Adaptive DEMA Momentum Oscillator (ADMO)Overview:
The Adaptive DEMA Momentum Oscillator (ADMO) is an open-source technical analysis tool developed to measure market momentum using a Double Exponential Moving Average (DEMA) and adaptive standard deviation. By dynamically combining price deviation from the moving average with normalized standard deviation, ADMO provides traders with a powerful way to interpret market conditions.
Key Features:
Double Exponential Moving Average (DEMA):
The core calculation of the indicator is based on DEMA, which is known for being more responsive to price changes compared to traditional moving averages. This makes the ADMO capable of capturing trend momentum effectively.
Standard Deviation Integration:
A normalized standard deviation is used to adaptively weight the oscillator. This makes the indicator more sensitive to market volatility, enhancing responsiveness during high volatility and reducing sensitivity during calmer periods.
Oscillator Representation:
The final oscillator value is derived from the combination of the DEMA-based Z-score and the normalized standard deviation. This final value is visualized as a color-coded histogram, reflecting bullish or bearish momentum.
Color-Coded Histogram:
Bullish Momentum: Values above zero are colored using a customizable bullish color (default: light green).
Bearish Momentum: Values below zero are colored using a customizable bearish color (default: red).
How It Works:
Inputs:
DEMA Length: Defines the period used for calculating the Double Exponential Moving Average. It can be adjusted from 1 to 200 to suit different trading styles.
Standard Deviation Length: Sets the lookback period for standard deviation calculations, which influences the responsiveness of the oscillator.
Standard Deviation Weight (StdDev Weight): Controls the weight given to the normalized standard deviation, allowing customization of the oscillator's sensitivity to volatility.
Calculation Steps:
Double Exponential Moving Average Calculation:
The DEMA is calculated using two exponential moving averages, which helps in reducing lag compared to a simple moving average.
Z-score Calculation:
The Z-score is derived by comparing the difference between the DEMA and its smoothed average (LSMA) to the standard deviation. This indicates how far the current value is from the mean in units of standard deviation.
Normalized Standard Deviation:
The standard deviation is normalized by subtracting the mean standard deviation and dividing by the standard deviation of the values. This helps to make the oscillator adaptive to recent changes in volatility.
Final Oscillator Value:
The final value is calculated by multiplying the Z-score with a factor based on the normalized standard deviation, resulting in a momentum indicator that adapts to different market conditions.
Visualization:
Histogram: The oscillator is plotted as a histogram, with color-coded bars showing the strength and direction of market momentum.
Positive (bullish) values are shown in green, indicating upward momentum.
Negative (bearish) values are shown in red, indicating downward momentum.
Zero Line: A zero line is plotted to provide a reference point, helping users quickly determine whether the current momentum is bullish or bearish.
Example Use Cases:
Momentum Identification:
ADMO helps identify the current market momentum by dynamically adapting to changes in market volatility. When the histogram is above zero and green, it indicates bullish conditions, whereas values below zero and red suggest bearish momentum.
Volatility-Adjusted Signals:
The normalized standard deviation weighting allows the ADMO to provide more reliable signals during different market conditions. This makes it particularly useful for traders who want to be responsive to market volatility while avoiding false signals.
Trend Confirmation and Divergence:
ADMO can be used to confirm the strength of a trend or identify potential divergences between price and momentum. This helps traders spot potential reversal points or continuation signals.
Summary:
The Adaptive DEMA Momentum Oscillator (ADMO) offers a unique approach by combining momentum analysis with adaptive standard deviation. The integration of DEMA makes it responsive to price changes, while the standard deviation adjustment helps it stay relevant in both high and low volatility environments. It's a versatile tool for traders who need an adaptive, momentum-based approach to technical analysis.
Feel free to explore the code and adapt it to your trading strategy. The open-source nature of this tool allows you to adjust the settings and visualize the output to fit your personal trading preferences.
Rata-Rata Pergerakan / Moving Averages
Simple Moving Average with Regime Detection by iGrey.TradingThis indicator helps traders identify market regimes using the powerful combination of 50 and 200 SMAs. It provides clear visual signals and detailed metrics for trend-following strategies.
Key Features:
- Dual SMA System (50/200) for regime identification
- Colour-coded candles for easy trend visualisation
- Metrics dashboard
Core Signals:
- Bullish Regime: Price < 200 SMA
- Bearish Regime: Price > 200 SMA
- Additional confirmation: 50 SMA Cross-over or Cross-under (golden cross or death cross)
Metrics Dashboard:
- Current Regime Status (Bull/Bear)
- SMA Distance (% from price to 50 SMA)
- Regime Distance (% from price to 200 SMA)
- Regime Duration (bars in current regime)
Usage Instructions:
1. Apply the indicator to your chart
2. Configure the SMA lengths if desired (default: 50/200)
3. Monitor the color-coded candles:
- Green: Bullish regime
- Red: Bearish regime
4. Use the metrics dashboard for detailed analysis
Settings Guide:
- Length: Short-term SMA period (default: 50)
- Source: Price calculation source (default: close)
- Regime Filter Length: Long-term SMA period (default: 200)
- Regime Filter Source: Price source for regime calculation (default: close)
Trading Tips:
- Use bullish regimes for long positions
- Use bearish regimes for capital preservation or short positions
- Consider regime duration for trend strength
- Monitor distance metrics for potential reversals
- Combine with other systems for confluence
#trend-following #moving average #regime #sma #momentum
Risk Management:
- Not a standalone trading system
- Should be used with proper position sizing
- Consider market conditions and volatility
- Always use stop losses
Best Practices:
- Monitor multiple timeframes
- Use with other confirmation tools
- Consider fundamental factors
Version: 1.0
Created by: iGREY.Trading
Release Notes
// v1.1 Allows table overlay customisation
// v1.2 Update to v6 pinescript
Dual Strategy Selector V2 - CryptogyaniOverview:
This script provides traders with a dual-strategy system that they can toggle between using a simple dropdown menu in the input settings. It is designed to cater to different trading styles and needs, offering both simplicity and advanced filtering techniques. The strategies are built around moving average crossovers, enhanced by configurable risk management tools like take profit levels, trailing stops, and ATR-based stop-loss.
Key Features:
Two Strategies in One Script:
Strategy 1: A classic moving average crossover strategy for identifying entry signals based on trend reversals. Includes user-defined take profit and trailing stop-loss options for profit locking.
Strategy 2: An advanced trend-following system that incorporates:
A higher timeframe trend filter to confirm entry signals.
ATR-based stop-loss for dynamic risk management.
Configurable partial take profit to secure gains while letting the trade run.
Highly Customizable:
All key parameters such as SMA lengths, take profit levels, ATR multiplier, and timeframe for the trend filter are adjustable via the input settings.
Dynamic Toggle:
Traders can switch between Strategy 1 and Strategy 2 with a single dropdown, allowing them to adapt the strategy to market conditions.
How It Works:
Strategy 1:
Entry Logic: A long trade is triggered when the fast SMA crosses above the slow SMA.
Exit Logic: The trade exits at either a user-defined take profit level (percentage or pips) or via an optional trailing stop that dynamically adjusts based on price movement.
Strategy 2:
Entry Logic: Builds on the SMA crossover logic but adds a higher timeframe trend filter to align trades with the broader market direction.
Risk Management:
ATR-Based Stop-Loss: Protects against adverse moves with a volatility-adjusted stop-loss.
Partial Take Profit: Allows traders to secure a percentage of gains while keeping some exposure for extended trends.
How to Use:
Select Your Strategy:
Use the dropdown in the input settings to choose Strategy 1 or Strategy 2.
Configure Parameters:
Adjust SMA lengths, take profit, and risk management settings to align with your trading style.
For Strategy 2, specify the higher timeframe for trend filtering.
Deploy and Monitor:
Apply the script to your preferred asset and timeframe.
Use the backtest results to fine-tune settings for optimal performance.
Why Choose This Script?:
This script stands out due to its dual-strategy flexibility and enhanced features:
For beginners: Strategy 1 provides a simple yet effective trend-following system with minimal setup.
For advanced traders: Strategy 2 includes powerful tools like trend filters and ATR-based stop-loss, making it ideal for challenging market conditions.
By combining simplicity with advanced features, this script offers something for everyone while maintaining full transparency and user customization.
Default Settings:
Strategy 1:
Fast SMA: 21, Slow SMA: 49
Take Profit: 7% or 50 pips
Trailing Stop: Optional (disabled by default)
Strategy 2:
Fast SMA: 20, Slow SMA: 50
ATR Multiplier: 1.5
Partial Take Profit: 50%
Higher Timeframe: 1 Day (1D)
SMA200 & RSI [Tarun]The SMA200 & RSI Signal Indicator is a powerful tool designed for traders who want to identify potential entry zones based on a combination of price action and momentum. This indicator combines two essential trading components:
SMA200 (Simple Moving Average): A widely used trend-following tool that highlights the overall direction of the market.
RSI (Relative Strength Index): A momentum oscillator that measures the speed and change of price movements.
How It Works:
Price Above SMA200: Indicates bullish market conditions.
RSI Between 40 and 20: Suggests that the asset is in a potential oversold or pullback zone within a bullish trend.
When both conditions are met, the indicator triggers:
Background Highlight: The chart background turns green to indicate a potential signal zone.
Disclaimer:
This indicator is not a standalone trading strategy. Use it in conjunction with other analysis methods such as support and resistance, candlestick patterns, or volume analysis. Always practice proper risk management.
FRAMA Channel [BigBeluga]This is a trend-following indicator that utilizes the Fractal Adaptive Moving Average (FRAMA) to create a dynamic channel around the price. The FRAMA Channel helps identify uptrends, downtrends, and ranging markets by examining the relationship between the price and the channel's boundaries. It also marks trend changes with arrows, optionally displaying either price values or average volume at these key points.
🔵 IDEA
The core idea behind the FRAMA Channel indicator is to use the fractal nature of markets to adapt to different market conditions. By creating a channel around the FRAMA line, it not only tracks price trends but also adapts its sensitivity based on market volatility. When the price crosses the upper or lower bands of the channel, it signals a potential shift in trend direction. If the price remains within the channel and crosses over the upper or lower bands without a breakout, the market is likely in a ranging phase with low momentum. This adaptive approach makes the FRAMA Channel effective in both trending and ranging market environments.
🔵 KEY FEATURES & USAGE
◉ Dynamic FRAMA Channel with Trend Signals:
The FRAMA Channel uses a fractal-based moving average to create an adaptive channel around the price. When the price crosses above the upper band, it signals an uptrend and plots an upward arrow with the price (or average volume) value. Conversely, when the price crosses below the lower band, it signals a downtrend and marks the point with a downward arrow. This dynamic adaptation to market conditions helps traders identify key trend shifts effectively.
◉ Ranging Market Detection:
If the price remains within the channel, and only the high crosses the upper band or the low crosses the lower band, the indicator identifies a ranging market with low momentum. In this case, the channel turns gray, signaling a neutral trend. This is particularly useful for avoiding false signals during periods of market consolidation.
◉ Color-Coded Candles and Channel Bands:
Candles and channel bands are color-coded to reflect the current trend direction. Green indicates an upward trend, blue shows a downward trend, and gray signals a neutral or ranging market. This visual representation makes it easy to identify the market condition at a glance, helping traders make informed decisions quickly.
◉ Customizable Display of Price or Average Volume:
On trend change signals, the indicator allows users to choose whether to display the price at the point of trend change or the average volume of 10 bars. This flexibility enables traders to focus on the information that is most relevant to their strategy, whether it's the exact price entery or the volume context of the market shift. Displaying the average volume allows to see the strength of the trend change.
Price Data:
Average Volume of points:
🔵 CUSTOMIZATION
Length & Bands Distance: Adjust the length for the FRAMA calculation to control the sensitivity of the channel. A shorter length makes the channel more reactive to price changes, while a longer length smooths it out. The Bands Distance setting determines how far the bands are from the FRAMA line, helping to define the breakout and ranging conditions.
Signals Data: Choose between displaying the price or the average volume on trend change arrows. This allows traders to focus on either the exact price level of trend change or the market volume context.
Color Settings: Customize the colors for upward momentum, downward momentum, and neutral states to suit your charting preferences. You can also toggle whether to color the candles based on the momentum for a clearer visual of the trend direction.
The FRAMA Channel indicator adapts to market conditions, providing a versatile tool for identifying trends and ranging markets with clear visual cues.
Optimized Grid with KNN_2.0Strategy Overview
This strategy, named "Optimized Grid with KNN_2.0," is designed to optimize trading decisions using a combination of grid trading, K-Nearest Neighbors (KNN) algorithm, and a greedy algorithm. The strategy aims to maximize profits by dynamically adjusting entry and exit thresholds based on market conditions and historical data.
Key Components
Grid Trading:
The strategy uses a grid-based approach to place buy and sell orders at predefined price levels. This helps in capturing profits from market fluctuations.
K-Nearest Neighbors (KNN) Algorithm:
The KNN algorithm is used to optimize entry and exit points based on historical price data. It identifies the nearest neighbors (similar price movements) and adjusts the thresholds accordingly.
Greedy Algorithm:
The greedy algorithm is employed to dynamically adjust the stop-loss and take-profit levels. It ensures that the strategy captures maximum profits by adjusting thresholds based on recent price changes.
Detailed Explanation
Grid Trading:
The strategy defines a grid of price levels where buy and sell orders are placed. The openTh and closeTh parameters determine the thresholds for opening and closing positions.
The t3_fast and t3_slow indicators are used to generate trading signals based on the crossover and crossunder of these indicators.
KNN Algorithm:
The KNN algorithm is used to find the nearest neighbors (similar price movements) in the historical data. It calculates the distance between the current price and historical prices to identify the most similar price movements.
The algorithm then adjusts the entry and exit thresholds based on the average change in price of the nearest neighbors.
Greedy Algorithm:
The greedy algorithm dynamically adjusts the stop-loss and take-profit levels based on recent price changes. It ensures that the strategy captures maximum profits by adjusting thresholds in real-time.
The algorithm uses the average_change variable to calculate the average price change of the nearest neighbors and adjusts the thresholds accordingly.
Correlation Confluence Trend IndicatorCorrelation Confluence Trend Indicator
Overview
The Correlation Confluence Trend Indicator combines exponential moving averages (EMAs) and statistical correlation measures to identify high-confidence trend alignments between an asset and a benchmark. By filtering signals through correlation strength, this indicator highlights opportunities when the asset and benchmark move together. In other words, it defines a trend and then uses correlation strength and the trend of a second asset to identify high-confidence trends.
Key Features
Dual EMA Trend Analysis :
Calculates fast and slow EMAs for both the asset and the selected benchmark (e.g., SPY) to identify bullish and bearish trends.
Correlation Strength Filtering :
Evaluates correlation between the asset and benchmark, identifying stronger-than-average relationships based on the mean and standard deviation.
Background Color Coding :
- Green : Strong correlation, both asset and benchmark bullish.
- Aqua : Weak correlation, both asset and benchmark bullish.
- Red : Strong correlation, both asset and benchmark bearish.
- Fuchsia : Weak correlation, both asset and benchmark bearish.
- Orange : Strong correlation, benchmark bullish, asset bearish.
- Yellow : Weak correlation, benchmark bullish, asset bearish.
- Purple : Strong correlation, benchmark bearish, asset bullish.
- Lime : Weak correlation, benchmark bearish, asset bullish.
Visual Trend Indicators :
Plots fast and slow EMAs for the asset, dynamically colored based on aggregate trend signals. The color of this corresponds to the main trend signal.
Inputs
Benchmark Symbol : Symbol of the benchmark asset to compare against.
Fast EMA Length : Period for the fast EMA calculation.
Slow EMA Length : Period for the slow EMA calculation.
Correlation Length : Number of bars for correlation calculation.
Correlation Mean Length : Number of bars for mean and standard deviation calculation.
Std Dev Multiplier : Multiplier for standard deviation to define correlation strength. When the correlation is Std Dev Multiplier standard deviations above the mean, it counts as a strong correlation.
Set Background Color : Toggle background coloring on or off.
Notes
This indicator is primarily designed for trend-following strategies. By combining trend analysis and correlation filtering, it ensures that signals occur during aligned market conditions, reducing false signals.
Before incorporating this indicator into your trading strategy:
Always backtest on historical data to evaluate its performance before committing capital.
Use proper risk management to control position sizes and mitigate potential losses.
Remember that no indicator guarantees success. I'm quite proud of this one, but it's not the holy grail.
Weighted Average Strength Index (WASI)Weighted Average Strength Index (WASI)
The Weighted Average Strength Index (WASI) is a variation of the standard RSI. It uses the Weighted Moving Average (WMA) instead of the Running Moving Average (RMA), making it more responsive to recent price changes. The hypothesis is that this weighted calculation might better capture momentum shifts, providing traders with more timely insights.
How to Use:
Backtest WASI on your preferred assets and timeframes to evaluate its effectiveness for your strategy.
Use for trend following or mean reversion :
- Overbought/Oversold (OB/OS) levels can signal potential mean-reversion opportunities.
- Midline (50 level) crossovers can be used for trend-following strategies.
- WASI and its moving average (MA) crossovers offer additional trend-following or reversal signals.
Parameters and Their Functions:
WASI Length: Determines the number of periods for WASI calculation. A longer length smooths the indicator but increases lag, while a shorter length makes it more sensitive. (When in doubt, go longer).
Source: The price source for the calculation (e.g., close, open, high, or low).
MA Type: Specifies the type of moving average applied to the WASI (options include SMA, EMA, WMA, HMA, and others).
MA Length: The number of periods for the moving average used on the WASI. Higher will lead to a smoother moving average.
Indicator Features:
Dynamic OB/OS Levels: Default overbought (70) and oversold (30) levels help identify potential reversal zones.
Midline Crossover: WASI crossing above or below the 50 level may indicate a trend shift.
WASI-MA Crossover: Crossovers between WASI and its moving average can signal trend-following or mean-reversion opportunities.
Disclaimer:
This indicator is a tool for analysis and should be used in conjunction with other forms of analysis or confirmation. Past performance does not guarantee future results.
Non-repainting ticker
The objective here is to provide a "non-repainting" source to indicators, meaning being sure that data is stable and will not affect the results, w/o having to make any change into the indicators
To use it :
1- include this "NRT" indicators onto your page : nothing will be displayed, just keep it.
2- as an exemple, when running any other indicator onto this page, and willing to select "close" as a source, just select instead " NRT: close" into source input; your indicator will then run "non-repainting"
Available sources : open, high, low , close, hl2, hlc3, ohlc4, hlcc4
Daily MAs on Intraday ChartsThis is a very simple, yet powerful indicator, for intraday and swing traders.
The indicator plots price levels of key daily moving averages as horizontal lines onto intraday charts.
The key daily moving averages being:
5-day EMA
10-day EMA
21-day EMA
50-day SMA
100-day SMA
200-day SMA
The moving averages above can be toggled on and off to the users liking and different colours selected to show the locations of daily moving average price levels on intraday charts.
Below is a chart of the SPY on the 30-minute timeframe. The black line represents the price level of the SPY's 10-day EMA, and the blue line represents the price level of the SPY's 21-day EMA.
Key daily moving averages like those mentioned above can be areas of support or resistance for major indexes, ETFs, and individual stocks. Therefore, when using multiple timeframe analysis combining daily charts and intraday charts, it's useful to be aware of these key daily moving average levels for potential reversals.
This indicator clearly shows where the key daily moving average price levels are on intraday charts for the chosen ticker symbol, thus helping traders to identify potential points of interest for trading ideas - i.e., going long or pullbacks into key daily moving averages, or short on rallies into key daily moving averages subject to the trader's thoughts at the time.
By using the 'Daily MAs on Intraday Charts' the trader can now have a multi-chart layout and be easily aware of key price levels from daily moving averages when looking at various intraday timeframe charts such as the 1-minute, 5-minute, 15-minute, 30-minute, 1-hour etc. This can be essential information for opening long and short trading ideas.
3 Confirmation BearThe "3 Confirmation Bear" indicator is designed to help traders identify strong bearish market conditions with three key confirmations:
Price Below EMA15:
The price trading below the 15-period Exponential Moving Average (EMA) signals bearish momentum.
RSI Below a Threshold:
The Relative Strength Index (RSI) is below a user-defined threshold (default: 50), confirming a lack of bullish strength and momentum favoring the downside.
Downtrend Confirmation:
The indicator ensures the market is in a downtrend by checking for lower highs and lower lows over a specified lookback period.
Key Features:
Bearish Signals: Displays a red downward-pointing label above the price bar when all three conditions are met, making bearish setups easy to identify.
Customizable Inputs: Traders can adjust the EMA length, RSI threshold, and downtrend lookback period to suit their specific strategies.
Versatile Application: Ideal for short entries, trend validation, or avoiding long trades during bearish conditions.
How to Use:
Use the "3 Confirmation Bear" indicator to:
Confirm Short Trades: Enter bearish trades when the signal aligns with your strategy.
Validate Trends: Ensure a clear downtrend is present before committing to a position.
Filter Trades: Avoid long positions during bearish momentum.
This indicator simplifies decision-making by focusing on high-probability bearish setups. Perfect for day traders, swing traders, and those seeking clear confirmation before entering a trade.
3 Confirmation Bull This script is designed to help traders identify strong bullish conditions by providing a signal when three key confirmations align:
Price is Above the 15-period EMA:
This shows that the price is trading above a short-term average, a sign of bullish momentum.
RSI is Above a Threshold:
The Relative Strength Index (RSI) is used to measure the strength of price movements. When RSI is above the user-defined threshold (default 50), it indicates bullish momentum and avoids overbought zones.
Price is in an Uptrend:
An uptrend is confirmed when there are both higher highs and higher lows over a specified lookback period. This ensures that the price structure supports upward movement.
Key Features:
Visual Alerts: A green label appears below the price bar whenever all three conditions are met, making it easy to spot trading opportunities.
Customizable Settings: Adjust the EMA length, RSI threshold, and uptrend lookback period to match your trading style or timeframe.
Versatility: Suitable for intraday, swing, or positional trading in trending markets.
How to Use:
This indicator is ideal for traders looking to confirm a bullish setup. Use it to:
Enter Trades: As confirmation for long positions when the signal appears.
Validate Trends: Ensure conditions are favorable before committing to a trade.
Combine with Other Strategies: Enhance your trading system by pairing it with volume analysis, candlestick patterns, or support/resistance levels.
By combining these three confirmations, the script helps traders filter out false signals and focus on higher-probability setups, streamlining their decision-making process.
TICKFLOW_FUTURES-ATR-ZONESThe TICKFLOW_FUTURES-ATR-ZONES script is a dynamic indicator designed to help traders identify key zones of price action based on ATR (Average True Range) and Bollinger Bands. This script combines customizable moving averages, volatility-based bands, and trend slope calculations to provide a clear visual framework for analyzing trends, detecting potential reversals, and identifying high-probability buy/sell zones.
Key Features:
Dynamic ATR Zones:
Upper and lower bands are calculated using ATR and adjusted dynamically based on the visible price range, ensuring alignment with current market conditions.
Slope-Based Color Coding:
The middle line (moving average) dynamically changes its color based on the slope to indicate bullish, bearish, or neutral trends.
Bollinger Band Squeeze Detection:
Highlights periods of price contraction using Bollinger Band width, helping identify potential breakout setups.
Buy and Sell Signals:
Displays visual markers (BUY/SELL) based on slope changes and price action relative to the dynamic middle line.
Customizable Inputs:
Includes options to adjust ATR multiplier, Bollinger Band settings, moving average type, slope lookback period, and color preferences.
Visual Zones:
Shaded areas representing ATR-based upper and lower zones for a clear and intuitive price action framework.
Usage Instructions:
Clean Chart:
Use the script on a clean chart for best results. This ensures that the plotted zones, lines, and markers are easily interpretable without interference.
Understanding the Components:
The middle line represents the selected moving average type, providing the directional bias.
Upper and lower zones indicate potential reversal or continuation levels based on ATR.
BUY/SELL markers suggest trend initiation points but should be confirmed with additional analysis.
Customization:
Adjust input parameters (e.g., ATR multiplier, Bollinger Band settings) to fit your trading style and market conditions.
Important Notes:
This script works as a standalone tool and does not require other indicators to function.
Avoid using it with additional scripts on the same chart unless explicitly needed and described in your analysis.
4-Hour Moving AveragesTitle: 4-Hour Moving Averages Indicator
Description:
The "4-Hour Moving Averages" indicator is designed to help traders easily visualize key moving averages derived from the 4-hour timeframe, regardless of the chart interval they are using. This indicator plots four moving averages: a 15-period SMA (Short-Term), a 35-period SMA (Intermediate-Term), an 80-period SMA (Long-Term), and a 130-period SMA (Confirmation).
These moving averages provide a balanced approach for identifying short, medium, and long-term trends, as well as confirming significant market movements. Ideal for swing traders and those looking for clear trend signals, the indicator can be used for various markets, including stocks, forex, and cryptocurrencies.
The 4-hour moving averages overlay directly on the price chart, allowing for easy analysis of current price movements relative to important trend indicators. Use this script to enhance your trading decisions, identify opportunities, and avoid market traps by relying on consistent moving average trends.
Features:
- 15 SMA for Short-Term Trends (in red)
- 35 SMA for Intermediate-Term Trends (in orange)
- 80 SMA for Long-Term Trends (in green)
- 130 SMA for Confirmation (in blue)
Feel free to modify the settings to suit your specific strategy and market conditions.
Adaptive Moving AveragesThe Adaptive Moving Averages indicator stands out with several unique features that set it apart from traditional moving average indicators. Its most remarkable characteristic is the ability to automatically adjust the length of moving averages based on the chosen timeframe. This ensures consistency in analysis regardless of the time scale used, eliminating the need for manual recalculation of appropriate periods for each timeframe. It allows for a more fluid and accurate multi-temporal analysis.
Another innovative aspect is the indicator's consideration of different market types (stocks, forex, crypto). This approach recognizes the fundamental differences between these markets in terms of trading hours, allowing for more precise and representative calculations for each asset class. It offers increased flexibility for traders operating across various markets.
The method for calculating periods for different moving averages (week, month, quarter, semester, year) is particularly sophisticated. It takes into account the specifics of each market, such as trading days and opening hours, automatically adapting to timeframe changes. This ensures a more accurate representation of actual trading periods rather than arbitrary approximations.
The indicator offers a wide choice of moving average types, allowing traders to use their preferred method or compare different approaches. This flexibility adapts to various trading styles and technical analysis strategies, offering the possibility to experiment and find the most effective combination for each market or asset.
In conclusion, this indicator distinguishes itself through its ability to intelligently adapt to different trading contexts, offering a versatile and sophisticated solution for technical analysis. Its flexibility and adaptive approach make it a particularly interesting tool for traders seeking consistent analysis across different markets and time scales.
Bayesian Price Projection Model [Pinescriptlabs]📊 Dynamic Price Projection Algorithm 📈
This algorithm combines **statistical calculations**, **technical analysis**, and **Bayesian theory** to forecast a future price while providing **uncertainty ranges** that represent upper and lower bounds. The calculations are designed to adjust projections by considering market **trends**, **volatility**, and the historical probabilities of reaching new highs or lows.
Here’s how it works:
🚀 Future Price Projection
A dynamic calculation estimates the future price based on three key elements:
1. **Trend**: Defines whether the market is predisposed to move up or down.
2. **Volatility**: Quantifies the magnitude of the expected change based on historical fluctuations.
3. **Time Factor**: Uses the logarithm of the projected period (`proyeccion_dias`) to adjust how time impacts the estimate.
🧠 **Bayesian Probabilistic Adjustment**
- Conditional probabilities are calculated using **Bayes' formula**:
\
This models future events using conditional information:
- **Probability of reaching a new all-time high** if the price is trending upward.
- **Probability of reaching a new all-time low** if the price is trending downward.
- These probabilities refine the future price estimate by considering:
- **Higher volatility** increases the likelihood of hitting extreme levels (highs/lows).
- **Market trends** influence the expected price movement direction.
🌟 **Volatility Calculation**
- Volatility is measured using the **ATR (Average True Range)** indicator with a 14-period window. This reflects the average amplitude of price fluctuations.
- To express volatility as a percentage, the ATR is normalized by dividing it by the closing price and multiplying it by 200.
- Volatility is then categorized into descriptive levels (e.g., **Very Low**, **Low**, **Moderate**, etc.) for better interpretation.
---
🎯 **Deviation Limits (Upper and Lower)**
- The upper and lower limits form a **projected range** around the estimated future price, providing a framework for uncertainty.
- These limits are calculated by adjusting the ATR using:
- A user-defined **multiplier** (`factor_desviacion`).
- **Bayesian probabilities** calculated earlier.
- The **square root of the projected period** (`proyeccion_dias`), incorporating the principle that uncertainty grows over time.
🔍 **Interpreting the Model**
This can be seen as a **dynamic probabilistic model** that:
- Combines **technical analysis** (trends and ATR).
- Refines probabilities using **Bayesian theory**.
- Provides a **visual projection range** to help you understand potential future price movements and associated uncertainties.
⚡ Whether you're analyzing **volatile markets** or confirming **bullish/bearish scenarios**, this tool equips you with a robust, data-driven approach! 🚀
Español :
📊 Algoritmo de Proyección de Precio Dinámico 📈
Este algoritmo combina **cálculos estadísticos**, **análisis técnico** y **la teoría de Bayes** para proyectar un precio futuro, junto con rangos de **incertidumbre** que representan los límites superior e inferior. Los cálculos están diseñados para ajustar las proyecciones considerando la **tendencia del mercado**, **volatilidad** y las probabilidades históricas de alcanzar nuevos máximos o mínimos.
Aquí se explica su funcionamiento:
🚀 **Proyección de Precio Futuro**
Se realiza un cálculo dinámico del precio futuro estimado basado en tres elementos clave:
1. **Tendencia**: Define si el mercado tiene predisposición a subir o bajar.
2. **Volatilidad**: Determina la magnitud del cambio esperado en función de las fluctuaciones históricas.
3. **Factor de Tiempo**: Usa el logaritmo del período proyectado (`proyeccion_dias`) para ajustar cómo el tiempo afecta la estimación.
🧠 **Ajuste Probabilístico con la Teoría de Bayes**
- Se calculan probabilidades condicionales mediante la fórmula de **Bayes**:
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Esto permite modelar eventos futuros considerando información condicional:
- **Probabilidad de alcanzar un nuevo máximo histórico** si el precio sube.
- **Probabilidad de alcanzar un nuevo mínimo histórico** si el precio baja.
- Estas probabilidades ajustan la estimación del precio futuro considerando:
- **Mayor volatilidad** aumenta la probabilidad de alcanzar niveles extremos (máximos/mínimos).
- **La tendencia del mercado** afecta la dirección esperada del movimiento del precio.
🌟 **Cálculo de Volatilidad**
- La volatilidad se mide usando el indicador **ATR (Average True Range)** con un período de 14 velas. Este indicador refleja la amplitud promedio de las fluctuaciones del precio.
- Para obtener un valor porcentual, el ATR se normaliza dividiéndolo por el precio de cierre y multiplicándolo por 200.
- Además, se clasifica esta volatilidad en categorías descriptivas (e.g., **Muy Baja**, **Baja**, **Moderada**, etc.) para facilitar su interpretación.
🎯 **Límites de Desviación (Superior e Inferior)**
- Los límites superior e inferior representan un **rango proyectado** en torno al precio futuro estimado, proporcionando un marco para la incertidumbre.
- Estos límites se calculan ajustando el ATR según:
- Un **multiplicador** definido por el usuario (`factor_desviacion`).
- Las **probabilidades condicionales** calculadas previamente.
- La **raíz cuadrada del período proyectado** (`proyeccion_dias`), lo que incorpora el principio de que la incertidumbre aumenta con el tiempo.
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🔍 **Interpretación del Modelo**
Este modelo se puede interpretar como un **modelo probabilístico dinámico** que:
- Integra **análisis técnico** (tendencias y ATR).
- Ajusta probabilidades utilizando **la teoría de Bayes**.
- Proporciona un **rango de proyección visual** para ayudarte a entender los posibles movimientos futuros del precio y su incertidumbre.
⚡ Ya sea que estés analizando **mercados volátiles** o confirmando **escenarios alcistas/bajistas**, ¡esta herramienta te ofrece un enfoque robusto y basado en datos! 🚀
Trend Following Strategy with KNN
### 1. Strategy Features
This strategy combines the K-Nearest Neighbors (KNN) algorithm with a trend-following strategy to predict future price movements by analyzing historical price data. Here are the main features of the strategy:
1. **Dynamic Parameter Adjustment**: Uses the KNN algorithm to dynamically adjust parameters of the trend-following strategy, such as moving average length and channel length, to adapt to market changes.
2. **Trend Following**: Captures market trends using moving averages and price channels to generate buy and sell signals.
3. **Multi-Factor Analysis**: Combines the KNN algorithm with moving averages to comprehensively analyze the impact of multiple factors, improving the accuracy of trading signals.
4. **High Adaptability**: Automatically adjusts parameters using the KNN algorithm, allowing the strategy to adapt to different market environments and asset types.
### 2. Simple Introduction to the KNN Algorithm
The K-Nearest Neighbors (KNN) algorithm is a simple and intuitive machine learning algorithm primarily used for classification and regression problems. Here are the basic concepts of the KNN algorithm:
1. **Non-Parametric Model**: KNN is a non-parametric algorithm, meaning it does not make any assumptions about the data distribution. Instead, it directly uses training data for predictions.
2. **Instance-Based Learning**: KNN is an instance-based learning method that uses training data directly for predictions, rather than generating a model through a training process.
3. **Distance Metrics**: The core of the KNN algorithm is calculating the distance between data points. Common distance metrics include Euclidean distance, Manhattan distance, and Minkowski distance.
4. **Neighbor Selection**: For each test data point, the KNN algorithm finds the K nearest neighbors in the training dataset.
5. **Classification and Regression**: In classification problems, KNN determines the class of a test data point through a voting mechanism. In regression problems, KNN predicts the value of a test data point by calculating the average of the K nearest neighbors.
### 3. Applications of the KNN Algorithm in Quantitative Trading Strategies
The KNN algorithm can be applied to various quantitative trading strategies. Here are some common use cases:
1. **Trend-Following Strategies**: KNN can be used to identify market trends, helping traders capture the beginning and end of trends.
2. **Mean Reversion Strategies**: In mean reversion strategies, KNN can be used to identify price deviations from the mean.
3. **Arbitrage Strategies**: In arbitrage strategies, KNN can be used to identify price discrepancies between different markets or assets.
4. **High-Frequency Trading Strategies**: In high-frequency trading strategies, KNN can be used to quickly identify market anomalies, such as price spikes or volume anomalies.
5. **Event-Driven Strategies**: In event-driven strategies, KNN can be used to identify the impact of market events.
6. **Multi-Factor Strategies**: In multi-factor strategies, KNN can be used to comprehensively analyze the impact of multiple factors.
### 4. Final Considerations
1. **Computational Efficiency**: The KNN algorithm may face computational efficiency issues with large datasets, especially in real-time trading. Optimize the code to reduce access to historical data and improve computational efficiency.
2. **Parameter Selection**: The choice of K value significantly affects the performance of the KNN algorithm. Use cross-validation or other methods to select the optimal K value.
3. **Data Standardization**: KNN is sensitive to data standardization and feature selection. Standardize the data to ensure equal weighting of different features.
4. **Noisy Data**: KNN is sensitive to noisy data, which can lead to overfitting. Preprocess the data to remove noise.
5. **Market Environment**: The effectiveness of the KNN algorithm may be influenced by market conditions. Combine it with other technical indicators and fundamental analysis to enhance the robustness of the strategy.
Adaptive McGinley Cloud V1 Trend & Trade SignalsAdaptive McGinley Cloud V1 Trend & Trade Signals is a dynamic trend-following indicator designed to help traders identify market trends, trade opportunities, and manage risk. The script is built on the McGinley Dynamic, which adjusts the moving average based on the price and its volatility, providing a smoother and more adaptive trend-following tool. Here's a breakdown of its key features:
McGinley Dynamic: The core of the indicator, the McGinley Dynamic, is calculated to track price movements more closely than traditional moving averages. It reacts more quickly to price changes in volatile markets, making it more adaptive.
Upper and Lower Bands: The indicator uses standard deviation to calculate upper and lower bands around the McGinley Dynamic, which represent potential levels of market volatility and trend strength. These bands help define whether the price is trending strongly or consolidating.
Cloud Visualization: A cloud fills the area between the upper and lower bands. The cloud's color changes based on the strength of the trend, with the opacity reflecting how far the price is from the McGinley Dynamic. When the trend is bullish, the cloud color shifts to purple, and when the trend is bearish, the cloud becomes more transparent.
Trend Indicators: The script detects trend changes by comparing the price with the McGinley Dynamic and the bands. A bullish trend is signaled when the price is above the McGinley Dynamic and upper band, while a bearish trend is signaled when the price is below the lower band.
Buy and Sell Signals: The indicator generates buy (long) and sell (short) signals when the trend crosses from bearish to bullish (or vice versa). These signals are marked with upward and downward arrows on the chart.
Take Profit (TP) and Stop Loss (SL) Levels: The script calculates potential take profit and stop loss levels based on the distance between the price and the upper and lower bands. These levels adjust dynamically as the price moves, helping traders manage risk.
Alerts: Alerts are built into the script for key events such as trend changes, take profit conditions, and stop loss conditions. Traders can set alerts to be notified when these events occur.
This indicator is designed to provide traders with a comprehensive tool for identifying trends, spotting potential entry and exit points, and managing trades effectively. By using adaptive calculations and providing visual cues such as the cloud and arrows, it offers an intuitive way to follow market movements and make informed decisions.
1drv.ms
Dynamic Cloud and Trend Identification
Original McGinley Dynamic Indicator: The original McGinley Dynamic (MD) was essentially a smoothed moving average designed to adapt to changing market speeds. It is typically used to indicate the direction of the trend based on its relationship with the price.
Modified Indicator: The modified version of the McGinley Dynamic is enhanced by the addition of a cloud that visually represents the price volatility using standard deviation bands around the MD line. The cloud is filled based on the gradient, with colors indicating the trend’s strength and direction. The script adds:
Upper and Lower Bands: These are plotted based on the standard deviation, which dynamically adjusts with market volatility. These bands help to assess the range within which the price should move.
Cloud Fill: The area between the upper and lower bands is filled with color, making it easier to visually identify periods of strong trends and consolidations. The cloud color changes based on the gradient, indicating whether the market is moving in a bullish or bearish direction.
Why This Helps Traders:
The cloud visually highlights the strength of the trend, making it easier for traders to identify trend reversals and potential breakout points.
The gradient fill within the cloud allows traders to spot trends before they become obvious from just the price action, giving them an early warning of trend strength.
Trend Reversal and Signal Indicators
Original McGinley Dynamic Indicator: The original MD only provided the smoothed average to indicate the trend direction. It didn't offer specific buy/sell signals or a way to easily spot trend changes.
Modified Indicator: The modified version introduces trend reversal signals:
Up Arrows (▲): These are plotted when the price crosses above the McGinley Dynamic, signaling a potential bullish trend.
Down Arrows (▼): These are plotted when the price crosses below the McGinley Dynamic, signaling a potential bearish trend.
Why This Helps Traders:
The inclusion of clear trend reversal signals gives traders a visual cue for when a potential trend change is occurring, which they can use to time their entries.
The arrows provide an additional layer of confirmation when combined with the cloud, giving traders more confidence in making trading decisions.
Dynamic Take Profit (TP) and Stop Loss (SL) Levels
Original McGinley Dynamic Indicator: The original MD indicator does not include any functionality for setting or calculating take profit or stop loss levels. It’s primarily used to identify the trend.
Modified Indicator: The modified version uses the upper and lower bands to define levels for take profit (TP) and stop loss (SL). These levels are dynamically calculated based on the McGinley Dynamic and its surrounding bands.
Take Profit (TP): If the price moves beyond the upper band, it might indicate an overbought condition or a trend continuation point where a trader could take profits.
Stop Loss (SL): If the price moves below the lower band, it could indicate an oversold condition, and traders may consider stopping out of a position.
Why This Helps Traders:
Dynamic TP and SL levels based on market volatility (standard deviation) help to manage risk better than static levels, adjusting to market conditions as they change.
Traders can use these levels to protect profits and minimize losses automatically, making the indicator more useful for those who require risk management tools alongside trend identification.
Trend Strength and Gradient Visualization
Original McGinley Dynamic Indicator: The original MD smooths the price data and shows the direction of the trend but does not offer a visual measure of the strength of that trend.
Modified Indicator: The modified version calculates the gradient of the McGinley Dynamic relative to the price. This gradient value is used to assess the strength of the trend, which is then visualized in the form of a color gradient for the cloud.
The gradient is measured by calculating the difference between the McGinley Dynamic and the price, and then normalizing it to a 0-100 scale. This gives traders a clearer view of how strong the current trend is and whether it's likely to continue or reverse.
The cloud color also dynamically changes based on this gradient, so traders can visually gauge trend strength.
Why This Helps Traders:
By visualizing trend strength, the trader gets a better sense of whether the market is in a strong, sustained move or just a weak pullback. This helps them avoid false signals and stick to the more powerful trends.
The gradient-based cloud provides a more intuitive view of market conditions than just the price line alone.
Visual Trade and Trend Indicators
Original McGinley Dynamic Indicator: It would simply show the MD line without providing visual indicators of trends, reversals, or other key levels.
Modified Indicator: In addition to the cloud, arrows, and gradient, the modified version adds visual signals for potential trade actions:
Trend Change Indicators: The indicator plots up and down arrows to indicate trend changes, making it easier for traders to know when to enter or exit trades based on the McGinley Dynamic.
Bullish and Bearish Signals: Visual cues like arrows and shapes give more context and actionable data for trading decisions.
Why This Helps Traders:
The arrows and other visual signals allow traders to quickly recognize trend changes without needing to interpret complex data, making it easier to trade actively.
The clarity in trend shifts ensures that traders can time their entries and exits more effectively.
Summary: How the Modified Indicator Helps Traders
Enhanced Trend Detection: The modified indicator provides a clear visual representation of trends through the cloud and McGinley Dynamic, helping traders identify trends and reversals more easily.
Dynamic Risk Management: The automatic calculation of TP and SL levels based on market volatility and the McGinley Dynamic helps traders manage risk more effectively.
Visual Confirmation: With trend reversal arrows and a gradient-based cloud, traders get multiple confirmations for when to enter or exit trades, improving the accuracy of their decisions.
Trend Strength: The indicator not only shows the direction of the trend but also its strength, allowing traders to assess the sustainability of the current market conditions.
In conclusion, the modified McGinley Dynamic indicator is a powerful tool that not only tracks trends but also provides dynamic risk management, trend strength visualization, and clear entry/exit signals. It improves on the original by adding these features, making it a more comprehensive tool for traders looking for an automated way to assess market conditions and manage trades.
GoldenTradz EMA+SMA Insight Multi Timeframe - [TilakBala]GoldenTradz EMA+SMA Insight Multi-Timeframe
📊 Indicator By: TilakBala from GoldenTradz — Revolutionize your trading approach with precision and insight!
Unlock the full potential of moving averages with the GoldenTradz EMA+SMA Insight indicator. This feature-packed tool combines the strength of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA), offering unmatched flexibility and clarity for traders. Whether you're a beginner or a pro, this indicator empowers you to make well-informed trading decisions across multiple timeframes.
Key Features & Advantages:
Multi-Timeframe Analysis: Seamlessly analyze market trends using EMAs and SMAs from different timeframes on a single chart.
Gain a broader perspective by comparing short-term and long-term trends.
Customizable Settings:
Adjust EMA and SMA lengths, sources, and timeframes to fit your trading strategy perfectly.
Enable or disable specific moving averages for a clutter-free chart view.
Enhanced Trend Detection:
Identify bullish and bearish trends quickly using visually distinct EMAs and SMAs.
Use shorter EMAs for faster signals and longer SMAs for reliable trend confirmation.
Overlay Design:
Plots moving averages directly on the price chart for effortless analysis.
Distinct colors and line thicknesses ensure clear identification of each moving average.
Versatile Applications:
Suitable for scalping, day trading, swing trading, and long-term investments.
Works flawlessly with stocks, forex, cryptocurrencies, commodities, indices, and more.
Decision-Making Support:
Crossovers between EMAs and SMAs help identify potential buy or sell opportunities.
Monitor key support and resistance levels dynamically.
Efficiency in Market Noise:
EMAs provide rapid responsiveness in volatile markets.
SMAs help smooth out market noise for clearer long-term trends.
Adaptable to Any Strategy:
Perfect for breakout, trend-following, and mean-reversion strategies.
Combine with other indicators for a comprehensive trading system.
User-Friendly:
Intuitive interface with clear input fields for quick setup.
Suitable for traders of all experience levels.
📊 Indicator By: TilakBala from GoldenTradz — Revolutionize your trading approach with precision and insight!
Transform your trading with GoldenTradz EMA+SMA Insight — the ultimate tool for trend and momentum analysis.
SMB MagicSMB Magic
Overview: SMB Magic is a powerful technical strategy designed to capture breakout opportunities based on price movements, volume spikes, and trend-following logic. This strategy works exclusively on the XAU/USD symbol and is optimized for the 15-minute time frame. By incorporating multiple factors, this strategy identifies high-probability trades with a focus on risk management.
Key Features:
Breakout Confirmation:
This strategy looks for price breakouts above the previous high or below the previous low, with a significant volume increase. A breakout is considered valid when it is supported by strong volume, confirming the strength of the price move.
Price Movement Filter:
The strategy ensures that only significant price movements are considered for trades, helping to avoid low-volatility noise. This filter targets larger price swings to maximize potential profits.
Exponential Moving Average (EMA):
A long-term trend filter is applied to ensure that buy trades occur only when the price is above the moving average, and sell trades only when the price is below it.
Fibonacci Levels:
Custom Fibonacci retracement levels are drawn based on recent price action. These levels act as dynamic support and resistance zones and help determine the exit points for trades.
Take Profit/Stop Loss:
The strategy incorporates predefined take profit and stop loss levels, designed to manage risk effectively. These levels are automatically applied to trades and are adjusted based on the market's volatility.
Volume Confirmation:
A volume multiplier confirms the strength of the breakout. A trade is only considered when the volume exceeds a certain threshold, ensuring that the breakout is supported by sufficient market participation.
How It Works:
Entry Signals:
Buy Signal: A breakout above the previous high, accompanied by significant volume and price movement, occurs when the price is above the trend-following filter (e.g., EMA).
Sell Signal: A breakout below the previous low, accompanied by significant volume and price movement, occurs when the price is below the trend-following filter.
Exit Strategy:
Each position (long or short) has predefined take-profit and stop-loss levels, which are designed to protect capital and lock in profits at key points in the market.
Fibonacci Levels:
Fibonacci levels are drawn to identify potential areas of support or resistance, which can be used to guide exits and stop-loss placements.
Important Notes:
Timeframe Restriction: This strategy is designed specifically for the 15-minute time frame.
Symbol Restriction: The strategy works exclusively on the XAU/USD (Gold) symbol and is not recommended for use with other instruments.
Best Performance in Trending Markets: It works best in trending conditions where breakouts occur frequently.
Disclaimer:
Risk Warning: Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and make informed decisions before trading.
VD Zig Zag with SMAIntroduction
The VD Zig Zag with SMA indicator is a powerful tool designed to streamline technical analysis by combining Zig Zag swing lines with a Simple Moving Average (SMA). It offers traders a clear and intuitive way to analyze price trends, market structure, and potential reversals, all within a customizable framework.
Definition
The Zig Zag indicator is a trend-following tool that highlights significant price movements by filtering out smaller fluctuations. It visually connects swing highs and lows to reveal the underlying market structure. When paired with an SMA, it provides an additional layer of trend confirmation, helping traders align their strategies with market momentum.
Calculations
Zig Zag Logic:
Swing highs and lows are determined using a user-defined length parameter.
The highest and lowest points within the specified range are identified using the ta.highest() and ta.lowest() functions.
Zig Zag lines dynamically connect these swing points to visually map price movements.
SMA Logic:
The SMA is calculated using the closing prices over a user-defined period.
It smooths out price action to provide a clearer view of the prevailing trend.
The indicator allows traders to adjust the Zig Zag length and SMA period to suit their preferred trading timeframe and strategy.
Takeaways
Enhanced Trend Analysis: The Zig Zag lines clearly define the market's structural highs and lows, helping traders identify trends and reversals.
Customizable Parameters: Both the swing length and SMA period can be tailored for short-term or long-term trading strategies.
Visual Clarity: By filtering out noise, the indicator simplifies chart analysis and enables better decision-making.
Multi-Timeframe Support: Adapts seamlessly to the chart's timeframe, ensuring usability across all trading horizons.
Limitations
Lagging Nature: As with any indicator, the Zig Zag and SMA components are reactive and may lag during sudden price movements.
Sensitivity to Parameters: Improper parameter settings can lead to overfitting, where the indicator reacts too sensitively or misses significant trends.
Does Not Predict: This indicator identifies trends and structure but does not provide forward-looking predictions.
Summary
The VD Zig Zag with SMA indicator is a versatile and easy-to-use tool that combines the strengths of Zig Zag swing analysis and moving average trends. It helps traders filter market noise, visualize structural patterns, and confirm trends with greater confidence. While it comes with limitations inherent to all technical tools, its customizable features and multi-timeframe adaptability make it an excellent addition to any trader’s toolkit.
Additional Features
Have an idea or a feature you'd like to see added?
Feel free to reach out or share your suggestions here—I’m always open to updates!
Market Overview TableThis script creates a market overview table that aggregates the signals from seven technical indicators into a single overall market trend. The goal of the table is to provide a quick summary of the market condition based on the combined behavior of multiple popular indicators. Instead of displaying each individual indicator's trend separately, it summarizes them into one overall market signal, displayed as a triangle (either up or down). This simplifies the decision-making process by focusing on an easy-to-read visual cue.
how it works
The table pulls in signals from seven indicators:
rsi (relative strength index): Measures if the asset is overbought (above 70) or oversold (below 30). In this case, the condition checks if the rsi is above 50, indicating a bullish trend.
ema (exponential moving average): A trend-following indicator that gives more weight to recent prices. It checks if the current price is above the ema value, which suggests an upward market trend.
sma (simple moving average): Similar to ema, it calculates the average price over a set period. When the price is above the sma, it indicates a bullish trend.
vwma (volume-weighted moving average): This average takes volume into account. It checks if the price is above the vwma, indicating higher trading activity in the direction of the trend.
bb (bollinger bands): The script compares the price to the upper bollinger band. If the price is above the upper band, it suggests that the price is in an overbought condition, signaling a bullish market.
williams fractals: A pattern recognition indicator that detects market turning points. In this case, it checks if the price is above the fractal high, indicating a bullish breakout.
momentum: Measures the rate of change in price over a set period. If the momentum is positive (price is rising), it indicates a bullish trend.
overall market calculation
The overall market condition is determined by the sum of bullish conditions across all seven indicators. For each indicator, if it shows a bullish signal (e.g., price above the moving average, rsi above 50), it is counted as a bullish indicator. The total number of bullish indicators is then tallied up:
If 4 or more indicators are bullish, the market is considered bullish overall.
If less than 4 indicators are bullish, the market is considered bearish overall.
This method aggregates the data from all seven indicators into a single market trend signal, represented by a triangle.
the triangle
The triangle (▲ or ▼) is used as the visual signal for the overall market trend. If the market is determined to be bullish (4 or more bullish indicators), the triangle will point up (▲), indicating a positive or upward trend. If the market is bearish (fewer than 4 bullish indicators), the triangle will point down (▼), signaling a negative or downward trend.
difference from individual indicators
The main difference between this approach and traditional indicator-based methods is the aggregation of multiple indicators into one simple signal. Instead of displaying seven separate signals for each indicator, which can be overwhelming and difficult to interpret quickly, this table combines them into one clear visual cue for the overall market condition. This makes it easier for traders to make quick decisions without having to analyze each individual indicator in detail.
Here’s what makes this approach unique:
Simplicity: Rather than plotting individual indicator signals on the chart, which can clutter the screen, the table condenses the market’s trend into a single up or down triangle, which is easier to interpret at a glance.
Comprehensive view: By aggregating seven indicators, the table considers multiple aspects of the market (e.g., momentum, trend, volume) to give a more comprehensive view of the market’s behavior, rather than relying on just one or two indicators.
Dynamic nature: As market conditions change and indicators fluctuate, the overall market trend dynamically updates, providing real-time feedback on the market’s direction.
table structure
The table is structured with two columns:
The first column contains the "OVERALL MARKET" label.
The second column displays the triangle (▲ or ▼) indicating the market trend based on the combined signal from all seven indicators.
By keeping it simple and focusing only on the overall market trend, this table allows traders to quickly grasp the market’s condition without having to sift through individual indicator data.
conclusion
This table simplifies the complexity of analyzing multiple indicators by summarizing their signals into a single, easy-to-read visual indicator. It is ideal for traders who want a quick, comprehensive view of market conditions without diving deep into the details of each individual indicator. The approach of aggregating multiple indicators into one overall market trend provides a clearer picture and saves time while maintaining the reliability of a multi-indicator analysis.
Elite Trading Network | HQ: Quantum Edge V2Elite Trading Network HQ: Quantum Edge V2 is a sophisticated market structure analysis tool designed to help traders make informed decisions based on a deep understanding of market conditions. This script blends structural trend analysis with AI-based predictive models to provide dynamic, real-time insights into market behavior. Here is what makes Quantum Edge V2 unique:
Key Features:
Adaptive Market Structure Analysis:
The script uses a multi-level algorithm to identify key market structures, such as swing highs and swing lows, to help traders understand the underlying strength or weakness of the current market trend. It dynamically tracks critical market boundaries using historical price action and recalculates trend levels as new data emerges.
Range and Trend Condition Detection:
Quantum Edge V2 detects whether the market is trending or ranging by analyzing historical structure breaks. This detection helps identify moments of consolidation (yellow zones) or periods of trend continuation. By calculating average structural break durations, the indicator alerts users to conditions that may require caution, such as ranging markets.
Predictive AI Analysis for Entry Optimization:
An AI-powered module evaluates volume thresholds and ATR (Average True Range) to provide users with an understanding of the current market risk. The ATR is calculated based on a user-defined timeframe, giving flexibility in how users approach different market conditions. This feature also determines the risk per trade and calculates the optimal position size, ensuring that users can tailor their risk according to their trading plan.
Real-Time Alerts and Visual Indicators:
The indicator includes alerts for key conditions:
Green Condition: Signals optimal market entry conditions.
Yellow Condition: Indicates a cautionary ranging market, alerting traders to the potential lack of strong trends.
Red Condition: Identifies unsuitable market conditions for entry due to insufficient volume or unfavorable metrics.
Color-coded background visuals provide instant clarity regarding market conditions—red, yellow, or green—allowing traders to make quick, informed decisions.
Dynamic Multi-Timeframe Analysis:
The user can select a custom entry timeframe, while the script internally calculates and adapts to a higher timeframe for deep trend analysis. This approach gives traders a complete view of both the short-term (entry) and higher timeframe (overall trend) dynamics.
How to Use:
Identify Trend Conditions: The indicator visually plots key market structures (green and red structural lines) to help users determine where the market may find support or resistance. The background changes color to indicate trending (green), ranging (yellow), or high-risk (red) conditions.
Make Informed Entries: Use the real-time alerts and label information to get insights into current market conditions. If the background is green and metrics align, the indicator suggests an optimal time for entry.
Position Sizing and Risk Management: The calculated risk per trade and position size (displayed on-screen) assist users in managing risk effectively. Users can utilize this data to adjust trade sizes and maximize profit potential while adhering to their risk tolerance.
What Sets Quantum Edge V2 Apart:
Unlike other indicators that solely provide trend direction, Quantum Edge V2 offers an integrated understanding of market structure, volume analysis, and predictive AI models.
The ranging market detection (yellow zones) is particularly valuable for traders looking to avoid low-probability trades during periods of market indecision.
The use of ATR-based risk calculation ensures the position sizing is always aligned with market volatility, adding an extra layer of protection for capital.
Important Notes:
Educational Value: This script does not just tell you when to enter or exit. It provides deep insights into market dynamics, giving traders a tool to learn and improve their market understanding. The ability to view market structure across different timeframes and visualize areas of caution is crucial for long-term growth as a trader.
No Guaranteed Results: This indicator is a powerful tool for analysis, but like all trading strategies, it does not guarantee profits. Always practice proper risk management.
Why It's Worth Using: This indicator combines multi-timeframe structure analysis, volume metrics, and predictive AI modeling—an approach typically reserved for professional trading systems. Traders looking to incorporate a systematic approach to risk, ranging markets, and trend detection will find Quantum Edge V2 invaluable.
Closed-source Explanation: The script uses proprietary algorithms and unique concepts for trend detection and volume-based analysis that ensure high levels of accuracy in defining market structure and determining entry signals. Because of its complexity and the unique blend of tools, it remains closed-source.
Feedback and Support:
If you have questions or suggestions about this script, feel free to comment or reach out. We value your input as we strive to improve and provide traders with cutting-edge tools.
