Weighted Average Price (VWAP) and its associated standard deviation bands over specified time periods, providing traders with a clear understanding of price trends, volatility, and potential support/resistance levels.
Inputs
Deviation
StDev mult 1: Multiplier for the first standard deviation band (Default: 1.0)
StDev mult 2: Multiplier for the second standard deviation band (Default: 2.0)
StDev mult 3: Multiplier for the third standard deviation band (Default: 3.0)
StDev mult 4: Multiplier for the fourth standard deviation band (Default: 4.0)
Line width: Width of the lines for the bands (Default: 2)
Custom Vwap session reset settings
Many different options are considered when a session is going to be reset.
Plot and Fill Options
Enable Fills: Enable/disable filling between bands.
Plot +4: Enable/disable plotting the +4 standard deviation band.
Plot +3: Enable/disable plotting the +3 standard deviation band.
Plot +2: Enable/disable plotting the +2 standard deviation band.
Plot +1: Enable/disable plotting the +1 standard deviation band.
Plot VWAP: Enable/disable plotting the VWAP line.
Plot -1: Enable/disable plotting the -1 standard deviation band.
Plot -2: Enable/disable plotting the -2 standard deviation band.
Plot -3: Enable/disable plotting the -3 standard deviation band.
Plot -4: Enable/disable plotting the -4 standard deviation band.
How to Use the Indicator
Adding the Indicator
Add the indicator to your chart through your trading platform's indicator menu.
Configuring the VWAP Reset
Specify reset intervals based on time, days of the week, or specific dates.
Adjust the time zone if necessary.
Customizing Standard Deviation Bands
Set the multipliers for the standard deviation bands.
Choose line width for better visualization.
Enabling Plots and Fills
Select which bands to display.
Enable or disable fills between the bands.
Practical Application of VWAP Bands
Understanding VWAP
VWAP is a trading benchmark that calculates the average price a security has traded at throughout the day based on volume and price. It is primarily used for intraday trading but can also offer insights during end-of-day reviews.
Using VWAP for Trading
Intraday Trading
Entry and Exit Points: VWAP can help identify optimal buy and sell points. Buy when the price is above VWAP and sell when it's below.
Support and Resistance: VWAP often acts as a dynamic support/resistance level. Prices tend to revert to VWAP, making it a crucial level for intraday traders.
Trend Confirmation
Uptrends and Downtrends: In an uptrend, the price will generally stay above VWAP. Conversely, in a downtrend, it will stay below. Use this to confirm market direction.
Combining with Other Indicators
Moving Averages and Bollinger Bands: Combining VWAP with these indicators can provide a more robust trading signal, confirming trends and potential reversals.
Setting Stop-Loss and Profit Targets
Conservative Stop Orders: Place stop orders at recent lows for pullback trades.
Profit Targets: Use daily highs or Fibonacci extension levels to set profit targets.
Strategies for Using VWAP
Pullback Strategy
Buy during pullbacks to VWAP in an uptrend, and sell during rallies to VWAP in a downtrend.
Breakout Strategy
Look for breakouts above/below VWAP after the market open to capitalize on new trends.
Momentum Trading
Use VWAP to confirm the strength of a trend. Buy when the price is consistently above VWAP and sell when it's consistently below.
Institutional Strategies
Institutional traders use VWAP to execute large orders without causing significant market impact, ensuring trades are made around the average price.
By incorporating these strategies, traders can better understand market dynamics, make informed trading decisions, and manage their risk effectively.
Some setup possibilities
KillZones + ACD Fisher [TradingFinder] Sessions + Reversal Level🔵 Introduction
🟣 ACD Method
"The Logical Trader" opens with a thorough exploration of the ACD Methodology, which focuses on pinpointing particular price levels associated with the opening range.
This approach enables traders to establish reference points for their trades, using "A" and "C" points as entry markers. Additionally, the book covers the concept of the "Pivot Range" and how integrating it with the ACD method can help maximize position size while minimizing risk.
🟣 Session
The forex market is operational 24 hours a day, five days a week, closing only on Saturdays and Sundays. Typically, traders prefer to concentrate on one specific forex trading session rather than attempting to trade around the clock.
Trading sessions are defined time periods when a particular financial market is active, allowing for the execution of trades.
The most crucial trading sessions within the 24-hour cycle are the Asia, London, and New York sessions, as these are when substantial money flows and liquidity enter the market.
🟣 Kill Zone
Traders in financial markets earn profits by capitalizing on the difference between their buy/sell prices and the prevailing market prices.
Traders vary in their trading timelines.Some traders engage in daily or even hourly trading, necessitating activity during periods with optimal trading volumes and notable price movements.
Kill zones refer to parts of a session characterized by higher trading volumes and increased price volatility compared to the rest of the session.
🔵 How to Use
🟣 Session Times
The "Asia Session" comprises two parts: "Sydney" and "Tokyo." This session begins at 23:00 and ends at 06:00 UTC. The "Asia KillZone" starts at 23:00 and ends at 03:55 UTC.
The "London Session" includes "Frankfurt" and "London," starting at 07:00 and ending at 14:25 UTC. The "London KillZone" runs from 07:00 to 09:55 UTC.
The "New York" session starts at 14:30 and ends at 19:25 UTC, with the "New York am KillZone" beginning at 14:30 and ending at 22:55 UTC.
🟣 ACD Methodology
The ACD strategy is versatile, applicable to various markets such as stocks, commodities, and forex, providing clear buy and sell signals to set price targets and stop losses.
This strategy operates on the premise that the opening range of trades holds statistical significance daily, suggesting that initial market movements impact the market's behavior throughout the day.
Known as a breakout strategy, the ACD method thrives in volatile or strongly trending markets like crude oil and stocks.
Some key rules for employing the ACD strategy include :
Utilize points A and C as critical reference points, continually monitoring these during trades as they act as entry and exit markers.
Analyze daily and multi-day pivot ranges to understand market trends. Prices above the pivots indicate an upward trend, while prices below signal a downward trend.
In forex trading, the ACD strategy can be implemented using the ACD indicator, a technical tool that gauges the market's supply and demand balance. By evaluating trading volume and price, this indicator assists traders in identifying trend strength and optimal entry and exit points.
To effectively use the ACD indicator, consider the following :
Identifying robust trends: The ACD indicator can help pinpoint strong, consistent market trends.
Determining entry and exit points: ACD generates buy and sell signals to optimize trade timing.
Bullish Setup :
When the "A up" line is breached, it’s wise to wait briefly to confirm it’s not a "Fake Breakout" and that the price stabilizes above this line.
Upon entering the trade, the most effective stop loss is positioned below the "A down" line. It's advisable to backtest this to ensure the best outcomes. The recommended reward-to-risk ratio for this strategy is 1, which should also be verified through backtesting.
Bearish Setup :
When the "A down" line is breached, it’s prudent to wait briefly to ensure it’s not a "Fake Breakout" and that the price stabilizes below this line.
Upon entering the trade, the most effective stop loss is positioned above the "A up" line. Backtesting is recommended to confirm the best results. The recommended reward-to-risk ratio for this strategy is 1, which should also be validated through backtesting.
Advantages of Combining Kill Zone and ACD Method in Market Analysis :
Precise Trade Timing : Integrating the Kill Zone strategy with the ACD Method enhances precision in trade entries and exits. The ACD Method identifies key points for trading, while the Kill Zone focuses on high-activity periods, together ensuring optimal timing for trades.
Better Trend Identification : The ACD Method’s pivot ranges help spot market trends, and when combined with the Kill Zone’s emphasis on periods of significant price movement, traders can more effectively identify and follow strong market trends.
Maximized Profits and Minimized Risks : The ACD Method's structured approach to setting price targets and stop losses, coupled with the Kill Zone's high-volume trading periods, helps maximize profit potential while reducing risk.
Robust Risk Management : Combining these methods provides a comprehensive risk management strategy, strategically placing stop losses and protecting capital during volatile periods.
Versatility Across Markets : Both methods are applicable to various markets, including stocks, commodities, and forex, offering flexibility and adaptability in different trading environments.
Enhanced Confidence : Using the combined insights of the Kill Zone and ACD Method, traders gain confidence in their decision-making process, reducing emotional trading and improving consistency.
By merging the Kill Zone’s focus on trading volumes and the ACD Method’s structured breakout strategy, traders benefit from a synergistic approach that enhances precision, trend identification, and risk management across multiple markets.
Scalping System by Machine# Custom Trading System Indicator
This Pine Script indicator is designed to identify potential trading setups based on a specific set of rules. It's intended for use on lower timeframes (M1-M5) in the forex market, particularly during the New York-London overlap period.
## Key Features
1. **EMA Condition**: Uses a 20-period Exponential Moving Average (EMA) to determine trend direction.
2. **Candle Analysis**: Identifies strong bars and candle color changes.
3. **Volume Confirmation**: Checks for increasing volume.
4. **Volatility Filter**: Utilizes the Average True Range (ATR) to gauge market volatility.
5. **Time-based Filter**: Highlights the New York-London overlap period.
6. **Visual Aids**: Plots potential entry points, stop losses, and take profit levels.
## Trading Rules
1. **Buy Signal**:
- Price is above the 20 EMA
- Candle color changes from red to green
- Current candle is a strong bar (closing within 75% of its range)
- Volume is higher than the previous bar
- ATR(14) is above 4 pips OR it's during the NY-London overlap
2. **Sell Signal**:
- Price is below the 20 EMA
- Candle color changes from green to red
- Current candle is a strong bar (closing within 75% of its range)
- Volume is higher than the previous bar
- ATR(14) is above 4 pips OR it's during the NY-London overlap
3. **Stop Loss**: Placed near the low of the setup candle for buys, or near the high for sells.
4. **Take Profit**: Aimed at 1R (one times the range of the setup candle).
## Visual Elements
- **20 EMA**: Plotted as a blue line on the chart.
- **Buy Signals**: Green triangles below the candles.
- **Sell Signals**: Red triangles above the candles.
- **Stop Loss Levels**: Small red dots at the calculated stop loss prices.
- **Take Profit Levels**: Small green dots at the calculated take profit prices.
- **Information Table**: Displays current values for ATR, strong bar condition and volume condition.
## Usage Notes
1. This indicator is designed for manual trading, not automated execution.
2. It works best when combined with analysis of major trend lines, support, and resistance levels.
3. Exercise caution with very large setup candles.
4. Consider additional filters or money management rules for enhanced performance.
5. For higher timeframe bias validation, consider incorporating a 100-period break of structure (BOS) analysis.
## Customization
The indicator includes several input parameters that can be adjusted:
- EMA Length
- ATR Length and Threshold
- Volume Multiplier
- Strong Bar Percentage
Users can also toggle the visibility of stop loss and take profit markers.
Remember, while this indicator can identify potential setups, it should be used in conjunction with other forms of analysis and risk management strategies. Always consider the overall market context and your personal risk tolerance when making trading decisions.
Glitch IndexGlitch Index is an oscillator from an unknown origin that is discovered in 2013 as a lua indicator taken from MetaStock days and we are not really sure how far back the original idea goes.
How it Works?
As I found this indicator and looking at it's code in different platform I can see it comes back from a basic idea of getting a price value, calculating it's smoothed average with a set multiplier and getting the difference then presenting it on a simplified scale. It appears to be another interpretation of figuring out price acceleration and velocity. The main logic is calculated as below:
price = priceSet(priceType)
_ma = getAverageName(price, MaMethod, MaPeriod)
rocma = ((_ma - _ma ) * 0.1) + 1
maMul = _ma * rocma
diff = price - maMul
gli_ind = (diff / price) * -10
How to Use?
Glitch Index can be used based on different implementations and along with your already existing trading system as a confirmation. Yoıu can use it as a Long signal when the histogram crosses inner levels or you can use it as an overbough and oversold signals when the histogram crosses above outter levels and gets back in the range between outter and inner levels.
You can customise the settings and set your prefered inner and outter levels in indicator settings along with gradient or static based coloring and modify the code as you see fit. The coloring code is set below:
gli_col = gli_ind > outterLevel ? color.green : gli_ind < -outterLevel ? color.red : gli_ind > innerLevel ? color.rgb(106, 185, 109, 57) : gli_ind < -innerLevel ? color.rgb(233, 111, 111, 40) : color.new(color.yellow, 60)
gradcol = color.from_gradient(gli_ind, -outterLevel, outterLevel, color.red, color.green)
colorSelect = colorType == "Gradient" ? gradcol : gli_col
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.
----------------------------------------------------------------------
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.
ALT - ATR Percent Rank🔵 Description
The "ALT - ATR Percent Rank" indicator is a financial analysis tool designed to assess the volatility of an asset relative to its historical behavior, using the Average True Range (ATR) metric.
🔵 Purpose
The indicator aims to provide traders with insights into how the current volatility of an asset compares to its past levels. By evaluating the Percent Rank of the ATR, traders can determine if the current ATR value is high or low in the context of a specified historical period.
🔵 Functionality
• Asset and Timeframe Flexibility
Selectable Asset: Users can choose to apply the indicator to a different asset than the one currently displayed on the chart. This is particularly useful for comparing the volatility of multiple assets without switching charts.
Customizable Timeframe: The indicator can be set to analyze the ATR on different timeframes, regardless of the chart's current timeframe. This allows for multi-timeframe analysis without changing the view of the current chart.
• ATR Calculation
The Average True Range (ATR) is calculated over a user-defined number of bars (ATR Length). ATR is a commonly used measure of volatility that captures the degree of price movement per bar.
REF: Average True Range (ATR) Calculation
• Percent Rank Analysis
The indicator computes the Percent Rank of the current ATR value based on a specified lookback period (Percent Rank Lookback). This tells users how the current ATR compares to ATR values over the recent past, expressed as a percentile. For example, a Percent Rank of 90% indicates that the current ATR is higher than 90% of its values over the chosen lookback period, suggesting higher volatility.
• Visualization
The result is plotted as a line on a separate panel below the main trading chart, making it easy to view changes in volatility relative to historical levels.
🔵 Use Cases
• Trend Confirmation
Traders might use the indicator to confirm if a price movement is backed by significant volatility changes, which could validate the strength of a trend.
• Risk Management
Understanding when an asset is experiencing unusually high or low volatility could help in adjusting trading strategies, such as altering position sizes or setting stop-loss orders.
• Comparative Analysis
By enabling the analysis of different assets or timeframes, traders can perform comparative volatility studies, which can be essential in portfolio management or when seeking diversification opportunities.
This indicator is a valuable tool for traders who rely on volatility analysis to make informed trading decisions, providing a clear, quantifiable measure of how current market conditions compare to historical data.
Wyckoff Springs [QuantVue]The Wyckoff Springs indicator is designed to identify potential bullish reversal patterns known as "springs" in the Wyckoff Method. A Wyckoff spring occurs when the price temporarily dips below a support level, then quickly rebounds, suggesting a false breakdown and a
potential buying opportunity.
How it works:
Pivot detection:
The indicator identifies pivot lows based on the specified pivot length.
These pivot points are stored and analyzed for potential spring patterns.
Volume and Range Checks:
If volume confirmation is enabled, the indicator checks if the current volume exceeds a threshold based on the average volume over the specified period.
The indicator ensures that the price undercuts the defined trading range before confirming a spring pattern.
Spring Identification
The indicator checks for price conditions indicative of a Wyckoff spring: a temporary dip below a pivot low followed by a close above it. The recovery must take place within 3 bars.
If these conditions are met, a spring label is placed below the bar.
Features:
Pivot Length:
The user can set the pivot length to match any style of trading.
Volume Confirmation:
An optional feature where the user can specify if volume confirmation is required for a spring signal.
Volume threshold can be set to determine what constitutes significant volume compared to the average volume over a specified period. By default it is set to 1.5
How to Trade a Spring:
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MA MACD BB BackTesterOverview:
This Pine Script™ code provides a comprehensive backtesting tool that combines Moving Average (MA), Moving Average Convergence Divergence (MACD), and Bollinger Bands (BB). It is designed to help traders analyze market trends and make informed trading decisions by testing various strategies over historical data.
Key Features:
1. Customizable Indicators:
Moving Average (MA): Smooths out price data for clearer trend direction.
MACD: Measures trend momentum through MACD Line, Signal Line, and Histogram.
Bollinger Bands (BB): Identifies overbought or oversold conditions with upper and lower bands.
2. Flexible Trading Direction: Choose between long or short positions to adapt to different market conditions.
3. Risk Management: Efficiently allocate your capital with customizable position sizes.
4. Signal Generation:
Buy Signals: Triggered by crossovers for MACD, MA, and BB.
Sell Signals: Triggered by crossunders for MACD, MA, and BB.
5. Automated Trading: Automatically enter and exit trades based on signal conditions and strategy parameters.
How It Works:
1. Indicator Selection: Select your preferred indicator (MA, MACD, BB) and trading direction (Long/Short).
2. Risk Management Configuration: Set the percentage of capital to allocate per position to manage risk effectively.
3.Signal Detection: The algorithm identifies and plots buy/sell signals directly on the chart based on the chosen indicator.
4. Trade Execution: The strategy automatically enters and exits trades based on signal conditions and configured strategy parameters.
Use Cases:
- Backtesting: Evaluate the effectiveness of trading strategies using historical data to understand potential performance.
- Strategy Development: Customize and expand the strategy to incorporate additional indicators or conditions to fit specific trading styles.
ADDONS That Affect Strategy:
1. Indicator Parameters:
Adjustments to the settings of MACD (e.g., fast length, slow length), MA (e.g., length), and BB (e.g., length, multiplier) will directly impact the detection of signals and the strategy's performance.
2. Trading Direction:
Changing the trading direction (Long/Short) will alter the entry and exit conditions based on the detected signals.
3. Risk Management Settings:
Modifying the position size percentage affects capital allocation and overall risk exposure per trade.
ADDONS That Do Not Affect Strategy:
1. Visual Customizations:
Changes to the color, shape, and style of the plotted lines and signals do not impact the core functionality of the strategy but enhance visual clarity.
2. Text and Labels:
Modifying text labels for the signals (such as renaming "Buy MACD" to "MACD Buy Signal") is purely cosmetic and does not influence the strategy’s logic or outcomes.
Notes:
- Customization: The indicator is highly customizable to fit various trading styles and market conditions.
- Risk Management: Adjust position sizes and risk parameters according to your risk tolerance and account size.
- Optimization: Regularly backtest and optimize parameters to adapt to changing market dynamics for better performance.
Getting Started:
-Add the script to your chart.
-Adjust the input parameters to suit your analysis preferences.
-Observe the marked buy and sell signals on your chart to make informed trading decisions.
[KVA] KATRThe KATR indicator enhances the traditional ATR by leveraging the most common candle body percentage range, tailoring volatility measurement to specific market contexts. This advanced tool provides more relevant insights tailored to current market conditions.
Key Features:
Configurable ATR Length : Allows users to set the period for the ATR calculation, providing flexibility to adapt to different trading strategies and timeframes.
Multiple Smoothing Options : Offers a choice of RMA, SMA, EMA, and WMA for smoothing the ATR, enabling traders to select the method that best suits their analysis style.
Histogram Visualization for ATR Differences: The histogram visually represents the difference between the ATR and its moving average. This difference, or "dif," is calculated and smoothed, then multiplied by a user-defined factor. The histogram color indicates market conditions:
Light Red: Increasing but below zero, signaling potential weakening.
Light Green: Increasing and above zero, indicating strengthening.
Dark Green: Decreasing but above zero, showing potential weakening.
Dark Red: Decreasing and below zero, indicating strong weakening.
Ideal for Traders:
This indicator is perfect for traders seeking precise, context-sensitive volatility assessments to optimize trade timing and risk management strategies. Integrated seamlessly with other technical indicators, the KATR enhances your trading dashboard by adding depth to volatility analysis.
Detailed Explanation:
ATR Calculation: The ATR is derived by taking the average true range over a specified period, multiplied by the most common body percentage found in historical data.
Smoothing: Users can smooth the ATR using different methods, adding flexibility and customization to suit various trading styles.
Histogram: The histogram's primary function is to visualize the difference between the current ATR and its smoothed average. This provides clear, visual signals for potential volatility expansions or contractions, aiding in better decision-making.
Whether you're a day trader or a long-term investor, the KATR helps you stay ahead of market trends with reliable and easy-to-interpret insights. Elevate your trading strategy with the KATR's innovative approach to volatility measurement.
Bollinger Bands Fast Trend Indicator [DCD]Description:
The Bollinger Bands Fast Trend Detector indicator is an advanced tool designed to provide traders with more precise trend detection and clearer entry and exit signals. This script builds upon the traditional Bollinger Bands indicator by adding customizable standard deviations and incorporating multiple moving averages to enhance the accuracy of the signals.
Main Features:
1. **Customizable Bollinger Bands**:
- Each Bollinger Band has its own standard deviation setting, allowing for more granular control and better trend detection.
- The short Bollinger Band is set to a 10-period SMA for faster trend recognition.
2. **Multiple Moving Averages**:
- The indicator includes several types of moving averages (SMA, EMA, LSMA, HMA, WMA) applied to the Bollinger Trend value, giving traders flexibility to choose the best fit for their strategy.
3. **Crossover and Crossdown Detection**:
- The script identifies crossover and crossdown points between the Bollinger Trend value and the selected moving average, marking potential buy and sell signals with green and red circles, respectively.
4. **Color-Coded Histogram**:
- The histogram bars are color-coded to indicate the strength and direction of the trend, making it easy to visualize market conditions at a glance.
Instructions:
1. **Adding the Script to Your Chart**:
- Open your TradingView chart and add the Bollinger Bands Fast Trend Detector indicator.
2. **Adjusting Parameters**:
- Customize the Bollinger Bands and moving average settings according to your trading preferences:
- `Short BB Length` (default: 10): Adjusts the length of the short Bollinger Band.
- `Long BB Length` (default: 50): Adjusts the length of the long Bollinger Band.
- `StdDev` (for both bands): Sets the standard deviation multiplier.
- `Moving Average Type`: Choose between SMA, EMA, LSMA, HMA, and WMA.
- `Moving Average Length` (default: 14): Sets the length of the moving average.
3. **Interpreting the Output**:
- Observe the BBTrend and moving average plots on your chart.
- Look for green circles indicating crossover points (potential buy signals) and red circles indicating crossdown points (potential sell signals).
- Use the color-coded histogram bars to assess the strength and direction of the trend.
Configurable Parameters:
- `shortLengthInput` (default: 10): Length of the short Bollinger Band.
- `longLengthInput` (default: 50): Length of the long Bollinger Band.
- `shortDevMultInput` (default: 1.0): Standard deviation multiplier for the short Bollinger Band.
- `longDevMultInput` (default: 2.0): Standard deviation multiplier for the long Bollinger Band.
- `maTypeInput` (default: SMA): Type of moving average (options: SMA, EMA, LSMA, HMA, WMA).
- `maLengthInput` (default: 14): Length of the moving average.
Code Explanation:
The script calculates two sets of Bollinger Bands with distinct lengths and standard deviations. The difference between the lower bands and upper bands is normalized by the short middle band to compute the BBTrend value. A selected moving average is then applied to this BBTrend value. The script plots the BBTrend, the moving average, and uses color-coded histogram bars to represent trend strength and direction. It also identifies and marks crossover and crossdown points to provide potential trading signals.
Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always perform your own analysis before making any trading decisions.
Dynamic Bollinger Bands with Momentum and Volume (DBBMV)Overview
The Dynamic Bollinger Bands with Momentum and Volume (DBBMV) indicator enhances the traditional Bollinger Bands by dynamically adjusting their width and position based on momentum and volume. This provides a more responsive and context-aware indication of price volatility and potential reversals.
Key Features
Momentum Adjusted Bands: Adjusts the bands' width based on the momentum indicator, reflecting the rate of change in price.
Volume Weighted Bands: Further adjusts the bands based on trading volume to reflect market activity and price volatility.
Signal Alerts: Provides buy and sell signals based on price action relative to the dynamic bands, helping traders identify entry and exit points.
Customizable Parameters: Allows users to adjust the lookback period, momentum sensitivity, and volume weighting for personalized analysis.
How It Works
The DBBMV indicator starts with the traditional Bollinger Bands, which are calculated using a moving average and standard deviation of the selected price source. The width of these bands is then adjusted based on the momentum of the price, making them more sensitive to price changes. Further adjustments are made based on trading volume, which ensures that the bands accurately reflect current market conditions. This results in a set of dynamic Bollinger Bands that provide more nuanced insights into price volatility and potential reversals.
Usage Instructions
Identify Volatile Periods: Use the dynamically adjusted bands to identify periods of high and low volatility in the market.
Spot Reversals: Look for buy signals when the price crosses above the lower band and sell signals when the price crosses below the upper band.
Adjust Sensitivity: Customize the lookback period, momentum sensitivity, and volume weighting to fine-tune the indicator to your specific trading strategy and market conditions.
Enhance Analysis: Combine the DBBMV indicator with other technical analysis tools for a more comprehensive market analysis.
Volume Confirmation: Use the volume-weighted adjustments to confirm the strength of price movements and potential breakouts.
The Dynamic Bollinger Bands with Momentum and Volume (DBBMV) indicator provides traders with a powerful tool to understand market dynamics better and make informed trading decisions based on adjusted volatility and market activity.
Average Session Range [QuantVue]The Average Session Range or ASR is a tool designed to find the average range of a user defined session over a user defined lookback period.
Not only is this indicator is useful for understanding volatility and price movement tendencies within sessions, but it also plots dynamic support and resistance levels based on the ASR.
The average session range is calculated over a specific period (default 14 sessions) by averaging the range (high - low) for each session.
Knowing what the ASR is allows the user to determine if current price action is normal or abnormal.
When a new session begins, potential support and resistance levels are calculated by breaking the ASR into quartiles which are then added and subtracted from the sessions opening price.
The indicator also shows an ASR label so traders can know what the ASR is in terms of dollars.
Session Time Configuration:
The indicator allows users to define the session time, with default timing set from 13:00 to 22:00.
ASR Calculation:
The ASR is calculated over a specified period (default 14 sessions) by averaging the range (high - low) of each session.
Various levels based on the ASR are computed: 0.25 ASR, 0.5 ASR, 0.75 ASR, 1 ASR, 1.25 ASR, 1.5 ASR, 1.75 ASR, and 2 ASR.
Visual Representation:
The indicator plots lines on the chart representing different ASR levels.
Customize the visibility, color, width, and style (Solid, Dashed, Dotted) of these lines for better visualization.
Labels for these lines can also be displayed, with customizable positions and text properties.
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Sharpe and Sortino Ratios█ OVERVIEW
This indicator calculates the Sharpe and Sortino ratios using a chart symbol's periodic price returns, offering insights into the symbol's risk-adjusted performance. It features the option to calculate these ratios by comparing the periodic returns to a fixed annual rate of return or the returns from another selected symbol's context.
█ CONCEPTS
Returns, risk, and volatility
The return on an investment is the relative gain or loss over a period, often expressed as a percentage. Investment returns can originate from several sources, including capital gains, dividends, and interest income. Many investors seek the highest returns possible in the quest for profit. However, prudent investing and trading entails evaluating such returns against the associated risks (i.e., the uncertainty of returns and the potential for financial losses) for a clearer perspective on overall performance and sustainability.
The profitability of an investment typically comes at the cost of enduring market swings, noise, and general uncertainty. To navigate these turbulent waters, investors and portfolio managers often utilize volatility , a measure of the statistical dispersion of historical returns, as a foundational element in their risk assessments because it provides a tangible way to gauge the uncertainty in returns. High volatility suggests increased uncertainty and, consequently, higher risk, whereas low volatility suggests more stable returns with minimal fluctuations, implying lower risk. These concepts are integral components in several risk-adjusted performance metrics, including the Sharpe and Sortino ratios calculated by this indicator.
Risk-free rate
The risk-free rate represents the rate of return on a hypothetical investment carrying no risk of financial loss. This theoretical rate provides a benchmark for comparing the returns on a risky investment and evaluating whether its excess returns justify the risks. If an investment's returns are at or below the theoretical risk-free rate or the risk premium is below a desired amount, it may suggest that the returns do not compensate for the extra risk, which might be a call to reassess the investment.
Since the risk-free rate is a theoretical concept, investors often utilize proxies for the rate in practice, such as Treasury bills and other government bonds. Conventionally, analysts consider such instruments "risk-free" for a domestic holder, as they are a form of government obligation with a low perceived likelihood of default.
The average yield on short-term Treasury bills, influenced by economic conditions, monetary policies, and inflation expectations, has historically hovered around 2-3% over the long term. This range also aligns with central banks' inflation targets. As such, one may interpret a value within this range as a minimum proxy for the risk-free rate, as it may correspond to the minimum rate required to maintain purchasing power over time. This indicator uses a default value of 2% as the risk-free rate in its Sharpe and Sortino ratio calculations. Users can adjust this value from the "Risk-free rate of return" input in the "Settings/Inputs" tab.
Sharpe and Sortino ratios
The Sharpe and Sortino ratios are two of the most widely used metrics that offer insight into an investment's risk-adjusted performance . They provide a standardized framework to compare the effectiveness of investments relative to their perceived risks. These metrics can help investors determine whether the returns justify the risks taken to achieve them, promoting more informed investment decisions.
Both metrics measure risk-adjusted performance similarly. However, they have some differences in their formulas and their interpretation:
1. Sharpe ratio
The Sharpe ratio , developed by Nobel laureate William F. Sharpe, measures the performance of an investment compared to a theoretically risk-free asset, adjusted for the investment risk. The ratio uses the following formula:
Sharpe Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑎
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑎 = Standard deviation of the investment's returns (volatility)
A higher Sharpe ratio indicates a more favorable risk-adjusted return, as it signifies that the investment produced higher excess returns per unit of increase in total perceived risk.
2. Sortino ratio
The Sortino ratio is a modified form of the Sharpe ratio that only considers downside volatility , i.e., the volatility of returns below the theoretical risk-free benchmark. Although it shares close similarities with the Sharpe ratio, it can produce very different values, especially when the returns do not have a symmetrical distribution, since it does not penalize upside and downside volatility equally. The ratio uses the following formula:
Sortino Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑑
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑑 = Downside deviation (standard deviation of negative excess returns, or downside volatility)
The Sortino ratio offers an alternative perspective on an investment's return-generating efficiency since it does not consider upside volatility in its calculation. A higher Sortino ratio signifies that the investment produced higher excess returns per unit of increase in perceived downside risk.
The risk-free rate (𝑅𝑓) in the numerator of both ratio formulas acts as a baseline for comparing an investment's performance to a theoretical risk-free alternative. By subtracting the risk-free rate from the expected return (𝑅𝑎−𝑅𝑓), the numerator essentially represents the risk premium of the investment.
Comparison with another symbol
In addition to the conventional Sharpe and Sortino ratios, which compare an instrument's returns to a risk-free rate, this indicator can also compare returns to a user-specified benchmark symbol , allowing the calculation of Information ratios .
An Information ratio is a generalized form of the Sharpe ratio that compares an investment's returns to a risky benchmark , such as SPY, rather than a risk-free rate. It measures the investment's active return (the difference between its returns and the benchmark returns) relative to its tracking error (i.e., the volatility of the active return) using the following formula:
𝐼𝑅 = (𝑅𝑝 − 𝑅𝑏) / 𝑇𝐸
Where:
• 𝑅𝑝 = Average return on the portfolio or investment
• 𝑅𝑏 = Average return from the benchmark instrument
• 𝑇𝐸 = Tracking error (volatility of 𝑅𝑝 − 𝑅𝑏)
Comparing returns to a benchmark instrument rather than a theoretical risk-free rate offers unique insights into risk-adjusted performance. Higher Information ratios signify that the investment produced higher active returns per unit of increase in risk relative to the benchmark. Conventional choices for non-risk-free benchmarks include major composite indices like the S&P 500 and DJIA, as the resulting ratios can provide insight into the effectiveness of an investment relative to the broader market.
Users can enable this generalized calculation for both the Sharpe and Sortino ratios by selecting the "Benchmark symbol returns" option from the "Benchmark type" dropdown in the "Settings/Inputs" tab.
It's crucial to note that this indicator compares the charts symbol's rate of change (return) to the rate of change in the benchmark symbol. Consequently, not all symbols available on TradingView are suitable for use with these ratios due to the nature of what their values represent. For instance, using a bond as a benchmark will produce distorted results since each bar's values represent yields rather than prices, meaning it compares the rate of change in the yield. To maintain consistency and relevance in the calculated ratios, ensure the values from the compared symbols strictly represent price information.
█ FEATURES
This indicator provides traders with two widely used metrics for assessing risk-adjusted performance, generalized to allow users to compare the chart symbol's price returns to a fixed risk-free rate or the returns from another risky symbol. Below are the key features of this indicator:
Timeframe selection
The "Returns timeframe" input determines the timeframe of the calculated price returns. Users can select any value greater than or equal to the chart's timeframe. The default timeframe is "1M".
Periodic returns tracking
This indicator compounds and collects requested price returns from the selected timeframe over monthly or daily periods, similar to how the Broker Emulator works when calculating strategy performance metrics on trade data. It employs the following logic:
• Track returns over monthly periods if the chart's data spans at least two months.
• Track returns over daily periods if the chart's data spans at least two days but not two months.
• Do not track or collect returns if the data spans less than two days, as the amount of data is insufficient for meaningful ratio calculations.
The indicator uses the returns collected from up to a specified number of periods to calculate the Sharpe and Sortino ratios, depending on the available historical data. It also uses these periodic returns to calculate the average returns it displays in the Data Window.
Users can control the maximum number of periods the indicator analyzes with the "Max no. of periods used" input in the "Settings/Inputs" tab. The default value is 60 periods.
Benchmark specification
The "Benchmark return type" input specifies the benchmark type the indicator compares to the chart symbol's returns in the ratio calculations. It features the following two options:
• "Risk-free rate of return (%)": Compares the price returns to a user-specified annual rate of return representing a theoretical risk-free rate (e.g., 2%).
• "Benchmark symbol return": Compares the price returns to a selected benchmark symbol (e.g., "AMEX:SPY) to calculate Information ratios.
When comparing a chart symbol's returns to a specified benchmark symbol, this indicator aligns the times of data points from the benchmark with the times of data points from the chart's symbol to facilitate a fair comparison between symbols with different active sessions.
Visualization and display
• The indicator displays the periodic returns requested from the specified "Returns timeframe" in a separate pane. The plot includes dynamic colors to signify positive and negative returns.
• When the "Returns timeframe" value represents a higher timeframe, the indicator displays background highlights on the main chart pane to signify when a new value is available and whether the return is positive or negative.
• When the specified benchmark return type is a benchmark symbol, the indicator displays the requested symbol's returns in the separate pane as a gray line for visual comparison.
• Within the separate pane, the indicator displays a single-cell table that shows the base period it uses for periodic returns, the number of periods it uses in the calculation, the timeframe of the requested data, and the calculated Sharpe and Sortino ratios.
• The Data Window displays the chart symbol and benchmark returns, their periodic averages, and the Sharpe and Sortino ratios.
█ FOR Pine Script™ CODERS
• This script utilizes the functions from our RiskMetrics library to determine the size of the periods, calculate and collect periodic returns, and compute the Sharpe and Sortino ratios.
• The `getAlignedPrices()` function in this script requests price data for the chart's symbol and a benchmark symbol with consistent time alignment by utilizing spread symbols , which helps facilitate a fair comparison between different symbol types. Retrieving prices from spreads avoids potential information loss and data misalignment that can otherwise occur when using separate requests from each symbol's context when those symbols have different sessions or data times.
• For consistency, the `getAlignedPrices()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences for fair comparison between futures instruments.
• This script uses the `changePercent()` function from our ta library to calculate the percentage changes of the requested data.
• The newly released `force_overlay` parameter in display-related functions allows indicators to display visuals on the main chart and a separate pane simultaneously. We use the parameter in this script's bgcolor() call to display background highlights on the main chart.
Look first. Then leap.
Historical Volatility (adjustable time period)Historical Volatility with Adjustable Time Period and Moving Average
This indicator calculates the historical volatility of an asset within a user-defined date range. Volatility is a measure of the dispersion of returns and is commonly used to assess the risk and potential price fluctuations of an asset.
How It Works
User-Defined Date Range: You can specify the start and end dates to focus on a particular period for volatility calculation. This is useful for analyzing specific historical events or trends within a defined timeframe.
Daily Returns Calculation: The script calculates the daily returns as the percentage change between the current close price and the previous close price. This percentage change is essential for determining the asset's volatility.
Volatility Calculation: The historical volatility is computed as the standard deviation of the daily returns over a specified period. The standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of values.
Moving Average: An optional feature allows you to plot a moving average of the volatility. You can customize the type (SMA, EMA, WMA, VWMA) and the period of the moving average, helping to smooth out the volatility data and identify trends.
Indicator Settings
Start Date: Select the beginning date of the period for which you want to calculate volatility.
End Date: Select the end date of the period.
Period: Set the number of bars (days) over which to calculate the average volatility.
Show Moving Average: Toggle to display the moving average of the volatility.
Moving Average Period: Define the length of the moving average.
Moving Average Type: Choose the type of moving average: Simple (SMA), Exponential (EMA), Weighted (WMA), or Volume-Weighted (VWMA).
How to Use
Configure Date Range: Set the start and end dates to focus on the specific historical period you are interested in.
Adjust Period for Volatility Calculation: Select the period over which you want to calculate the average volatility. A shorter period will be more sensitive to recent price changes, while a longer period will provide a more smoothed view.
Enable and Configure Moving Average: If desired, enable the moving average and select the type and period that best fits your analysis style.
Example Use Cases
Market Analysis: Identify periods of high or low volatility to assess market conditions.
Risk Management: Use historical volatility to evaluate the risk associated with a particular asset.
Event Impact: Analyze how specific events within the selected date range affected the asset's volatility.
By providing these functionalities, this indicator is a valuable tool for traders looking to understand and analyze the volatility of assets over custom time periods with the flexibility of adding a moving average for trend analysis.
LBR-S310ROC @shrilssOriginally made by Linda Raschke, The S310ROC Indicator combines the Rate of Change (ROC) indicator with the 3-10 Oscillator (Modified MACD) and plots to capture rapid price movements and gauge market momentum.
- Rate of Change (ROC): This component of the indicator measures the percentage change in price over a specified short interval, which can be set by the user (default is 2 days). It is calculated by subtracting the closing price from 'X' days ago from the current close.
- 3-10 Oscillator (MACD; 3,10,16): This is a specialized version of the Moving Average Convergence Divergence (MACD) but uses simple moving averages instead of exponential. Using a fast moving average of 3 days and a slow moving average of 10 days with a smoothing period of 16.
- ROC Dots: A great feature based on the oscillator's readings. Dots are displayed directly on the oscillator or the price chart to provide visual momentum cues:
- Aqua Dots: Appear when all lines (ROC, MACD, Slowline) are sloping downwards, indicating bearish momentum and potentially signaling a sell opportunity.
- White Dots: Appear when all lines are sloping upwards, suggesting bullish momentum and possibly a buy signal.
ROC [CHE] with Kernel SelectionIntroduction:
The script titled "ROC with Kernel Selection" utilizes Rate of Change (ROC) to analyze price momentum in financial markets. It incorporates a kernel selection mechanism to smooth ROC values, enhancing clarity in trend identification.
Middle Part:
The script begins by calculating ROC over a specified period using the formula:
roc = (close - close ) / close * 100
The period length determined by the user. The result is plotted alongside a zero line for reference.
The kernel selection aspect allows users to choose from various smoothing techniques:
Linear
Exponential
Epanechnikov
Triangular
Cosine
Each kernel applies a different weighting function to ROC values, influencing the sensitivity and smoothness of the plotted line. Users can customize parameters such as bandwidth and color preferences for up and down movements, facilitating visual interpretation.
The main logic of the script involves iterating through historical data to compute weighted averages of ROC values based on the selected kernel. It adjusts graphical elements dynamically, highlighting changes in momentum direction with color-coded lines and directional symbols (▲ or ▼).
Conclusion:
In conclusion, "ROC with Kernel Selection" offers a flexible toolset for traders and analysts to assess price momentum robustly. By integrating kernel-based smoothing techniques, it enhances the clarity of ROC signals, aiding in the identification of trends and potential reversals in financial markets.
