MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe between 30 min and 4 hours and chart (optimal performance observed on 45 min BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Cerca negli script per "backtesting"
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
Bias Finder [UAlgo]The "Bias Finder " indicator is a tool designed to help traders identify market bias and trends effectively. This indicator leverages smoothed Heikin Ashi candles and oscillators to provide a clear visual representation of market trends and potential reversals. By utilizing higher timeframes and smoothing techniques, the indicator aims to filter out market noise and offer a more reliable signal for trading decisions.
🔶 Key Features
Heikin Ashi Candles: The indicator uses Heikin Ashi candles, a special type of candlestick that incorporates information from the previous candle to potentially provide smoother visuals and highlight potential trend direction.
Oscillator: The indicator calculates an oscillator based on the difference between the smoothed opening and closing prices of a higher timeframe. This oscillator helps visualize the strength of the bias.
Light Teal: Strong bullish trend.
Dark Teal: Weakening bullish trend.
Light Red: Strong bearish trend.
Dark Red: Weakening bearish trend.
Standard Deviation: The indicator can optionally display upper and lower standard deviation bands based on the Heikin Ashi high and low prices. These bands can help identify potential breakout areas.
Oscillator Period: Adjust the sensitivity of the oscillator.
Higher Timeframe: Select a timeframe for the Heikin Ashi candles and oscillator calculations (must be equal to or greater than the chart's timeframe).
Display Options: Choose whether to display Heikin Ashi candles, market bias fill, standard deviation bands, and HA candle colors based on the bias.
Alerts: Enable/disable specific alerts and customize their messages.
🔶 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.
Internal/External Market Structure [UAlgo]The "Internal/External Market Structure " indicator is a tool designed to identify and visualize internal and external market structure based on swing highs and lows. It helps traders understand short-term (internal) and long-term (external) price behavior.
🔶 What are ChoCH and BoS?
Change of Character (ChoCH)
Change of character refers to the reversal of market trend either from bullish to bearish or bearish to bullish. ChoCH is also a break of market structure but in opposite direction.
If market is in bullish trend but it breaks it previous (higher) low and makes a lower low, it will be termed a “bearish change of character” as price changed its trend from bullish to bearish.
Like wise if price is in bearish trend and it breaks its previous (lower) high making a higher high it will be marked as “bullish change of character” as price changed its trend from bearish to bullish.
Break of Structure (BoS)
When price breaks its structure in direction of previous trend its called break of structure (BoS). So its a trend continuation pattern.
As you know in bullish trend price makes higher highs. Each time when price break a previous high and marks a new high its known as bullish break of structure.
But in bearish trend price makes lower lows so every time when price breaks previous low and makes a new low it is called as bearish break of structure.
🔶 Key Features
Internal Swing Length: Allowing for fine-tuning of sensitivity to smaller, more frequent market movements.
External Swing Length: Focusing on capturing broader market trends.
The indicator differentiates between internal and external market structures, using different styles and colors to represent each. Internal structures are shown with solid lines, while external structures use dashed lines, providing clear visual cues.
Internal Market Structure:
The internal market structure focuses on shorter-term swings and is useful for identifying minor trend changes and short-term price movements. Breaks of internal swing highs or lows can indicate potential changes in the market's direction or momentum. The labels "CHoCH" and "BoS" help distinguish between changes in character and break of structure events, respectively.
External Market Structure:
The external market structure captures larger, more significant market moves. It is particularly useful for identifying major trend changes and key support and resistance levels. The dashed lines and corresponding labels "CHoCH+" and "BoS+" indicate more substantial shifts in market sentiment.
For BoS (Break of Structure):
For ChoCH (Change of Character):
🔶 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 K-Means Clustering [UAlgo]The "RSI K-Means Clustering " indicator is a technical analysis tool that combines the Relative Strength Index (RSI) with K-means clustering techniques. This approach aims to provide more nuanced insights into market conditions by categorizing RSI values into overbought, neutral, and oversold clusters.
The indicator adjusts these clusters dynamically based on historical RSI data, allowing for more adaptive and responsive thresholds compared to traditional fixed levels. By leveraging K-means clustering, the indicator identifies patterns in RSI behavior, which can help traders make more informed decisions regarding market trends and potential reversals.
🔶 Key Features
K-means Clustering: The indicator employs K-means clustering, an unsupervised machine learning technique, to dynamically determine overbought, neutral, and oversold levels based on historical RSI data.
User-Defined Inputs: You can customize various aspects of the indicator's behavior, including:
RSI Source: Select the data source used for RSI calculation (e.g., closing price).
RSI Length: Define the period length for RSI calculation.
Training Data Size: Specify the number of historical RSI values used for K-means clustering.
Number of K-means Iterations: Set the number of iterations performed by the K-means algorithm to refine cluster centers.
Overbought/Neutral/Oversold Levels: You can define initial values for these levels, which will be further optimized through K-means clustering.
Alerts: The indicator can generate alerts for various events, including:
Trend Crossovers: Alerts for when the RSI crosses above/below the neutral zone, signaling potential trend changes.
Overbought/Oversold: Alerts when the RSI reaches the dynamically determined overbought or oversold thresholds.
Reversals: Alerts for potential trend reversals based on RSI crossing above/below the calculated overbought/oversold levels.
RSI Classification: Alerts based on the current RSI classification (ranging, uptrend, downtrend).
🔶 Interpreting Indicator
Adjusted RSI Value: The primary plot represents the adjusted RSI value, calculated based on the relative position of the current RSI compared to dynamically adjusted overbought and oversold levels. This value provides an intuitive measure of the market's momentum. The final overbought, neutral, and oversold levels are determined by K-means clustering and are displayed as horizontal lines. These levels serve as dynamic support and resistance points, indicating potential reversal zones.
Classification Symbols : The "RSI K-Means Clustering " indicator uses specific symbols to classify the current market condition based on the position of the RSI value relative to dynamically determined clusters. These symbols provide a quick visual reference to help traders understand the prevailing market sentiment. Here's a detailed explanation of each classification symbol:
Ranging Classification ("R")
This symbol appears when the RSI value is closest to the neutral threshold compared to the overbought or oversold thresholds. It indicates a ranging market, where the price is moving sideways without a clear trend direction. In this state, neither buyers nor sellers are in control, suggesting a period of consolidation or indecision. This is often seen as a time to wait for a breakout or reversal signal before taking a position.
Up-Trend Classification ("↑")
The up-trend symbol, represented by an upward arrow, is displayed when the RSI value is closer to the overbought threshold than to the neutral or oversold thresholds. This classification suggests that the market is in a bullish phase, with buying pressure outweighing selling pressure. Traders may consider this as a signal to enter or hold long positions, as the price is likely to continue rising until the market reaches an overbought condition.
Down-Trend Classification ("↓")
The down-trend symbol, depicted by a downward arrow, appears when the RSI value is nearest to the oversold threshold. This indicates a bearish market condition, where selling pressure dominates. The market is likely experiencing a downward movement, and traders might view this as an opportunity to enter or hold short positions. This symbol serves as a warning of potential further declines, especially if the RSI continues to move toward the oversold level.
Bullish Reversal ("▲")
This signal occurs when the RSI value crosses above the oversold threshold. It indicates a potential shift from a downtrend to an uptrend, suggesting that the market may start to move higher. Traders might use this signal as an opportunity to enter long positions.
Bearish Reversal ("▼")
This signal appears when the RSI value crosses below the overbought threshold. It suggests a possible transition from an uptrend to a downtrend, indicating that the market may begin to decline. This signal can alert traders to consider entering short positions or taking profits on long positions.
These classification symbols are plotted near the adjusted RSI line, with their positions adjusted based on the standard deviation and a distance multiplier. This placement helps in visualizing the classification's strength and ensuring clarity in the indicator's presentation. By monitoring these symbols, traders can quickly assess the market's state and make more informed trading decisions.
🔶 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.
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 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.
Money Flow Index Trend Zone Strength [UAlgo]The "Money Flow Index Trend Zone Strength " indicator is designed to analyze and visualize the strength of market trends and OB/OS zones using the Money Flow Index (MFI). The MFI is a momentum indicator that incorporates both price and volume data, providing insights into the buying and selling pressure in the market. This script enhances the traditional MFI by introducing trend and zone strength analysis, helping traders identify potential trend reversals and continuation points.
🔶 Customizable Settings
Amplitude: Defines the range for the MFI Zone Strength calculation.
Wavelength: Period used for the MFI calculation and Stochastic calculations.
Smoothing Factor: Smoothing period for the Stochastic calculations.
Show Zone Strength: Enables/disables visualization of the MFI Zone Strength line.
Show Trend Strength: Enables/disables visualization of the MFI Trend Strength area.
Trend Strength Signal Length: Period used for the final smoothing of the Trend Strength indicator.
Trend Anchor: Selects the anchor point (0 or 50) for the Trend Strength Stochastic calculation.
Trend Transform MA Length: Moving Average length for the Trend Transform calculation.
🔶 Calculations
Zone Strength (Stochastic MFI):
The highest and lowest MFI values over a specified amplitude are used to normalize the MFI value:
MFI Highest: Highest MFI value over the amplitude period.
MFI Lowest: Lowest MFI value over the amplitude period.
MFI Zone Strength: (MFI Value - MFI Lowest) / (MFI Highest - MFI Lowest)
By normalizing and smoothing the MFI values, we aim to highlight the relative strength of different market zones.
Trend Strength:
The smoothed MFI zone strength values are further processed to calculate the trend strength:
EMA of MFI Zone Strength: Exponential Moving Average of the MFI Zone Strength over the wavelength period.
Stochastic of EMA: Stochastic calculation of the EMA values, smoothed with the same smoothing factor.
Purpose: The trend strength calculation provides insights into the underlying market trends. By using EMA and stochastic functions, we can filter out noise and better understand the overall market direction. This helps traders stay aligned with the prevailing trend and make more informed trading decisions.
🔶 Usage
Interpreting Zone Strength: The zone strength plot helps identify overbought and oversold conditions. A higher zone strength indicates potential overbought conditions, while a lower zone strength suggests oversold conditions, can suggest areas for entry/exit decisions.
Interpreting Trend Strength: The trend strength plot visualizes the underlying market trend, can help signal potential trend continuation or reversal based on the chosen anchor point.
Using the Trend Transform: The trend transform plot provides an additional layer of trend analysis, helping traders identify potential trend reversals and continuation points.
Combine the insights from the zone strength and trend strength plots with other technical analysis tools to make informed trading decisions. Look for confluence between different indicators to increase the reliability of your trades.
🔶 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.
Momentum & Squeeze Oscillator [UAlgo]The Momentum & Squeeze Oscillator is a technical analysis tool designed to help traders identify shifts in market momentum and potential squeeze conditions. This oscillator combines multiple timeframes and periods to provide a detailed view of market dynamics. It enhances the decision-making process for both short-term and long-term traders by visualizing momentum with customizable colors and alerts.
🔶 Key Features
Custom Timeframe Selection: Allows users to select a custom timeframe for oscillator calculations, providing flexibility in analyzing different market periods.
Recalculation Option: Enables or disables the recalculation of the indicator, offering more control over real-time data processing.
Squeeze Background Visualization: Highlights potential squeeze conditions with a background color, helping traders quickly spot consolidation periods.
Adjustable Squeeze Sensitivity: Users can modify the sensitivity of the squeeze detection, tailoring the indicator to their specific trading style and market conditions.
Bar Coloring Condition: Option to color the price bars based on momentum conditions, enhancing the visual representation of market trends.
Threshold Bands: Option to fill threshold bands for a clearer visualization of overbought and oversold levels.
Reference Lines: Display reference lines for overbought, oversold, and mid-levels, aiding in quick assessment of momentum extremes.
Multiple Output Modes: Offers different output visualization modes, including:
ALL: Displays all calculated momentum values (fast, medium, slow).
AVG: Shows the average momentum, providing a consolidated view.
STD: Displays the standard deviation of momentum, useful for understanding volatility.
Alerts: Configurable alerts for key momentum events such as crossovers and squeeze conditions, keeping traders informed of important market changes.
🔶 Usage
The Momentum & Squeeze Oscillator can be used for various trading purposes:
Trend Identification: Use the oscillator to determine the direction and strength of market trends. By analyzing the average, fast, medium, and slow momentum lines, traders can gain insights into short-term and long-term market movements.
Squeeze Detection: The indicator highlights periods of low volatility (squeeze conditions) which often precede significant price movements. Traders can use this information to anticipate and prepare for potential breakouts.
Overbought/Oversold Conditions: The oscillator helps identify overbought and oversold conditions, indicating potential reversal points. This is particularly useful for timing entry and exit points in the market.
Momentum Shifts: By monitoring the crossover of momentum lines with key levels (e.g., the 50 level), traders can spot shifts in market momentum, allowing them to adjust their positions accordingly.
🔶 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.
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.
Adaptive Bollinger-RSI Trend Signal [CHE]Adaptive Bollinger-RSI Trend Signal
Indicator Overview:
The "Adaptive Bollinger-RSI Trend Signal " (ABRT Signal ) is a sophisticated trading tool designed to provide clear and actionable buy and sell signals by combining the power of Bollinger Bands and the Relative Strength Index (RSI). This indicator aims to help traders identify potential trend reversals and confirm entry and exit points with greater accuracy.
Key Features:
1. Bollinger Bands Integration:
- Utilizes Bollinger Bands to detect price volatility and identify overbought or oversold conditions.
- Configurable parameters: Length, Source, and Multiplier for precise adjustments based on trading preferences.
- Color customization: Change the colors of the basis line, upper band, lower band, and the fill color between bands.
2. RSI Integration:
- Incorporates the Relative Strength Index (RSI) to validate potential buy and sell signals.
- Configurable parameters: Length, Source, Upper Threshold, and Lower Threshold for customized signal generation.
3. Signal Generation:
- Buy Signal: Generated when the price crosses below the lower Bollinger Band and the RSI crosses above the lower threshold, indicating a potential upward trend.
- Sell Signal: Generated when the price crosses above the upper Bollinger Band and the RSI crosses below the upper threshold, indicating a potential downward trend.
- Color customization: Change the colors of the buy and sell signal labels.
4. State Tracking:
- Tracks and records crossover and crossunder states of the price and RSI to ensure signals are only generated under the right conditions.
- Monitors the basis trend (SMA of the Bollinger Bands) to provide context for signal validation.
5. Counters and Labels:
- Labels each buy and sell signal with a counter to indicate the number of consecutive signals.
- Counters reset upon the generation of an opposite signal, ensuring clarity and preventing signal clutter.
6. DCA (Dollar-Cost Averaging) Calculation:
- Stores the close price at each signal and calculates the average entry price (DCA) for both buy and sell signals.
- Displays the number of positions and DCA values in a label on the chart.
7. Customizable Inputs:
- Easily adjustable parameters for Bollinger Bands, RSI, and colors to suit various trading strategies and timeframes.
- Boolean input to show or hide the table label displaying position counts and DCA values.
- Intuitive and user-friendly configuration options for traders of all experience levels.
How to Use:
1. Setup:
- Add the "Adaptive Bollinger-RSI Trend Signal " to your TradingView chart.
- Customize the input parameters to match your trading style and preferred timeframe.
- Adjust the colors of the indicator elements to your preference for better visibility and clarity.
2. Interpreting Signals:
- Buy Signal: Look for a "Buy" label on the chart, indicating a potential entry point when the price is oversold and RSI signals upward momentum.
- Sell Signal: Look for a "Sell" label on the chart, indicating a potential exit point when the price is overbought and RSI signals downward momentum.
3. Trade Execution:
- Use the buy and sell signals to guide your trade entries and exits, aligning them with your overall trading strategy.
- Monitor the counter labels to understand the strength and frequency of signals, helping you make informed decisions.
4. Adjust and Optimize:
- Regularly review and adjust the indicator parameters based on market conditions and backtesting results.
- Combine this indicator with other technical analysis tools to enhance your trading accuracy and performance.
5. Monitor DCA Values:
- Enable the table label to display the number of positions and average entry prices (DCA) for both buy and sell signals.
- Use this information to assess the cost basis of your trades and make strategic adjustments as needed.
Conclusion:
The Adaptive Bollinger-RSI Trend Signal is a powerful and versatile trading tool designed to help traders identify and capitalize on trend reversals with confidence. By combining the strengths of Bollinger Bands and RSI, this indicator provides clear and reliable signals, making it an essential addition to any trader's toolkit. Customize the settings, interpret the signals, and execute your trades with precision using this comprehensive indicator.
[INVX] Post-Earnings Announcement DriftWhat does this strategy do?
This Pine Script strategy implements the Post-earnings announcement drift (PEAD) strategy, which is a financial market anomaly where a stock's price tends to drift in the direction of the firm's earnings surprise for an extended period of time.
Ref: en.wikipedia.org
An earnings announcement is an official public statement of a company's profitability for a specific time period, typically a quarter or a year. It includes various financial metrics but the most watched figure is the Earnings Per Share (EPS). Analysts estimate the EPS before the announcement, and the actual EPS is compared to this estimate to determine if there was an earnings surprise.
An earnings surprise occurs when the actual EPS is significantly different from the analysts' estimates. A positive earnings surprise indicates that the actual EPS is higher than the estimate, while a negative earnings surprise suggests the EPS is lower than anticipated.
The script takes the following inputs
" Holding periods (bar) " : This input defines the number of periods (or bars) the script will hold a position after the earnings announcement.
" Surprise threshold (%) ": This input sets the minimum percentage for an earnings surprise, which triggers the strategy to enter either a long or short position. In essence, it represents the minimum deviation between the estimated and actual Earnings Per Share (EPS) that will trigger a trade. A higher threshold may lead to fewer, potentially more significant trades, while a lower threshold might result in more frequent, possibly less impactful trades. This parameter allows you to adjust the sensitivity of the strategy to earnings surprises.
Positive earnings surprise
After the earnings announcement, the script compares the actual EPS with the estimated EPS to identify an earnings surprise. If there is a positive earnings surprise, the script will enter a long position. A long position is a bullish strategy where the investor expects the stock price to rise.
Negative earnings surprise
On the other hand, if there is a negative earnings surprise, the script will enter a short position. A short position is a bearish strategy where the investor expects the stock price to fall.
In both scenarios, the position (either long or short) is held for the number of periods specified in the "Holding periods (bar)" input. This strategy is based on the assumption that the stock price will continue to drift in the direction of the earnings surprise for the specified holding period.
Disclaimer: The script provided herein is for educational purposes only. It should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Past performance is not indicative of future results.
The results of the Pine Script backtesting are hypothetical and should not be considered as a true reflection of the results that might be achieved in a live trading environment. The backtest results are based on historical data and may not take into account certain factors such as actual transaction costs, taxes, or changes in market conditions.
Investors should consult with their financial advisor before making any investment decisions. All investments involve risk, including the potential loss of all invested capital.
ADX + CCI + MA - Uncle SamStrategy Name: ADX + CCI + MA - Uncle Sam
Overview
This strategy aims to capitalize on trending markets by combining the Average Directional Index (ADX), Commodity Channel Index (CCI), and a customizable Moving Average (MA). It's designed for traders seeking a balanced approach to both long (buy) and short (sell) opportunities. Special thanks to the creators of the ADX and CCI indicators for their invaluable contributions to technical analysis.
Strategy Concept
The core idea is to identify strong trends with the ADX, confirm potential entry points with the CCI, and use the MA to filter trades in the direction of the broader trend. This approach seeks to avoid entering positions during periods of consolidation or when the trend is weak.
Indicator Logic
ADX (Average Directional Index): The ADX measures the strength of a trend, regardless of its direction. A value above the customizable adx_threshold (default 20) signals a strong trend, making it a prime environment for this strategy.
CCI (Commodity Channel Index): The CCI is a momentum oscillator that helps identify overbought (above 100) and oversold (below -100) conditions. We use CCI crossovers to time entries in the direction of the prevailing trend.
MA (Moving Average): The MA acts as a trend filter, ensuring we only enter trades aligned with the overall market direction. You have flexibility in choosing the MA type (SMA, EMA, etc.) and its length to suit your trading style and timeframe.
Entry Conditions
Long (Buy):
ADX is above the adx_threshold.
CCI crosses above 100.
Price is above the chosen Moving Average (if MA trend filtering is enabled).
Short (Sell):
ADX is above the adx_threshold.
CCI crosses below -100.
Price is below the chosen Moving Average (if MA trend filtering is enabled).
Exit Conditions
Stop Loss (SL): Each position has a customizable stop-loss percentage to manage risk. The default setting is 1%.
Take Profit (TP): Each position has a customizable take-profit percentage to secure gains. The default setting is 5%.
MA-Based Risk Management (Optional): This feature allows for early exits if the price closes against the MA trend for a specified number of candles. The default setting is 2 candles.
Default Settings
CCI Period: 15
ADX Length: 10
ADX Threshold: 20
MA Type: HMA
MA Length: 200
MA Source: Close
Commission Fee: $0.0
A commission fee is not added, add your trading/platform commission for realistic trading costs.
Backtest Results
The strategy has been backtested on with the default settings and a starting capital of $1000, with 0.0% commission fee. It shows promising results.
Disclaimer: Backtesting is hypothetical and does not guarantee future performance.
Important Considerations:
Customization: The strategy offers extensive customization to tailor it to your preferences. Experiment with different parameters and settings to find what works best for your trading style.
Risk Management: Always use proper risk management techniques, including position sizing and stop losses, to protect your capital.
TSI w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "Trend Strength Index" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█ Introduction and How it is Different
The "TSI with SuperTrend Decision - Strategy" combines the Trend Strength Index (TSI) with SuperTrend indicators to determine entry and exit points. Unlike traditional strategies that rely solely on one indicator, this method leverages the strengths of both TSI and SuperTrend to provide a more nuanced and adaptive trading strategy.
This dual approach allows for capturing trends more effectively, especially in volatile markets.
BTCUSD 8h LS Performance
█ Strategy, How it Works: Detailed Explanation
🔶 Trend Strength Index (TSI)
The TSI is a momentum oscillator that shows both the direction and strength of a trend. It is calculated by comparing the price movement with the bar index over a specified period. The formula for TSI is as follows:
```
TSI = (PC / |PC|)
where:
PC = Change in price over the period
```
In this strategy, TSI is calculated using the closing prices and a default period of 64 bars. The TSI values help identify overbought and oversold conditions, providing signals for potential market reversals.
🔶 SuperTrend Indicator
The SuperTrend is a trend-following indicator based on the average true range (ATR). It helps in identifying the direction of the market trend. The SuperTrend calculation involves:
```
SuperTrend = HLC3 ± (Factor * ATR)
where:
HLC3 = (High + Low + Close) / 3
Factor = User-defined multiplier
ATR = Average True Range over a period
```
The SuperTrend settings in this strategy include a length of 10 bars and a factor of 3.0.
Last Bull Cycle of BTC
🔶 Entry and Exit Conditions
The strategy uses the TSI and SuperTrend together to determine entry and exit points:
- Long Entry: When the SuperTrend indicates a downward trend (st.d < 0) and the TSI is above the oversold level (-0.241).
- Long Exit: When the SuperTrend indicates an upward trend (st.d > 0) and the TSI is below the overbought level (0.241).
- Short Entry: When the SuperTrend indicates an upward trend (st.d > 0) and the TSI is below the overbought level (0.241).
- Short Exit: When the SuperTrend indicates a downward trend (st.d < 0) and the TSI is above the oversold level (-0.241).
█ Trade Direction
The strategy allows users to select the trade direction through the `tradeDirection` input. The options are:
- Both: Enables both long and short trades.
- Long: Enables only long trades.
- Short: Enables only short trades.
█ Default Settings
- TSI Length: 64
- SuperTrend Length: 10
- SuperTrend Factor: 3.0
- Trade Direction: Both
- Take Profit (%): 30.0
- Stop Loss (%): 20.0
Impact of Default Settings
- TSI Length: A longer TSI period smooths out noise but may lag in identifying trends. A shorter period is more responsive but can generate false signals.
- SuperTrend Length: A shorter length provides quicker signals but can be prone to whipsaws. A longer length is more reliable but may delay entries and exits.
- SuperTrend Factor: A higher factor increases the distance of the SuperTrend from the price, reducing sensitivity to minor price fluctuations.
- Trade Direction: Allows flexibility in trading strategies by enabling both long and short trades based on market conditions.
- Take Profit and Stop Loss: These settings manage risk by automatically closing trades at predefined profit or loss levels. Higher percentages provide larger potential gains but also higher risk.
VAWSI and Trend Persistance Reversal Strategy SL/TPThis is a completely revamped version of my "RSI and ATR Trend Reversal Strategy."
What's New?
The RSI has been replaced with an original indicator of mine, the "VAWSI," as I've elected to call it.
The standard RSI measures a change in an RMA to determine the strength of a movement.
The VAWSI performs very similarly, except it uses another original indicator of mine, the VAWMA.
VAWMA stands for "Volume (and) ATR Weight Moving Average." It takes an average of the volume and ATR and uses the ratio of each bar to weigh a moving average of the source.
It has the same formula as an RSI, but uses the VAWMA instead of an RMA.
Next we have the Trend Persistence indicator, which is an index on how long a trend has been persisting for. It is another original indicator. It takes the max deviation the source has from lowest/highest of a specified length. It then takes a cumulative measure of that amount, measures the change, then creates a strength index with that amount.
The VAWSI is a measure of an emerging trend, and the Trend Persistence indicator is a measure of how long a trend has persisted.
Finally, the 3rd main indicator, is a slight variation of an ATR. Rather than taking the max of source - low or high- source and source - source , it instead takes the max of high-low and the absolute value of source - the previous source. It then takes the absolute value of the change of this, and normalizes it with the source.
Inputs
Minimum SL/TP ensures that the Stop Loss and Take Profit still exist in untrendy markets. This is the minimum Amount that will always be applied.
VAWSI Weight is a divided by 100 multiplier for the VAWSI. So value of 200 means it is multiplied by 2. Think of it like a percentage.
Trend Persistence weight and ATR Weight are applied the same. Higher the number, the more impactful on the final calculation it is.
Combination Mult is an outright multiplier to the final calculation. So a 2.0 = * 2.0
Trend Persistence Smoothing Length is the length of the weighted moving average applied to the Trend Persistence Strength index.
Length Cycle Decimal is a replacement of length for the script.
Here we used BlackCat1402's Dynamic Length Calculation, which can be found on his page. With his permission we have implemented it into this script. Big shout out to them for not only creating, but allowing us to use it here.
The Length Cycle Decimal is used to calculate the dynamic length. Because TradingView only allows series int for their built-in library, a lot of the baseline indicators we use have to be manually recreated as functions in the following section.
The Strategy
As usual, we use Heiken Ashi values for calculations.
We begin by establishing the minimum SL/TP for use later.
Next we determine the amount of bars back since the last crossup or crossdown of our threshold line.
We then perform some normalization of our multipliers. We want a larger trend or larger VAWSI amount to narrow the threshold, so we have 1 divide them. This way, a higher reading outputs a smaller number and vice versa. We do this for both Trend Persistence, and the VAWSI.
The VAWSI we also normalize, where rather than it being a 0-100 reading of trend direction and strength, we absolute it so that as long as a trend is strong, regardless of direction, it will have a higher reading. With these normalized values, we add them together and simply subtract the ATR measurement rather than having 1 divide it.
Here you can see how the different measurements add up. A lower final number suggests imminent reversal, and a higher final number suggests an untrendy or choppy market.
ATR is in orange, the Trend Persistence is blue, the VAWSI is purple, and the final amount is green.
We take this final number and depending on the current trend direction, we multiply it by either the Highest or Lowest source since the last crossup or crossdown. We then take the highest or lowest of this calculation, and have it be our Stop Loss or Take Profit. This number cannot be higher/lower than the previous source to ensure a rapid spike doesn't immediately close your position on a still continuing trend. As well, the threshold cannot be higher/ lower than the the specified Stop Loss and Take Profit
Only after the source has fully crossed these lines do we consider it a crossup or crossdown. We confirm this with a barstate.isconfirmed to prevent repainting. Next, each time there is a crossup or crossdown we enter a long or a short respectively and plot accordingly.
I have the strategy configured to "process on order close" to ensure an accurate backtesting result. You could also set this to false and add a 1 bar delay to the "if crossup" and "if crossdown" lines under strategy so that it is calculated based on the open of the next bar.
Final Notes
The amounts have been preconfigured for performance on RIOT 5 Minute timeframe. Other timeframes are viable as well. With a few changes to the parameters, this strategy has backtested well on NVDA, AAPL, TSLA, and AMD. I recommend before altering settings to try other timeframes first.
This script does not seem to perform nearly as well in typically untrendy and choppy markets such as crypto and forex. With some setting changes, I have seen okay results with crypto, but overfitting could be the cause there.
Thank you very much, and please enjoy.
Entry Fragger - Strategy
For basic instructions please visit my other script "Entry Fragger".
The Signal Logic is explained there.
v1.4:
- Added advanced backtesting with fully customizable entries.
- Fully automated Buy Signals (profitable).
- Adjustable timeframes for signal logic. (requested)
Every setting affects the accuracy and profitability greatly now, based on settings applied.
The strategy performs best on high timeframes with larger capital and no leverage.
Useless for Forex, but absolutely smashes stocks and crypto on mid to high timeframes.
Please read through my other scripts description.
Set values as preferred and try your assets.
It does NOT work on low timeframes and forex!
Hint: BTC 4H, Custom Timeframe 1h, Moon Mode and Show Sell Signals enabled, R2R: 2.
Korneev Reverse RSIRethinking the Legendary Relative Strength Index by John Welles Wilder
The essence of the new approach lies in the reverse use of the so-called "overbought" and "oversold" zones. In his 1978 book, "New Concepts in Technical Trading Systems," where the RSI mechanism was thoroughly described, Wilder writes that one way to use the oscillator is to open a long position when the RSI drops into oversold territory (below 30) and to open a short position when the RSI rises to overbought levels (above 70). However, backtesting this strategy with such inputs yields rather mediocre results.
Based on the calculation formula, the RSI calculates the rate of price change over a certain period. Therefore, overbought and oversold zones will have relative significance (relative to the set calculation period). It is no coincidence that the word "relative" was added to the name of the oscillator. It is worth accepting as an axiom the assertion that the price of an asset is fair at every moment in time.
Essentially, the RSI calculates the strength of a trend. If the oscillator value is above 70, it is highly likely that an upward movement is occurring in the market. Therefore, in the current strategy, a long position is opened precisely at the moment of greatest buyer strength (when RSI > 80), i.e., in the direction of the trend, since counter-trend trading with the RSI has proven to be ineffective. The position is closed after the buyers lose their advantage and the RSI drops to 40.
The strategy is recommended to be used only with long positions, as short positions show negative results. The strategy uses a moving average for the RSI with a period of 14 to smooth the oscillator data.
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Переосмысление легендарного осциллятора Relative strength index Джона Уэллса Уайлдера
Суть нового подхода заключается в реверсивном использовании так называемых зон "перекупленности" и "перепроданности". В своей книге от 1978 года "New concepts in tecnical trading systems", в которой был подробно описан механизм работы RSI, Уайлдер пишет, что один из способов использования осциллятора - открытие длинной позиции при снижении RSI в перепроданность (ниже 30) и открытие короткой позиции при повышении RSI до перекупленности (выше 70). Однако бэктест стратегии с такими вводными дает весьма посредственные результаты.
Исходя из формулы расчета, RSI рассчитывает скорость изменения цены за определенный период. Поэтому зоны перекупленности и перепроданности будут иметь относительное значение (относительно установленного периода расчета). Не зря ведь в названии осциллятора было добавлено слово "относительной". Стоит принять за аксиому утверждение, что цена актива справедлива в каждый момент времени.
По сути, RSI рассчитывает силу тренда. Если значение осциллятора выше 70, то на рынке с высокой долей вероятности происходит восходящее движение. Поэтому в текущей стратегии открытие лонга происходит именно в момент наибольшей силы покупателей (когда RSI > 80), то есть в сторону тренда, поскольку контртрендовая торговля по RSI показала свою несостоятельность. Закрытие позиции происходит после того, как покупатели теряют преимущество и RSI снижается до 40.
Стратегию рекомендуется использовать только с длинными позициями, поскольку короткие позиции показывают отрицательный результат. В стратегии используется скользящая средняя для RSI с периодом 14 для сглаживания данных осциллятора.
Volume Breaker Blocks [UAlgo]The "Volume Breaker Blocks " indicator is designed to identify breaker blocks in the market based on volume and price action. It is a concept that emerges when an order block fails, leading to a change in market structure. It signifies a pivotal point where the market shifts direction, offering traders opportunities to enter trades based on anticipated trend continuation.
🔶 Key Features
Identifying Breaker Blocks: The indicator identifies breaker blocks by detecting pivot points in price action and corresponding volume spikes.
Breaker Block Sensitivity: Traders can adjust breaker block detection sensitivity, length to be used to find pivot points.
Mitigation Method (Close or Wick): Traders can choose between "Close" and "Wick" as the mitigation method. This choice determines whether the indicator considers closing prices or wicks in identifying breaker blocks. Selecting "Close" implies that breaker blocks will be considered broken when the closing price violates the block, while selecting "Wick" implies that the wick of the candle must violate the block for it to be considered broken.
Show Last X Breaker Blocks: Users can specify how many of the most recent breaker blocks to display on the chart.
Visualization: Volume breaker blocks are visually represented on the chart with customizable colors and text labels, allowing for easy interpretation of market conditions. Each breaker block is accompanied by informational text, including whether it's bullish or bearish and the corresponding volume, aiding traders in understanding the significance of each block.
🔶 Disclaimer
Educational Purpose: The "Volume Breaker Blocks " indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to engage in trading activities.
Risk of Loss: Trading in financial markets involves inherent risks, including the risk of loss of capital. Users should carefully consider their financial situation, risk tolerance, and investment objectives before engaging in trading activities.
Accuracy Not Guaranteed: While the indicator aims to identify potential reversal points in the market, its accuracy and effectiveness may vary. Users should conduct thorough testing and analysis before relying solely on the indicator for trading decisions.
Past Performance: Past performance is not indicative of future results. Historical data and backtesting results may not accurately reflect actual market conditions or future performance.
Sticky Notes, Checklist, To-do, Journal [algoat]I forgot to bring my notes again...
Ever feel like your trading notes are all over the place, much like your portfolio after a market dip? Worry not! With this script, you'll have all your trading notes, tasks, and brilliant (or not so brilliant) ideas neatly organized right on your chart. It's like having a sticky note board, but way cooler and without the risk of paper cuts.
⭐ Features :
To-Do Lists
Keep track of tasks with satisfying checkmarks for those dopamine hits.
Journal Entries
Document your market insights, trade plans, or just random thoughts. "I forgot something" – we've all been there.
Due Dates
Never miss an important deadline again. Red alert for overdue tasks because procrastination is a trader's worst enemy.
Customization
Choose the size and position of your notes because one size doesn't fit all.
Perfect for the organized trader who loves a bit of fun or the chaotic one who needs a bit of structure. Embrace the power of notes and stay on top of your trading game!
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🧠 General advice
Trading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. By integrating multiple analytical approaches, traders can tailor their strategies to fit their unique trading styles and objectives.
Confirming Signals with other indicators
As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade.
Use proper risk management
When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing.
Combining with other technical indicators
The indicator can be effectively used alongside other technical indicators to create a comprehensive trading strategy and provide additional confirmation.
Keep in mind
Thorough research and backtesting are essential before making any trading decisions. Furthermore, it's crucial to have a solid understanding of the indicator and its behavior. Additionally, incorporating fundamental analysis and considering market sentiment can be vital factors to take into account in your trading approach.
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⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. A word to the wise is enough: developed by traders, for traders — pioneering innovations for the modern era.
Risk Notice
Everything provided by algoat — from scripts, tools, and articles to educational materials — is intended solely for educational and informational purposes. Past performance does not assure future returns.
Trend Following Parabolic Buy Sell Strategy [TradeDots]The Trend Following Parabolic Buy-Sell Strategy leverages the Parabolic SAR in combination with moving average crossovers to deliver buy and sell signals within a trend-following framework.
This strategy synthesizes proven methodologies sourced from various trading tutorials available on platforms such as YouTube and blogs, enabling traders to conduct robust backtesting on their selected trading pairs to assess the strategy's effectiveness.
HOW IT WORKS
This strategy employs four key indicators to orchestrate its trading signals:
1. Trend Alignment: It first assesses the relationship between the price and the predominant trendline to determine the directional stance—taking long positions only when the price trends above the moving average, signaling an upward market trajectory.
2. Momentum Confirmation: Subsequent to trend alignment, the strategy looks for moving average crossovers as a confirmation that the price is gaining momentum in the direction of the intended trades.
3. Signal Finalization: Finally, buy or sell signals are validated using the Parabolic SAR indicator. A long order is validated when the closing price is above the Parabolic SAR dots, and similarly, conditions are reversed for short orders.
4. Risk Management: The strategy institutes a fixed stop-loss at the moving average trendline and a take-profit level determinable by a prefixed risk-reward ratio calculated from the moving average trendline. These parameters are customizable by the users within the strategy settings.
APPLICATION
Designed for assets exhibiting pronounced directional momentum, this strategy aims to capitalize on clear trend movements conducive to achieving set take-profit targets.
As a lagging strategy that waits for multiple confirmatory signals, entry into trades might occasionally lag beyond optimal timing.
Furthermore, in periods of consolidation or sideways movement, the strategy may generate several false signals, suggesting the potential need for additional market condition filters to enhance signal accuracy during volatile phases.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
LumleyTrading GapsName: LumleyTrading Gaps
Description:
The Gap Tracker Indicator is a powerful tool designed for traders to identify, monitor, and capitalize on price gaps in financial markets. It serves two primary functions:
Identifying Gaps: The indicator scans price action to detect instances where the current trading session's opening price significantly differs from the previous session's closing price. These disparities indicate the presence of price gaps.
Tracking Gap Fills: Once a gap is identified, the indicator continues to monitor the price movement. It dynamically adjusts its parameters to track whether and when the price retraces back to fill the gap. As soon as the gap is filled, the indicator generates a signal to notify traders of this occurrence.
Key Features:
Customizable Parameters: Traders can adjust the sensitivity and criteria for what constitutes a significant gap based on their trading preferences and the market conditions.
Visual Alerts: The indicator provides clear visual signals on price charts, highlighting the presence of gaps and indicating when they are filled. This helps traders to easily spot trading opportunities and make informed decisions.
Alert Notifications: In addition to visual cues, traders can opt to receive real-time alerts via email, SMS, or within their trading platform, ensuring they never miss an opportunity or a filled gap.
Historical Analysis: The indicator may also offer historical gap data, allowing traders to conduct backtesting and analyze the performance of trading strategies based on gap patterns.
Benefits:
Gap Trading Opportunities: Traders can use the indicator to identify potential areas of price continuation or reversal, leveraging the phenomenon of gap trading for profit.
Risk Management: By tracking gap fills, traders can manage their risk more effectively, knowing when a gap is likely to act as support or resistance and adjusting their positions accordingly.
Enhanced Decision Making: With real-time gap detection and fill tracking, traders gain valuable insights into market sentiment and price dynamics, empowering them to make timely and informed trading decisions.
Compatibility:
The Gap Tracker Indicator is compatible with popular trading platforms and can be seamlessly integrated into various technical analysis tools and strategies.
Conclusion:
In the fast-paced world of financial markets, identifying and understanding price gaps is crucial for successful trading. The Gap Tracker Indicator provides traders with a reliable tool to spot, track, and capitalize on gap opportunities, enhancing their trading efficiency and profitability.
Normalised T3 Oscillator [BackQuant]Normalised T3 Oscillator
The Normalised T3 Oscillator is an technical indicator designed to provide traders with a refined measure of market momentum by normalizing the T3 Moving Average. This tool was developed to enhance trading decisions by smoothing price data and reducing market noise, allowing for clearer trend recognition and potential signal generation. Below is a detailed breakdown of the Normalised T3 Oscillator, its methodology, and its application in trading scenarios.
1. Conceptual Foundation and Definition of T3
The T3 Moving Average, originally proposed by Tim Tillson, is renowned for its smoothness and responsiveness, achieved through a combination of multiple Exponential Moving Averages and a volume factor. The Normalised T3 Oscillator extends this concept by normalizing these values to oscillate around a central zero line, which aids in highlighting overbought and oversold conditions.
2. Normalization Process
Normalization in this context refers to the adjustment of the T3 values to ensure that the oscillator provides a standard range of output. This is accomplished by calculating the lowest and highest values of the T3 over a user-defined period and scaling the output between -0.5 to +0.5. This process not only aids in standardizing the indicator across different securities and time frames but also enhances comparative analysis.
3. Integration of the Oscillator and Moving Average
A unique feature of the Normalised T3 Oscillator is the inclusion of a secondary smoothing mechanism via a moving average of the oscillator itself, selectable from various types such as SMA, EMA, and more. This moving average acts as a signal line, providing potential buy or sell triggers when the oscillator crosses this line, thus offering dual layers of analysis—momentum and trend confirmation.
4. Visualization and User Interaction
The indicator is designed with user interaction in mind, featuring customizable parameters such as the length of the T3, normalization period, and type of moving average used for signals. Additionally, the oscillator is plotted with a color-coded scheme that visually represents different strength levels of the market conditions, enhancing readability and quick decision-making.
5. Practical Applications and Strategy Integration
Traders can leverage the Normalised T3 Oscillator in various trading strategies, including trend following, counter-trend plays, and as a component of a broader trading system. It is particularly useful in identifying turning points in the market or confirming ongoing trends. The clear visualization and customizable nature of the oscillator facilitate its adaptation to different trading styles and market environments.
6. Advanced Features and Customization
Further enhancing its utility, the indicator includes options such as painting candles according to the trend, showing static levels for quick reference, and alerts for crossover and crossunder events, which can be integrated into automated trading systems. These features allow for a high degree of personalization, enabling traders to mold the tool according to their specific trading preferences and risk management requirements.
7. Theoretical Justification and Empirical Usage
The use of the T3 smoothing mechanism combined with normalization is theoretically sound, aiming to reduce lag and false signals often associated with traditional moving averages. The practical effectiveness of the Normalised T3 Oscillator should be validated through rigorous backtesting and adjustment of parameters to match historical market conditions and volatility.
8. Conclusion and Utility in Market Analysis
Overall, the Normalised T3 Oscillator by BackQuant stands as a sophisticated tool for market analysis, providing traders with a dynamic and adaptable approach to gauging market momentum. Its development is rooted in the understanding of technical nuances and the demand for a more stable, responsive, and customizable trading indicator.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Consecutive count backtester / quantifytools- Overview
Consecutive counting is a simple method to mechanically define trending states to the upside and downside. Consecutive counts are calculated by taking reference price level (e.g. close 4 candles ago) and count closes above/below it up to a maximum count that resets the consecutive count back to 1. This tool provides the means to backtest each count by measuring % change in price after each count (e.g. % gain 2 candles after a given count).
Users can define reference source that starts the consecutive count (e.g. close 4 candles ago), maximum count where counter resets (e.g. after 9th count) and backtesting period (e.g. price change 2 candles after count).
Filters add extra conditions that must be met on the consecutive count to qualify as valid, which are also reflected on the backtest metrics. The counts can be refined using the following filters:
- RSI above/below X
- Price above/below/at moving average of choice
- Relative volume above/below X
Average gain corresponding to each count as they occur can be toggled off for less clutter. Average price change can also be visualized using candle color. Colors, gradient and table/label sizes are fully customizable.
- Practical guide
Example #1: Identify reversal potential
Consecutive counting is a simple yet effective method to for detecting reversals, for which 7-9 counts are traditionally used. Whether that holds true or not can now be put through a test with different variations of the method as well as using additional filters to improve the probability of a turn.
Example #2: Identify trend following potential
Consecutive counts can also have utility value for trend following. When historical short term change is to the downside, expect downside, when to the upside, expect upside.
