Support and Resistance with Buy/Sell SignalsSwing Highs and Lows:
The script identifies swing highs and lows using the ta.highest and ta.lowest functions over a user-defined swing_length period.
Swing highs are treated as resistance levels.
Swing lows are treated as support levels.
Buy Signal:
A buy signal is generated when the price closes above the resistance level (ta.crossover(close, swing_high)).
Sell Signal:
A sell signal is generated when the price closes below the support level (ta.crossunder(close, swing_low)).
Plotting:
Support and resistance levels are plotted on the chart.
Buy and sell signals are displayed as labels on the chart.
Background Highlighting:
The background is highlighted in green for buy signals and red for sell signals (optional).
Médias Móveis
IB & Hammer at SMA(20,50|200)IB & Hammer at SMA (20, 50, 200) Breakout/Breakdown Indicator
Overview:
The IB (Inside Bar) & Hammer at SMA Breakout/Breakdown Indicator is designed to identify breakout and breakdown opportunities using Inside Bars (IB) in combination with Simple Moving Averages (SMA 20, 50, 200) as key trend filters. This indicator is useful for traders looking to catch momentum moves after consolidation phases, confirming the trend direction with moving averages.
Indicator Logic:
Inside Bar (IB) Detection:
An Inside Bar is a candlestick that is completely within the range of the previous candle (i.e., lower high and higher low).
Inside Bars indicate consolidation, suggesting a potential breakout.
SMA Trend Confirmation:
The script uses three moving averages (SMA 20, 50, 200) to determine the trend direction.
Bullish trend: Price is above the 50 & 200 SMAs.
Bearish trend: Price is below the 50 & 200 SMAs.
The 20 SMA is used as a dynamic short-term momentum filter.
Breakout & Breakdown Conditions:
Breakout: When price breaks above the Inside Bar’s high, and the trend is bullish (above key SMAs).
Breakdown: When price breaks below the Inside Bar’s low, and the trend is bearish (below key SMAs).
Alerts can be set to notify traders of potential trade opportunities.
Features:
✅ Identifies Inside Bars (consolidation zones).
✅ Uses SMA (20, 50, 200) for trend confirmation.
✅ Breakout/Breakdown signals based on Inside Bar structure.
✅ Customizable Moving Averages & Alerts.
✅ Visual markers for easy trade identification.
How to Use:
Confirm Trend Direction:
If the price is above SMA 50 & 200, look for breakout trades.
If the price is below SMA 50 & 200, look for breakdown trades.
Watch for Inside Bars:
The script highlights Inside Bars with a specific color (configurable).
These bars indicate a low-volatility phase, preparing for a breakout.
Trade on Breakout/Breakdown:
Breakout: Enter long when the price breaks above the Inside Bar’s high (bullish trend).
Breakdown: Enter short when the price breaks below the Inside Bar’s low (bearish trend).
MTF Ichimoku Conversion Line SMA with H/L mirrored levelsWelcome to MTF Ichimoku Conversion Line with SMA Highs/Lows Extended Lines!
1. Overview
It is designed to provide a multi-timeframe view of market trends and potential support/resistance levels by obtaining a Simple Moving Average (SMA) of the Conversion Line of Ichimoku Equibilium (Ichimoku Kinko-Hyo), which acts as a substantial trend line on the candlestick chart. The SMA of the conversion line smooths out price fluctuations and indicates the overall trend direction—if the candles are above it, the trend can be read as an uptrend, while below it, the trend can be read as a downtrend.
2. Calculation
The indicator first calculates the Conversion Line (see the description of Ichimoku theory anywhere, e.g., Wikipedia), as the average of the highest high and lowest low over a user-defined period (Conversion Line Length, default is 9, also recommended is 9).
It then retrieves this Conversion Line from a higher timeframe (MTF Timeframe) to add a broader perspective. Using a specified period (SMA Length)., an SMA is computed on this multi-timeframe conversion line. This SMA serves as a trend line that visually represents the prevailing price trend, making it easier to assess market direction.
3. Pivot Highs/low detection and drawing their extensions
In addition, the indicator identifies pivot highs and lows from the SMA data using a defined pivot length. When these pivots occur, horizontal lines are drawn and extended across the chart. These extended lines (drawn in a yellowish color by default) include a full extension, a half extension, and a middle extension line representing the midpoint between the high and low pivot.
4. Mirror lines
The indicator also offers optional mirror line features. When the Mirror Upside option is enabled, five additional lines are drawn above the highest extended yellow line at equal intervals. Similarly, when the Mirror Downside option is enabled, five lines are drawn below the lowest extended yellow line. These light gray mirror lines serve as extra reference levels, which can help identify potential support or resistance zones.
5. Parameters
User parameters include:
- Conversion Line Length: The period used to calculate the conversion line.
- MTF Timeframe: The higher timeframe from which the conversion line is obtained.
- SMA Length: The period over which the SMA is calculated on the conversion line.
- SMA Mode: A toggle to display either the SMA or the raw conversion line (SMA recommended).
- SMA Line Width: The thickness of the SMA line.
- Pivot Length for SMA Highs/Lows: The period used to detect pivot highs and lows in the SMA.
- Horizontal Extension: Number of bars by which the pivot and extended lines are drawn across the chart
- Colors for High and Low Pivot Lines and Extended Lines: Customizable colors are used to draw the lines.
Mirror Upside and Mirror Downside: These options enable drawing additional mirror lines above and below the extended lines.
- Hide Old Lines: An option to hide previous pivot lines once new ones are drawn for a cleaner chart. Turned on by default.
6. Conclusion
Overall, the Conversion Line SMA in this indicator smooths out the conversion line data and effectively functions as a trend line for the candlestick chart, helping traders visually interpret the underlying market trend. The extended and mirror lines provide further context for potential price reversal or continuation areas, making this a powerful tool for multi-timeframe technical analysis.
Market Phase MAMarket Phase MA is an advanced trend-following indicator designed to provide traders with a dynamically colored moving average that adapts to market conditions. It uses a powerful combination of Average True Range (ATR) and Average Directional Index (ADX) to classify market trends in real-time. The indicator integrates a fully customizable moving average (SMA or EMA) to highlight trend phases clearly and effectively.
Key Features & Advantages:
✔ Adaptive Trend Classification: Detects uptrends, downtrends, and sideways markets using a refined mix of ATR and ADX for more precise trend identification.
✔ Color-Coded Moving Average: The moving average dynamically changes color based on trend classification, providing a clean visual representation of market sentiment.
✔ Advanced ATR & ADX Filtering:
- ATR measures market volatility and identifies ranging periods.
- ADX confirms trend strength, reducing false signals.
- A weighted approach balances ATR and ADX, ensuring reliability.
✔ Fully Customizable Moving Average: Traders can select between SMA and EMA while adjusting the moving average length directly from the settings panel.
✔ Smooth & Responsive Adjustments: The smoothing factor can be fine-tuned to control signal sensitivity and noise reduction, making it suitable for scalping, swing trading, and long-term trend monitoring.
What Makes It Unique:
- Unlike traditional trend indicators, Market Phase MA provides **direct visual feedback** on a moving average rather than using a separate oscillator.
- It **adapts dynamically** to market conditions instead of relying on fixed thresholds.
- The combination of **volatility and trend strength analysis** enhances precision in identifying valid trends.
- Users can optimize **reaction speed vs. reliability** with adjustable parameters for better decision-making.
How to Use It:
- Identify Market Phases: The moving average color shifts based on trend type—**teal** for uptrends, **red** for downtrends, and **gray** for sideways markets.
- Confirm Trend Strength: Persistent color shifts indicate strong trends, while frequent changes may suggest market indecision.
- Use as a Trade Confirmation Tool: Complement it with **support & resistance zones, price action analysis, and volume indicators** for stronger confirmation signals.
Market Phase MA is designed for traders seeking a clear, efficient, and highly adaptable moving average trend detection system. Whether you are a day trader, swing trader, or long-term investor, this indicator will help you identify and follow trends with confidence.
Smoothed Low-Pass Butterworth Filtered Median [AlphaAlgos]Smoothed Low-Pass Butterworth Filtered Median
This indicator is designed to smooth price action and filter out noise while maintaining the dominant trend. By combining a Butterworth low-pass filter with a median-based smoothing approach , it effectively reduces short-term fluctuations, allowing traders to focus on the true market direction.
How It Works
Median Smoothing: The indicator calculates the 50th percentile (median) of closing prices over a customizable period , making it more robust against outliers compared to traditional moving averages.
Butterworth Filtering: A low-pass filter is applied using an approximation of the Butterworth formula , controlled by the Cutoff Frequency , helping to eliminate high-frequency noise while preserving trends.
EMA Refinement: A 7-period EMA is applied to further smooth the signal, providing a more reliable trend representation.
Features
Trend Smoothing: Reduces market noise and highlights the dominant trend.
Dynamic Color Signals: The EMA line changes color to indicate trend strength and direction.
Configurable Parameters: Customize the median length, cutoff frequency, and EMA length to fit your strategy.
Versatile Use Case: Suitable for both trend-following and mean-reversion strategies.
How to Use
Bullish Signal: When the EMA is below the price and rising , indicating upward momentum.
Bearish Signal: When the EMA is above the price and falling , signaling a potential downtrend.
Reversal Zones: Monitor for trend shifts when the color of the EMA changes.
This indicator provides a clear, noise-free view of market trends , making it ideal for traders seeking improved trend identification and entry signals .
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
Combo Gama Exposure + EMA + SMA 1.0Gamma Exposure (GEX) for the CBOE Volatility Index ( TVC:VIX ) is an estimate of how much option sellers need to hedge for every 1% change in the underlying asset's price. It's also known as Gamma Levels.
How is GEX calculated?
GEX is calculated based on a 1% move of the underlying security
It's calculated and updated throughout the day
It's based on market positioning and open interest
These regions are important because they show the regions where players can act more aggressively to defend their positions. When inserting the indicator on the chart, a popup will open requesting the GEX levels (Put wall, Vix Call Wall 0DTE, etc.)
In addition, 3 moving averages will be inserted into the chart. A 9-period exponential moving average, a 20-period arithmetic moving average, and a 200-period arithmetic moving average. These moving averages aim to indicate the possible trend of the asset, where pullbacks in these averages can signal a possible entry in favor of the trend.
Moneyball EMA-MACD indicator [VinnieTheFish]Summary of the Moneyball EMA-MACD Indicator Script
Author: VinnieTheFish
Purpose:
This indicator helps traders identify trend direction, momentum shifts, and potential trade signals based on EMA and MACD crossovers.
This Pine Script is a custom indicator that combines Exponential Moving Averages (EMAs) and MACD (Moving Average Convergence Divergence) to analyze price trends and momentum. The script uses a custom 9/50 MACD with a 16 smoothing period. The script is written in a way that you can create your own custom MACD settings and create alerts based on those parameters. The chart bars are color coded based on the relative position of the MACD and Signal line primarily for bullish long trade setups.
Bar color coding helps the trader spot potential reversals based on where the price currently resides in relation to the custom 9/50 EMA based MACD and the 16 period smoothing period for the signal line. Indicator also has custom alerts to notify the trader when a potential trade setup exists that correspond with the bar color change.
Question: So why is this called the Moneywell EMA-MACD Indicator?
Answer: In the movie Moneyball the Oakland A's broke down how to win a championship based on data. To make the playoffs you needed so many wins, then broken down by runs and then broken down to base hits. A base hit was good as a walk. With trading often times we look too often for home runs and ignore the importance of getting on base with small wins. This indicator was designed on shorter timeframes to identify those base hits, but can also be adapted to higher timeframes for swing trading.
Key Features:
User Inputs:
Configurable fast and slow lengths for MACD calculation.
Choice between SMA and EMA for oscillator and signal line smoothing.
Customizable signal smoothing length.
EMA Calculation:
Computes 3 EMA, 9 EMA, 20 EMA, and 50 EMA to track short-term and long-term trends.
MACD Calculation:
Computes MACD using either SMA or EMA based on user selection.
Generates the MACD signal line for comparison.
Crossover Conditions:
Detects MACD and Signal line crossovers above and below the zero line.
Identifies price momentum shifts.
Bar Coloring Logic:
Green: MACD is above 0 and above the signal line.
White: MACD is below the signal line.
Orange: MACD is below 0 but above the signal line.
Fuchsia: Bullish EMA 3/9 cross but price is still below the 20/50 EMA.
Alerts for Key Trading Signals:
MACD crossing above/below the zero line.
Signal line crossing above/below the zero line.
MACD reaching new highs/lows.
Alerts for colored bar conditions.
SNR Quarter Pointsfor btmm swingers
this is qp /quater point find in trading view
Here's a description for your TradingView Pine Script indicator:
---
**Support & Resistance (SNR) Lines Indicator**
This TradingView indicator automatically draws Support and Resistance (SNR) lines on the chart at every 250-pip level, starting from 0.0000. The indicator aims to help traders identify key price levels where the market is likely to experience reversal or consolidation. By plotting lines at regular intervals, the script provides a clear visual representation of potential support and resistance zones, aiding traders in making more informed trading decisions. The levels are dynamically adjusted based on market price movement, ensuring they stay relevant for active trading.
---
Let me know if you’d like to tweak it further!
EMA/SMA Ribbon Pro (AUTO HTF + Labels)This indicator is a multi-timeframe (MTF) moving average ribbon that dynamically adjusts to the next highest timeframe. It provides a visual representation of market trends by stacking multiple EMAs and SMAs with customizable color fills and labels.
Features
✅ Multi-Timeframe (MTF) Support: Automatically detects the next highest time frame or allows for manual selection
✅ Customizable Moving Averages: Supports EMA and SMA with different lengths for flexible configuration
✅ Ribbon Visualization: Smooth color transitions between different moving averages for better trend identification
✅ Crossover Labels: Detects bullish and bearish EMA/SMA crossovers and marks them on the chart
✅ Price Labels & Timeframe Display: Displays moving average values to the right of the price axis with customizable label padding and colors
How It Works
Select the HTF mode: Manual or automatic
Choose EMA/SMA lengths to create different ribbons
Enable/disable price labels for each moving average
Customize colors and transparency for ribbons and labels
Crossover labels appear when faster moving averages cross slower ones and vice versa
Use Cases
📌 Trend Identification: Identify bullish and bearish trends using multiple EMAs and SMAs
📌 Support & Resistance Zones: MAs can act as dynamic support and resistance levels
📌 Reversal & Confirmation Signals: Watch for MTF crossovers to confirm trend changes
Customization
🔹 Standard EMA Lengths: 6, 8, 13, 21, 34, 48, 100, 200, 300, 400
🔹 SMA Lengths: 48, 100, 200
🔹 Color Adjustments: Set custom colors for bullish/bearish ribbons
🔹 Crossovers: Enable/disable custom crossover pairs (e.g., 100/200 EMA, 200 EMA/SMA).
This indicator is perfect for traders who rely on multi-timeframe confluence while seeking to enhance their market analysis and decision-making process.
As always, by combining EMA/SMA Ribbon with other tools, traders ensure that they are not relying on a single indicator. This layered approach can reduce the likelihood of false signals and improve overall trading accuracy.
As always, be sure to use any indicator with price action and volume indicators for better trade confirmation!
EMA Ribbon overlay with Trend-Based Color TransitionThis indicator visualizes an EMA Ribbon with a trend-based color transition. It helps traders quickly identify market trends and transitions between bullish and bearish movements.
How It Works
Exponential Moving Averages (EMAs)
The indicator calculates 8 EMAs based on user-defined lengths.
Default values range from 21 to 55 periods.
Trend Identification
A bullish trend is detected when all EMAs are stacked in an upward sequence (shorter EMAs above longer ones).
A bearish trend is detected when all EMAs are stacked in a downward sequence (shorter EMAs below longer ones).
Trend Reversal Detection
A trend shift to bullish occurs when a previously bearish trend turns bullish.
A trend shift to bearish occurs when a previously bullish trend turns bearish.
Color Transition Logic
Green when transitioning from a bearish to bullish trend.
Red when transitioning from a bullish to bearish trend.
Visualization
EMAs are plotted on the chart.
The area between EMAs is filled with green or red, depending on the trend shift.
Use Case
Identifying Trend Shifts: Traders can use color transitions to detect potential entry and exit points.
Confirming Market Direction: Helps confirm bullish and bearish trends before making trading decisions.
Enhanced Visual Clarity: The ribbon structure makes it easy to see trend momentum and potential reversals.
This indicator is useful for trend-following strategies and can be combined with other technical analysis tools for better decision-making. 🚀
Monthly Cummulated Moving Average (MCMA)A specialized moving average indicator that helps identify statistically advantageous trading opportunities based on price position relative to the MCMA line.
📊 Key Statistical Edge
The core strength of this indicator lies in its ability to identify higher probability trades:
Trades taken when price is above MCMA historically show higher win rates
Monthly calculations provide a robust baseline for trend identification
Daily updates allow for precise entry timing while maintaining monthly context
🎯 Trading Applications
Long Entry Filter:
Wait for price to trade above MCMA before considering long positions
Use as a primary filter to avoid lower probability setups
Combines daily precision with monthly trend context
Risk Management:
MCMA serves as a dynamic invalidation level
Consider closing longs when price falls below MCMA
Use as a trailing reference for position management
📈 Implementation
Calculates on daily bars for precision
Resets monthly for trend context
Plots a single line that serves as a statistical reference
Simple yet effective design focused on practical trading application
💡 Best Practices
Focus on long setups when price is trading above MCMA
Combine with volume analysis for confirmation
Pay attention to how price interacts with the MCMA line
Use alongside your existing strategy as a statistical filter
🔧 Technical Details
Built in Pine Script™ v5
Updates daily for maximum precision
Maintains monthly context for trend alignment
Optimized for computational efficiency
Cognitive Echo IndexCognitive Echo Index – User Guide
Overview
The Cognitive Echo Index is a composite indicator that combines several technical aspects—including price deviation from a moving average, normalized volatility (via ATR), and volume variations—to create a single numeric value. The output is scaled between -100 and +100, offering insights into market momentum and potential trend reversals.
How It Works
Price Component:
The indicator calculates the percentage change between the current price and its 14-period simple moving average (SMA). This helps identify how far the price deviates from its recent trend.
Volatility Component:
Using the Average True Range (ATR) over a 14-period, the script normalizes current ATR against its 14-period SMA. This shows relative volatility, highlighting unusual market activity.
Volume Component:
It computes the percentage change between the current volume and its 14-period SMA to detect spikes or drops in trading activity.
Composite Calculation:
The three components are summed together to produce the final index value, which is then clipped to remain between -100 and +100.
Interpreting the Indicator
Indicator Value Scale:
Positive Values (0 to +100):
Suggest that bullish forces are stronger. Higher values (e.g., above +50) could indicate a strong bullish sentiment.
Negative Values (0 to -100):
Indicate bearish pressures. Lower values (e.g., below -50) may signal strong bearish conditions.
Zero Level:
The midline indicates a balanced market condition with no dominant trend.
Key Horizontal Levels:
+50 Level:
When the indicator crosses above +50, it can be interpreted as a strong bullish signal.
-50 Level:
When the indicator crosses below -50, it can be considered a strong bearish signal.
Usage Tips
Confirmation Tool:
Use the Cognitive Echo Index as an additional confirmation tool in conjunction with other technical indicators or chart patterns to make more informed trading decisions.
Parameter Adjustments:
The script uses a 14-period setting for the moving average, ATR, and volume SMA by default. Depending on your trading timeframe or asset, consider tweaking these periods for better sensitivity.
Trend Analysis:
Watch how the indicator behaves during major price moves. A divergence between the index and the price trend (e.g., price rises while the index falls) may suggest a potential reversal or a false breakout.
Risk Management:
Always incorporate sound risk management practices. Use stop losses and position sizing rules, and consider the indicator as one part of your overall trading strategy.
Customization
Adjusting the Weights:
Although the current version gives equal weight to all three components, advanced users can modify the script to apply different weights to the price, volatility, and volume components based on historical performance or specific market conditions.
Adding Additional Inputs:
Future versions could incorporate external sentiment data or other technical factors if accessible. For now, the indicator focuses on technical inputs available directly within TradingView.
By following this guide, traders can integrate the Cognitive Echo Index into their TradingView platform to gain a unique perspective on market momentum and potential turning points. Enjoy testing and refining the indicator to better suit your trading style!
BTC Future Gamma-Weighted Momentum Model (BGMM)The BTC Future Gamma-Weighted Momentum Model (BGMM) is a quantitative trading strategy that utilizes the Gamma-weighted average price (GWAP) in conjunction with a momentum-based approach to predict price movements in the Bitcoin futures market. The model combines the concept of weighted price movements with trend identification, where the Gamma factor amplifies the weight assigned to recent prices. It leverages the idea that historical price trends and weighting mechanisms can be utilized to forecast future price behavior.
Theoretical Background:
1. Momentum in Financial Markets:
Momentum is a well-established concept in financial market theory, referring to the tendency of assets to continue moving in the same direction after initiating a trend. Any observed market return over a given time period is likely to continue in the same direction, a phenomenon known as the “momentum effect.” Deviations from a mean or trend provide potential trading opportunities, particularly in highly volatile assets like Bitcoin.
Numerous empirical studies have demonstrated that momentum strategies, based on price movements, especially those correlating long-term and short-term trends, can yield significant returns (Jegadeesh & Titman, 1993). Given Bitcoin’s volatile nature, it is an ideal candidate for momentum-based strategies.
2. Gamma-Weighted Price Strategies:
Gamma weighting is an advanced method of applying weights to price data, where past price movements are weighted by a Gamma factor. This weighting allows for the reinforcement or reduction of the influence of historical prices based on an exponential function. The Gamma factor (ranging from 0.5 to 1.5) controls how much emphasis is placed on recent data: a value closer to 1 applies an even weighting across periods, while a value closer to 0 diminishes the influence of past prices.
Gamma-based models are used in financial analysis and modeling to enhance a model’s adaptability to changing market dynamics. This weighting mechanism is particularly advantageous in volatile markets such as Bitcoin futures, as it facilitates quick adaptation to changing market conditions (Black-Scholes, 1973).
Strategy Mechanism:
The BTC Future Gamma-Weighted Momentum Model (BGMM) utilizes an adaptive weighting strategy, where the Bitcoin futures prices are weighted according to the Gamma factor to calculate the Gamma-Weighted Average Price (GWAP). The GWAP is derived as a weighted average of prices over a specific number of periods, with more weight assigned to recent periods. The calculated GWAP serves as a reference value, and trading decisions are based on whether the current market price is above or below this level.
1. Long Position Conditions:
A long position is initiated when the Bitcoin price is above the GWAP and a positive price movement is observed over the last three periods. This indicates that an upward trend is in place, and the market is likely to continue in the direction of the momentum.
2. Short Position Conditions:
A short position is initiated when the Bitcoin price is below the GWAP and a negative price movement is observed over the last three periods. This suggests that a downtrend is occurring, and a continuation of the negative price movement is expected.
Backtesting and Application to Bitcoin Futures:
The model has been tested exclusively on the Bitcoin futures market due to Bitcoin’s high volatility and strong trend behavior. These characteristics make the market particularly suitable for momentum strategies, as strong upward or downward movements are often followed by persistent trends that can be captured by a momentum-based approach.
Backtests of the BGMM on the Bitcoin futures market indicate that the model achieves above-average returns during periods of strong momentum, especially when the Gamma factor is optimized to suit the specific dynamics of the Bitcoin market. The high volatility of Bitcoin, combined with adaptive weighting, allows the model to respond quickly to price changes and maximize trading opportunities.
Scientific Citations and Sources:
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637–654.
• Fama, E. F., & French, K. R. (1992). The Cross-Section of Expected Stock Returns. The Journal of Finance, 47(2), 427–465.
GWAP (Gamma Weighted Average Price)Gamma Weighted Average Price (GWAP) Indicator
The Gamma Weighted Average Price (GWAP) is a dynamic financial indicator that applies exponentially decaying weights to historical prices to calculate a weighted average. The method leverages the exponential decay function, controlled by a gamma factor, to prioritize recent price data while gradually diminishing the influence of older observations. This approach builds upon techniques commonly found in time-series analysis, including Exponentially Weighted Moving Averages (EWMA), which are extensively used in financial modeling (Campbell, Lo & MacKinlay, 1997).
Theoretical Context and Justification
The gamma-weighted approach follows principles similar to those in Exponentially Weighted Moving Averages (EWMA), often used in volatility modeling, where weights decay exponentially over time. The exponential decay model can improve signal responsiveness compared to simple moving averages (Hyndman & Athanasopoulos, 2018). This design helps capture recent market dynamics without ignoring past trends, a common requirement in high-frequency trading systems (Bandi & Russell, 2006).
Practical Applications
1. Trend Detection:
The GWAP can help identify bullish and bearish trends:
• When the price is above GWAP, the market exhibits bullish momentum.
• Conversely, when the price is below GWAP, bearish momentum prevails.
2. Volatility Filtering:
Because of the gamma weighting mechanism, GWAP reduces the noise commonly seen in volatile markets, making it a useful tool for traders looking to smooth price fluctuations while retaining actionable signals.
3. Crossovers for Trade Signals:
Similar to moving average strategies, traders can use price crossovers with the GWAP as trade signals:
• Buy Signal: When the price crosses above the GWAP.
• Sell Signal: When the price crosses below the GWAP.
4. Adaptive Gamma Weighting:
The gamma factor allows for further customization.
• Higher gamma values (>1) place greater emphasis on older data, suitable for long-term trend analysis.
• Lower gamma values (<1) heavily weight recent price movements, ideal for fast-moving markets.
Example Use Case
A trader analyzing the S&P 500 may use a gamma factor of 0.92 with a 14-period GWAP to detect shifts in market sentiment during periods of heightened volatility. When the index price crosses above the GWAP, this could signal a potential recovery, prompting a buy entry. Conversely, when the price moves below the GWAP during a correction, it may suggest a short-selling opportunity.
Scientific References
• Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets. Princeton University Press.
• Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice. OTexts.
• Bandi, F. M., & Russell, J. R. (2006). Microstructure Noise, Realized Variance, and Optimal Sampling. Econometrica.
Sma Indicator with Ratio (pr)SMA Indicator with Ratio (PR) is a technical analysis tool designed to provide insights into the relationship between multiple Simple Moving Averages (SMAs) across different time frames. This indicator combines three key SMAs: the 111-period SMA, 730-period SMA, and 1400-period SMA. Additionally, it introduces a ratio-based approach, where the 730-period SMA is multiplied by factors of 2, 3, 4, and 5, allowing users to analyze potential market trends and price movements in relation to different SMA levels.
What Does This Indicator Do?
The primary function of this indicator is to track the movement of prices in relation to several SMAs with varying periods. By visualizing these SMAs, users can quickly identify:
Short-term trends (111-period SMA)
Medium-term trends (730-period SMA)
Long-term trends (1400-period SMA)
Additionally, the multiplied versions of the 730-period SMA provide deeper insights into potential price reactions at different levels of market volatility.
How Does It Work?
The 111-period SMA tracks the shorter-term price trend and can be used for identifying quick market movements.
The 730-period SMA represents a longer-term trend, helping users gauge overall market sentiment and direction.
The 1400-period SMA acts as a very long-term trend line, giving users a broad perspective on the market’s movement.
The ratio-based SMAs (2x, 3x, 4x, 5x of the 730-period SMA) allow for an enhanced understanding of how the price reacts to higher or lower volatility levels. These ratios are useful for identifying key support and resistance zones in a dynamic market environment.
Why Use This Indicator?
This indicator is useful for traders and analysts who want to track the interaction of price with different moving averages, enabling them to make more informed decisions about potential trend reversals or continuations. The added ratio-based values enhance the ability to predict how the market might react at different levels.
How to Use It?
Trend Confirmation: Traders can use the indicator to confirm the direction of the market. If the price is above the 111, 730, or 1400-period SMA, it may indicate an uptrend, and if below, a downtrend.
Support/Resistance Levels: The multiplied versions of the 730-period SMA (2x, 3x, 4x, 5x) can be used as dynamic support or resistance levels. When the price approaches or crosses these levels, it might indicate a change in the trend.
Volatility Insights: By observing how the price behaves relative to these SMAs, traders can gauge market volatility. Higher multiples of the 730-period SMA can signal more volatile periods where price movements are more pronounced.
Engulfing Pattern with Volume and EMAs
**Strategy Overview:
This strategy combines price action (Engulfing patterns), volume analysis, trend confirmation (EMAs), and noise reduction (ATR filter) to generate high-probability trading signals.
Engulfing Pattern with Volume, EMAs, and Market Noise Filter**
This strategy identifies bullish and bearish Engulfing candlestick patterns, combined with volume analysis, moving averages (EMAs), and a market noise filter to generate trading signals.
**Key Components:**
1. **Engulfing Pattern Detection:**
- **Bullish Engulfing**: A green candle completely engulfs the previous red candle.
- **Bearish Engulfing**: A red candle completely engulfs the previous green candle.
2. **Volume Filter:**
- Signals are validated only if the current volume is higher than the 20-period Simple Moving Average (SMA) of volume.
3. **EMA Indicators:**
- Three EMAs are plotted: 50-period (blue), 89-period (orange), and 200-period (red).
- These EMAs help identify the trend direction and provide additional confirmation.
4. **Market Noise Filter:**
- Uses the Average True Range (ATR) to filter out insignificant price movements.
- A signal is considered valid only if the price movement (absolute difference between open and close) is greater than 0.5 times the 14-period ATR.
**Trading Signals:**
**Buy Signal**:
- Bullish Engulfing pattern + High volume (above SMA 20) + Significant price movement (filtered by ATR).
- Plotted as a green "BUY" label below the candle.
**Sell Signal**:
- Bearish Engulfing pattern + High volume (above SMA 20) + Significant price movement (filtered by ATR).
- Plotted as a red "SELL" label above the candle.
**Customization:**
- Users can adjust EMA lengths, volume SMA period, and ATR multiplier to suit their trading preferences.
EMA CROSS v1.0 by ScorpioneroIndicator Description: Multi-Timeframe SMA Table & Plot
This indicator displays a structured table of Simple Moving Averages (SMA) across multiple timeframes and plots them directly on the chart for better trend analysis.
Features:
✅ Multi-Timeframe SMA Calculation: Computes SMAs for different periods (10, 60, and 223) across six timeframes (1m, 3m, 5m, 15m, 30m, 60m).
✅ Sorted SMA Table: Displays a table in the bottom-right corner of the chart, showing the three SMAs per timeframe, sorted in descending order.
✅ Color-Coded Cells: Each SMA is highlighted with a specific color:
🟡 Yellow → 10-period SMA
🔵 Blue → 60-period SMA
🟣 Purple → 223-period SMA
⚪ Gray → Other values
✅ SMA Plotting on the Chart: All calculated SMAs are plotted directly on the price chart, allowing users to visualize their interaction with price movements.
How to Use:
The table provides a quick overview of SMA rankings across timeframes, helping identify bullish or bearish trends.
The SMA plots on the chart can be used for dynamic support/resistance analysis and trend confirmation.
This indicator is ideal for traders who rely on multi-timeframe trend analysis to make informed trading decisions! 🚀
by Scorpionero
ORB with 100 EMAORB Trading Strategy for FX Pairs on the 30-Minute Time Frame
Overview
This Opening Range Breakout (ORB) strategy is designed for trading FX pairs on the 30-minute time frame. The strategy is structured to take advantage of price momentum while aligning trades with the overall trend using the 100-period Exponential Moving Average (100EMA). The primary objective is to enter trades when price breaks and closes above or below the Opening Range (OR), with additional confirmation from a retest of the OR level if the initial entry is missed.
Strategy Rules
1. Defining the Opening Range (OR)
- The OR is determined by the high and low of the first 30-minute candle after market open.
- This range acts as the key level for breakout trading.
2. Trend Confirmation Using the 100EMA
- The 100EMA serves as a filter to determine trade direction:
- Buy Setup: Only take buy trades when the OR is above the 100EMA.
- Sell Setup: Only take sell trades when the OR is below the 100EMA.
3. Entry Criteria
- Buy Trade: Enter a long position when a candle breaks and closes above the OR high, confirming the breakout.
- Sell Trade: Enter a short position when a candle breaks and closes below the OR low, confirming the breakout.
- Retest Entry: If the initial entry is missed, wait for a price retest of the OR level for a secondary entry opportunity.
4. Risk-to-Reward Ratio (R2R)
- The goal is to target a 1:1 Risk-to-Reward (R2R) ratio.
- Stop-loss placement:
- Buy Trade: Place stop-loss just below the OR low.
- Sell Trade: Place stop-loss just above the OR high.
- Take profit at a distance equal to the stop-loss for a 1:1 R2R.
5. Risk Management
- Risk per trade should be based on personal risk tolerance.
- Adjust lot sizes accordingly to maintain a controlled risk percentage of account balance.
- Avoid over-leveraging, and consider moving stop-loss to breakeven if the price moves favourably.
Additional Considerations
- Avoid trading during major news events that may cause high volatility and unpredictable price movements.
- Monitor market conditions to ensure breakout confirmation with strong momentum rather than false breakouts.
- Use additional confluences such as candlestick patterns, support/resistance zones, or volume analysis for stronger trade validation.
This ORB strategy is designed to provide structured trade opportunities by combining breakout momentum with trend confirmation via the 100EMA. The strategy is straightforward, allowing traders to capitalise on clear breakout movements while implementing effective risk management practices. While the 1:1 R2R target provides a balanced approach, traders should always adapt their risk tolerance and market conditions to optimise trade performance.
By following these rules and maintaining discipline, traders can use this strategy effectively across various FX pairs on the 30-minute time frame.
Position resetThe "Position Reset" indicator
The Position Reset indicator is a sophisticated technical analysis tool designed to identify possible entry points into short positions based on an analysis of market volatility and the behavior of various groups of bidders. The main purpose of this indicator is to provide traders with information about the current state of the market and help them decide whether to open short positions depending on the level of volatility and the mood of the main players.
The main components of the indicator:
1. Parameters for the RSI (Relative Strength Index):
The indicator uses two sets of parameters to calculate the RSI: one for bankers ("Banker"), the other for hot money ("Hot Money").
RSI for Bankers:
RSIBaseBanker: The baseline for calculating bankers' RSI. The default value is 50.
RSIPeriodBanker: The period for calculating the RSI for bankers. The default period is 14.
RSI for hot money:
RSIBaseHotMoney: The baseline for calculating the RSI of hot money. The default value is 30.
RSIPeriodHotMoney: The period for calculating the RSI for hot money. The default period is 21.
These parameters allow you to adjust the sensitivity of the indicator to the actions of different groups of market participants.
2. Sensitivity:
Sensitivity determines how strongly changes in the RSI will affect the final result of calculations. It is configured separately for bankers and hot money:
SensitivityBanker: Sensitivity for bankers' RSI. It is set to 2.0 by default.
SensitivityHotMoney: Sensitivity for hot money RSI. It is set to 1.0 by default.
Changing these parameters allows you to adapt the indicator to different market conditions and trader preferences.
3. Volatility Analysis:
Volatility is measured based on the length of the period, which is set by the volLength parameter. The default length is 30 candles. The indicator calculates the difference between the highest and lowest value for the specified period and divides this difference by the lowest value, thus obtaining the volatility coefficient.
Based on this coefficient, four levels of volatility are distinguished.:
Extreme volatility: The coefficient is greater than or equal to 0.25.
High volatility: The coefficient ranges from 0.125 to 0.2499.
Normal volatility: The coefficient ranges from 0.05 to 0.1249.
Low volatility: The coefficient is less than 0.0499.
Each level of volatility has its own significance for making decisions about entering a position.
4. Calculation functions:
The indicator uses several functions to process the RSI and volatility data.:
rsi_function: This function applies to every type of RSI (bankers and hot money). It adjusts the RSI value according to the set sensitivity and baseline, limiting the range of values from 0 to 20.
Moving Averages: Simple moving averages (SMA), exponential moving averages (EMA), and weighted moving averages (RMA) are used to smooth fluctuations. They are applied to different time intervals to obtain the average values of the RSI.
Thus, the indicator creates a comprehensive picture of market behavior, taking into account both short-term and long-term dynamics.
5. Bearish signals:
Bearish signals are considered situations when the RSI crosses certain levels simultaneously with a drop in indicators for both types of market participants (bankers and hot money).:
The bankers' RSI crossing is below the level of 8.5.
The current hot money RSI is less than 18.
The moving averages for banks and hot money are below their signal lines.
The RSI values for bankers are less than 5.
These conditions indicate a possible beginning of a downtrend.
6. Signal generation:
Depending on the current level of volatility and the presence of bearish signals, the indicator generates three types of signals:
Orange circle: Extremely high volatility and the presence of a bearish signal.
Yellow circle: High volatility and the presence of a bearish signal.
Green circle: Low volatility and the presence of a bearish signal.
These visual markers help the trader to quickly understand what level of risk accompanies each specific signal.
7. Notifications:
The indicator supports the function of sending notifications when one of the three types of signals occurs. The notification contains a brief description of the conditions under which the signal was generated, which allows the trader to respond promptly to a change in the market situation.
Advantages of using the "Position Reset" indicator:
Multi-level analysis: The indicator combines technical analysis (RSI) and volatility assessment, providing a comprehensive view of the current market situation.
Flexibility of settings: The ability to adjust the sensitivity parameters and the RSI baselines allows you to adapt the indicator to any market conditions and personal preferences of the trader.
Clear visualization: The use of colored labels on the chart simplifies the perception of information and helps to quickly identify key points for entering a trade.
Notification support: The notification sending feature makes it much easier to monitor the market, allowing you to respond to important events in time.
KEMAD | QuantumResearchQuantumResearch KEMAD Indicator
The QuantumResearch KEMAD Indicator is a sophisticated trend-following and volatility-based tool designed for traders who demand precision in detecting market trends and price reversals. By leveraging advanced techniques implemented in PineScript, this indicator integrates a Kalman filter, an Exponential Moving Average (EMA), and dynamic ATR-based deviation bands to produce clear, actionable trading signals.
1. Overview
The KEMAD Indicator aims to:
Reduce Market Noise: Employ a Kalman filter to smooth price data.
Identify Trends: Use an EMA of the filtered price to define the prevailing market direction.
Set Dynamic Thresholds: Adjust breakout levels with ATR-based deviation bands.
Generate Signals: Provide clear long and short trading signals along with intuitive visual cues.
2. How It Works
A. Kalman Filter Smoothing
Purpose: The Kalman filter refines the selected price source (e.g., close price) by reducing short-term fluctuations, thus offering a clearer view of the underlying price movement.
Customization: Users can adjust key parameters such as:
Process Noise: Controls the filter’s sensitivity to recent changes.
Measurement Noise: Determines how responsive the filter is to incoming price data.
Filter Order: Sets the number of data points considered in the smoothing process.
B. EMA-Based Trend Detection
Primary Trend EMA: A 25-period EMA is applied to the Kalman-filtered price, serving as the core trend indicator.
Signal Mechanism:
Long Signal: Triggered when the price exceeds the EMA plus an ATR-based upper deviation.
Short Signal: Triggered when the price falls below the EMA minus an ATR-based lower deviation.
C. ATR Deviation Bands
ATR Utilization: The Average True Range (ATR) is computed (default length of 21) to assess market volatility.
Dynamic Thresholds:
Upper Deviation: Calculated by adding 1.5× ATR to the EMA (for long signals).
Lower Deviation: Calculated by subtracting 1.1× ATR from the EMA (for short signals).
These bands adapt to current volatility, ensuring that signal thresholds are both dynamic and market-sensitive.
3. Visual Representation
The indicator’s design emphasizes clarity and ease of use:
Color-Coded Bar Signals:
Green Bars: Indicate bullish conditions when a long signal is active.
Red Bars: Indicate bearish conditions when a short signal is active.
Trend Confirmation Line: A 54-period EMA is plotted to further validate trend direction. Its color dynamically changes to reflect the active trend.
Background Fill: The space between a calculated price midpoint (typically the average of high and low) and the EMA is filled, visually emphasizing the prevailing market trend.
4. Customization & Parameters
The KEMAD Indicator is highly configurable, allowing traders to tailor the tool to their specific trading strategies and market conditions:
ATR Settings:
ATR Length: Default is 21; adjusts sensitivity to market volatility.
EMA Settings:
Trend EMA Length: Default is 25; smooths price action for trend detection.
Confirmation EMA Length: Default is 54; aids in confirming the trend.
Kalman Filter Parameters:
Process Noise: Default is 0.01.
Measurement Noise: Default is 3.0.
Filter Order: Default is 5.
Deviation Multipliers:
Long Signal Multiplier: Default is 1.5× ATR.
Short Signal Multiplier: Default is 1.1× ATR.
Appearance: Eight customizable color themes are available to suit individual visual preferences.
5. Trading Applications
The versatility of the KEMAD Indicator makes it suitable for various trading strategies:
Trend Following: It helps identify and ride sustained bullish or bearish trends by filtering out market noise.
Breakout Trading: Detects when prices move beyond the ATR-based deviation bands, signaling potential breakout opportunities.
Reversal Detection: Alerts traders to potential trend reversals when price crosses the dynamically smoothed EMA.
Risk Management: Offers clearly defined entry and exit points, based on volatility-adjusted thresholds, enhancing trade precision and risk control.
6. Final Thoughts
The QuantumResearch KEMAD Indicator represents a unique blend of advanced filtering (via the Kalman filter), robust trend analysis (using EMAs), and dynamic volatility assessment (through ATR deviation bands).
Its PineScript implementation allows for a high degree of customization, making it an invaluable tool for traders looking to reduce noise, accurately detect trends, and manage risk effectively.
Whether used for trend following, breakout strategies, or reversal detection, the KEMAD Indicator is designed to adapt to varying market conditions and trading styles.
Important Disclaimer: Past data does not predict future behavior. This indicator is provided for informational purposes only; no indicator or strategy can guarantee future results. Always perform thorough analysis and use proper risk management before trading.
End-of-Session ProbabilityThis indicator estimates the probability that the market will finish the session above a specified target price. It blends a statistical probability model with directional bias and optional morning momentum weighting to help traders gauge end-of-day market expectations.
Key Features:
• Statistical Probability Model:
Uses a normal distribution (with a custom normal CDF approximation) scaled by the square-root-of-time rule. The indicator dynamically adjusts the standard deviation for the remaining session time to compute a z‑score and ultimately the probability that the session close exceeds the target.
• Directional Bias via Daily HullMA (Exponential):
A daily Hull Moving Average (calculated using an exponential method) is used as a big-picture trend indicator. The model allows you to select your bias method—either by comparing the current price to the daily HullMA (Price method) or by using the HullMA’s slope (Slope method). A drift multiplier scales this bias, which then shifts the mean used in the probability calculations.
• Optional Morning Momentum Weight:
For traders who believe that early session moves provide useful clues about the day’s momentum, you can enable an optional weighting. The indicator captures the percentage change from the morning open (within a user-defined time window) and adjusts the expected move accordingly. A multiplier lets you control the strength of this adjustment.
• Visual Outputs:
The indicator plots quantile lines (approximately the 25%, 50%, and 75% levels) for the expected price distribution at session end. An abbreviated on-chart label displays key information:
• Target: The target price (current price plus a user-defined offset)
• Prob Above: The probability (in percentage) that the session close will exceed the target price
• Time: The time remaining in the session (in minutes)
How to Use:
1. Set Your Parameters:
• Expected Session Move: Input your estimated standard deviation for the full-session move in price units.
• Daily Hull MA Settings: Adjust the period for the daily HullMA and choose the bias method (Price or Slope). Modify the drift multiplier to tune the strength of the directional bias.
• Target Offset: Specify an offset from the current price to set your target level.
• Morning Momentum (Optional): Enable the morning momentum weight if you want the indicator to adjust the expected move based on early session price changes. Define the morning session window and set the momentum multiplier.
2. Interpret the Output:
• Quantile Lines: These represent the range of possible end-of-session prices based on your model.
• Abbreviated Label: Provides a quick snapshot of the target price, probability of finishing above that target, and time remaining in the session.
3. Trading Application:
Use the probability output as a guide to assess if the market is likely to continue in the current direction or reverse by session close. The indicator can help you decide on trade entries, exits, or adjustments based on your overall strategy and risk management approach.
This tool is designed to offer a dynamic, statistically driven snapshot of the market’s expected end-of-day behavior, combining both longer-term trend bias and short-term momentum cues.
Custom Length Moving AverageThe Custom Length Moving Average is a dynamic indicator that allows traders to plot a moving average with an adjustable length based on their preferred number of days. Users can choose between Simple Moving Average (SMA), Exponential Moving Average (EMA), or Weighted Moving Average (WMA) to match their trading strategy. The script automatically calculates the moving average length by factoring in the chart’s timeframe and trading session duration, ensuring precision and adaptability. This makes it an ideal tool for traders looking for a flexible moving average that adjusts to different market conditions and timeframes.
