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.
Moving Averages
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.
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.
-------------------------------------------
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.
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.
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).
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!
Options Series - MTF 1 and 3 Minute
Objective:
The indicator is named "Options Series - MTF 1 and 3 Minute", suggesting it's designed to analyze options series with multiple time frames (MTF), particularly focusing on 1-minute and 3-minute intervals.
OHLC Values Of Candle:
The code fetches the Open, High, Low, and Close (OHLC) values of the current candle for the specified ticker and timeframes (current, 1 minute, and 3 minutes). Additionally, it calculates the 200-period Simple Moving Average (SMA) of the closing prices for each timeframe.
Bull vs. Bear Condition:
It defines conditions for Bullish and Bearish scenarios based on comparing the current close price with the previous 200-period SMA close price for both 1-minute and 3-minute timeframes. If the current close price is higher than the previous 200-period SMA close price, it's considered Bullish, and if it's lower, it's considered Bearish.
Final Color Condition and Plot:
It determines the color of the candlestick based on the Bullish or Bearish condition. If the conditions for a Bullish scenario are met, the candlestick color is set to green (GreenColorCandle). If the conditions for a Bearish scenario are met, the candlestick color is set to red (RedColorCandle). If neither condition is met (i.e., the candle is neither Bullish nor Bearish), the color remains gray.
The code then plots the 200-period SMA values for both 1-minute and 3-minute timeframes and colors them based on the candlestick color. It also colors the bars based on the candlestick color.
Insights:
This indicator focuses on comparing current close prices with the 200-period SMA close prices to determine market sentiment (Bullish or Bearish).
It utilizes multiple time frames (1 minute and 3 minutes) to provide a broader perspective on market movements.
The color-coded candlesticks and bars make it visually easy to identify Bullish and Bearish trends.
This indicator can be used as part trading based on the identified market sentiment.
SMA, 20%UP, 20% SMA, LTH newFeatures:
Simple Moving Averages (SMAs):
200 SMA (Gray): Long-term trend indicator. A widely used benchmark in many trading strategies.
50 SMA (Red): Mid-term trend indicator.
20 SMA (Green): Short-term trend indicator. These three SMAs allow traders to visualize the general market trend over different time horizons.
20% Gain on Green Candles:
This feature tracks continuous green candles and calculates the percentage gain from the lowest low to the highest high in that series.
If the gain is greater than or equal to 20%, the script highlights it with a purple triangle above the candle.
If the series of green candles starts with a candle where the low is below the 200 SMA, a purple diamond appears under the bar, indicating potential strong buying signals.
Lifetime High (LTH):
The script automatically tracks and displays the Lifetime High (LTH), i.e., the highest price ever recorded on the chart.
This level is important for identifying potential resistance areas and monitoring long-term market tops.
Once a new LTH is reached, it is displayed as a green line across the chart.
Support Levels from LTH:
The script calculates 30%, 50%, and 67% down from the LTH, marking key support levels.
These levels are plotted on the chart as orange lines and labeled to assist in spotting potential buy zones or market reversals.
52-Week Low:
It also calculates and displays the 52-week low for quick reference, plotted as a green line.
This helps traders assess major market bottoms and potential areas of support.
Daily Moving Average for Intraday TimeframesThis indicator provides a dynamic tool for visualizing the Daily Moving Average (DMA) on intraday timeframes.
It allows you to analyze how the price behaves in relation to the daily moving average in timeframes from 1 minute up to 1 day.
KEY FEATURES
DMA on Intraday timeframes only : This indicator is designed to work exclusively on intraday charts with timeframes between 1 minute and 1 day. It will not function on tick, second-based, or daily-and-above charts.
Color-Coded Zones for Trend Identification :
Green Zone: The price is above a rising DMA, signaling a bullish momentum.
Red Zone: The price is below a falling DMA, signaling a bearish momentum.
Yellow Zone: Signaling uncertainty or mixed conditions, where either the price is above a falling DMA or below a rising/flat DMA.
Configurable DMA Period : You can adjust the number of days over which the DMA is calculated (default is 5 days). This can be customized based on your trading strategy or market preferences.
24/7 Market Option : For assets that trade continuously (e.g., cryptocurrencies), activate the "Is trading 24/7?" setting to ensure accurate calculations.
WHAT IS THE DMA AND WHY USE IT INTRADAY?
The Daily Moving Average is a Simple Moving Average indicator used to smooth out price fluctuations over a specified period (in days) and reveal the underlying trend.
Typically, a SMA takes price value for the current timeframe and reveal the trend for this timeframe. It gives you the average price for the last N candles for the given timeframe.
But what makes the Intraday DMA interesting is that it shows the underlying trend of the Daily timeframe on a chart set on a shorter timeframe . This helps to align intraday trades with broader market movements.
HOW IS THE DMA CALCULATED?
If we are to build a N-day Daily Moving Average using a Simple Moving Average, we need to take the amount of candles A needed in that timeframe to account for a period of a day and multiply it by the number of days N of the desired DMA.
So for instance, let say we want to compute the 5-Day DMA on the 10 minute timeframe :
In the 10 minute timeframe there are 39 candles in a day in the regular session.
We would take the 39 candles per day and then multiply that by 5 days. 39 x 5 = 195.
So a 5-day moving average is represented by a simple moving average with a period of 195 when looking at a 10 minute timeframe.
So for each period, to create a 5-day DMA, you would have to set the period of your simple moving average like so :
- 195 minutes = 10 period
- 130 minutes = 15 period
- 65 minutes = 30 period
- 30 minutes = 65 period
- 15 minutes = 130 period
- 10 minutes = 195 period
- 5 minutes = 390 period
and so on.
This indicator attempts to do this calculation for you on any intraday timeframe and whatever the period you want to use is for your DMA. You can create a 10-day moving average, a 30-day moving average, etc.
Auto Signal Buy/SellAuto Signal Buy/Sell with Time Filter and Dynamic ZLEMA (GMT+2) 🌟
Are you looking for an indicator that combines efficiency and simplicity while integrating advanced elements like SuperTrend, ZLEMA (Zero Lag EMA), and a MACD DEMA for clear and precise buy/sell signals? 📈 Introducing Auto Signal Buy/Sell, the ultimate indicator designed for intraday and swing traders, optimized for market hours in GMT+2.
🛠️ Key Features:
- **Advanced SuperTrend**: Follow the dominant trend with a robust SuperTrend, adjustable to your preferences (customizable multiplier and period).
- **Dynamic ZLEMA**: Get a zero-lag EMA curve with a visual signal. Additionally, the ZLEMA turns blue when it’s nearly flat, helping you easily spot market consolidation phases.
- **MACD DEMA**: An enhanced version of the traditional MACD, using the Double EMA to capture more responsive buy/sell cross signals. 📊
- **Buy/Sell Signals**: Visual arrows clearly indicate potential entry and exit points on your chart, filtered by MACD crossovers and the SuperTrend trend.
- **Smart Time Filter (GMT+2)**: This script adapts to trading hours (customizable) and only displays signals during trading hours. The background turns light blue when the market is closed, preventing confusion during inactivity periods. 🕒
⚙️ Full Customization:
- Adjustable trading hours (default 9 AM to 5 PM in GMT+2) with dynamic background indicating when markets are closed.
- Flexible settings for SuperTrend, ZLEMA, and MACD DEMA to suit any strategy.
🎯 Why Choose This Indicator?
- Optimized for maximum precision with advanced algorithms like ZLEMA and DEMA.
- Easy to use: it provides clear, visual signals directly on the chart—no need to decipher complex indicators.
- A complete intraday and swing indicator that combines trend analysis and signal filtering with precise market hours.
🚀 Boost Your Trading!
Add this indicator to your toolkit and enhance your decision-making. Thanks to its intuitive interface and clear visual signals, you can trade with confidence. 💡
Don't forget to like 👍 and comment if you find this indicator useful! Your feedback helps us continue improving such tools. 🚀
📌 How to Use:
1. Add the indicator to your chart.
2. Adjust the SuperTrend and ZLEMA settings to suit your needs.
3. Follow the buy/sell signals and watch for the light blue background outside of trading hours.
4. Trade effectively and stay in control, even during consolidation phases.
Geometric Mean IndicatorThis script calculates and plots the Geometric Mean (GM) of two significant price levels (in this case, moving averages) to identify balance points or equilibrium levels in the market.
Key Components of the Script:
Input Variables:
length1: Defines the period for the first moving average (representing the first radius 𝑥x).
length2: Defines the period for the second moving average (representing the second radius
𝑦y).
Moving Averages (Price Levels):
ma1: The first moving average (calculated using the closing price over the period defined by length1).
ma2: The second moving average (calculated using the closing price over the period defined by length2).
Geometric Mean (GM) Calculation:
The geometric mean between the two moving averages is calculated as:
GM = sqrt(ma1 * ma2)
This value represents the midpoint or balance between the two price levels (analogous to the geometric mean between the radii in the mathematical discovery).
Plotting the Values:
The script plots:
ma1: First moving average (blue line).
ma2: Second moving average (red line).
geometric_mean: The geometric mean of the two moving averages (green line), which serves as the dynamic equilibrium point.
Visual Markers for Crossovers:
The script detects when the price crosses above or below the geometric mean:
Green markers (below the bar) indicate a crossover above the geometric mean.
Red markers (above the bar) indicate a crossover below the geometric mean.
Purpose of the Indicator:
The Geometric Mean Indicator is designed to:
Highlight equilibrium points: The geometric mean between two price levels can signal areas where the market is balanced or poised for a potential breakout.
Detect potential trend reversals: When the price crosses above or below the geometric mean, it can indicate shifts in market momentum, similar to how the GM in geometry represents a transition point.
How to Use:
Dynamic Equilibrium: The geometric mean (green line) represents a balance between two price levels (moving averages) and can act as support or resistance.
Price Crossovers: Watch for price crossing the geometric mean to identify potential trend changes or areas of significant price action.
Adjust Inputs: You can modify the lengths of the moving averages (length1 and length2) to adjust the sensitivity of the indicator based on different timeframes or strategies.
Summary in Context of the Geometric Proof:
The script applies the geometric concept of the Geometric Mean (GM) as a balance point between two radii (represented by moving averages in this case).
It mirrors the idea that the GM is the midpoint of the tangent slope between two circles, where the moving averages (or price levels) serve as the "radii" in the market context.
Bull Trade Zone IndicatorThe BULL TRADE ZONE INDICATOR is a powerful trading tool designed to help traders identify optimal entry and exit points in the market. This script uses a combination of two Exponential Moving Averages (EMA) and the Average True Range (ATR) to generate buy and sell signals, making it ideal for traders looking to enhance their trading strategy with precise and timely alerts.
Key Features:
Dynamic Buy and Sell Signals: The indicator generates buy signals when the 14 EMA crosses above the 150 EMA and the price is trading above the 150 EMA. Sell signals are generated when the 14 EMA crosses below the 150 EMA and the price is below the 150 EMA, providing clear guidance on potential market trends.
Built-In Stop-Loss Levels: Automatic stop-loss levels are calculated based on the ATR, helping traders manage risk effectively by setting realistic stop-loss points based on market volatility.
Minimal Chart Clutter: To maintain a clean and focused trading environment, the 14 EMA and 150 EMA values are privately used within the script without being visibly plotted on the chart, ensuring that the focus remains on actionable signals.
Clear Visual Alerts: Buy and sell signals are highlighted directly on the chart with intuitive labels, making it easy to spot trading opportunities at a glance.
Who Is This For?
This indicator is suitable for traders of all levels—whether you are a beginner looking for a straightforward trading tool or an experienced trader seeking to add an additional layer of confirmation to your strategy. The BULL TRADE ZONE INDICATOR helps you stay ahead of the market by precisely identifying key trading zones.
How to Use:
Add the indicator to your chart.
Monitor the buy and sell signals generated by the script.
Use the plotted stop-loss levels to manage your trades effectively.
Customize your trading strategy using the indicator’s signals to align with your risk appetite and market view.
Disclaimer:
This indicator is a technical analysis tool designed to assist with decision-making. It should be used alongside other analyses and strategies, not as the sole basis for trading decisions. Always perform your due diligence and risk management when trading.
TPS Short Strategy by Larry ConnersThe TPS Short strategy aims to capitalize on extreme overbought conditions in an ETF by employing a scaling-in approach when certain technical indicators signal potential reversals. The strategy is designed to short the ETF when it is deemed overextended, based on the Relative Strength Index (RSI) and moving averages.
Components:
200-Day Simple Moving Average (SMA):
Purpose: Acts as a long-term trend filter. The ETF must be below its 200-day SMA to be eligible for shorting.
Rationale: The 200-day SMA is widely used to gauge the long-term trend of a security. When the price is below this moving average, it is often considered to be in a downtrend (Tushar S. Chande & Stanley Kroll, "The New Technical Trader: Boost Your Profit by Plugging Into the Latest Indicators").
2-Period RSI:
Purpose: Measures the speed and change of price movements to identify overbought conditions.
Criteria: Short 10% of the position when the 2-period RSI is above 75 for two consecutive days.
Rationale: A high RSI value (above 75) indicates that the ETF may be overbought, which could precede a price reversal (J. Welles Wilder, "New Concepts in Technical Trading Systems").
Scaling-In Mechanism:
Purpose: Gradually increase the short position as the ETF price rises beyond previous entry points.
Scaling Strategy:
20% more when the price is higher than the first entry.
30% more when the price is higher than the second entry.
40% more when the price is higher than the third entry.
Rationale: This incremental approach allows for an increased position size in a worsening trend, potentially increasing profitability if the trend continues to align with the strategy’s premise (Marty Schwartz, "Pit Bull: Lessons from Wall Street's Champion Day Trader").
Exit Conditions:
Criteria: Close all positions when the 2-period RSI drops below 30 or the 10-day SMA crosses above the 30-day SMA.
Rationale: A low RSI value (below 30) suggests that the ETF may be oversold and could be poised for a rebound, while the SMA crossover indicates a potential change in the trend (Martin J. Pring, "Technical Analysis Explained").
Risks and Considerations:
Market Risk:
The strategy assumes that the ETF will continue to decline once shorted. However, markets can be unpredictable, and price movements might not align with the strategy's expectations, especially in a volatile market (Nassim Nicholas Taleb, "The Black Swan: The Impact of the Highly Improbable").
Scaling Risks:
Scaling into a position as the price increases may increase exposure to adverse price movements. This method can amplify losses if the market moves against the position significantly before any reversal occurs.
Liquidity Risk:
Depending on the ETF’s liquidity, executing large trades in increments might affect the price and increase trading costs. It is crucial to ensure that the ETF has sufficient liquidity to handle large trades without significant slippage (James Altucher, "Trade Like a Hedge Fund").
Execution Risk:
The strategy relies on timely execution of trades based on specific conditions. Delays or errors in order execution can impact performance, especially in fast-moving markets.
Technical Indicator Limitations:
Technical indicators like RSI and SMA are based on historical data and may not always predict future price movements accurately. They can sometimes produce false signals, leading to potential losses if used in isolation (John Murphy, "Technical Analysis of the Financial Markets").
Conclusion
The TPS Short strategy utilizes a combination of long-term trend filtering, overbought conditions, and incremental shorting to potentially profit from price reversals. While the strategy has a structured approach and leverages well-known technical indicators, it is essential to be aware of the inherent risks, including market volatility, liquidity issues, and potential limitations of technical indicators. As with any trading strategy, thorough backtesting and risk management are crucial to its successful implementation.