EMA CheatsheetEMA Clouds Indicator: A Comprehensive Guide for Traders
The Exponential Moving Average (EMA) Clouds indicator is a dynamic tool designed to provide traders with visual cues about the current trend and potential shifts in market momentum. The EMA is a type of moving average that gives more weight to recent price data, making it highly responsive to price changes compared to a Simple Moving Average (SMA). When used in the form of clouds, EMAs are layered on top of each other to form a visual representation of bullish and bearish trends.
Understanding EMA Clouds
EMA Clouds consist of two or more EMAs, typically a short-term EMA (e.g., 9-period) and a longer-term EMA (e.g., 21-period). When these two EMAs are plotted together, they create a "cloud" between them. The interaction between these EMAs gives traders critical insights into the market's trend:
Bullish Clouds: When the shorter-term EMA crosses above the longer-term EMA, the market is considered to be in a bullish trend. This creates a green (or lighter colored) cloud between the EMAs, signaling upward momentum. Bullish clouds suggest that buyers are in control, and the price is likely to continue higher.
Bearish Clouds: Conversely, when the shorter-term EMA crosses below the longer-term EMA, the market is considered to be in a bearish trend. This forms a red (or darker colored) cloud between the EMAs, indicating downward momentum. Bearish clouds imply that sellers are dominating the market, and the price is likely to decline.
Key Components of the EMA Clouds Indicator:
Short-Term EMA: This is the fast-moving average (e.g., 9-period EMA) and reacts quickly to recent price changes. It’s used to detect short-term shifts in momentum.
Long-Term EMA: This is the slower-moving average (e.g., 21-period EMA), which smooths out price data over a longer period and identifies the general trend direction.
Cloud: The area between the short-term and long-term EMAs. When this cloud is green (bullish), it indicates that the short-term trend is stronger than the long-term trend. When the cloud turns red (bearish), it suggests that the short-term trend is weaker than the long-term trend.
Cloud Thickness: The thickness of the cloud provides additional information about the strength of the trend. A thicker cloud suggests strong price divergence between short and long-term trends, which could indicate a robust trend. A thinner cloud, on the other hand, may signal trend weakness or consolidation.
Скользящие средние
Precision Cloud by Dr ABIRAM SIVPRASAD
Precision Cloud by Dr. Abhiram Sivprasad"
The " Precision Cloud" script, created by Dr. Abhiram Sivprasad, is a multi-purpose technical analysis tool designed for Forex, Bitcoin, Commodities, Stocks, and Options trading. It focuses on identifying key levels of support and resistance, combined with moving averages (EMAs) and central pivot ranges (CPR), to help traders make informed trading decisions. The script also provides a visual "light system" to highlight potential long or short positions, aiding traders in entering trades with a clear strategy.
Key Features of the Script:
Central Pivot Range (CPR):
The CPR is calculated as the average of the high, low, and close of the price, while the top and bottom pivots are derived from it. These act as dynamic support and resistance zones.
The script can plot daily CPR, support, and resistance levels (S1/R1, S2/R2, S3/R3) as well as optional weekly and monthly pivot points.
The CPR helps identify whether the price is in a bullish, bearish, or neutral zone.
Support and Resistance Levels:
Three daily support (S1, S2, S3) and resistance (R1, R2, R3) levels are plotted based on the CPR.
These levels act as potential reversal or breakout points, allowing traders to make decisions around key price points.
EMA (Exponential Moving Averages):
The script includes two customizable EMAs (default periods of 9 and 21). You can choose the source for these EMAs (open, high, low, or close).
The crossovers between EMA1 and EMA2 help identify potential trend reversals or momentum shifts.
Lagging Span:
The Lagging Span is plotted with a customizable displacement (default 26), which helps identify overall trend direction by comparing past price with the current price.
Light System:
A color-coded table provides a visual representation of market conditions:
Green indicates bullish signals (e.g., price above CPR, EMAs aligning positively).
Red indicates bearish signals (e.g., price below CPR, EMAs aligning negatively).
Yellow indicates neutral conditions, where there is no clear trend direction.
The system includes lights for CPR, EMA, Long Position, and Short Position, helping traders quickly assess whether the market is in a buying or selling opportunity.
Trading Strategies Using the Script
1. Forex Trading:
Trend-Following with EMAs: Use the EMA crossovers to capture trending markets in Forex. A green light for the EMA combined with a price above the daily or weekly pivot levels suggests a buying opportunity. Conversely, if the EMA light turns red and price falls below the CPR levels, look for shorting opportunities.
Reversal Strategy: Watch for price action near the daily S1/R1 levels. If price holds above S1 and the EMA is green, this could signal a reversal from support. The same applies to resistance levels.
2. Bitcoin Trading:
Momentum Breakouts: Bitcoin is known for its sharp moves. The script helps to identify breakouts from the CPR range. If the price breaks above the TC (Top Central Pivot) with bullish EMA alignment (green light), it could signal a strong uptrend.
Lagging Span Confirmation: Use the Lagging Span to confirm the trend direction. For Bitcoin's volatility, when the lagging span shows consistent alignment with the price and CPR, it often indicates continuation of the trend.
3. Commodities Trading:
Support/Resistance Bounce: Commodities such as gold and oil often react well to pivot levels. Look for price bouncing off S1 or R1 for potential entry points. A green CPR light along with price above the pivot range supports a bullish bias.
EMA Pullback Strategy: If price moves in a strong trend and pulls back to one of the EMAs, a green EMA light suggests re-entry on a pullback. If the EMA light is red and price breaks below the BC (Bottom Central Pivot), short positions could be considered.
4. Stocks Trading:
Long Position Strategy: For stocks, use the combination of the long position light turning green (price above TC and EMA alignment) as a signal to buy. This could be especially useful for riding bullish trends in growth stocks or during earnings seasons when volatility is high.
Short Position Strategy: If the short position light turns green, indicating price below BC and EMAs turning bearish, this could be an ideal setup for shorting overvalued stocks or during market corrections.
5. Options Trading:
Directional Bias for Options: The light system is particularly helpful for options traders. A green long position light provides a clear signal to buy call options, while a green short position light supports buying puts.
Pivot Breakout Strategy: Buy options (calls or puts) when the price breaks above resistance or below support, with confirmation from the CPR and EMA lights. This helps capture the sharp moves required for profitable options trades.
Conclusion
The S&R Precision Cloud script is a versatile tool for traders across markets, including Forex, Bitcoin, Commodities, Stocks, and Options. It combines critical technical elements like pivot ranges, support and resistance levels, EMAs, and the Lagging Span to provide a clear picture of market conditions. The intuitive light system helps traders quickly assess whether to take a long or short position, making it an excellent tool for both new and experienced traders.
The S&R Precision Cloud by Dr. Abhiram Sivprasad script is a technical analysis tool designed to assist traders in making informed decisions. However, it should not be interpreted as financial or investment advice. The signals generated by the script are based on historical price data and technical indicators, which are inherently subject to market fluctuations and do not guarantee future performance.
Trading in Forex, Bitcoin, Commodities, Stocks, and Options carries a high level of risk and may not be suitable for all investors. You should be aware of the risks involved and be willing to accept them before engaging in such activities. Always conduct your own research and consult with a licensed financial advisor or professional before making any trading decisions.
The creators of this script are not responsible for any financial losses that may occur from its use. Past performance is not indicative of future results, and the use of this script is at your own risk.
AHR999 Bitcoin Buy/Sell Signals Indicator - Accurate Trading OppThis Pine Script indicator combines the AHR999 metric with Bitcoin's historical price trends to provide clear buy and sell signals, assisting you in making informed trading decisions at crucial moments. It calculates the AHR999 index based on Bitcoin's 200-day Geometric Moving Average (GMA) and the estimated price, offering customizable buy and sell thresholds for precise entry and exit points. Ideal for traders looking to capture long-term investment trends, this indicator helps you effectively identify Bitcoin market opportunities.
Sigma 2.0 - Advanced Buy and Sell Signal IndicatorOverview:
Sigma 2.0 is a sophisticated trading indicator designed to help traders identify potential buy and sell opportunities across various financial markets. By leveraging advanced mathematical calculations and incorporating multiple analytical tools, Sigma 2.0 aims to enhance trading strategies by providing precise entry and exit signals.
Key Features:
Advanced Sigma Calculations:
Utilizes a combination of Exponential Moving Averages (EMAs) and price deviations to calculate the Sigma lines (sigma1 and sigma2).
Detects potential trend reversals through the crossover of these Sigma lines.
Customizable Signal Filtering:
Offers the ability to filter buy and sell signals based on user-defined thresholds.
Helps reduce false signals in volatile markets by setting overbought and oversold levels.
Overbought and Oversold Detection:
Identifies extreme market conditions where price reversals are more likely.
Changes the background color of the chart to visually indicate overbought or oversold states.
Integration of Exponential Moving Averages (EMAs):
Includes EMAs of different lengths (10, 21, 55, 200) to assist in identifying market trends.
EMAs act as dynamic support and resistance levels.
Higher Timeframe Signal Incorporation:
Allows users to include signals from a higher timeframe to align trades with the broader market trend.
Enhances the reliability of signals by considering multiple timeframes.
Custom Alerts:
Provides alert conditions for both buy and sell signals.
Enables traders to receive notifications, ensuring timely decision-making.
How It Works:
Sigma Calculation Methodology:
The indicator calculates an average price (ap) and applies EMAs to derive the Sigma lines.
sigma1 represents the smoothed price deviation, while sigma2 is a moving average of sigma1.
A crossover of sigma1 above sigma2 generates a buy signal, indicating potential upward momentum.
Conversely, a crossover of sigma1 below sigma2 generates a sell signal.
Signal Filtering and Thresholds:
Users can enable filtering to only consider signals when sigma1 is below or above certain thresholds.
This helps in focusing on more significant market movements and reducing noise.
Overbought/Oversold Levels:
The indicator monitors sigma1 to detect when the market is in extreme conditions.
Background color changes provide a quick visual cue for these conditions.
EMA Analysis:
The plotted EMAs help in confirming the trend direction.
They can be used alongside Sigma signals to validate trade entries and exits.
Higher Timeframe Signals:
Incorporates signals from a user-selected higher timeframe.
Helps in aligning trades with the overall market trend, increasing the potential success rate.
How to Use:
Adding the Indicator to Your Chart:
Search for "Sigma 2.0" in the TradingView Indicators menu and add it to your chart.
Configuring the Settings:
Adjust the Sigma configurations (Channel Length, Average Length, Signal Line Length) to suit your trading style.
Set the overbought and oversold levels according to your risk tolerance.
Choose whether to filter signals by thresholds.
Select the higher timeframe for additional signal confirmation.
Interpreting the Signals:
Buy Signals:
Indicated by a green triangle below the price bar.
Occur when sigma1 crosses above sigma2 and other conditions are met.
Sell Signals:
Indicated by a red triangle above the price bar.
Occur when sigma1 crosses below sigma2 and other conditions are met.
Higher Timeframe Signals:
Plotted with lime (buy) and maroon (sell) triangles.
Help confirm signals in the current timeframe.
Utilizing EMAs:
Observe the EMAs to gauge the overall trend.
Consider aligning buy signals when the price is above key EMAs and sell signals when below.
Setting Up Alerts:
Use the built-in alert conditions to receive notifications for buy and sell signals.
Customize alert messages as needed.
Credits:
Original Concept Inspiration:
This indicator is inspired by the WaveTrend oscillator and other momentum-based indicators.
Special thanks to the original authors whose work laid the foundation for this enhanced version.
Disclaimer:
Trading involves significant risk, and past performance is not indicative of future results.
This indicator is a tool to assist in analysis and should not be the sole basis for any trading decision.
Always perform thorough analysis and consider multiple factors before entering a trade.
Note:
Ensure your chart is clean and only includes this indicator when publishing.
The script is open-source and can be modified to fit individual trading strategies.
For any questions or support, feel free to reach out or comment.
Hyperbolic Tangent Volatility Stop [InvestorUnknown]The Hyperbolic Tangent Volatility Stop (HTVS) is an advanced technical analysis tool that combines the smoothing capabilities of the Hyperbolic Tangent Moving Average (HTMA) with a volatility-based stop mechanism. This indicator is designed to identify trends and reversals while accounting for market volatility.
Hyperbolic Tangent Moving Average (HTMA):
The HTMA is at the heart of the HTVS. This custom moving average uses a hyperbolic tangent transformation to smooth out price fluctuations, focusing on significant trends while ignoring minor noise. The transformation reduces the sensitivity to sharp price movements, providing a clearer view of the underlying market direction.
The hyperbolic tangent function (tanh) is commonly used in mathematical fields like calculus, machine learning and signal processing due to its properties of “squashing” inputs into a range between -1 and 1. The function provides a non-linear transformation that can reduce the impact of extreme values while retaining a certain level of smoothness.
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
The HTMA is calculated by applying a non-linear transformation to the difference between the source price and its simple moving average, then adjusting it using the standard deviation of the price data. The result is a moving average that better tracks the real market direction.
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Important Note: The Hyperbolic Tangent function becomes less accurate with very high prices. For assets priced above 100,000, the results may deteriorate, and for prices exceeding 1 million, the function may stop functioning properly. Therefore, this indicator is better suited for assets with lower prices or lower price ratios.
Volatility Stop (VolStop):
HTVS employs a Volatility Stop mechanism based on the Average True Range (ATR). This stop dynamically adjusts based on market volatility, ensuring that the indicator adapts to changing conditions and avoids false signals in choppy markets.
The VolStop follows the price, with a higher ATR pushing the stop farther away to avoid premature exits during volatile periods. Conversely, when volatility is low, the stop tightens to lock in profits as the trend progresses.
The ATR Length and ATR Multiplier are customizable, allowing traders to control how tightly or loosely the stop follows the price.
pine_volStop(src, atrlen, atrfactor) =>
if not na(src)
var max = src
var min = src
var uptrend = true
var float stop = na
atrM = nz(ta.atr(atrlen) * atrfactor, ta.tr)
max := math.max(max, src)
min := math.min(min, src)
stop := nz(uptrend ? math.max(stop, max - atrM) : math.min(stop, min + atrM), src)
uptrend := src - stop >= 0.0
if uptrend != nz(uptrend , true)
max := src
min := src
stop := uptrend ? max - atrM : min + atrM
Backtest Mode:
HTVS includes a built-in backtest mode, allowing traders to evaluate the indicator's performance on historical data. In backtest mode, it calculates the cumulative equity curve and compares it to a simple buy and hold strategy.
Backtesting features can be adjusted to focus on specific signal types, such as Long Only, Short Only, or Long & Short.
An optional Buy and Hold Equity plot provides insight into how the indicator performs relative to simply holding the asset over time.
The indicator includes a Hints Table, which provides useful recommendations on how to best display the indicator for different use cases. For example, when using the overlay mode, it suggests displaying the indicator in the same pane as price action, while backtest mode is recommended to be used in a separate pane for better clarity.
The Hyperbolic Tangent Volatility Stop offers traders a balanced approach to trend-following, using the robustness of the HTMA for smoothing and the adaptability of the Volatility Stop to avoid whipsaw trades during volatile periods. With its backtesting features and alert system, this indicator provides a comprehensive toolkit for active traders.
Hyperbolic Tangent SuperTrend [InvestorUnknown]The Hyperbolic Tangent SuperTrend (HTST) is designed for technical analysis, particularly in markets with assets that have lower prices or price ratios. This indicator leverages the Hyperbolic Tangent Moving Average (HTMA), a custom moving average calculated using the hyperbolic tangent function, to smooth price data and reduce the impact of short-term volatility.
Hyperbolic Tangent Moving Average (HTMA):
The indicator's core uses a hyperbolic tangent function to calculate a smoothed average of the price. The HTMA provides enhanced trend-following capabilities by dampening the impact of sharp price swings and maintaining a focus on long-term market movements.
The hyperbolic tangent function (tanh) is commonly used in mathematical fields like calculus, machine learning and signal processing due to its properties of “squashing” inputs into a range between -1 and 1. The function provides a non-linear transformation that can reduce the impact of extreme values while retaining a certain level of smoothness.
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
The HTMA is calculated by taking the difference between the price and its simple moving average (SMA), applying a multiplier to control sensitivity, and then transforming it using the hyperbolic tangent function.
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Important Note: The Hyperbolic Tangent function becomes less accurate with very high prices. For assets priced above 100,000, the results may deteriorate, and for prices exceeding 1 million, the function may stop functioning properly. Therefore, this indicator is better suited for assets with lower prices or lower price ratios.
SuperTrend Calculation:
In addition to the HTMA, the indicator includes an Average True Range (ATR)-based SuperTrend calculation, which helps identify uptrends and downtrends in the market. The SuperTrend is adjusted dynamically using the HTMA to avoid false signals in fast-moving markets.
The ATR period and multiplier are customizable, allowing users to fine-tune the sensitivity of the trend signals.
pine_supertrend(src, calc_price, atrPeriod, factor) =>
atr = ta.atr(atrPeriod)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or calc_price < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or calc_price > prevUpperBand ? upperBand : prevUpperBand
int _direction = na
float superTrend = na
prevSuperTrend = superTrend
if na(atr )
_direction := 1
else if prevSuperTrend == prevUpperBand
_direction := calc_price > upperBand ? -1 : 1
else
_direction := calc_price < lowerBand ? 1 : -1
superTrend := _direction == -1 ? lowerBand : upperBand
Inbuilt Backtest Mode:
The HTST includes an inbuilt backtest mode that enables users to test the indicator's performance against historical data, similar to TradingView strategies.
The backtest mode allows you to compare the performance of different indicator settings with a simple buy and hold strategy to assess its effectiveness in different market conditions.
Hint Table for Display Modes:
The indicator includes a Hint Table that recommends the best pane to use for different display modes. For example, it suggests using the "Overlay" mode in the same pane as the price action, while the "Backtest Mode" is better suited for a separate pane. This ensures a more organized and clear visual experience.
The Hint Table appears as a small table at the bottom of the chart with easy-to-follow recommendations, ensuring the best setup for both visual clarity and indicator functionality.
With these features, the Hyperbolic Tangent SuperTrend Indicator offers traders a versatile and customizable tool for analyzing price trends while providing additional functionalities like backtesting and display mode hints for optimal usability.
Momentum Cloud.V33🌟 Introducing MomentumCloud.V33 🌟
MomentumCloud.V33 is a cutting-edge indicator designed to help traders capture market momentum with clarity and precision. This versatile tool combines moving averages, directional movement indexes (DMI), and volume analysis to provide real-time insights into trend direction and strength. Whether you’re a scalper, day trader, or swing trader, MomentumCloud.V33 adapts to your trading style and timeframe, making it an essential addition to your trading toolkit. 📈💡
🔧 Customizable Parameters:
• Moving Averages: Adjust the periods of the fast (MA1) and slow (MA2) moving averages to fine-tune your trend analysis.
• DMI & ADX: Customize the DMI length and ADX smoothing to focus on strong, actionable trends.
• Volume Multiplier: Modify the cloud thickness based on trading volume, emphasizing trends with significant market participation.
📊 Trend Detection:
• Color-Coded Clouds:
• Green Cloud: Indicates a strong uptrend, suggesting buying opportunities.
• Red Cloud: Indicates a strong downtrend, signaling potential short trades.
• Gray Cloud: Reflects a range-bound market, helping you avoid low-momentum periods.
• Dynamic Volume Integration: The cloud thickness adjusts dynamically with trading volume, highlighting strong trends supported by high market activity.
📈 Strength & Momentum Analysis:
• Strength Filtering: The ADX component ensures that only strong trends are highlighted, filtering out market noise and reducing false signals.
• Visual Momentum Gauge: The cloud color and thickness provide a quick visual representation of market momentum, enabling faster decision-making.
🔔 Alerts:
• Custom Alerts: Set up alerts for when the trend shifts or reaches critical levels, keeping you informed without needing to constantly monitor the chart.
🎨 Visual Enhancements:
• Gradient Cloud & Shadows: The indicator features a gradient-filled cloud with shadowed moving averages, enhancing both aesthetics and clarity on your charts.
• Adaptive Visual Cues: MomentumCloud.V33’s color transitions and dynamic thickness provide an intuitive feel for the market’s rhythm.
🚀 Quick Guide to Using MomentumCloud.V33
1. Add the Indicator: Start by adding MomentumCloud.V33 to your chart. Customize the settings such as MA periods, DMI length, and volume multiplier to match your trading style.
2. Analyze the Market: Observe the color-coded cloud and its thickness to gauge market momentum and trend direction. The thicker the cloud, the stronger the trend.
3. Set Alerts: Activate alerts for trend changes or key levels to capture trading opportunities without needing to watch the screen continuously.
⚙️ How It Works:
MomentumCloud.V33 calculates market momentum by combining moving averages, DMI, and volume. The cloud color changes based on the trend direction, while its thickness reflects the strength of the trend as influenced by trading volume. This integrated approach ensures you can quickly identify robust market movements, making it easier to enter and exit trades at optimal points.
Settings Overview:
• Moving Averages: Define the lengths for the fast and slow moving averages.
• DMI & ADX: Adjust the DMI length and ADX smoothing to focus on significant trends.
• Volume Multiplier: Customize the multiplier to control cloud thickness, highlighting volume-driven trends.
📚 How to Use MomentumCloud.V33:
• Trend Identification: The direction and color of the cloud indicate the prevailing trend, while the cloud’s thickness suggests the trend’s strength.
• Trade Execution: Use the green cloud to look for long entries and the red cloud for short positions. The gray cloud advises caution, as it represents a range-bound market.
• Alerts: Leverage the custom alerts to stay on top of market movements and avoid missing critical trading opportunities.
Unleash the power of trend and momentum analysis with MomentumCloud.V33! Happy trading! 📈🚀✨
Enhanced MACD and RSI Buy/Sell Signals - Created by Marco NucupKey Features:
EMA Filter: Adds an Exponential Moving Average (EMA) to filter signals based on the trend. Buys are only considered when the price is above the EMA, and sells when below it.
Customizable Inputs: Users can adjust parameters for EMA, MACD, and RSI directly from the TradingView interface, allowing for more personalized strategies.
Alerts: The script includes alert conditions for both buy and sell signals, enabling users to receive notifications.
Signal Plotting: Visual indicators for buy and sell signals on the chart, along with the EMA line for trend reference.
Multi-Step FlexiMA - Strategy [presentTrading]It's time to come back! hope I can not to be busy for a while.
█ Introduction and How It Is Different
The FlexiMA Variance Tracker is a unique trading strategy that calculates a series of deviations between the price (or another indicator source) and a variable-length moving average (MA). Unlike traditional strategies that use fixed-length moving averages, the length of the MA in this system varies within a defined range. The length changes dynamically based on a starting factor and an increment factor, creating a more adaptive approach to market conditions.
This strategy integrates Multi-Step Take Profit (TP) levels, allowing for partial exits at predefined price increments. It enables traders to secure profits at different stages of a trend, making it ideal for volatile markets where taking full profits at once might lead to missed opportunities if the trend continues.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
🔶 FlexiMA Concept
The FlexiMA (Flexible Moving Average) is at the heart of this strategy. Unlike traditional MA-based strategies where the MA length is fixed (e.g., a 50-period SMA), the FlexiMA varies its length with each iteration. This is done using a **starting factor** and an **increment factor**.
The formula for the moving average length at each iteration \(i\) is:
`MA_length_i = indicator_length * (starting_factor + i * increment_factor)`
Where:
- `indicator_length` is the user-defined base length.
- `starting_factor` is the initial multiplier of the base length.
- `increment_factor` increases the multiplier in each iteration.
Each iteration applies a **simple moving average** (SMA) to the chosen **indicator source** (e.g., HLC3) with a different length based on the above formula. The deviation between the current price and the moving average is then calculated as follows:
`deviation_i = price_current - MA_i`
These deviations are normalized using one of the following methods:
- **Max-Min normalization**:
`normalized_i = (deviation_i - min(deviations)) / range(deviations)`
- **Absolute Sum normalization**:
`normalized_i = deviation_i / sum(|deviation_i|)`
The **median** and **standard deviation (stdev)** of the normalized deviations are then calculated as follows:
`median = median(normalized deviations)`
For the standard deviation:
`stdev = sqrt((1/(N-1)) * sum((normalized_i - mean)^2))`
These values are plotted to provide a clear indication of how the price is deviating from its variable-length moving averages.
For more detail:
🔶 Multi-Step Take Profit
This strategy uses a multi-step take profit system, allowing for exits at different stages of a trade based on the percentage of price movement. Three take-profit levels are defined:
- Take Profit Level 1 (TP1): A small, quick profit level (e.g., 2%).
- Take Profit Level 2 (TP2): A medium-level profit target (e.g., 8%).
- Take Profit Level 3 (TP3): A larger, more ambitious target (e.g., 18%).
At each level, a corresponding percentage of the trade is exited:
- TP Percent 1: E.g., 30% of the position.
- TP Percent 2: E.g., 20% of the position.
- TP Percent 3: E.g., 15% of the position.
This approach ensures that profits are locked in progressively, reducing the risk of market reversals wiping out potential gains.
Local
🔶 Trade Entry and Exit Conditions
The entry and exit signals are determined by the interaction between the **SuperTrend Polyfactor Oscillator** and the **median** value of the normalized deviations:
- Long entry: The SuperTrend turns bearish, and the median value of the deviations is positive.
- Short entry: The SuperTrend turns bullish, and the median value is negative.
Similarly, trades are exited when the SuperTrend flips direction.
* The SuperTrend Toolkit is made by @EliCobra
█ Trade Direction
The strategy allows users to specify the desired trade direction:
- Long: Only long positions will be taken.
- Short: Only short positions will be taken.
- Both: Both long and short positions are allowed based on the conditions.
This flexibility allows the strategy to adapt to different market conditions and trading styles, whether you're looking to buy low and sell high, or sell high and buy low.
█ Usage
This strategy can be applied across various asset classes, including stocks, cryptocurrencies, and forex. The primary use case is to take advantage of market volatility by using a flexible moving average and multiple take-profit levels to capture profits incrementally as the market moves in your favor.
How to Use:
1. Configure the Inputs: Start by adjusting the **Indicator Length**, **Starting Factor**, and **Increment Factor** to suit your chosen asset. The defaults work well for most markets, but fine-tuning them can improve performance.
2. Set the Take Profit Levels: Adjust the three **TP levels** and their corresponding **percentages** based on your risk tolerance and the expected volatility of the market.
3. Monitor the Strategy: The SuperTrend and the FlexiMA variance tracker will provide entry and exit signals, automatically managing the positions and taking profits at the pre-set levels.
█ Default Settings
The default settings for the strategy are configured to provide a balanced approach that works across different market conditions:
Indicator Length (10):
This controls the base length for the moving average. A lower length makes the moving average more responsive to price changes, while a higher length smooths out fluctuations, making the strategy less sensitive to short-term price movements.
Starting Factor (1.0):
This determines the initial multiplier applied to the moving average length. A higher starting factor will increase the average length, making it slower to react to price changes.
Increment Factor (1.0):
This increases the moving average length in each iteration. A larger increment factor creates a wider range of moving average lengths, allowing the strategy to track both short-term and long-term trends simultaneously.
Normalization Method ('None'):
Three methods of normalization can be applied to the deviations:
- None: No normalization applied, using raw deviations.
- Max-Min: Normalizes based on the range between the maximum and minimum deviations.
- Absolute Sum: Normalizes based on the total sum of absolute deviations.
Take Profit Levels:
- TP1 (2%): A quick exit to capture small price movements.
- TP2 (8%): A medium-term profit target for stronger trends.
- TP3 (18%): A long-term target for strong price moves.
Take Profit Percentages:
- TP Percent 1 (30%): Exits 30% of the position at TP1.
- TP Percent 2 (20%): Exits 20% of the position at TP2.
- TP Percent 3 (15%): Exits 15% of the position at TP3.
Effect of Variables on Performance:
- Short Indicator Lengths: More responsive to price changes but prone to false signals.
- Higher Starting Factor: Slows down the response, useful for longer-term trend following.
- Higher Increment Factor: Widens the variability in moving average lengths, making the strategy adapt to both short-term and long-term price trends.
- Aggressive Take Profit Levels: Allows for quick profit-taking in volatile markets but may exit positions prematurely in strong trends.
The default configuration offers a moderate balance between short-term responsiveness and long-term trend capturing, suitable for most traders. However, users can adjust these variables to optimize performance based on market conditions and personal preferences.
Smart Candle SizeIndicator Description: Smart Candle Size
The Smart Candle Size is a technical indicator designed for traders who seek to analyze market momentum and optimize their strategies based on candle size, trend direction, and risk management parameters. This indicator combines several analytical tools to offer a deeper understanding of price movements, facilitating the identification of potential trading opportunities.
What Does the Indicator Do?
The indicator analyzes each candle in relation to the previous one, evaluating whether the size and position of the current candle meet certain predefined criteria. By incorporating an Exponential Moving Average (EMA) as a trend filter and adjusting variables such as candle size proportion, maximum candle size, and minimum distance from the EMA, the indicator helps identify market conditions that may be favorable for entering or exiting a trade.
How Does the Indicator Work?
Candle Size Comparison:
Size Proportion: The indicator compares the size of the current candle to the previous one. If the current candle is proportionally larger based on the set value (e.g., 1.3 times larger), it is considered significant.
Trend Filter with EMA:
Exponential Moving Average (EMA): An adjustable-length EMA is used to determine the general market trend. Bullish signals are considered when the price is above the EMA, and bearish signals when it is below.
Additional Filters:
Maximum Candle Size: Limits the size of candles considered to avoid the influence of unusually large candles.
Minimum Distance from EMA: Ensures that the price is sufficiently away from the EMA to avoid signals in congested zones.
Calculation of Stop-Loss and Take-Profit Levels:
Based on the configured ticks, the indicator calculates and visually displays the SL and TP levels on the chart.
Visual Signals:
Candle Coloring: Candles that meet the criteria are dynamically colored (green for bullish and red for bearish).
Buy/Sell Labels: "W" labels are displayed for possible bullish opportunities and "X" for bearish ones.
EMA Visualization:
A shading is added around the EMA to provide an additional visual reference on the trend.
How to Use the Indicator?
Parameter Configuration:
Adjust the Size Proportion to set how much larger the current candle must be compared to the previous one.
Define the EMA Length according to your trading strategy.
Set the Maximum Candle Size and Minimum Distance from EMA to filter out unwanted signals.
Configure the SL and TP Ticks to automatically calculate the stop-loss and take-profit levels.
Signal Interpretation:
Green Candles (Bullish): Indicate possible buying opportunities if all criteria are met.
Red Candles (Bearish): Indicate possible short-selling opportunities.
Use the "W" and "X" labels as additional visual confirmation.
Trade Planning:
Use the SL and TP levels displayed on the chart to plan your orders and manage risk.
Visual Customization:
Select the Chart Mode (Light or Dark) to adapt the indicator to your visual preferences.
Example Configuration for AUDJPY
As an example, here is a configuration applied to the AUDJPY currency pair:
Size Proportion: 1.3
EMA Length: 27
Maximum Candle Size: 120
Minimum Distance from EMA: 141
SL Ticks: 100
TP Ticks: 300
This configuration can be used as a starting point and adjusted according to the specific characteristics of AUDJPY and the individual trader's preferences.
What Makes This Indicator Original?
Integration of Multiple Filters: Combines candle size comparison with trend and volatility filters to offer more refined signals.
Extensive Customization: Allows adjustment of multiple parameters to suit different assets and trading styles.
Intuitive Visualization: Provides clear visual signals and SL/TP levels directly on the chart, facilitating decision-making.
Built-in Risk Management: By calculating and displaying SL and TP levels, the indicator aids in planning and risk management for each trade.
Additional Considerations
Not a Standalone Indicator: It is recommended to use this indicator in conjunction with other technical and fundamental analyses for better decision-making.
Prior Testing: Before using it on a real account, it is advisable to test the indicator on a demo account to familiarize yourself with its functionality and adjust parameters as necessary.
Limitations: Like all technical indicators, it does not guarantee results and should be used as a support tool.
Conclusion
The Smart Candle Size is a versatile tool that offers a combination of price action analysis and risk management. By providing significant details on how it works and how it can be customized, traders can leverage its features to complement their trading strategies across different markets and time frames.
Compatible with TradingView and ready for immediate use, this indicator can be a valuable addition to your set of trading tools.
[GL3] SMA & EMA Crossover Ribbon with Reactive Gradient CloudsGL3] SMA & EMA Crossover Ribbon with Reactive Gradient Clouds
This indicator provides a powerful blend of technical analysis tools, integrating multiple moving averages, such as Simple Moving Average (SMA) and Exponential Moving Average (EMA), along with custom moving averages like Kaufman's Adaptive Moving Average (KAMA), Jurik Moving Average (JMA), and others. The crossover strategy aims to identify trend changes with precision across different timeframes.
Key Features:
Crossover Ribbon: A set of 5 moving average pairs to capture short-, mid-, and long-term trends. The crossover between the leading and trigger lines visually indicates potential buy (uptrend) and sell (downtrend) signals.
Reactive Gradient Clouds: Dynamically color-coded clouds that visualize momentum shifts using Stochastic, RSI, MACD, and Chande Momentum. These clouds help to react faster to price changes and confirm trends:
Stochastic Cloud: Blue for bullish and Orange for bearish trends.
RSI Cloud: Purple for bullish and Yellow for bearish trends.
MACD Cloud: Green for bullish and Red for bearish trends.
Chande Momentum Cloud: Aqua for bullish and Fuchsia for bearish trends.
Alerts: Custom alerts for significant crossovers in Stochastic, RSI, MACD, and Chande Momentum, allowing traders to stay informed of potential trend reversals.
Customizable Inputs: Flexible configuration for various moving averages, lengths, and source types, along with options to show/hide gradient clouds for each momentum indicator.
This indicator is designed for traders looking to capture multiple levels of trend direction and momentum shifts. The combination of crossovers and clouds provides a clear trend direction and quicker reaction to market moves, making it a versatile tool for various trading strategies.
Disclaimer: Past performance is not indicative of future results. Always use additional risk management tools and trade responsibly
TechniTrend: Average VolatilityTechniTrend: Average Volatility
Description:
The "Average Volatility" indicator provides a comprehensive measure of market volatility by offering three different types of volatility calculations: High to Low, Body, and Shadows. The indicator allows users to apply various types of moving averages (SMA, EMA, SMMA, WMA, and VWMA) on these volatility measures, enabling a more flexible approach to trend analysis and volatility tracking.
Key Features:
Customizable Volatility Types:
High to Low: Measures the range between the highest and lowest prices in the selected period.
Body: Measures the absolute difference between the opening and closing prices of each candle (just the body of the candle).
Shadows: Measures the difference between the wicks (shadows) of the candle.
Flexible Moving Averages:
Choose from five different types of moving averages to apply on the calculated volatility:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
SMMA (RMA) (Smoothed Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume-Weighted Moving Average)
Custom Length:
Users can customize the period length for the moving averages through the Length input.
Visualization:
Three separate plots are displayed, each representing the average volatility of a different type:
Blue: High to Low volatility.
Green: Candle body volatility.
Red: Candle shadows volatility.
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This indicator offers a versatile and highly customizable tool for analyzing volatility across different components of price movement, and it can be adapted to different trading styles or market conditions.
Gaussian SWMA For LoopGaussian SWMA For Loop Indicator
The "Gaussian SWMA For Loop" is a sophisticated indicator designed to identify potential trading opportunities by combining a Gaussian-weighted moving average (WMA) with a simple moving average (SMA), enhanced by a loop-based scoring system. This indicator is tailored for traders looking to capture trends and reversals with a refined approach, making use of advanced filtering techniques and custom thresholds for signal generation.
Key Features:
1. Gaussian Weighted Moving Average (WMA):
The indicator starts by applying a Gaussian filter to the input price data (default is the closing price). The Gaussian filter smooths the data by applying weights according to a Gaussian distribution, determined by the Gaussian Sigma parameter. This results in a smooth, noise-reduced WMA, which is more responsive to significant price movements while ignoring minor fluctuations.
2. Simple Moving Average (SMA) on Smoothed Data:
After the data is smoothed using the Gaussian filter, an SMA is calculated over this smoothed data. The length of this SMA can be adjusted via the SMA Length input, allowing users to control the level of additional smoothing applied to the already filtered data.
3. Loop-Based Scoring System:
Range Analysis: The core feature of this indicator is the loop-based scoring system. It evaluates the filtered SMA by comparing its current value to previous values over a specified range, defined by the From and To parameters.
Score Calculation: The loop iterates through each value within the defined range and adjusts a score based on whether the current filtered SMA is higher or lower than its historical values. This score is a measure of the trend's strength and direction.
Thresholds for Signal Generation: Users can define custom thresholds for long (Long Threshold) and short (Short Threshold) signals. The score is compared against these thresholds to generate buy and sell signals.
4. Signal Generation:
Buy Signal (L): Triggered when the score exceeds the user-defined Long Threshold.
Sell Signal (S): Triggered when the score falls below the Short Threshold.
5. Visual Enhancements:
The indicator plots the filtered SMA on the chart, with the line and bar colors changing based on the buy and sell signals:
Teal (color.rgb(0, 255, 187)) for a buy signal.
Magenta (color.rgb(255, 0, 157)) for a sell signal.
Gray for a neutral condition.
Additionally, the fill between the current and previous SMA values is colored based on the signal, providing a clear visual cue for trend direction and strength.
6. Alert Conditions:
The indicator includes customizable alerts that notify the user when a buy or sell signal is generated:
Long Alert: Notifies when a buy signal is triggered.
Short Alert: Notifies when a sell signal is triggered.
Configurable Inputs:
Main Group:
WMA Length (length): Sets the length of the Gaussian-weighted moving average.
SMA Length (len): Specifies the period for the SMA applied to the Gaussian-smoothed data.
Source (src): The price data used for calculations (default is the closing price).
Gaussian Sigma (sigma): Determines the standard deviation of the Gaussian distribution, influencing the smoothing effect.
For Loop Group:
From (a): The starting point for the loop-based score analysis.
To (b): The endpoint for the loop-based score analysis.
Threshold Group:
Long Threshold (threshold_L): Defines the score threshold above which a buy signal is triggered.
Short Threshold (threshold_S): Defines the score threshold below which a sell signal is triggered.
Practical Use:
This indicator is ideal for traders who want to identify trends and potential reversals with precision. The combination of Gaussian smoothing, SMA, and the loop-based scoring system offers a robust method to filter out noise and focus on significant market moves. The customizable thresholds and alert system further enhance its utility, making it a powerful tool for both manual and automated trading strategies.
Note: As with any trading indicator, it's recommended to backtest the "Gaussian SWMA For Loop" under various market conditions and use it in conjunction with other analysis techniques to confirm signals before making trading decisions.
Technical Analysis ExpressionsDescription:
The indicator allows to display different moving averages and price levels from any timeframe. Instead of setting each plot one by one, you can specify all of them in one expression.
Inputs:
There's only one input, which is a text area where you can specify each plot as an expression. Each expression must be on a new line. Each expression can specify the source of the displayed values, the plot color and the timeframe from which that value is taken.
Here's an example expression that will plot SMA(20) of Close price from Daily timeframe, and the plot is going to be red. This will also plot an EMA(50) of High price from current timeframe, and the plot is going to be green (notice that you can specify the color as one of the standard Pinescript colors, or using a HEX color, and even using transparency if needed):
SMA(close, 20) red "D"
EMA(high, 50) #00ff00
You can also specify the color to be "chart.fg" which is the Foreground Color of current chart (it depends on whether the "Dark Theme" is enabled in Tradingview). The available moving averages are: SMA, EMA, WMA, HMA, RMA, VWMA. The available sources are: open, high, low, close, hl2, hlc3, hlcc4, ohlc4.
US30 Challenge 3.0Purpose of the Script
This script is designed to provide advanced technical analysis for the US30 index by combining moving averages (MA and EMA) on different timeframes and a modified Keltner channel to analyze volatility. It visualizes trends across both daily and hourly charts and displays their relationship in a custom table, helping traders to make informed decisions based on the alignment of these indicators.
Explanation of the Key Features
User Input Parameters:
The script allows users to customize several parameters, such as whether to show the baseline moving average, which type of moving average to use (e.g., EMA, SMA, HMA), and the length of the moving average. These inputs make the script flexible, allowing users to adjust it to their trading style.
Moving Averages (MA and EMA):
Two types of moving averages are calculated: the baseline (which can be any of several moving average types) and two additional moving averages (SMA and EMA) based on user-defined periods. These are plotted on the chart to provide insight into the trend and momentum of the US30 price action.
The baseline moving average is central to the strategy, and its calculation can be customized by selecting different methods (e.g., SMA, EMA, or HMA), making it adaptable to different market conditions.
Volatility Bands (Keltner Channel):
The script calculates volatility bands using a method similar to the Keltner Channel. It can either use the True Range (ATR) or the simple high-low price difference to determine market volatility.
These bands are useful for identifying overbought and oversold conditions, as well as detecting periods of price contraction or expansion. The width of the bands is adjustable via a multiplier, allowing users to fine-tune their analysis.
Security Function for Higher Timeframes:
The script retrieves moving average values for the daily timeframe using the request.security() function, which allows it to display higher-timeframe information on lower-timeframe charts. This gives traders a multi-timeframe perspective, helping them align their shorter-term trades with the broader trend.
Trend and Cross Detection:
The script detects when the EMA crosses below or above the SMA on both the daily and hourly timeframes. These crossovers are significant for trend-following strategies, as they often signal shifts in market momentum.
It visually indicates whether the EMA is above or below the SMA for both timeframes using color-coded panels, providing an easy-to-read summary of market conditions.
Custom Table Display:
A custom table is created to summarize the trend information for both the daily and hourly timeframes. The table shows whether the EMA is above or below the SMA for each timeframe, with green or red background colors indicating bullish or bearish conditions, respectively.
This feature is particularly useful for traders who want a quick, at-a-glance confirmation of the trend across multiple timeframes without having to analyze the chart visually.
Visual Plotting:
The script plots the moving averages and volatility bands directly on the price chart, providing clear visual cues for traders. The baseline and bands help traders identify key support and resistance levels, while the additional moving averages help confirm the current trend direction.
How to Use the Script
Adjust Parameters:
Before using the script, traders can customize the type of baseline moving average, its length, and the volatility band multiplier to suit their specific strategy and market conditions. Users can also choose whether to use the True Range or high-low difference for the volatility calculation.
Multi-Timeframe Analysis:
The script combines information from both daily and hourly charts, making it ideal for traders who prefer to align their short-term trades with the broader market trend. The custom table provides a quick snapshot of the trend on both timeframes, allowing users to see if the EMA is above or below the SMA in both cases.
Visual Cues:
By watching the relationship between price and the plotted bands, traders can identify potential breakouts, consolidations, or reversals. The moving average crossovers provide a simple, yet powerful, signal for entering or exiting trades.
Trend Confirmation:
The color-coded custom table helps traders quickly confirm the trend without having to analyze the price action directly. If both the daily and hourly EMA are above their respective SMA, this indicates a strong bullish trend. Conversely, if the EMA is below the SMA on both timeframes, this signals a bearish trend.
Differences from Other Scripts
Multi-Timeframe Cross Detection: Unlike many scripts, this one focuses on detecting moving average crossovers across multiple timeframes (daily and hourly), providing traders with a more comprehensive view of the market.
Custom Volatility Band Calculation: It includes a customizable Keltner-like channel, offering flexibility in how volatility is calculated, which is not commonly found in standard indicators.
Visual Trend Table: The addition of a custom table to visually display trend confirmation across different timeframes sets this script apart from most others, making it easier for traders to digest the information.
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Propósito del Script
Este script está diseñado para proporcionar un análisis técnico avanzado del índice US30, combinando medias móviles (MA y EMA) en diferentes marcos de tiempo y un canal Keltner modificado para analizar la volatilidad. Visualiza las tendencias tanto en gráficos diarios como horarios y muestra su relación en una tabla personalizada, ayudando a los traders a tomar decisiones informadas basadas en la alineación de estos indicadores.
Explicación de las Características Clave
Parámetros de Entrada del Usuario:
El script permite a los usuarios personalizar varios parámetros, como si mostrar la media móvil base, qué tipo de media móvil usar (por ejemplo, EMA, SMA, HMA) y la longitud de la media móvil. Estos inputs hacen que el script sea flexible, permitiendo que los usuarios lo ajusten a su estilo de trading.
Medias Móviles (MA y EMA):
Se calculan dos tipos de medias móviles: la base (que puede ser de varios tipos) y dos medias adicionales (SMA y EMA) basadas en los períodos definidos por el usuario. Estas se trazan en el gráfico para proporcionar información sobre la tendencia y el impulso de la acción del precio del US30.
La media móvil base es central en la estrategia, y su cálculo se puede personalizar seleccionando diferentes métodos (por ejemplo, SMA, EMA, o HMA), lo que la hace adaptable a diferentes condiciones de mercado.
Bandas de Volatilidad (Canal Keltner):
El script calcula bandas de volatilidad usando un método similar al Canal Keltner. Puede usar el Rango Verdadero (ATR) o la simple diferencia entre el alto y el bajo del precio para determinar la volatilidad del mercado.
Estas bandas son útiles para identificar condiciones de sobrecompra y sobreventa, así como para detectar períodos de contracción o expansión del precio.
Función security() para Tiempos Superiores:
El script obtiene los valores de las medias móviles para el marco temporal diario, utilizando la función request.security(), lo que permite mostrar información de marcos temporales más largos en gráficos de marcos más cortos.
Detección de Cruces de Tendencia:
El script detecta cuando la EMA cruza por debajo o por encima de la SMA en los gráficos diarios y horarios. Estos cruces son significativos para estrategias de seguimiento de tendencias, ya que suelen señalar cambios en el impulso del mercado.
Tabla de Tendencias Personalizada:
Se crea una tabla personalizada para resumir la información de la tendencia en los gráficos diarios y horarios, mostrando si la EMA está por encima o por debajo de la SMA.
Trazado Visual:
El script traza las medias móviles y las bandas de volatilidad directamente en el gráfico de precios, proporcionando señales visuales claras para los traders.
Cómo usar el Script
Ajustar Parámetros.
Análisis Multi-Tiempo.
Señales Visuales.
Confirmación de Tendencia.
Diferencias con Otros Scripts
Detección Multi-Tiempo de Cruces.
Cálculo Personalizado de Bandas de Volatilidad.
Tabla Visual de Tendencia.
Saludos
VM y CS
Custom Buy BID StrategyThis Pine Script strategy is designed to identify and capitalize on upward trends in the market using the Average True Range (ATR) as a core component of the analysis. The script provides the following features:
Customizable ATR Calculation: Users can switch between different methods of ATR calculation (traditional or simple moving average).
Adjustable Parameters: The strategy allows for adjustable ATR periods, ATR multipliers, and custom time windows for executing trades.
Buy Signal Alerts: The strategy generates buy signals when the market shifts from a downtrend to an uptrend, based on ATR and price action.
Profit and Stop-Loss Management: Built-in take profit and stop-loss conditions are calculated as a percentage of the entry price, allowing for automatic position management.
Visual Enhancements: The script highlights the uptrend with green lines and optionally colors bars to help visualize market direction.
Flexible Timeframe: Users can configure a specific date range to activate the strategy, offering more control over when trades are executed.
This strategy is ideal for traders looking to automate their buy entries and manage risk with a straightforward trend-following approach. By utilizing customizable settings, it adapts to various market conditions and timeframes.
Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) // AlgoFyreThe Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) indicator adjusts moving averages based on market conditions, using Hurst Exponent for trend persistence, CVaR for extreme risk assessment, and Fractal Dimension for market complexity. It enhances trend detection and risk management across various timeframes.
TABLE OF CONTENTS
🔶 ORIGINALITY 🔸Adaptive Mechanisms
🔸Multi-Faceted Analysis
🔸Versatility Across Timeframes
🔸Multi-Scale Combination
🔶 FUNCTIONALITY 🔸Hurst Exponent (H)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Conditional Value at Risk (CVaR)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Fractal Dimension (FD)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔶 INSTRUCTIONS 🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) indicator stands out due to its unique approach of dynamically adjusting moving averages based on advanced statistical measures, making it highly responsive to varying market conditions. Unlike traditional moving averages that rely on static periods, this indicator adapts in real-time using three distinct adaptive methods: Hurst Exponent, CVaR, and Fractal Dimension.
🔸Adaptive Mechanisms
Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Multi-Scale Adaptive MAs employ adaptive methods to adjust the MA length dynamically, providing a more accurate reflection of current market conditions.
🔸Multi-Faceted Analysis
By integrating Hurst Exponent, CVaR, and Fractal Dimension, the indicator offers a comprehensive market analysis. It captures different aspects of market behavior, including trend persistence, risk of extreme movements, and complexity, which are often missed by standard MAs.
🔸Versatility Across Timeframes
The indicator’s ability to switch between different adaptive methods based on market conditions allows traders to analyze short-term, medium-term, and long-term trends with enhanced precision.
🔸Multi-Scale Combination
Utilizing multiple adaptive MAs in combination provides a more nuanced view of the market, allowing traders to see how short, medium, and long-term trends interact. This layered approach helps in identifying the strength and consistency of trends across different scales, offering more reliable signals and aiding in complex decision-making processes. When combined, these MAs can also signal key market shifts when they converge or diverge, offering deeper insights than a single MA could provide.
🔶 FUNCTIONALITY The indicator adjusts moving averages based on a variety of different choosable adaptives. The Hurst Exponent to identify trend persistence or mean reversion, adapting to market conditions for both short-term and long-term trends. Using CVaR, it evaluates the risk of extreme price movements, ensuring the moving average is more conservative during high-risk periods, protecting against potential large losses. By incorporating the Fractal Dimension, the indicator adapts to market complexity, adjusting to varying levels of price roughness and volatility, which allows it to respond more accurately to different market structures and patterns.
Let's dive into the details:
🔸Hurst Exponent (H)
Measures the degree of trend persistence or mean reversion.
By using the Hurst Exponent, the indicator adjusts to capture the strength and duration of trends, helping traders to stay in profitable trades longer and avoid false reversals in ranging markets.
It enhances the detection of trends, making it suitable for both short-term scalping and identifying long-term trends.
🞘 How it works Rescaled Range (R/S) Analysis Calculate the mean of the closing prices over a set window.
Determine the deviation of each price from the mean.
Compute the cumulative sum of these deviations over the window.
Calculate the range (R) of the cumulative deviations (maximum minus minimum).
Compute the standard deviation (S) of the price series over the window.
Obtain the R/S ratio as R/S.
Linear Regression for Hurst Exponent Calculate the logarithm of multiple window sizes and their corresponding R/S values.
Use linear regression to determine the slope of the line fitting the log(R/S) against log(window size).
The slope of this line is an estimate of the Hurst Exponent.
🞘 How to calculate Range (R)
Calculate the maximum cumulative deviation:
R=max(sum(deviation))−min(sum(deviation))
Where deviation is the difference between each price and the mean.
Standard Deviation (S)
Calculate the standard deviation of the price series:
S=sqrt((1/(n−1))∗sum((Xi−mean)2))
Rescaled Range (R/S)
Divide the range by the standard deviation:
R/S=R/S
Hurst Exponent
Perform linear regression to estimate the slope of:
log(R/S) versus log(windowsize)
The slope of this line is the Hurst Exponent.
🞘 Code extract // Hurst Exponent
calc_hurst(source_, adaptive_window_) =>
window_sizes = array.from(adaptive_window_/10, adaptive_window_/5, adaptive_window_/2, adaptive_window_)
float hurst_exp = 0.5
// Calculate Hurst Exponent proxy
rs_list = array.new_float()
log_length_list = array.new_float()
for i = 0 to array.size(window_sizes) - 1
len = array.get(window_sizes, i)
// Ensure we have enough data
if bar_index >= len * 2
mean = adaptive_sma(source_, len)
dev = source_ - mean
// Calculate cumulative deviations over the window
cum_dev = ta.cum(dev) - ta.cum(dev )
r = ta.highest(cum_dev, len) - ta.lowest(cum_dev, len)
s = ta.stdev(source_, len)
if s != 0
rs = r / s
array.push(rs_list, math.log(rs))
array.push(log_length_list, math.log(len))
// Linear regression to estimate Hurst Exponent
n = array.size(log_length_list)
if n > 1
mean_x = array.sum(log_length_list) / n
mean_y = array.sum(rs_list) / n
sum_num = 0.0
sum_den = 0.0
for i = 0 to n - 1
x = array.get(log_length_list, i)
y = array.get(rs_list, i)
sum_num += (x - mean_x) * (y - mean_y)
sum_den += (x - mean_x) * (x - mean_x)
hurst_exp := sum_den != 0 ? sum_num / sum_den : 0.5
else
hurst_exp := 0.5 // Default to 0.5 if not enough data
hurst_exp
🔸Conditional Value at Risk (CVaR)
Assesses the risk of extreme losses by focusing on tail risk.
This method adjusts the moving average to account for market conditions where extreme price movements are likely, providing a more conservative approach during periods of high risk.
Traders benefit by better managing risk and avoiding major losses during volatile market conditions.
🞘 How it works Calculate Returns Determine the returns as the percentage change between consecutive closing prices over a specified window.
Percentile Calculation Identify the percentile threshold (e.g., the 5th percentile) for the worst returns in the dataset.
Average of Extreme Losses Calculate the average of all returns that are less than or equal to this percentile, representing the CVaR.
🞘 How to calculate Return Calculation
Calculate the return as the percentage change between consecutive prices:
Return = (Pt − Pt−1) / Pt−1
Where Pt is the price at time t.
Percentile Threshold
Identify the return value at the specified percentile (e.g., 5th percentile):
PercentileValue=percentile(returns,percentile_threshold)
CVaR Calculation
Compute the average of all returns below the percentile threshold:
CVaR = (1/n)∗sum(Return) for all Return≤PercentileValue
Where n is the total number of returns.
🞘 Code extract // Percentile
calc_percentile(data, percentile, window) =>
arr = array.new_float(0)
for i = 0 to window - 1
array.push(arr, data )
array.sort(arr)
index = math.floor(percentile / 100 * (window - 1))
array.get(arr, index)
// Conditional Value at Risk
calc_cvar(percentile_value, returns, window) =>
// Collect returns worse than the threshold
cvar_sum = 0.0
cvar_count = 0
for i = 0 to window - 1
ret = returns
if ret <= percentile_value
cvar_sum += ret
cvar_count += 1
// Calculate CVaR
cvar = cvar_count > 0 ? cvar_sum / cvar_count : 0.0
cvar
🔸Fractal Dimension (FD)
Evaluates market complexity and roughness by analyzing how price movements behave across different scales.
It enables the moving average to adapt based on the level of market noise or structure, allowing for smoother MAs during complex, volatile periods and more sensitive MAs during clear trends.
This adaptability is crucial for traders dealing with varying market states, improving the indicator's responsiveness to price changes.
🞘 How it works Total Distance (L) Calculation Sum the absolute price movements between consecutive periods over a given window.
Maximum Distance (D) Calculation Calculate the maximum displacement from the first to the last price point within the window.
Calculate Fractal Dimension Use Katz's method to estimate the Fractal Dimension as the ratio of the logarithms of L and D, divided by the logarithm of the number of steps (N).
🞘 How to calculate Total Distance (L)
Sum the absolute price changes over the window:
L=sum(abs(Pt−Pt−1)) for t from 2 to n
Where Pt is the price at time t.
Maximum Distance (D)
Find the maximum absolute displacement from the first to the last price in the window:
D=max(abs(Pn-P1))
Fractal Dimension Calculation
Use Katz's method to estimate fractal dimension:
FD=log(L/D)/log(N)
Where N is the number of steps in the window.
🞘 Code extract // Fractal Dimension
calc_fractal(source_, adaptive_window_) =>
// Calculate the total distance (L) traveled by the price
L = 0.0
for i = 1 to adaptive_window_
L += math.abs(source_ - source_ )
// Calculate the maximum distance between first and last price
D = math.max(math.abs(source_ - source_ ), 1e-10) // Avoid division by zero
// Calculate the number of steps (N)
N = adaptive_window_
// Estimate the Fractal Dimension using Katz's formula
math.log(L / D) / math.log(N)
🔶 INSTRUCTIONS The Multi-Scale Adaptive MAs indicator can be set up by adding it to your TradingView chart and configuring the adaptive method (Hurst, CVaR, or Fractal) to match current market conditions. Look for price crossovers and changes in the slope for potential entry signals. Set take profit and stop-loss levels based on dynamic changes in the moving average, and consider combining it with other indicators for confirmation. Adjust settings and use adaptive strategies for enhanced trend detection and risk management.
🔸Step-by-Step Guidelines 🞘 Setting Up the Indicator Adding the Indicator to the Chart: Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator: Open the indicator settings by clicking on the gear icon next to its name on the chart.
Adaptive Method: Choose between "Hurst," "CVaR," and "Fractal" depending on the market condition and your trading style.
Length: Set the base length for the moving average (e.g., 20, 50, or 100). This length will be adjusted dynamically based on the selected adaptive method.
Other Parameters: Adjust any other parameters as needed, such as window sizes or scaling factors specific to each adaptive method.
Chart Setup: Ensure you have an appropriate timeframe selected (e.g., 1-hour, 4-hour, daily) based on your trading strategy.
Consider using additional indicators like volume or RSI to confirm signals.
🞘 Understanding What to Look For on the Chart Indicator Behavior: Observe how the adaptive moving average (AMA) behaves compared to standard moving averages, e.g. notice how it might change direction with strength (Hurst).
For example, the AMA may become smoother during high market volatility (CVaR) or more responsive during strong trends (Hurst).
Crossovers: Look for crossovers between the price and the adaptive moving average.
A bullish crossover occurs when the price crosses above the AMA, suggesting a potential uptrend.
A bearish crossover occurs when the price crosses below the AMA, indicating a possible downtrend.
Slope and Direction: Pay attention to the slope of the AMA. A rising slope suggests a bullish trend, while a declining slope indicates a bearish trend.
The slope’s steepness can give you clues about the trend's strength.
🞘 Possible Entry Signals Bullish Entry: Crossover Entry: Enter a long position when the price crosses above the AMA and the AMA has a positive slope.
Confirmation Entry: Combine the crossover with other indicators like RSI (above 50) or increasing volume for confirmation.
Bearish Entry: Crossover Entry: Enter a short position when the price crosses below the AMA and the AMA has a negative slope.
Confirmation Entry: Use additional indicators like RSI (below 50) or decreasing volume to confirm the bearish trend.
Adaptive Method Confirmation: Hurst: Enter when the AMA indicates a strong trend (steeper slope). Suitable for trend-following strategies.
CVaR: Be cautious during high-risk periods. Enter only if confirmed by other indicators, as the AMA may become more conservative.
Fractal: Ideal for capturing reversals in complex markets. Look for crossovers in volatile markets.
🞘 Possible Take Profit Strategies Static Take Profit Levels: Set take profit levels based on predefined ratios (e.g., 1:2 or 1:3 risk-reward ratio).
Place take profit orders at recent swing highs (for long positions) or swing lows (for short positions).
Trailing Stop Loss: Use a trailing stop based on a percentage of the AMA value to lock in profits as the trend progresses.
Adjust the trailing stop dynamically to follow the AMA, allowing profits to run while protecting gains.
Adaptive Method Based Exits: Hurst: Exit when the AMA begins to flatten or turn in the opposite direction, signaling a potential trend reversal.
CVaR: Consider taking profits earlier during high-risk periods when the AMA suggests caution.
Fractal: Use the AMA to exit in complex markets when it smooths out, indicating reduced volatility.
🞘 Possible Stop-Loss Levels Initial Stop Loss: Place an initial stop loss below the AMA (for long positions) or above the AMA (for short positions) to protect against adverse movements.
Use a buffer (e.g., ATR value) to avoid being stopped out by normal price fluctuations.
Adaptive Stop Loss: Adjust the stop loss dynamically based on the AMA. Move the stop loss along the AMA as the trend progresses to minimize risk.
This helps in adapting to changing market conditions and avoiding premature exits.
Adaptive Method-Specific Stop Loss: Hurst: Use wider stops during trending markets to allow for minor pullbacks.
CVaR: Adjust stops in high-risk periods to avoid being stopped out prematurely during price fluctuations.
Fractal: Place stops at recent support/resistance levels in highly volatile markets.
🞘 Additional Tips Combine with Other Indicators: Enhance your strategy by combining the AMA with other technical indicators like MACD, RSI, or Bollinger Bands for better signal confirmation.
Backtesting and Practice: Backtest the indicator on historical data to understand how it performs in different market conditions.
Practice using the indicator on a demo account before applying it to live trading.
Market Awareness: Always be aware of market conditions and fundamental events that might impact price movements, as the AMA reacts to price action and may not account for sudden news-driven events.
🔸Customize settings 🞘 Time Override: Enables or disables the ability to override the default time frame for the moving averages. When enabled, you can specify a custom time frame for the calculations.
🞘 Time: Specifies the custom time frame to use when the Time Override setting is enabled.
🞘 Enable MA: Enables or disables the moving average. When disabled, MA will not be displayed on the chart.
🞘 Show Smoothing Line: Enables or disables the display of a smoothing line for the moving average. The smoothing line helps to reduce noise and provide a clearer trend.
🞘 Show as Horizontal Line: Displays the moving average as a horizontal line instead of a dynamic line that follows the price.
🞘 Source: Specifies the data source for the moving average calculation (e.g., close, open, high, low).
🞘 Length: Sets the period length for the moving average. A longer length will result in a smoother moving average, while a shorter length will make it more responsive to price changes.
🞘 Time: Specifies a custom time frame for the moving average, overriding the default time frame if Time Override is enabled.
🞘 Method: Selects the calculation method for the moving average (e.g., SMA, EMA, SMMA, WMA, VWMA).
🞘 Offset: Shifts the moving average forward or backward by the specified number of bars.
🞘 Color: Sets the color for the moving average line.
🞘 Adaptive Method: Selects the adaptive method to dynamically adjust the moving average based on market conditions (e.g., Hurst, CVaR, Fractal).
🞘 Window Size: Sets the window size for the adaptive method, determining how much historical data is used for the calculation.
🞘 CVaR Scaling Factor: Adjusts the influence of CVaR on the moving average length, controlling how much the length changes based on calculated risk.
🞘 CVaR Risk: Specifies the percentile cutoff for the worst-case returns used in the CVaR calculation to assess extreme losses.
🞘 Smoothing Method: Selects the method for smoothing the moving average (e.g., SMA, EMA, SMMA, WMA, VWMA).
🞘 Smoothing Length: Sets the period length for smoothing the moving average.
🞘 Fill Color to Smoothing Moving Average: Enables or disables the color fill between the moving average and its smoothing line.
🞘 Transparency: Sets the transparency level for the color fill between the moving average and its smoothing line.
🞘 Show Label: Enables or disables the display of a label for the moving average on the chart.
🞘 Show Label for Smoothing: Enables or disables the display of a label for the smoothing line of the moving average on the chart.
🔶 CONCLUSION The Multi-Scale Adaptive MAs indicator offers a sophisticated approach to trend analysis and risk management by dynamically adjusting moving averages based on Hurst Exponent, CVaR, and Fractal Dimension. This adaptability allows traders to respond more effectively to varying market conditions, capturing trends and managing risks with greater precision. By incorporating advanced statistical measures, the indicator goes beyond traditional moving averages, providing a nuanced and versatile tool for both short-term and long-term trading strategies. Its unique ability to reflect market complexity and extreme risks makes it an invaluable asset for traders seeking a deeper understanding of market dynamics.
Price Touches 50-Day MA and Fails to CrossOverview: The Price Touches 50-Day MA and Fails to Cross Indicator is a powerful tool designed for traders and analysts using TradingView to monitor and identify key interactions between an asset's price and its 50-day Simple Moving Average (SMA). This indicator specifically highlights moments when the price touches the 50-day MA but fails to cross it, signaling potential support or resistance levels that could influence future price movements.
Key Features:
50-Day Simple Moving Average (SMA) Calculation:
Automatically calculates and plots the 50-day SMA on your chart, providing a clear reference point for price action analysis.
Touch Detection:
Identifies when the closing price comes within a user-defined tolerance (default is 0.1%) of the 50-day MA, indicating a "touch."
Failure to Cross Confirmation:
Determines if the price, after touching the MA, fails to cross it in the subsequent bar. This helps in recognizing potential reversal points or consolidation zones.
Visual Indicators:
Plots red downward triangles above the bars where a touch-and-fail event occurs, making it easy to spot these critical moments at a glance.
Customizable Touch Tolerance:
Allows users to adjust the sensitivity of touch detection by modifying the touch tolerance percentage, catering to different trading strategies and asset volatilities.
Alert Conditions:
Offers the option to set up alerts that notify you whenever a touch-and-fail event is detected, ensuring you never miss significant trading signals.
How It Works:
Calculating the 50-Day SMA:
The indicator computes the 50-day SMA using the closing prices, providing a smooth average that reflects the asset's mid-term trend.
Detecting a Touch:
A "touch" is registered when the absolute difference between the closing price and the 50-day SMA is less than or equal to the specified tolerance. This proximity suggests a potential support or resistance level.
Confirming Failure to Cross:
After a touch is detected, the indicator checks whether the price fails to move beyond the 50-day MA in the next bar. If the price remains on the original side of the MA, it signifies a failed attempt to cross, highlighting a possible reversal or consolidation.
Plotting Indicators:
When a touch-and-fail event is confirmed, a red downward triangle is plotted above the corresponding bar, providing a clear visual cue for traders.
Setting Up Alerts:
Users can enable alert conditions to receive real-time notifications whenever a touch-and-fail event is detected, allowing for timely trading decisions.
Customization Options:
Touch Tolerance (%):
Adjust the touch_tolerance input to set how close the price needs to be to the 50-day MA to be considered a touch. This flexibility allows the indicator to be tailored to different trading styles and asset behaviors.
Visual Styles:
Customize the appearance of the SMA line and the touch-fail indicators to match your charting preferences, ensuring seamless integration with your existing setup.
Benefits:
Enhanced Decision-Making:
By highlighting key interactions with the 50-day MA, this indicator aids in identifying potential entry and exit points, improving overall trading strategy.
Time Efficiency:
Automates the process of monitoring price movements relative to the 50-day MA, saving traders valuable time and reducing the need for constant manual analysis.
Versatility:
Suitable for various asset classes, including stocks, forex, commodities, and cryptocurrencies, making it a versatile tool for any trader's toolkit.
Happy Trading!
EMA Volume [MacroGlide]EMA Volume is a versatile tool designed to track and analyze market volumes by calculating the Exponential Moving Averages (EMAs) of total, bullish, and bearish volumes. This indicator helps traders visualize volume dynamics, identify buying and selling pressure, and make informed trading decisions based on volume activity.
Key Features:
• Volume EMAs: The indicator calculates the EMAs of total, bullish, and bearish volumes, allowing users to observe how volume trends evolve over time. This helps identify shifts in market sentiment and potential reversals.
• Separation of Bullish and Bearish Volumes: By separating bullish and bearish volumes, the indicator provides a clear view of buying versus selling activity. This distinction is valuable for understanding the market's underlying momentum and direction.
• Customizable Visuals: Users can customize the line style and color for each volume type, allowing them to tailor the display of the indicator to their personal preferences and enhance the visual interpretation of the data.
How to Use:
• Add the indicator to your chart and adjust the EMA settings and display parameters according to your needs.
• Use the difference between bullish and bearish volumes to assess current market sentiment and analyze potential trend changes.
• Monitor the EMA of total volume to identify overall volume trends that can serve as additional signals for entering or exiting positions.
Methodology:
The indicator calculates the EMAs for total, bullish, and bearish volumes based on the trading volumes associated with price increases or decreases. This tool helps evaluate the strength of buying and selling at different times, making it especially useful for volume and market dynamics analysis.
Originality and Usefulness:
EMA Volume stands out for its ability to separate buying and selling volumes and present them in a clear visual format, significantly simplifying the analysis of market activity and decision-making in trading.
Charts:
The indicator displays clean and clear charts, where each type of volume is represented by its own line and color, making visual interpretation easier. The charts focus solely on key information for analysis: EMAs of total, bullish, and bearish volumes. These features make the charts highly useful for quick analysis and trading decision-making.
Enjoy the game!
Opening Range with Breakouts & Targets [LuxAlgo]Opening Range with Breakouts & Targets is based on the long-standing Opening Range Breakout strategy popularized by traders such as Toby Crabel and Mark Fisher.
This indicator measures and displays the price range created from the first period within a new trading session, along with price breakouts from that range and targets associated with the range width.
🔶 USAGE
The Opening Range (OR) can be a powerful tool for making a clear distinction between ranging and trending trading days. Using a rigid structure for drawing a range, provides a consistent basis to make judgments and comparisons that will better assist the user in determining a hypothesis for the day's price action.
NOTE: During a suspected "Range Day", the Opening Range can be used for reversion strategies, typically targeting the opposite extreme of the range or the mean of the range. However, more commonly the Opening Range is used for breakouts on suspected "Trend Days", targeting further upward or downward market movement.
The common Opening Range Breakout Strategy (ORB) outlines a structure to enter and exit positions based on rigid points determined by the Opening Range. This methodology can be adjusted based on markets or trading styles.
Determine Opening Range High & Low: These are the high and low price within a chosen period of time after the market opens. This can be customized to the user's trading style and preference. Common Ranges are from 5-60 mins.
Watch for a Breakout with Volume: A Breakout occurs when price crosses the OR High (ORH) or OR Low (ORL), an increase in volume is typically desired when witnessing these breakouts to confirm a stronger movement.
Manage Risk: Based on user preference and the appropriately determined amount of risk, multiple ways can be determined to manage risk by using Opening Range.
For Example: A stop-loss could be set at OR Mean (ORM) or the opposite side of the range, while a profit target could optionally be set at the first price target generated by the script.
Alternatively, a user might want to use a Moving Average (MA) as an adaptive stop-loss and use price targets to scale out. These are just 2 examples of the possible options, both capable with this tool.
🔹 Signals
Signals will fire based on the break of the opening range, this is indicated by arrows above and below the range boundaries.
Optionally, a bias can be added to these signals to aid in mitigating false signals by using a directional filter based on the current day's OR relative to the previous day's OR.
Regardless of the signal bias being enabled, the Opening Range Zone will always be colored directionally according to this.
If the current day's OR is above the previous day's OR, the Zone will be Green.
If the current day's OR is below the previous day's OR, the Zone will be Red.
By enabling the signal bias, signals in the opposite direction of the daily bias will fire on the cross of the first target in that direction.
🔹 Targets
In this indicator, targets are not limited and will generate infinitely based on a % width of the Opening Range.
Additionally, there are 2 display methods for these targets.
Extended: Extends the targets to the current bar and displays all targets that have been crossed so far within the session.
Adaptive: Extends only the 2 closest targets surrounding price, allowing for a display consisting of fewer lines at one time.
🔶 DETAILS
🔹 Historical Display
This indicator can be utilized in multiple ways, for use in real-time, and for historical analysis to form methods. Because of this, the indicator has an option to display only the current day's data or the entire historical data. This can also help clean up the chart when it is in use.
🔹 Time Period
The specific time period to create the opening range is entirely up to each user's preference, by default it is set to 30 mins; however, this time period can be edited with full control if desired.
Simply toggle on the "Custom Range" and input a range of time to create the range.
🔹 Session Moving Average
The Session Moving Average is a common Moving Average, which resets at the beginning of a new session. This allows for an unbiased MA that was created entirely from the current session's price action.
Note: The start of the session is determined by the start of the Opening Range if using a custom range of time.
🔶 SETTINGS
Show Historical Data: Choose to display only the current session's data or the full history of data.
Opening Range Time Period: Select the time period to form the opening range from. This operates on Session Start, so it will change with the chart.
Custom Range: Opt for a custom Range by enabling this and inputting your range times as well as your needed timezone.
Breakout Signal Bias: Select if the Breakout Signals will use a Daily Directional Bias for firing.
Target % of Range: Sets the % of the Range width that will be used as an increment for the Targets to display in.
Target Cross Source: Choose to use the Close price or High/Low price as the crossing level for Target displays. When this source crosses a target it will generate more targets.
Target Display: Choose which style of display to use for targets.
Session Moving Average: Optionally enable a Moving average of your choice that resets at the beginning of each session (start of opening range).
HFT V.2 EnhancedTitle: HFT V.2 Enhanced - ATR Dynamic Stop-Loss & Take-Profit
Description:
The HFT V.2 Enhanced strategy is designed for high-frequency trading with dynamic trade management and robust entry/exit logic. This strategy uses simple moving averages (SMA) for trend identification and the relative strength index (RSI) for momentum confirmation. In this enhanced version, the strategy also incorporates dynamic stop-loss and take-profit levels based on the Average True Range (ATR), offering better adaptability to market volatility.
Features:
Moving Average Crossover: Uses a fast and slow SMA to capture trend reversals and generate trade entries.
RSI Confirmation: Ensures momentum is in the direction of the trade by incorporating the RSI threshold for both long and short entries.
Dynamic Stop-Loss and Take-Profit: Stop-loss and take-profit levels are calculated based on the ATR, allowing the strategy to adjust its exit points according to market volatility. This helps manage risk more effectively and capture larger trends.
Auto-Close Opposing Positions: Automatically closes any open long positions when a short entry is triggered, and vice versa.
Once-Per-Bar Execution: Ensures that a position is entered only once per bar, avoiding multiple trades within the same bar.
Parameters:
Fast MA Length: Defines the length of the fast-moving average.
Slow MA Length: Defines the length of the slow-moving average.
RSI Length: Sets the period for the RSI indicator.
RSI Threshold: Controls the RSI level for confirming momentum (50 by default).
ATR Length: Determines the period for the ATR calculation.
ATR Multiplier for Stop-Loss/Take-Profit: Adjusts the sensitivity of the stop-loss and take-profit levels based on ATR.
How it Works:
Long Entry: The strategy opens a long trade when the fast SMA crosses above the slow SMA, and the RSI is above the user-defined threshold. A dynamic stop-loss is placed below the entry price, and a take-profit target is set based on ATR.
Short Entry: The strategy opens a short trade when the fast SMA crosses below the slow SMA, and the RSI is below the inverse threshold. A stop-loss is placed above the entry price, and a take-profit target is set using ATR.
Risk Management: The strategy adapts to changing market conditions by dynamically adjusting its stop-loss and take-profit levels, ensuring it remains responsive to market volatility.
This script is ideal for traders looking for a high-frequency strategy with advanced trade management, including dynamic exits and volatility-based risk management.
Disclaimer: Always backtest and optimize the parameters to fit your trading style and risk tolerance before using the strategy in live trading.
Trend Magic with EMA, SMA, and Auto-TradingRelease Notes
Strategy Name: Trend Magic with EMA, SMA, and Auto-Trading
Purpose: This strategy is designed to capture entry and exit points in the market using the Trend Magic indicator and three moving averages (EMA45, SMA90, and SMA180). Specifically, it uses the perfect order of the moving averages and the color changes in Trend Magic to identify trend reversals and potential trading opportunities.
Uniqueness and Usefulness
Uniqueness: The strategy utilizes the Trend Magic indicator, which is based on price and volatility, along with three moving averages to assess the strength of trends. The signals are generated only when the moving averages are in perfect order, and the Trend Magic color changes, ensuring that the entry is made during established trends. This combination provides a higher degree of reliability compared to strategies that rely solely on price action or single indicators.
Usefulness: This strategy is particularly useful for traders looking to capture trends over longer periods. It is effective at reducing noise in the market, only providing signals when the moving averages align and the Trend Magic indicator confirms a trend reversal. It works well in both trending and volatile markets.
Entry Conditions
Long Entry:
Condition: A perfect order (EMA45 > SMA90 > SMA180) is established, and Trend Magic changes color from red to blue.
Signal: A buy signal is generated, indicating the start of an uptrend.
Short Entry:
Condition: A perfect order (EMA45 < SMA90 < SMA180) is established, and Trend Magic changes color from blue to red.
Signal: A sell signal is generated, indicating the start of a downtrend.
Exit Conditions
Exit Strategy:
This strategy automatically enters and exits trades based on signals, but traders are encouraged to manage exits manually according to their own risk management preferences. The strategy includes stop loss and take profit settings based on risk-to-reward ratios for better risk management.
Risk Management
The strategy includes built-in risk management by using the SMA90 level at the time of entry as the stop-loss point and setting the take profit at a 1:1.5 risk-to-reward ratio. The stop-loss level is fixed at the entry point and does not move as the market progresses. Traders are advised to implement additional risk management, such as trailing stops, for added protection.
Account Size: ¥100,000
Commissions and Slippage: Assumes 94 pips for commissions and 1 pip for slippage per trade
Risk per Trade: 10% of account equity (adjust this based on personal risk tolerance)
Configurable Options
Configurable Options:
CCI Period: Set the period for the CCI used to calculate the Trend Magic indicator (default is 21).
ATR Multiplier: Set the multiplier for ATR used in the Trend Magic calculation (default is 1.0).
EMA/SMA Periods: The periods for the three moving averages (default is EMA45, SMA90, and SMA180).
Signal Display Control: An option to toggle the display of buy and sell signals on the chart.
Adequate Sample Size
To ensure the robustness and reliability of this strategy, it is recommended to backtest it with a sufficiently long period of historical data. Testing across different market conditions, including high and low volatility periods, is also advised.
Credits
Acknowledgments:
This strategy is based on the Trend Magic indicator combined with moving averages and draws on contributions from the technical analysis and trading community.
Clean Chart Description
Chart Appearance:
To maintain a clean and simple chart, this strategy includes options to turn off the display of Trend Magic, moving averages, and entry signals. Traders can adjust these display settings as needed to minimize visual clutter and focus on effective trend analysis.
Addressing the House Rule Violations
Omissions and Unrealistic Claims
Clarification:
This strategy does not make any unrealistic or unsupported claims about its performance. All signals are intended for educational purposes only and do not guarantee future results. It is important to note that past performance does not guarantee future outcomes, and proper risk management is crucial.
Power MarketPower Market Indicator
Description: The Power Market Indicator is designed to help traders assess market strength and make informed decisions for entering and exiting positions. This innovative indicator provides a comprehensive view of the evolution of Simple Moving Averages (SMA) over different periods and offers a clear measure of market strength through a total score.
Key Features:
Multi-Period SMA Analysis:
Calculates Simple Moving Averages (SMA) for 10 different periods ranging from 10 to 100.
Provides detailed analysis by comparing the current closing price with these SMAs.
Market Strength Measurement:
Assesses market strength by calculating a total score based on the relationship between the closing price and the SMAs.
The total score is displayed as a histogram with distinct colors for positive and negative values.
Smoothed Curve for Better View:
A smoothing of the total score is applied using a 5-period Simple Moving Average to represent the overall trend more smoothly.
Dynamic Information Table:
Real-time display of the maximum and minimum values among the SMAs, as well as the difference between these values, providing valuable insights into the variability of moving averages.
Visual Reference Lines:
Horizontal lines at zero, +50, and -50 for easy evaluation of key score levels.
How to Use the Indicator:
Position Entries: Use high positive scores to identify buying opportunities when market strength is strong.
Position Exits: Negative scores may signal market weakness, allowing you to exit positions or wait for a better opportunity.
Data Analysis: The table helps you understand the variability of SMAs, offering additional context for your trading decisions.
This powerful tool provides an in-depth view of market dynamics and helps you navigate your trading strategies with greater confidence. Embrace the Power Market Indicator and optimize your trading decisions today!
