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. 🚀
Скользящие средние
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.
VMA [Extreme Advanced Custom Table for BTCUSD]This indicator implements a Variable Moving Average (VMA) with a 33-period length—selected in homage to the Tesla 369 concept—to dynamically adjust to market conditions. It not only calculates the adaptive VMA but also displays a custom table of key metrics directly on the chart. Here’s how to use it:
Apply to Your Chart:
Add the indicator to your chart (optimized for BTCUSD, though it can be used on other symbols) and choose your desired source (e.g., close).
Customize Your Visuals:
Trend & Price Lines: Toggle the trend colors, price line, and bar coloring based on the VMA’s direction.
Channels & Slope: Enable the volatility channel and slope line to visualize market volatility and the VMA’s momentum.
Pivot Points & Super VMA: Activate pivot high/low markers for potential reversal points and a Super VMA (SMA of VMA) for an extra smoothing layer.
Table Customization: Adjust the table’s position, colors, and font sizes as needed for your viewing preference.
Monitor Key Metrics:
The dynamic table displays essential information:
VMA Value & Trend: See the current VMA and whether the trend is Bullish, Bearish, or Neutral.
Volatility Index (vI) & Slope: Quickly assess market volatility and the VMA’s slope (both absolute and percentage).
Price-VMA Difference & Correlation: Evaluate how far the price is from the VMA and its correlation.
Higher Timeframe VMA: Compare the current VMA with its higher timeframe counterpart (set via the “Higher Timeframe” input).
Alerts for Key Conditions:
Built-in alert conditions notify you when:
The trend changes (bullish/bearish).
The VMA slope becomes extreme.
The price and VMA correlation falls below a defined threshold.
The VMA crosses its higher timeframe average.
How to Use the Script:
Add to Your Chart:
Open TradingView and apply the indicator to your BTCUSD (or any other) chart.
The indicator will overlay on your chart, plotting the VMA along with optional elements such as the price line, volatility channels, and higher timeframe VMA.
Customize Your Settings:
Inputs:
Choose your data source (e.g., close price).
Adjust the VMA length (default is 33) if desired.
Visual Options:
Toggle trend colors, bar coloring, and additional visuals (price line, volatility channels, slope line, pivot points, and Super VMA) to suit your trading style.
Table Customization:
Set the table position, colors, border width, and font size to ensure key metrics are easily visible.
Higher Timeframe:
You can change the higher timeframe input (default is Daily) to better fit your analysis routine.
Interpret the Indicator:
Trend Analysis:
Watch the color-coded VMA line. A rising (orange) VMA suggests bullish momentum, while a falling (red) one indicates bearish conditions.
What Sets This Script Apart:
Dynamic Adaptation:
Unlike a fixed-period moving average, the VMA adjusts its sensitivity in real time by integrating a volatility measure, making it more adaptive to market swings.
Multi-Layered Analysis:
With integrated volatility channels, pivot points, slope analysis, and a higher timeframe VMA, this tool gives you a fuller picture of market dynamics.
Immediate Data at a Glance:
The real-time table consolidates multiple key metrics into one view, saving time and reducing the need for additional indicators.
Custom Alerts:
Pre-built alert conditions allow for timely notifications, ensuring you don’t miss critical market changes.
Pivot Breakouts with MA FilterPivot Breakouts with MA Filter
This script identifies pivot breakouts (both bullish and bearish) using support and resistance levels and overlays breakout labels, arrows, and customizable Moving Averages. It allows traders to fine-tune their analysis with multiple options to customize the display and behavior of the breakout signals.
Key Features:
Pivot Support and Resistance:
Support is defined by the lowest low in a given range (using the lookback period).
Resistance is defined by the highest high in a given range (using the lookback period).
The script draws support and resistance boxes on the chart when these levels change, providing clear visual markers for potential breakout areas.
Breakout Detection:
Bullish Breakout: A breakout above resistance and the price is above the selected moving average (MA).
Bearish Breakout: A breakdown below support and the price is below the selected MA.
Breakout events trigger labels indicating "Resistance Breakout" (for bullish) and "Support Breakout" (for bearish).
The option to show Breakout Labels (with customizable colors) is available in the settings.
Moving Average Filter:
You can select the type of moving average (SMA or EMA) to use for filtering breakout signals.
MA Filter Length: This input allows you to set the period of the moving average to act as a filter for breakout conditions. This helps ensure the breakout aligns with the broader trend.
Multiple Moving Averages (Optional):
You can add up to four different moving averages (SMA or EMA), each with its own length and color.
You have the option to toggle each moving average on or off and adjust their appearance settings (color and length).
The script supports dynamic plots for each moving average, helping to visualize multiple trends at once.
Breakout Arrows:
The script can display arrows (or other shapes) below the bar for bullish breakouts and above the bar for bearish breakouts.
Arrows are optional and can be turned on/off in the settings.
You can customize the shape of the arrows (e.g., arrow, circle, square, or even a large or small triangle).
Customizable Colors and Labels:
The color of the breakout labels and arrows can be customized in the settings to make them fit your chart's style and personal preferences.
Alerts:
Alerts can be set for new support and resistance levels, as well as when breakouts occur (either bullish or bearish).
The alert system helps to notify traders when significant price action takes place without needing to constantly monitor the chart.
Settings:
Select Moving Average Type (SMA or EMA)
MA Filter Length: Length of the moving average used for filtering breakout conditions.
Lookback Range: Determines the range over which the pivot points (support and resistance) are calculated.
Breakout Labels: Option to turn on/off breakout labels, and customize label colors.
Show Breakout Arrows: Enable or disable breakout arrows with shape options (arrow, circle, square, large triangle, small triangle).
Multiple Moving Averages: Option to show up to 4 MAs with customizable colors and lengths.
Scalping Tool with Dynamic Take Profit & Stop Loss### **Scalping Indicator: Summary and User Guide**
The **Scalping Indicator** is a powerful tool designed for traders who focus on short-term price movements. It combines **Exponential Moving Averages (EMA)** for trend identification and **Average True Range (ATR)** for dynamic stop loss and take profit levels. The indicator is highly customizable, allowing traders to adapt it to their specific trading style and risk tolerance.
---
### **Key Features**
1. **Trend Identification**:
- Uses two EMAs (Fast and Slow) to identify trend direction.
- Generates **Buy Signals** when the Fast EMA crosses above the Slow EMA.
- Generates **Sell Signals** when the Fast EMA crosses below the Slow EMA.
2. **Dynamic Take Profit (TP) and Stop Loss (SL)**:
- **Take Profit (TP)**:
- TP levels are calculated as a percentage above (for long trades) or below (for short trades) the entry price.
- TP levels are **dynamically recalculated** when the price reaches the initial target, allowing for multiple TP levels during a single trade.
- **Stop Loss (SL)**:
- SL levels are calculated using the ATR multiplier, providing a volatility-based buffer to protect against adverse price movements.
3. **Separate Settings for Long and Short Trades**:
- Users can independently enable/disable and configure TP and SL for **Buy** and **Sell** orders.
- This flexibility ensures that the indicator can be tailored to different market conditions and trading strategies.
4. **Visual Signals and Levels**:
- **Buy/Sell Signals**: Clearly marked on the chart with labels ("BUY" or "SELL").
- **TP and SL Levels**: Plotted on the chart for both long and short trades, making it easy to visualize risk and reward.
---
### **How to Use the Scalping Indicator**
#### **1. Setting Up the Indicator**
- Apply the indicator to your chart in TradingView.
- Configure the input parameters based on your trading preferences:
- **Fast Length**: The period for the Fast EMA (default: 5).
- **Slow Length**: The period for the Slow EMA (default: 13).
- **ATR Length**: The period for the ATR calculation (default: 14).
- **Buy/Sell TP and SL**: Enable/disable and set the percentage or ATR multiplier for TP and SL levels.
#### **2. Interpreting the Signals**
- **Buy Signal**:
- When the Fast EMA crosses above the Slow EMA, a "BUY" label appears below the price bar.
- The TP and SL levels for the long trade are plotted on the chart.
- **Sell Signal**:
- When the Fast EMA crosses below the Slow EMA, a "SELL" label appears above the price bar.
- The TP and SL levels for the short trade are plotted on the chart.
#### **3. Managing Trades**
- **Take Profit (TP)**:
- When the price reaches the initial TP level, the indicator automatically recalculates the next TP level based on the new close price.
- This allows traders to capture additional profits as the trend continues.
- **Stop Loss (SL)**:
- The SL level is based on the ATR multiplier, providing a dynamic buffer against market volatility.
- If the price hits the SL level, the trade is considered closed, and the indicator resets.
#### **4. Customization**
- Adjust the **Fast Length** and **Slow Length** to suit your trading timeframe (e.g., shorter lengths for scalping, longer lengths for swing trading).
- Modify the **ATR Multiplier** and **TP Percentage** to align with your risk-reward ratio.
- Enable/disable TP and SL for long and short trades based on your trading strategy.
---
### **Tips for Getting the Best Results**
1. **Combine with Price Action**:
- Use the Scalping Indicator in conjunction with support/resistance levels, candlestick patterns, or other technical analysis tools to confirm signals.
2. **Optimize for Your Timeframe**:
- For **scalping**, use shorter EMA lengths (e.g., Fast: 5, Slow: 13).
- For **swing trading**, use longer EMA lengths (e.g., Fast: 10, Slow: 20).
3. **Adjust Risk Management**:
- Use a smaller **ATR Multiplier** for tighter stop losses in low-volatility markets.
- Increase the **TP Percentage** to allow for larger price movements in high-volatility markets.
4. **Backtest and Practice**:
- Test the indicator on historical data to understand its performance in different market conditions.
- Use a demo account to practice trading with the indicator before applying it to live trading.
---
### **Conclusion**
The **Scalping Indicator** is a versatile and user-friendly tool for traders who want to capitalize on short-term price movements. By combining trend-following EMAs with dynamic TP and SL levels, it provides a clear and systematic approach to trading. Whether you're a scalper or a swing trader, this indicator can help you identify high-probability setups and manage risk effectively. Customize it to fit your strategy, and always remember to combine it with sound risk management principles for the best results.
AE - ATR Exhaustion ChannelAE - ATR Exhaustion Channel
📈 Overview
Identify Exhaustion Zones & Trend Breakouts with ATR Precision!
The AE - ATR Exhaustion Channel is a powerful volatility-based trading tool that combines an averaged SMA with ATR bands to dynamically highlight potential trend exhaustion zones. It provides real-time breakout detection by marking when price moves beyond key volatility bands, helping traders spot overextensions and reversals with ease.
🔑 Key Features
✔️ ATR-SMA Hybrid Channel: Uses an averaged SMA as the core trend filter while incorporating adaptive ATR-based bands for precise volatility tracking.
✔️ Dynamic Exhaustion Markers: Marks red crosses when price exceeds the upper band and green crosses when price drops below the lower band.
✔️ Customizable ATR Sensitivity: Adjust the ATR multiplier and length settings to fine-tune band sensitivity based on market conditions.
✔️ Clear Channel Visualization: A gray SMA midpoint and a blue-filled ATR band zone make it easy to track market structure.
📚 How It Works
1️⃣ Averaged SMA Calculation: The script calculates an averaged SMA over a user-defined range (min/max period). This smooths out short-term fluctuations while preserving trend direction.
2️⃣ ATR Band Construction: The ATR value (adjusted by a multiplier) is added to/subtracted from the SMA to form dynamic upper and lower volatility bands.
3️⃣ Exhaustion Detection:
If high > upper ATR band, a red cross is plotted (potential overextension).
If low < lower ATR band, a green cross is plotted (potential reversal zone).
4️⃣ Filled ATR Channel: The area between the upper and lower bands is shaded blue, providing a visual trading range.
🎨 Customization & Settings
⚙️ ATR Length – Adjusts the ATR calculation period (default: 14).
⚙️ ATR Multiplier – Scales the ATR bands for tighter or wider volatility tracking (default: 0.8, adjustable in 0.1 steps).
⚙️ SMA Range (Min/Max Length) – Defines the period range for calculating the averaged SMA (default: 5-20).
⚙️ Rolling Lookback Length – Controls how far back the high/low comparison is calculated (default: 50 bars).
🚀 Practical Usage
📌 Spotting Exhaustion Zones – Look for red/green markers appearing outside the ATR bands, signaling potential trend exhaustion and possible reversal opportunities.
📌 Breakout Confirmation – Price consistently breaching the upper band with momentum could indicate continuation, while repeated touches without strong closes may hint at reversal zones.
📌 Trend Reversal Signals – Watch for green markers below the lower band in uptrends (buy signals) and red markers above the upper band in downtrends (sell signals).
🔔 Alerts & Notifications
📢 Set Alerts for Exhaustion Signals!
Traders can configure alerts to trigger when price breaches the ATR bands, allowing for instant notifications when volatility-based exhaustion is detected.
📊 Example Scenarios
✔ Trend Exhaustion in Overextended Moves – A series of red crosses near resistance may indicate a short opportunity.
✔ Trend Exhaustion in Overextended Moves – A series of red crosses near resistance may indicate an opportunity to open a short trade.
✔ Volatility Compression Breakouts – If price consolidates within the ATR bands and suddenly breaks out, it could signify a momentum shift.
✔ Reversal Catching in Trending Markets – Spot potential trend reversals by looking for green markers below the ATR bands in bullish markets.
🌟 Why Choose AE - ATR Exhaustion Channel?
Trade with Confidence. Spot Volatility. Catch Breakouts.
The AE - ATR Exhaustion Channel is an essential tool for traders looking to identify trend exhaustion, detect breakouts, and manage volatility effectively. Whether you're trading stocks, crypto, or forex, this ATR-SMA hybrid system provides clear visual cues to help you stay ahead of market moves.
✅ Customizable to Fit Any Market
✅ Combines Volatility & Trend Analysis
✅ Easy-to-Use with Instant Breakout Detection
Opening ScoreOverview:
The Composite Open Strategy Indicator is designed to provide traders with a unified, early-session directional bias by aggregating multiple non-correlated signals. By combining diverse analytical methods—spanning price action, volume, volatility, and time—the indicator helps you gauge whether the market is leaning bullish or bearish during the critical opening hours.
How It Works:
• Open Range Breakout (ORB) Signal:
The indicator captures the opening range (defined up to a user-specified time, e.g., 9:45 AM ET) and assigns a bullish signal when the price breaks above the high of that range, and a bearish signal when it drops below the low.
• VWAP Signal:
It compares the current price to the Volume Weighted Average Price (VWAP). A price above VWAP suggests buying pressure, while below indicates selling pressure.
• Trend Signal:
Using a simple moving average (with an adjustable period, typically around 20 bars), the indicator determines the prevailing trend. Price above the MA contributes a bullish bias, and price below contributes a bearish bias.
• Volatility Signal:
A volatility filter is applied via the Average True Range (ATR). An increasing ATR relative to the previous bar suggests rising volatility (bullish if combined with upward moves), whereas a decreasing ATR indicates the opposite.
Each of these four signals is assigned an equal weight (modifiable as needed), and their sum forms the composite score.
Display and Timing:
• Separate Panel:
The composite score is plotted as a histogram in its own indicator panel, ensuring your main price chart remains uncluttered.
• Session Filter:
The indicator is active only during the early session—from 9:30 AM to 12:30 PM Eastern Time—when the initial directional move is most relevant. Outside this time window, the indicator remains inactive.
Trading Insights:
• A positive composite score suggests a bullish bias, indicating that the aggregated signals lean toward an upward trend.
• A negative composite score points to a bearish bias, indicating a downward directional outlook.
Usage:
Ideal for traders looking to capture the market’s early trend direction, this indicator can be used as part of a broader strategy. Its design encourages consistency by combining multiple perspectives (price, volume, volatility, time) into one clear signal, allowing you to focus on setups that align with the dominant early-session move.
Before fully automating your trading approach, you can test and refine this composite method on TradingView using the built-in manual review process. Once confident in its performance, further automation can help integrate this directional bias seamlessly into your overall trading strategy.
Dynamic RSI Bollinger Bands with Waldo Cloud
TradingView Indicator Description: Dynamic RSI Bollinger Bands with Waldo Cloud
Title: Dynamic RSI Bollinger Bands with Waldo Cloud
Short Title: Dynamic RSI BB Waldo
Overview:
Introducing an experimental indicator, the Dynamic RSI Bollinger Bands with Waldo Cloud, designed for adventurous traders looking to explore new dimensions in technical analysis. This indicator overlays on your chart, providing a unique perspective by integrating the Relative Strength Index (RSI) with Bollinger Bands, creating a dynamic trading tool that adapts to market conditions through the lens of momentum and volatility.
What is it?
This innovative indicator combines the traditional Bollinger Bands with the RSI in a way that hasn't been commonly explored. Here's a breakdown:
RSI Integration: The RSI is calculated with customizable length settings, and its values are used not just for momentum analysis but as the basis for the Bollinger Bands. This means the position and width of the bands are directly influenced by the RSI, offering a visual representation of momentum within the context of price volatility.
Dynamic Bollinger Bands: Instead of using price directly, the Bollinger Bands are calculated using a scaled version of the RSI. This scaling is done to fit the RSI values into the price range, ensuring the bands are relevant to the actual price movement. The standard deviation for these bands is also scaled accordingly, providing a unique volatility measure that's momentum-driven.
Waldo Cloud: Named after a visual representation concept, the 'Waldo Cloud' refers to the colored area between the Bollinger Bands, which changes based on various conditions:
Purple when RSI is overbought.
Blue when RSI is oversold.
Green for bullish conditions, defined by the fast-moving average crossing above the slow one, RSI is bullish, and the price is above the slow MA.
Red for bearish conditions, when the fast MA crosses below the slow MA, the RSI is bearish, and the price is below the slow MA.
Gray for neutral market conditions.
Moving Averages: Two simple moving averages (Fast MA and Slow MA) are included, which can be toggled on or off, offering additional trend analysis through crossovers.
How to Use It:
Given its experimental nature, this indicator should be used with caution and in conjunction with other analysis methods:
Identifying Market Conditions: Use the color of the Waldo Cloud to gauge market sentiment. A green cloud might suggest a good time to consider long positions, while a red cloud could indicate potential shorting opportunities. Purple and blue clouds highlight extreme conditions that might precede reversals.
Volatility and Momentum: The dynamic nature of the Bollinger Bands based on RSI provides insight into how momentum is affecting price volatility. When the bands are wide, it might indicate high momentum and potential trend continuation or reversal, depending on the RSI's position relative to its overbought/oversold levels.
Trend Confirmation: The moving average crossovers can act as confirmation signals. For instance, a bullish crossover (fast MA over slow MA) within a green cloud might strengthen a buy signal, whereas a bearish crossover in a red cloud might reinforce a sell decision.
Customization: Adjust the RSI length, overbought/oversold levels, and moving average lengths to suit different trading styles or market conditions. Experiment with these settings to find what works best for your strategy.
Combining with Other Indicators: Since this is an experimental tool, it's advisable to use it alongside established indicators like traditional Bollinger Bands, MACD, or trend lines to validate signals.
Conclusion:
The Dynamic RSI Bollinger Bands with Waldo Cloud is an experimental venture into combining momentum with volatility visually and interactively. It's designed for traders who are open to exploring new methods of market analysis.
Remember, due to its experimental status, this indicator should be part of a broader trading strategy, and backtesting or paper trading is recommended before applying it in live trading scenarios. Keep an eye on how the market reacts to the signals provided by this indicator and always consider risk management practices.
Waldo Cloud Bollinger Bands
Waldo Cloud Bollinger Bands Indicator Description for TradingView
Title: Waldo Cloud Bollinger Bands
Short Title: Waldo Cloud BB
Overview:
The Waldo Cloud Bollinger Bands indicator is a sophisticated tool designed for traders looking to combine the volatility analysis of Bollinger Bands with the momentum insights of the Relative Strength Index (RSI) and moving average crossovers. This indicator overlays on your chart, providing a visual representation that helps in identifying potential trading opportunities based on price action, momentum, and trend direction.
Concept:
This indicator merges three key technical analysis concepts:
Bollinger Bands: These are used to measure market volatility. The bands consist of a central moving average (basis) with an upper and lower band that are standard deviations away from this average. In this indicator, you can customize the type of moving average used for the basis (SMA, EMA, SMMA, WMA, VWMA), the length of the period, the source price, and the standard deviation multiplier, offering flexibility to adapt to different market conditions.
Relative Strength Index (RSI): The RSI is incorporated to provide insight into the momentum of price movements. Users can adjust the RSI length and overbought/oversold levels and even choose the price source for RSI calculation, allowing for tailored momentum analysis. The RSI values influence the cloud color between the Bollinger Bands, signaling market conditions.
Moving Average Crossovers: Two moving averages with customizable lengths and types are used to identify trend direction through crossovers. A fast MA (default 20 periods) and a slow MA (default 50 periods) are plotted when enabled, helping to signal potential bullish or bearish market conditions when they cross over each other.
Functionality:
Bollinger Bands Calculation: The basis of the Bollinger Bands is calculated using a user-defined moving average type, with a customizable length, source, and standard deviation multiplier. The upper and lower bands are then plotted around this basis.
RSI Calculation: The RSI is computed using a user-specified source, length, and overbought/oversold levels. This RSI value is used to determine the color of the cloud between the Bollinger Bands, which visually represents market sentiment:
Purple when RSI is overbought.
Blue when RSI is oversold.
Green for bullish conditions (when the fast MA crosses above the slow MA, RSI is bullish, and the price is above the slow MA).
Red for bearish conditions (when the fast MA crosses below the slow MA, RSI is bearish, and the price is below the slow MA).
Gray for neutral conditions.
Trend Analysis: The indicator uses two moving averages to help determine the trend direction.
When the fast MA crosses over the slow MA, it suggests a potential change in trend direction, which, combined with RSI conditions, provides a more comprehensive trading signal.
Customization:
Users can select the type of moving average for all calculations through the "Global MA Type" setting, ensuring consistency in how trends and volatility are interpreted.
The Bollinger Bands settings allow for adjustments in length, source, standard deviation, and offset, giving traders control over how volatility is measured.
RSI settings include the ability to change the RSI source, length, and overbought/oversold thresholds, which can be fine-tuned to match trading strategies.
The option to show or hide moving averages provides clarity on the chart, focusing on either the Bollinger Bands or including the MA crossovers for trend analysis.
Usage:
This indicator is ideal for traders who incorporate both volatility and momentum in their trading decisions.
By observing the color changes in the cloud, along with the position of the price relative to the moving averages, traders can gauge potential entry and exit points.
For instance, a green cloud with a price above the slow MA might suggest a strong buying opportunity, while a red cloud with a price below might indicate selling pressure.
Conclusion:
The Waldo Cloud Bollinger Bands indicator offers a unique blend of volatility, momentum, and trend analysis, providing traders with a multi-faceted view of market conditions. Its customization options make it adaptable to various trading styles and market environments, making it a valuable addition to any trader's toolkit on Trading View.
Moving Averages With Continuous Periods [macp]This script reimagines traditional moving averages by introducing floating-point period calculations, allowing for fractional lengths rather than being constrained to whole numbers. At its core, it provides SMA, WMA, and HMA variants that can work with any decimal length, which proves especially valuable when creating dynamic indicators or fine-tuning existing strategies.
The most significant improvement lies in the Hull Moving Average implementation. By properly handling floating-point mathematics throughout the calculation chain, this version reduces the overshoot tendencies that often plague integer-based HMAs. The result is a more responsive yet controlled indicator that better captures price action without excessive whipsaw.
The visual aspect incorporates a trend gradient system that can adapt to different trading styles. Rather than using fixed coloring, it offers several modes ranging from simple solid colors to more nuanced three-tone gradients that help identify trend transitions. These gradients are normalized against ATR to provide context-aware visual feedback about trend strength.
From a practical standpoint, the floating-point approach eliminates the subtle discontinuities that occur when integer-based moving averages switch periods. This makes the indicator particularly useful in systems where the MA period itself is calculated from market conditions, as it can smoothly transition between different lengths without artificial jumps.
At the heart of this implementation lies the concept of continuous weights rather than discrete summation. Traditional moving averages treat each period as a distinct unit with integer indexing. However, when we move to floating-point periods, we need to consider how fractional periods should behave. This leads us to some interesting mathematical considerations.
Consider the Weighted Moving Average kernel. The weight function is fundamentally a slope: -x + length where x represents the position in the averaging window. The normalization constant is calculated by integrating (in our discrete case, summing) this slope across the window. What makes this implementation special is how it handles the fractional component - when the length isn't a whole number, the final period gets weighted proportionally to its fractional part.
For the Hull Moving Average, the mathematics become particularly intriguing. The standard HMA formula HMA = WMA(2*WMA(price, n/2) - WMA(price, n), sqrt(n)) is preserved, but now each WMA calculation operates in continuous space. This creates a smoother cascade of weights that better preserves the original intent of the Hull design - to reduce lag while maintaining smoothness.
The Simple Moving Average's treatment of fractional periods is perhaps the most elegant. For a length like 9.7, it weights the first 9 periods fully and the 10th period at 0.7 of its value. This creates a natural transition between integer periods that traditional implementations miss entirely.
The Gradient Mathematics
The trend gradient system employs normalized angular calculations to determine color transitions. By taking the arctangent of price changes normalized by ATR, we create a bounded space between 0 and 1 that represents trend intensity. The formula (arctan(Δprice/ATR) + 90°)/180° maps trend angles to this normalized space, allowing for smooth color transitions that respect market volatility context.
This mathematical framework creates a more theoretically sound foundation for moving averages, one that better reflects the continuous nature of price movement in financial markets. The implementation recognizes that time in markets isn't truly discrete - our sampling might be, but the underlying process we're trying to measure is continuous. By allowing for fractional periods, we're creating a better approximation of this continuous reality.
This floating-point moving average implementation offers tangible benefits for traders and analysts who need precise control over their indicators. The ability to fine-tune periods and create smooth transitions makes it particularly valuable for automated systems where moving average lengths are dynamically calculated from market conditions. The Hull Moving Average calculation now accurately reflects its mathematical formula while maintaining responsiveness, making it a practical choice for both systematic and discretionary trading approaches. Whether you're building dynamic indicators, optimizing existing strategies, or simply want more precise control over your moving averages, this implementation provides the mathematical foundation to do so effectively.
EMA Crossover Backtest [BarScripts]This indicator lets you backtest an EMA crossover strategy with built-in risk management and trade tracking. It simulates long and short trades based on EMA crossovers, allowing you to fine-tune entry conditions, stop-loss placement, and reward/risk settings.
🔹 How It Works:
Long Entry: Fast EMA crosses above Slow EMA, and price closes above Fast EMA.
Short Entry: Fast EMA crosses below Slow EMA, and price closes below Fast EMA.
Stop Loss: Set based on previous bars or a fixed amount.
Take Profit: Adjustable reward/risk ratio.
Higher Timeframe Confluence: Confirms trades based on a larger timeframe.
Trade Hours Filter: Limits trades to specific time windows.
🔹 Key Features:
✅ Shows Entry & Exit Points with visual trade lines.
✅ Customizable EMA Lengths to fit any strategy.
✅ P&L Tracking & Statistics to measure performance.
✅ Position Sizing Options: Fixed position, fixed risk, or percentage of balance.
✅ Commissions Tracking (based on total trades, not contracts).
Use this tool to fine-tune your EMA crossover strategy and see how it performs over time! 🚀
💬 Let me know your feedback—suggest improvements, report issues, or request new features!
BullDozz MA-CandlesticksBullDozz MA-Candlesticks 🏗️📊
The BullDozz MA-Candlesticks indicator transforms traditional candlesticks by replacing their Open, High, Low, and Close values with various types of Moving Averages (MAs). This helps traders visualize market trends with smoother price action, reducing noise and enhancing decision-making.
🔹 Features:
✅ Choose from multiple MA types: SMA, EMA, WMA, DEMA, TEMA, LSMA
✅ Customizable MA period for flexibility
✅ Candlestick colors based on trend: Green for bullish, Red for bearish
✅ Works on any market and timeframe
This indicator is perfect for traders who want a clearer perspective on price movement using moving average-based candlesticks. 🚀 Try it now and refine your market analysis! 📈🔥
