Signals Pro [traderslog]The "Signals Pro" indicator is an advanced and versatile trading tool designed to help traders accurately identify key buy and sell signals using a combination of technical analysis factors such as candle patterns , RSI (Relative Strength Index) , and candle stability . It is highly customizable and offers a range of options that make it suitable for both short-term and long-term traders. By filtering market noise and providing actionable insights, this indicator enhances decision-making and helps traders capitalize on market movements.
At the core of the "Signals Pro" indicator is the concept of Candle Stability . The Candle Stability Index measures the ratio between a candle's body and its wicks, providing insight into the strength of the price movement during that period. A higher value indicates that the candle is more stable, meaning that the price has moved significantly without much retracement. This stability filter is crucial because it prevents the generation of signals during volatile or choppy market conditions where price direction is uncertain. Traders can adjust the Candle Stability Index from 0 to 1, allowing for precise control over how stable a candle must be for the indicator to generate a signal.
Another key feature is the use of RSI (Relative Strength Index) , a momentum oscillator that measures the speed and change of price movements. The RSI index parameter in the indicator can be customized to detect overbought or oversold conditions. When the RSI falls below the defined threshold, it signals that the market may be oversold , which can indicate a potential buying opportunity . Conversely, when the RSI exceeds a certain value, it suggests that the market is overbought , signaling a potential selling opportunity . This allows traders to time their trades more effectively by entering when market conditions are favorable and exiting before a potential reversal occurs.
The Candle Delta Length is another critical element of the "Signals Pro" indicator. This parameter measures how much the price has increased or decreased over a specific number of candles. By adjusting the Candle Delta Length , traders can define how many periods the indicator should analyze before generating a signal. A longer Candle Delta Length means the price has been trending in one direction for a longer period, providing more reliable signals. For instance, if the price has been steadily decreasing for five candles, this could signal a bullish reversal , triggering a buy signal .
To further enhance its accuracy, the "Signals Pro" indicator includes a unique feature that allows traders to disable repeating signals . This is particularly useful in situations where the market is moving sideways or during low volatility periods, where multiple signals may cluster close together, creating confusion. By enabling the disable repeating signals option, traders can prevent these repeated signals and focus on the most important and confirmed signals, ensuring cleaner charts and reducing the risk of overtrading.
A key technical aspect of the indicator is its ability to detect bullish and bearish engulfing patterns . The indicator looks for bullish engulfing patterns, which occur when a bullish candle fully engulfs the body of the previous bearish candle, signaling a potential bullish reversal . Conversely, bearish engulfing patterns occur when a bearish candle fully engulfs the previous bullish candle, indicating a bearish reversal . By incorporating these candle patterns with the Candle Stability Index and RSI levels , the indicator provides highly reliable signals based on price action and market sentiment.
Visual customization is another major advantage of the "Signals Pro" indicator. Traders can choose from several different label styles , such as text bubbles , triangles , or arrows to mark the buy and sell signals on the chart. This makes the signals stand out and easy to interpret at a glance. Furthermore, the color of these signals can be customized: green for buy signals and red for sell signals , along with options to adjust the text size and label styles for even more personalization. Traders can make the signals more or less prominent based on their preference, enhancing readability and workflow efficiency.
The indicator also includes a comprehensive alert system , ensuring traders never miss an opportunity. Alerts can be set for both buy and sell signals , and the system triggers in real-time when a valid signal is generated. This is especially useful for active traders who want to stay on top of the markets without constantly monitoring their screens. The alert system helps ensure that traders are notified of potential trading opportunities as soon as they arise, allowing them to act quickly in volatile markets.
From a practical standpoint, the "Signals Pro" indicator is designed to work seamlessly across multiple timeframes, making it suitable for scalpers, day traders, swing traders, and even long-term investors. Its flexibility allows it to adapt to different trading styles and time horizons, providing value for a wide range of market participants.
In summary, the Signals Pro indicator offers a robust and customizable solution for identifying buy and sell signals . By combining candle stability , RSI analysis , and engulfing patterns , the indicator provides traders with reliable signals to enter or exit trades. The ability to customize signal appearance, coupled with a real-time alert system , makes the "Signals Pro" indicator an invaluable tool for traders looking to improve their timing and decision-making. Whether you are looking to capture short-term price movements or want to time entries and exits in longer-term trends, this indicator offers the insights needed to navigate the markets with confidence.
M-oscillator
Aroon Oscillator [BigBeluga]Aroon Oscillator with Mean Reversion & Trend Signals is a versatile tool that helps traders identify both trend direction and potential mean reversion points. The core Aroon Oscillator tracks the strength of a trend by measuring how long it has been since a high or low price occurred within a specified period. This oscillator provides trend-following signals (LONG/SHORT) along with mean reversion signals, giving traders both the ability to ride trends and anticipate reversals.
The unique feature of this indicator is the Mean Reversion Signals, marked with dots on the main chart, indicating potential points where the trend might reverse or retrace. In addition, trend-following signals (LONG and SHORT) are plotted directly on the chart, providing clear entry and exit points when a trend is beginning or ending.
🔵 IDEA
The Aroon Oscillator with Mean Reversion indicator provides a combined approach of trend analysis and mean reversion. The core idea is to track the health and momentum of trends, while also identifying when those trends might reverse or slow down. This dual approach allows traders to both follow the prevailing market direction and also capture mean reversion opportunities.
The oscillator is smoothed with John Ehlers' Zero Lag function , which helps reduce noise and improves signal clarity by removing lag without sacrificing the indicator's responsiveness.
The indicator uses color-coded signals and an easy-to-read oscillator to visually represent different types of signals on the chart. This makes it easy for traders to spot important changes in market trends and take action based on both the trend-following and mean reversion aspects of the indicator.
🔵 KEY FEATURES & USAGE
Trend Following Signals (LONG/SHORT):
In addition to mean reversion signals, the indicator also provides clear trend-following signals. LONG signals (green arrows) are plotted when the oscillator crosses above zero, indicating a potential uptrend. Conversely, SHORT signals (blue arrows) are plotted when the oscillator crosses below zero, signaling a potential downtrend.
Mean Reversion Signals:
This indicator features unique mean reversion signals, represented by dots on the main chart. These signals occur when the oscillator crosses over or under a smoother signal line, indicating that the current trend might be losing strength and a reversal or retracement is possible. Green dots represent a possible upward reversion, while blue dots signal a potential downward reversion.
Color-Coded Signals and Oscillator:
The Aroon Oscillator is color-coded to make it visually easier for traders to differentiate between trends and mean reversion signals. When the oscillator is above zero, the area is filled with green, and when it is below zero, the area is filled with blue. This visual representation helps traders quickly identify the current market condition at a glance.
🔵 CUSTOMIZATION
Aroon Length & Smoothing: Control the sensitivity of the Aroon Oscillator by adjusting the lookback period and smoothing settings, allowing traders to fine-tune the indicator to match different market conditions.
Mean Reversion Signals: Enable or disable mean reversion signals based on your trading preferences. Adjust the signal line length to control when these reversal signals are triggered.
Color Customization: Customize the colors for the oscillator and signals to match your chart’s color scheme for better visual clarity.
Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
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.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Ultimate Oscillator Trading StrategyThe Ultimate Oscillator Trading Strategy implemented in Pine Script™ is based on the Ultimate Oscillator (UO), a momentum indicator developed by Larry Williams in 1976. The UO is designed to measure price momentum over multiple timeframes, providing a more comprehensive view of market conditions by considering short-term, medium-term, and long-term trends simultaneously. This strategy applies the UO as a mean-reversion tool, seeking to capitalize on temporary deviations from the mean price level in the asset’s movement (Williams, 1976).
Strategy Overview:
Calculation of the Ultimate Oscillator (UO):
The UO combines price action over three different periods (short-term, medium-term, and long-term) to generate a weighted momentum measure. The default settings used in this strategy are:
Short-term: 6 periods (adjustable between 2 and 10).
Medium-term: 14 periods (adjustable between 6 and 14).
Long-term: 20 periods (adjustable between 10 and 20).
The UO is calculated as a weighted average of buying pressure and true range across these periods. The weights are designed to give more emphasis to short-term momentum, reflecting the short-term mean-reversion behavior observed in financial markets (Murphy, 1999).
Entry Conditions:
A long position is opened when the UO value falls below 30, indicating that the asset is potentially oversold. The value of 30 is a common threshold that suggests the price may have deviated significantly from its mean and could be due for a reversal, consistent with mean-reversion theory (Jegadeesh & Titman, 1993).
Exit Conditions:
The long position is closed when the current close price exceeds the previous day’s high. This rule captures the reversal and price recovery, providing a defined point to take profits.
The use of previous highs as exit points aligns with breakout and momentum strategies, as it indicates sufficient strength for a price recovery (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages two well-established phenomena in financial markets: momentum and mean-reversion. Momentum, identified in earlier studies like those by Jegadeesh and Titman (1993), describes the tendency of assets to continue in their direction of movement over short periods. Mean-reversion, as discussed by Poterba and Summers (1988), indicates that asset prices tend to revert to their mean over time after short-term deviations. This dual approach aims to buy assets when they are temporarily oversold and capitalize on their return to the mean.
Multi-timeframe Analysis:
The UO’s incorporation of multiple timeframes (short, medium, and long) provides a holistic view of momentum, unlike single-period oscillators such as the RSI. By combining data across different timeframes, the UO offers a more robust signal and reduces the risk of false entries often associated with single-period momentum indicators (Murphy, 1999).
Trading and Market Efficiency:
Studies in behavioral finance, such as those by Shiller (2003), show that short-term inefficiencies and behavioral biases can lead to overreactions in the market, resulting in price deviations. This strategy seeks to exploit these temporary inefficiencies, using the UO as a signal to identify potential entry points when the market sentiment may have overly pushed the price away from its average.
Strategy Performance:
Backtests of this strategy show promising results, with profit factors exceeding 2.5 when the default settings are optimized. These results are consistent with other studies on short-term trading strategies that capitalize on mean-reversion patterns (Jegadeesh & Titman, 1993). The use of a dynamic, multi-period indicator like the UO enhances the strategy’s adaptability, making it effective across different market conditions and timeframes.
Conclusion:
The Ultimate Oscillator Trading Strategy effectively combines momentum and mean-reversion principles to trade on temporary market inefficiencies. By utilizing multiple periods in its calculation, the UO provides a more reliable and comprehensive measure of momentum, reducing the likelihood of false signals and increasing the profitability of trades. This aligns with modern financial research, showing that strategies based on mean-reversion and multi-timeframe analysis can be effective in capturing short-term price movements.
References:
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
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.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1976). Ultimate Oscillator. Market research and technical trading analysis.
Premium Signal Strategy [BRTLab]🔍 Overview
BRTLab Premium Signal Strategy is a comprehensive multi-indicator trading strategy based on the integration of key technical indicators such as ADX, RSX, CAND, V9, PP, MA, and LVL. The strategy allows users to flexibly adjust the parameters of each indicator to optimize for specific market conditions, making it effective for both trending markets and for identifying reversals and breakouts.
🌟 What makes this strategy unique is its seamless compatibility with the BRT Premium Signals tool, allowing traders not only to receive real-time signals but also to conduct robust backtests. This feature enables users to fine-tune the best parameter settings or even test out their own trading ideas through historical data analysis. The ability to backtest empowers traders to validate strategies before going live, significantly improving the chances of success by offering data-driven insights.
💡 Signal Logic:
ADX
The ADX-based signals reflect the strength of market trends. Bullish or bearish signals are generated when directional indicators (+DI or -DI) show increasing strength relative to one another, indicating the start or continuation of a strong trend.
RSX
These signals focus on divergences within RSI, identifying potential reversals by detecting either classic or hidden divergences when the market is overbought or oversold.
V9
Signals are generated when the price interacts with a dynamic threshold, indicating trend continuation or reversal. Additional filters can be applied to refine these signals further, enhancing the dashboard's overall effectiveness.
CAND
Candlestick-based signals are triggered by key patterns such as bullish or bearish engulfing formations. These signals are cross-checked with other conditions, such as RSI levels and candle stability, making them especially useful for short-term trading.
PP (Pivot Points)
Pivot Point signals reinforce candlestick patterns by aligning with key support or resistance levels, suggesting potential reversals or continuation opportunities at significant price points.
MA (Moving Average)
MA signals help identify trends by analyzing price action relative to a moving average. Optional filters like ADX add an additional layer of validation, ensuring only high-confidence signals are displayed on the dashboard.
LVL (Levels)
These signals are based on shifts in RSI and help traders spot potential breakouts or reversals. The dashboard integrates these signals alongside MA and ADX filters to enhance their accuracy.
📊 Risk Management
This strategy includes built-in risk management features to help minimize losses:
Initial Capital: The user can set the initial capital (default is 10000), adjusting the strategy to their financial goals.
Position Size: Set the position size (default is 1000), allowing better risk management and controlling potential losses.
Stop-Loss: Multiple stop-loss methods are available, including ATR-based, fixed percentage, or prior high/low levels.
Take-Profit: Users can configure take-profit settings (default is 1.3%) to lock in gains while managing risk effectively.
⚠️ RISK DISCLAIMER
Trading involves significant risks, and most day traders experience losses. All content, tools, scripts, and educational materials from BRTLab are provided for informational and educational purposes only. Past performance is not a guarantee of future results. Please ensure you use realistic backtesting settings, including proper account size, commission, and slippage, to reflect market conditions.
⚡ CONCLUSION
We believe that successful trading comes from using indicators as supportive tools rather than relying on them for guaranteed success. The BRTLab Premium Signal Strategy is designed to be a comprehensive, customizable toolset that helps traders understand and interpret technical indicators more effectively.
By leveraging the power of backtesting and indicator optimization, traders can make well-informed decisions and develop a deeper understanding of market dynamics. Use this strategy to build a trading framework that aligns with your personal goals and trading style.
Follow the author’s instructions below to access the BRTLab Premium suite and unlock the full potential of this strategy.
[3Commas] Signal BuilderSignal Builder is a tool designed to help traders create custom buy and sell signals by combining multiple technical indicators. Its flexibility allows traders to set conditions based on their specific strategy, whether they’re into scalping, swing trading, or long-term investing. Additionally, its integration with 3Commas bots makes it a powerful choice for those looking to automate their trades, though it’s also ideal for traders who prefer receiving alerts and making manual decisions.
🔵 How does Signal Builder work?
Signal Builder allows users to define custom conditions using popular technical indicators, which, when met, generate clear buy or sell signals. These signals can be used to trigger TradingView alerts, ensuring that you never miss a market opportunity. Additionally, all conditions are evaluated using "AND" logic, meaning signals are only activated when all user-defined conditions are met. This increases precision and helps avoid false signals.
🔵 Available indicators and recommended settings:
Signal Builder provides access to a wide range of technical indicators, each customizable to popular settings that maximize effectiveness:
RSI (Relative Strength Index): An oscillator that measures the relative strength of price over a specific period. Traders typically configure it with 14 periods, using levels of 30 (oversold) and 70 (overbought) to identify potential reversals.
MACD (Moving Average Convergence Divergence): A key indicator tracking the crossover between two moving averages. Common settings include 12 and 26 periods for the moving averages, with a 9-period signal line to detect trend changes.
Ultimate Oscillator: Combines three different time frames to offer a comprehensive view of buying and selling pressure. Popular settings are 7, 14, and 28 periods.
Bollinger Bands %B: Provides insight into where the price is relative to its upper and lower bands. Standard settings include a 20-period moving average and a standard deviation of 2.
ADX (Average Directional Index): Measures the strength of a trend. Values above 25 typically indicate a strong trend, while values below suggest weak or sideways movement.
Stochastic Oscillator: A momentum indicator comparing the closing price to its range over a defined period. Popular configurations include 14 periods for %K and 3 for %D smoothing.
Parabolic SAR: Ideal for identifying trend reversals and entry/exit points. Commonly configured with a 0.02 step and a 0.2 maximum.
Money Flow Index (MFI): Similar to RSI but incorporates volume into the calculation. Standard settings use 14 periods, with levels of 20 and 80 as oversold and overbought thresholds.
Commodity Channel Index (CCI): Measures the deviation of price from its average. Traders often use a 20-period setting with levels of +100 and -100 to identify extreme overbought or oversold conditions.
Heikin Ashi Candles: These candles smooth out price fluctuations to show clearer trends. Commonly used in trend-following strategies to filter market noise.
🔵 How to use Signal Builder:
Configure indicators: Select the indicators that best fit your strategy and adjust their settings as needed. You can combine multiple indicators to define precise entry and exit conditions.
Define custom signals: Create buy or sell conditions that trigger when your selected indicators meet the criteria you’ve set. For example, configure a buy signal when RSI crosses above 30 and MACD confirms with a bullish crossover.
TradingView alerts: Set up alerts in TradingView to receive real-time notifications when the conditions you’ve defined are met, allowing you to react quickly to market opportunities without constantly monitoring charts.
Monitor with the panel: Signal Builder includes a visual panel that shows active conditions for each indicator in real time, helping you keep track of signals without manually checking each indicator.
🔵 3Commas integration:
In addition to being a valuable tool for any trader, Signal Builder is optimized to work seamlessly with 3Commas bots through Webhooks. This allows you to automate your trades based on the signals you’ve configured, ensuring that no opportunity is missed when your defined conditions are met. If you prefer automation, Signal Builder can send buy or sell signals to your 3Commas bots, enhancing your trading process and helping you manage multiple trades more efficiently.
🔵 Example of use:
Imagine you trade in volatile markets and want to trigger a sell signal when:
Stochastic Oscillator indicates overbought conditions with the %K value crossing below 80.
Bollinger Bands %B shows the price has surpassed the upper band, suggesting a potential reversal.
ADX is below 20, indicating that the trend is weak and could be about to change.
With Signal Builder , you can configure these conditions to trigger a sell signal only when all are met simultaneously. Then, you can set up a TradingView alert to notify you as soon as the signal is activated, giving you the opportunity to react quickly and adjust your strategy accordingly.
👨🏻💻💭 If this tool helps your trading strategy, don’t forget to give it a boost! Feel free to share in the comments how you're using it or if you have any questions.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Williams %R StrategyThe Williams %R Strategy implemented in Pine Script™ is a trading system based on the Williams %R momentum oscillator. The Williams %R indicator, developed by Larry Williams in 1973, is designed to identify overbought and oversold conditions in a market, helping traders time their entries and exits effectively (Williams, 1979). This particular strategy aims to capitalize on short-term price reversals in the S&P 500 (SPY) by identifying extreme values in the Williams %R indicator and using them as trading signals.
Strategy Rules:
Entry Signal:
A long position is entered when the Williams %R value falls below -90, indicating an oversold condition. This threshold suggests that the market may be near a short-term bottom, and prices are likely to reverse or rebound in the short term (Murphy, 1999).
Exit Signal:
The long position is exited when:
The current close price is higher than the previous day’s high, or
The Williams %R indicator rises above -30, indicating that the market is no longer oversold and may be approaching an overbought condition (Wilder, 1978).
Technical Analysis and Rationale:
The Williams %R is a momentum oscillator that measures the level of the close relative to the high-low range over a specific period, providing insight into whether an asset is trading near its highs or lows. The indicator values range from -100 (most oversold) to 0 (most overbought). When the value falls below -90, it indicates an oversold condition where a reversal is likely (Achelis, 2000). This strategy uses this oversold threshold as a signal to initiate long positions, betting on mean reversion—an established principle in financial markets where prices tend to revert to their historical averages (Jegadeesh & Titman, 1993).
Optimization and Performance:
The strategy allows for an adjustable lookback period (between 2 and 25 days) to determine the range used in the Williams %R calculation. Empirical tests show that shorter lookback periods (e.g., 2 days) yield the most favorable outcomes, with profit factors exceeding 2. This finding aligns with studies suggesting that shorter timeframes can effectively capture short-term momentum reversals (Fama, 1970; Jegadeesh & Titman, 1993).
Scientific Context:
Mean Reversion Theory: The strategy’s core relies on mean reversion, which suggests that prices fluctuate around a mean or average value. Research shows that such strategies, particularly those using oscillators like Williams %R, can exploit these temporary deviations (Poterba & Summers, 1988).
Behavioral Finance: The overbought and oversold conditions identified by Williams %R align with psychological factors influencing trading behavior, such as herding and panic selling, which often create opportunities for price reversals (Shiller, 2003).
Conclusion:
This Williams %R-based strategy utilizes a well-established momentum oscillator to time entries and exits in the S&P 500. By targeting extreme oversold conditions and exiting when these conditions revert or exceed historical ranges, the strategy aims to capture short-term gains. Scientific evidence supports the effectiveness of short-term mean reversion strategies, particularly when using indicators sensitive to momentum shifts.
References:
Achelis, S. B. (2000). Technical Analysis from A to Z. McGraw Hill.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
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.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1979). How I Made One Million Dollars… Last Year… Trading Commodities. Windsor Books.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
This explanation provides a scientific and evidence-based perspective on the Williams %R trading strategy, aligning it with fundamental principles in technical analysis and behavioral finance.
Fourier Smoothed Volume Zone Oscillator ( FSVZO )Overview 🔎
The fourier smoothed Volume Zone Oscillator (FSVZO) is a versatile tool designed to provide traders with a detailed understanding of market conditions by examining volume dynamics. FSVZO applies a series of advanced regularization techniques aimed at trying to reduce market noise, making signals potentially more readable and actionable. This indicator combines traditional technical analysis tools with a unique set of smoothing functions, aimed at creating a more balanced and reliable oscillator that can assist traders in their decision-making process.
A Combination of Technical Elements for a Unique Edge 🔀
FSVZO integrates a variety of technical elements to offer a comprehensive perspective on the market. These elements can be used individually or in combination, depending on user preferences. Here are the main components:
Volume Zone Oscillator (VZO): This foundational element leverages volume data to identify trends and shifts in buying or selling pressure. Unlike a standalone VZO, the FSVZO incorporates a Fourier-based regularization technique to reduce false signals, allowing traders to focus on meaningful volume-driven movements.
Ehler's White Noise Filter: This component is a sophisticated filter that helps distinguish genuine market signals from white noise. By isolating the meaningful movements in price and volume, the white noise filter contributes to the clarity and reliability of the signals generated.
Divergences Detection: FSVZO also provides divergence signals (both hidden and regular) based on the oscillator and price action. Divergences can be used to anticipate possible market reversals or confirmations, enhancing the trader's ability to recognize significant market shifts.
Money Flow Index (MFI) Smoothing: The MFI is calculated and then smoothed using wavelet and whitenoise techniques, providing a cleaner view of money flow within the market. This helps reduce erratic fluctuations and focuses on more consistent trends.
Trendshift Visualization: The FSVZO features an optional trendshift indicator, highlighting shifts between bullish and bearish conditions. These visual cues make it easier to identify trend reversals, aiding traders in timely decision-making.
Flexible Display Options 📊
FSVZO offers a variety of display modes to cater to different trading styles and visual preferences:
Neon Style Plot: The oscillator is presented with neon-style plots primarily for aesthetic purposes.
Color Blindness Modes 🌈: FSVZO includes several color palettes to accommodate traders affected by different types of color blindness (Protanopia, Deuteranopia, Tritanopia, Achromatopsia). These options ensure that everyone can easily interpret the signals, regardless of visual impairments.
Take Profit Areas & Alerts: The indicator can display take profit areas based on overbought or oversold conditions of the smoothed oscillator, marked by background hues to provide a clear visual signal. Alerts for high and low thresholds can also be enabled to identify moments of increased buying or selling interest.
Divergences and Trend Analysis 🔍
FSVZO also aims to identify bullish and bearish divergences:
Regular Bullish/Bearish Divergence: These occur when the oscillator diverges from the price action, indicating a possible reversal.
Hidden Bullish/Bearish Divergence: These occur within a trend, signaling continuation opportunities that help traders capitalize on ongoing trends.
FSVZO also supports additional filtering for divergences, allowing users to refine the detection of divergences to better suit their trading preferences.
Enhanced Noise Filtering 🔄
One of the unique features of FSVZO is its Fourier Regularization and Ehler's White Noise Filter, which help improve signal reliability by reducing the impact of market noise. These filtering methods are beneficial for traders seeking to avoid whipsaws and focus on more meaningful market movements.
Why FSVZO Stands Out 🔑
Noise Reduction: By combining multiple filtering techniques, FSVZO is designed to react to price changes as quickly as possible while offering various smoothing options to reduce noise, which may make it less responsive but more stable.
Flexible Visualization: The option to use different display modes and the inclusion of color blindness-friendly palettes make FSVZO versatile and accessible to all traders.
Detailed Divergence Analysis: The integration of both regular and hidden divergence detection helps improve the potential for identifying trading opportunities.
Advanced Regularization Techniques: The use of Fourier transformation and white noise filters adds a unique aspect to volume analysis, differentiating FSVZO from other traditional volume oscillators.
Conclusion 🔒
The Regularized Volume Zone Oscillator (FSVZO) is a unique tool that brings together multiple advanced techniques to help traders better understand market conditions and volume dynamics. The indicator is designed to react to price changes as quickly as possible, which may lead to false signals; however, it also offers smoothing options to help reduce noise at the cost of reduced reaction speed. This balance between responsiveness and stability provides traders with flexibility in adapting the indicator to different market conditions. However, as with all indicators, it is crucial to combine FSVZO with other tools and maintain sound risk management practices.
FSVZO is primarily designed for more experienced traders due the number of different signals it provides. It offers enhanced insights into volume trends and market movement, and should be used alongside other indicators to reduce risk and false signals
Dont make me crossStrategy Overview
This trading strategy utilizes Exponential Moving Averages (EMAs) to generate buy and sell signals based on the crossover of two EMAs, which are shifted downwards by 50 points. The strategy aims to identify potential market reversals and trends based on these crossovers.
Components of the Strategy
Exponential Moving Averages (EMAs):
Short EMA: This is calculated over a shorter period (default is 9 periods) and is more responsive to recent price changes.
Long EMA: This is calculated over a longer period (default is 21 periods) and provides a smoother view of the price trend.
Both EMAs are adjusted by a fixed shift amount of -50 points.
Input Parameters:
Short EMA Length: The period used to calculate the short-term EMA. This can be adjusted based on the trader's preference or market conditions.
Long EMA Length: The period used for the long-term EMA, also adjustable.
Shift Amount: A fixed value (default -50) that is subtracted from both EMAs to shift their values downwards. This is useful for visual adjustments or specific strategy requirements.
Plotting:
The adjusted EMAs are plotted on the price chart. The short EMA is displayed in blue, and the long EMA is displayed in red. This visual representation helps traders identify the crossover points easily.
Signal Generation:
Buy Signal: A buy signal is generated when the short EMA crosses above the long EMA. This is interpreted as a bullish signal, indicating potential upward price movement.
Sell Signal: A sell signal occurs when the short EMA crosses below the long EMA, indicating potential downward price movement.
Trade Execution:
When a buy signal is triggered, the strategy enters a long position.
Conversely, when a sell signal is triggered, the strategy enters a short position.
Trading Logic
Market Conditions: The strategy is most effective in trending markets. During sideways or choppy market conditions, it may generate false signals.
Risk Management: While this script does not include explicit risk management features (like stop-loss or take-profit), traders should consider implementing these to manage their risk effectively.
Customization
Traders can customize the EMA lengths and the shift amount based on their analysis and preferences.
The strategy can also be enhanced with additional indicators, such as volume or volatility measures, to filter signals further.
Use Cases
This strategy can be applied to various timeframes, such as intraday, daily, or weekly charts, depending on the trader's style.
It is suitable for both novice and experienced traders, offering a straightforward approach to trading based on technical analysis.
Summary
The EMA Crossover Strategy with a -50 shift is a straightforward technical analysis approach that capitalizes on the momentum generated by the crossover of short and long-term EMAs. By shifting the EMAs downwards, the strategy can help traders visualize potential entry and exit points more clearly, although it's important to consider additional risk management and market context for effective trading.
3CRGANG - HISTOGRAMThe 3CRGANG - HISTOGRAM is a breakthrough tool, developed to consolidate multiple oscillators, including their Fibonacci-modified versions, into a single, streamlined indicator. This isn’t just a combination of tools—i t’s a carefully engineered solution built to address the nuanced challenges traders face, such as market noise, varying data availability, and trend alignment across multiple timeframes.
Behind the scenes, significant debugging ensures it performs flawlessly even in situations where volume data isn’t provided by brokers. With automatic adjustments that adapt to different conditions, the indicator allows traders to remain focused on decision-making. Every enhancement, from signal optimization to noise reduction, reflects careful design choices to provide practical, actionable insights.
This tool is designed to give traders clarity, speed, and an edge, enabling them to focus on the markets without worrying about technical details.
How It’s Different from Basic Indicators
Rather than simply mashing up popular indicators like MACD, RSI, and more , —it’s a strategic tool designed to detect key momentum shifts, divergences, and trends in real time.
This script combines Fibonacci-modified oscillators and classic indicators in a unique way, providing multi-dimensional insights to enhance your trading decisions.
Reduce market noise: Fast and slow averages are used to generate histograms that filter out false signals.
Optimize alerts: Fibonacci-based calculations fine-tune oscillators to detect trends at key turning points.
Multi-timeframe momentum: This allows for tracking higher timeframe momentum while making decisions on lower timeframes—a powerful feature for trend alignment.
Key Features and Unique Value
Oscillator Flexibility: Choose from multiple oscillators to fit your strategy, including both momentum-based and volatility-based approaches.
Fibonacci Enhancements: These versions increase precision, providing greater confidence in signals at critical levels.
MTF Compatibility: Analyze higher timeframe momentum on shorter charts to maintain alignment with the broader trend.
Custom Alerts: Color-coded histograms and moving averages provide visual cues to keep your trades in sync with momentum changes.
How It Works
The indicator plots fast and slow averages for the selected oscillator, and the difference between these averages forms the histogram. Custom color coding shows whether momentum is increasing or weakening. The proprietary modification factor adjusts the signal sensitivity, allowing traders to fine-tune the indicator for their strategy.
Visual Alerts:
Green Bars: Indicate bullish momentum.
Red Bars: Suggest bearish momentum.
Buy Only / Sell Only Zones: Alert traders when the indicator suggests favoring either long or short trades.
This indicator minimizes false signals by blending momentum oscillators with volume-weighted filters and smooth moving averages, ensuring better signal quality.
Use Case: Like a Traffic Light for Your Trades
Green means Go: Enter or hold long positions during green bars, signaling upward momentum.
Red means Stop (or Go Short): Exit long positions or enter short trades when red bars appear, indicating bearish momentum.
The Buy Only and Sell Only alerts help traders stay aligned with dominant trends and avoid counter-trend trades in high-momentum phases.
Real-World Examples :
Divergences (BTCUSD):
When the price action ranges, wedges, or behaves unusually, the histogram—being highly sensitive — alerts traders ahead of potential reversals or continuation moves.
This gives traders more time to assess market conditions and prepare their strategy before momentum shifts.
Multi-Timeframe Momentum (ADAUSD):
Momentum from a higher timeframe aligns with the trend on a lower timeframe, helping traders time their entries accurately.
The Priceless Edge for Traders
The 3CRGANG offers more than just another way to analyze markets—it provides a priceless edge by streamlining multiple indicators into a single tool. With the flexibility to switch between oscillators, multi-timeframe momentum tracking, and proprietary enhancements, it’s designed to help traders stay ahead in both trending and volatile markets.
Disclaimer
This indicator is a trading tool designed to provide insights into market trends, but it does not guarantee results. Trading involves risk, and past performance does not predict future outcomes. Use it alongside proper risk management practices.
Gauss IndicatorGauss Indicator
Class : oscillator
Trading type : any
Time frame : any
Purpose : reversal trading
Level of aggressiveness : any
About Gauss Indicator
Time series forecasting is quite a scientific task, for which specific econometrical models and methods have been developed.
Who is Gauss and Why his Curve is So Important
Johann Gauss was one of the best mathematicians of all times and he gave us a very specific curve (Gaussian Curve) to explain specifics of random variable behavior (so called Normal Distribution)
Gaussian curve has quite interesting property usually called “3 Sigmas Rule”: in a normal distribution: 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.
But Does It Work in the Financial Markets?
Normal Distribution is extremely typical for price behavior in financial markets: FOREX, stock Market, Commodities, Cryptocurrency market.
How can we forecast future prices based on “3 Sigmas Rule”?
If we know past prices (we actually know), we can calculate Mean and Standard Deviation.
After that following “3 Sigmas Rules” we can calculate the fluctuations range for the present day with a known probability (!).
• If we add 1 sigma to mean we can get the price value that wouldn’t be exceeded with a probability of 68%.
• If we add 2 sigmas to mean we can get the price value that wouldn’t be exceeded with a probability of 95%.
• If we add 3 sigmas to mean we can get the price value that wouldn’t be exceeded with a probability of 99%.
How Can I Get This Information?
Gauss indicator is a practical implementation of “3 sigmas rule” in trading.
Gauss allows to predict the ranges of price fluctuations for the selected time frames (week, day, hour, etc) with certain probabilities: 68%, 95% and 99%.
Gauss can be used to generate Trading signals, Stop-loss parameters, Take-profit parameters, Synthetic Levels (both Support and Resistance).
Actually, ALL information you need to trade.
Structure of the Gauss Indicator
1. Three blue lines – synthetic support lines. They describe 3 different buy zones with certain probabilities of success:
- First blue line (Buy zone #1) - the price today will not fall below this mark with a probability of 68%;
- Second blue line (Buy zone #2) - the price today will not fall below this mark with a probability of 95%;
- Third blue line (Buy zone #3) - the price today will not fall below this mark with a probability of 99%.
2. Three red lines – synthetic resistance lines. They describe 3 different sell zones with certain probabilities of success:
- First red line (Sell zone #1) - the price today will not rise above this mark with a probability of 68%;
- Second red line (Sell zone #2) - the price today will not rise above this mark with a probability of 95%;
- Third red line (Sell zone #3) - the price today will not rise above this mark with a probability of 99%.
3. Green line – shows current price. When it gets close to the red/blue line sell/buy signals are generated.
Trading rules
General rules are as follows: buy at the blue lines, sell at the red lines.
Take-profits for sells are set at the nearest blue line, for buys – at the nearest red line. Stop-losses for sells are set above the last red line, for buys – below the last blue line.
MomentumSignal Kit RSI-MACD-ADX-CCI-CMF-TSI-EStoch// ----------------------------------------
// Description:
// ----------------------------------------
// MomentumKit RSI/MACD-ADX-CCI-CMF-TSI-EStoch Suite is a comprehensive momentum indicator suite designed to provide robust buy and sell signals through the consensus of multiple normalized momentum indicators. This suite integrates the following indicators:
// - **Relative Strength Index (RSI)**
// - **Stochastic RSI**
// - **Moving Average Convergence Divergence (MACD)** with enhanced logic
// - **True Strength Index (TSI)**
// - **Commodity Channel Index (CCI)**
// - **Chaikin Money Flow (CMF)**
// - **Average Directional Index (ADX)**
// - **Ehlers' Stochastic**
//
// **Key Features:**
// 1. **Normalization:** Each indicator is normalized to a consistent scale, facilitating easier comparison and interpretation across different momentum metrics. This uniform scaling allows traders to seamlessly analyze multiple indicators simultaneously without the confusion of differing value ranges.
//
// 2. **Consensus-Based Signals:** By combining multiple indicators, MomentumKit generates buy and sell signals based on the agreement among various momentum measurements. This multi-indicator consensus approach enhances signal reliability and reduces the likelihood of false positives.
//
// 3. **Overlap Analysis:** The normalization process aids in identifying overlapping signals, where multiple indicators point towards a potential change in price or momentum. Such overlaps are strong indicators of significant market movements, providing traders with timely and actionable insights.
//
// 4. **Enhanced Logic for MACD:** The MACD component within MomentumKit utilizes enhanced logic to improve its responsiveness and accuracy in detecting trend changes.
//
// 5. **Debugging Features:** MomentumKit includes advanced debugging tools that display individual buy and sell signals generated by each indicator. These features are intended for users with technical and programming skills, allowing them to:
// - **Visualize Signal Generation:** See real-time buy and sell signals for each integrated indicator directly on the chart.
// - **Adjust Signal Thresholds:** Modify the criteria for what constitutes a buy or sell signal for each indicator, enabling tailored analysis based on specific trading strategies.
// - **Filter and Manipulate Signals:** Enable or disable specific indicators' contributions to the overall buy and sell signals, providing flexibility in signal generation.
// - **Monitor Indicator Behavior:** Utilize debug plots and labels to understand how each indicator reacts to market movements, aiding in strategy optimization.
//
// **Work in Progress:**
// MomentumKit is continuously evolving, with ongoing enhancements to its algorithms and user interface. Current debugging features are designed to offer deep insights for technically adept users, allowing for extensive customization and fine-tuning. Future updates aim to introduce more user-friendly interfaces and automated optimization tools to cater to a broader audience.
//
// **Usage Instructions:**
// - **Visibility Controls:** Users can toggle the visibility of individual indicators to focus on specific momentum metrics as needed.
// - **Parameter Adjustments:** Each indicator comes with customizable parameters, allowing traders to fine-tune the suite according to their trading strategies and market conditions.
// - **Debugging Features:** Enable the debugging mode to visualize individual indicator signals and adjust their contribution to the overall buy/sell signals. This requires a basic understanding of the underlying indicators and their operational thresholds.
//
// **Benefits:**
// - **Simplified Analysis:** Normalization simplifies the process of analyzing multiple indicators, making it easier to identify consistent signals across different momentum measurements.
// - **Improved Decision-Making:** Consensus-based signals backed by multiple normalized indicators provide a higher level of confidence in trading decisions.
// - **Versatility:** Suitable for various trading styles and market conditions, MomentumKit offers a versatile toolset for both novice and experienced traders.
//
// **Technical Requirements:**
// - **Programming Knowledge:** To fully leverage the debugging and signal manipulation features, users should possess a foundational understanding of Pine Script and the mechanics of momentum indicators.
// - **Customization Skills:** Ability to adjust indicator parameters and debug filters to align with specific trading strategies.
//
// **Disclaimer:**
// This indicator suite is intended for educational and analytical purposes only and does not constitute financial advice. Trading involves significant risk, and past performance is not indicative of future results. Always conduct your own analysis or consult a qualified financial advisor before making trading decisions.
Stochastics Confluences 4 in 1Description of the Pine Script:
This script plots the Full Stochastic indicator for four different time periods, and highlights conditions where potential buy or sell signals can be identified. The Stochastic indicator measures the position of the current closing price relative to the range of high and low prices over a defined period, helping traders identify overbought and oversold conditions.
Key Features:
Stochastic Calculation for 4 Different Periods:
The script calculates the Stochastic for four separate lookback periods: 9, 14, 40, and 60 bars.
Each Stochastic value is smoothed by a Simple Moving Average (SMA) to reduce noise and provide a clearer signal.
Visual Representation:
It plots each Stochastic value on the chart using different colors, allowing the user to see how the different periods of the indicator behave relative to each other.
Horizontal lines are drawn at 80 (Upper Bound) and 20 (Lower Bound), commonly used to identify overbought and oversold regions.
Highlighting Buy and Sell Conditions:
Green Highlight (Potential Buy Signal):
When all four Stochastic values (for the four different periods) are below 20, this suggests that the asset is in an oversold condition across multiple timeframes. The green background highlight appears when the Stochastic lines converge below 20, indicating a potential buy signal, as the price may be preparing to move upward from an oversold state.
Red Highlight (Potential Sell Signal):
When all four Stochastic values are above 80, the asset is in an overbought condition across multiple timeframes. The red background highlight appears when the Stochastic lines converge above 80, indicating a potential sell signal, as the price may soon reverse downward from an overbought state.
How to Interpret the Signals:
Buy Signals (Green Highlight):
When the chart is highlighted in green, it means the Stochastic indicators for all four periods are below 20, signaling that the asset is oversold and may be nearing a potential upward reversal. This condition suggests a possible buying opportunity, especially when other indicators confirm the potential for an upward trend.
Sell Signals (Red Highlight):
When the chart is highlighted in red, it indicates that the Stochastic indicators for all four periods are above 80, meaning the asset is overbought. This condition signals a possible downward reversal, suggesting a potential selling opportunity if the price begins to show signs of weakness.
By using this script, traders can visually identify periods of strong confluence across different timeframes when the Stochastic indicators are in extreme oversold or overbought conditions, which are traditionally seen as strong buy or sell signals.
This approach helps filter out weaker signals and focuses on moments when all timeframes align, increasing the probability of a successful trade.
Risk Matrix [QuantraSystems]Risk Matrix
The Risk Matrix is a sophisticated tool that aggregates a variety of fundamental inputs, primarily external (non-crypto) market data is used to assess investor risk appetite. By combining external macroeconomic factors and proxies for liquidity data with specific signals from the cryptomarket - the Risk Matrix provides a holistic view of market risk conditions. These insights are designed to help traders and investors make informed decisions on when to adopt a risk-on or risk-off approach.
Core Concept
The Risk Matrix functions as a dynamic risk assessment tool that integrates both fundamental and technical market indicators to generate an aggregated Z-score. This score helps traders to identify where the market is in a risk-off or risk-on state, The system provides both binary risk signals and a more nuanced “risk seasonality” mode for deeper analysis.
Key Features
Global Liquidity Aggregate - The Liquidity score is a custom measure of global liquidity, built by combining a variety of traditional financial metrics. These include data from central bank balance sheets, reverse repo operations and credit availability. This data is sourced from organizations such as the U.S. Federal Reserve, the European Central Bank, and the People’s Bank of China. The purpose of this aggregate is to gauge how much liquidity is available in the global financial system - which often correlates with risk sentiment. Rising liquidity tends to boost risk-on appetite, while liquidity contractions signal increased caution (risk-off) in the markets. The data sources used in this global liquidity aggregate include:
- U.S. Commercial Bank Credit data
- Federal Reserve balance sheet and reverse repo operations
- Liquidity from major central banks including the Fed, Bank of Japan, ECB, and PBoC
- Asset performance from major global financial indices such as the S&P 500, TLT, DXY (U.S. Dollar Index), MOVE (bond market volatility), and commodities like gold and oil.
Other key Z-scores (measured individually) - The Risk Matrix also incorporates other major Z-scores that represent different facets of the financial markets:
- Collateral Risk - A measure of US bond volatility, where higher values indicate higher interest rate risk - leading to potential market instability and cautious market behaviors.
- Stablecoin Dominance - The dominance of stablecoins in the crypto markets - which can signal risk aversion the total capital allocated to stables increases relative to other cryptocurrencies.
- US Currency Strength - The U.S. Dollar Index Z-score reflects currency market strength, with higher values typically indicating risk aversion as investors sell more volatile assets and flock to the dollar.
- Trans-pacific Monetary Bias - Signals capital flow and monetary trends that link between the East and West, heavily influencing global risk sentiment.
- Total - A measure of the total cryptocurrency market cap, signaling broader risk sentiment with the crypto market.
Neural Network Synthesis - The NNSYNTH component adds a machine learning inspired layer to the Risk Matrix. This custom indicator synthesizes inputs from various technical indicators (such as RSI, MACD, Bollinger Bands, and others) to generate a composite signal that reflects the health of the cryptomarket. While highly complex in its design, the NNSYNTH ultimately helps detect market shifts early by synthesizing multiple signals into one cohesive output. This score is particularly useful for gauging momentum and identifying potential turning points in market trends. Because the NNSYNTH is a closed source indicator, and it is included here, the Risk Matrix by extension is a closed source indicator.
How it Works
Z-score Aggregation - The Risk Matrix computes a final risk score by aggregating several Z-scores from different asset classes and data sources, all of which contribute proportionally to the overall market risk assessment. Each input is equally weighted - normalization allows for direct comparisons across global liquidity trends, currency fluctuations, bond market volatility and crypto market conditions. Furthermore, this system employs multi-calibration aggregation - where each individual matrix is itself an aggregate of multiple Z-scores derived from various timeframes. This ensures that each matrix captures a distinct average across different time horizons before being combined into the overall Risk Matrix. This layered, multi timeframe approach enhances the precision and robustness of the final Z-score.
Risk-On / Risk-Off Mode - The system’s binary mode provides a clear Risk On and Off signal. This nature of this signal is determined by the behavior of the Z-score relative to the midline, or Standard Deviation Bands, depending on specific conditions:
Risk-On is signaled when the aggregated final Z-score crosses above 0. However, in extreme oversold conditions, Risk-On can trigger early if the upper standard deviation band falls below the zero line. In such cases, the Risk-On signal is triggered when the z-score crosses the upper standard deviation band - without waiting to cross the midline.
Risk-Off is signaled when the final Z-score moves below 0. Similarly, Risk-Off can also be triggered early if the lower standard deviation band rises above the midline. In this instance, Risk-Off is triggered when the Z-score crosses below the lower band.
Risk Seasonality Mode - This mode offers a more gradual transition between risk states, measuring the change in the Z-score to visualize the shifts in risk appetite over time. It's useful for traders seeking to understand broader market cycles and risk phases. The seasonality view breaks down the market into the following phases:
Risk-On - High risk appetite where risk/cyclical markets are generally bullish.
Weakening - Markets showing signs of cooling off, here the higher beta assets tend to sell off first.
Risk-Off - Investors pull back, and bearish sentiment prevails.
Recovery - Signs of bottoming out, potential for market re-entry.
Component Matrices - Each individual Z-score is visualized as part of the component matrices - scaled to a 3 Sigma range. These component matrices allow traders to view how each data source is contributing to the overall risk assessment in real time - offering transparency and granularity.
Visuals and UI
Main Risk Matrix - The aggregated Z-Score is displayed saliently in the main risk matrix. Traders and investors can quickly see what season the Risk Matrix is signaling and adjust their strategies accordingly.
Overview Table - A detailed overview table shows the current confirmed Z-scores for each component, along with values from 2, and 3 bars back. This helps traders spot trends and the rate of change (RoC) between signals, offering additional insights for shorter-term risk management.
Customizability - Users can customize the visual elements of the matrix, including color palettes, table sizes, and positions. This allows for optimal integration into any trader’s existing workspace.
Usage Summary
The Risk Matrix is an incredibly versatile tool. It is especially valuable as a means of achieving a cross-market view of risk, incorporating both crypto-specific and macroeconomic factors. Some key use cases include:
Adjusting Capital Allocation Based on Risk Seasons - Traders can use the Risk Matrix to adjust their capital allocation dynamically. During Risk-On periods, they might increase exposure to long positions, capitalizing on stronger market conditions. Conversely, during Risk-Off periods, traders could reduce or hedge long positions and potentially scale up short positions or move into safer assets.
Complementing Other Trading Systems - The Risk Matrix can work alongside other technical systems to provide context to market moves. For instance, a trend-following strategy might suggest an entry, but the Risk Matrix could be used to verify whether the broader market conditions support this trade. If the Matrix is in a Risk-Off period, a trader might opt for more conservative trade sizes or avoid the trade entirely.
This flexibility allows traders to adjust their strategies and portfolio risk dynamically, enhancing decision making based on broader market conditions - as indicated by external macroeconomic factors, liquidity, and risk sentiment.
Important Note
The Risk Matrix always uses the most up-to-date data available, ensuring analysis reflects the latest market conditions and macroeconomic inputs. In rare cases, governments or financial institutions revise past data - and the Risk Matrix will adjust accordingly. This behavior can only be seen in the Liquidity Matrix. and can affect the final score. While this is uncommon, it highlights the benefit of using a system that adapts in real-time, incorporating the most accurate and current information to enhance decision making processes.
Money Wave Script (Visual Adaptive MFI)This Script is a visual modification of the Money Flow Index (MFI)
//@version=5
indicator(title="Money Flow Index", shorttitle="MFI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
length = input.int(title="Length", defval=14, minval=1, maxval=2000)
src = hlc3
mf = ta.mfi(src, length)
plot(mf, "MF", color=#7E57C2)
overbought=hline(80, title="Overbought", color=#787B86)
hline(50, "Middle Band", color=color.new(#787B86, 50))
oversold=hline(20, title="Oversold", color=#787B86)
fill(overbought, oversold, color=color.rgb(126, 87, 194, 90), title="Background")
This Money Wave Script is culled from. the Money Flow Index with visual representation to help traders identify money flow. In addition, the waves can be smoothened. Here’s a detailed overview based on its functionality, color coding, usage, risk management, and a concluding summary.
Functionality
The Money Wave Script operates as an oscillator that measures the inflow and outflow of money into an asset over a specified period. It calculates the MFI by considering both price and volume, which allows it to assess buying and selling pressures more accurately than traditional indicators that rely solely on price data.
Color Coding
The indicator employs a color-coded scheme to enhance visual interpretation:
Green Area: Indicates bullish conditions when the normalized Money wave is above zero, suggesting buying pressure.
Red Area: Indicates bearish conditions when the normalized Money wave is below zero, suggesting selling pressure.
Background Colors: The background changes to green when the MoneyWave exceeds the upper threshold (overbought) and red when it falls below the lower threshold (oversold), providing immediate visual cues about market conditions.
Usage
Traders utilize the Money Wave indicator in various ways:
Identifying Overbought and Oversold Levels: By observing the MFI readings, traders can determine when an asset may be overbought or oversold, prompting potential entry or exit points.
Spotting Divergences: Traders look for divergences between price and the MFI to anticipate potential reversals. For example, if prices are making new highs but the MFI is not, it could indicate weakening momentum.
Trend Confirmation: The indicator can help confirm trends by showing whether buying or selling pressure is dominating.
Customizable Settings: Users can adjust parameters such as the MFI length , Smoothen index and overbought/oversold thresholds to tailor the indicator to their trading strategies.
Conclusion
The Money Wave indicator is a powerful tool for traders seeking to analyze market conditions based on the flow of money into and out of assets. Its combination of price and volume analysis, along with clear visual cues, makes it an effective choice for identifying overbought and oversold conditions, spotting divergences, and confirming trends.
TEMA For Loop [Mattes]The TEMA For Loop indicator is a powerful tool designed for technical analysis, combining the Triple Exponential Moving Average (TEMA) with a custom scoring mechanism based on a for loop. It evaluates price trends over a specified period, allowing traders to identify potential entry and exit points in the market. This indicator enhances decision-making by providing visual cues through dynamic candle coloring, reflecting market sentiment and trends effectively.
Technical Details:
Triple Exponential Moving Average (TEMA):
- TEMA is known for its responsiveness to price changes, as it reduces lag compared to traditional moving averages. The TEMA calculation employs three nested Exponential Moving Averages (EMAs) to produce a smoother trend line, which helps traders identify the direction and momentum of the market.
Scoring Mechanism:
- The scoring mechanism is based on a custom for loop that compares the current TEMA value to previous values over a specified range. The loop counts how many previous values are less than the current value, generating a score that reflects the strength of the trend:
- A higher score indicates a stronger upward trend.
- A lower (negative) score suggests a downward trend.
Threshold Levels:
- Upper Threshold: A score above this level signals a potential long entry, indicating strong bullish momentum.
- Lower Threshold: A score below this level indicates a potential short entry, suggesting bearish sentiment.
>>>These thresholds are adjustable, allowing traders to fine-tune their strategy according to their risk tolerance and market conditions.
Signal Logic:
- The indicator provides clear signals for entering long or short positions based on the score crossing the defined thresholds.
>>Long Entry Signal: When the smoothed score crosses above the upper threshold.
>>Short Entry Signal: When the smoothed score crosses below the lower threshold.
Why This Indicator Is Useful:
>>> Enhanced Decision-Making: The TEMA For Loop indicator offers traders a clear and objective view of market trends, reducing the emotional aspect of trading. By visualizing bullish and bearish conditions, it assists traders in making timely decisions.
>>> Customizable Parameters: The ability to adjust TEMA period, thresholds, and other settings allows traders to tailor the indicator to their specific trading strategies and market conditions.
Visual Clarity: The integration of dynamic candle coloring provides immediate visual cues about the prevailing trend, making it easier for traders to spot potential trade opportunities at a glance.
The TEMA For Loop - Smoothed with Candle Colors indicator is a sophisticated trading tool that utilizes TEMA and a custom scoring mechanism to identify and visualize market trends effectively. By employing dynamic candle coloring, traders gain immediate insights into market sentiment, enabling informed decision-making for entry and exit strategies. This indicator is designed for traders seeking a systematic approach to trend analysis, enhancing their trading performance through clear, actionable signals.
Relative Strength Price Oscillator Indicator (RS PPO)Percentage Price Oscillator (PPO)
The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences.
PPO readings are not subject to the price level of the security and the PPO values for different securities can be compared, regardless of the price of the security.
Relative Strength (RS)
Relative strength is a strategy used in momentum investing and focuses on investing in stocks or other securities that have performed well relative to the market as a whole or to a relevant benchmark.
Chart
In the chart, Microsoft stock (MSFT) is plotted against the VanEck Semiconductor ETF (SMH).
In the example on the left, from the negative values of the RS PPO it can be seen that MSFT, although trending upward, is losing out in negative terms to the SMH etf.
In the example on the right, during a correction phase with a downward price trend, Microsoft held up relatively well compared to the Van Eck Semiconductor etf.
Momentum Nexus Oscillator [UAlgo]The "Momentum Nexus Oscillator " indicator is a comprehensive momentum-based tool designed to provide traders with visual cues on market conditions using multiple oscillators. By combining four popular technical indicators—RSI (Relative Strength Index), VZO (Volume Zone Oscillator), MFI (Money Flow Index), and CCI (Commodity Channel Index)—this heatmap offers a holistic view of the market's momentum.
The indicator plots two lines: one representing the current chart’s combined momentum score and the other representing a higher timeframe’s (HTF) score, if enabled. Through smooth gradient color transitions and easy-to-read signals, the Momentum Nexus Heatmap allows traders to easily identify potential trend reversals or continuation patterns.
Traders can use this tool to detect overbought or oversold conditions, helping them anticipate possible long or short trade opportunities. The option to use a higher timeframe enhances the flexibility of the indicator for longer-term trend analysis.
🔶 Key Features
Multi-Oscillator Approach: Combines four popular momentum oscillators (RSI, VZO, MFI, and CCI) to generate a weighted score, providing a comprehensive picture of market momentum.
Dynamic Color Heatmap: Utilizes a smooth gradient transition between bullish and bearish colors, reflecting market momentum across different thresholds.
Higher Timeframe (HTF) Compatibility: Includes an optional higher timeframe input that displays a separate score line based on the same momentum metrics, allowing for multi-timeframe analysis.
Customizable Parameters: Adjustable RSI, VZO, MFI, and CCI lengths, as well as overbought and oversold levels, to match the trader’s strategy or preference.
Signal Alerts: Built-in alert conditions for both the current chart and higher timeframe scores, notifying traders when long or short entry signals are triggered.
Buy/Sell Signals: Displays visual signals (▲ and ▼) on the chart when combined scores reach overbought or oversold levels, providing clear entry cues.
User-Friendly Visualization: The heatmap is separated into four sections representing each indicator, providing a transparent view of how each contributes to the overall momentum score.
🔶 Interpreting Indicator:
Combined Score
The indicator generates a combined score by weighing the individual contributions of RSI, VZO, MFI, and CCI. This score ranges from 0 to 100 and is plotted as a line on the chart. Lower values suggest potential oversold conditions, while higher values indicate overbought conditions.
Color Heatmap
The indicator divides the combined score into four distinct sections, each representing one of the underlying momentum oscillators (RSI, VZO, MFI, and CCI). Bullish (greenish) colors indicate upward momentum, while bearish (grayish) colors suggest downward momentum.
Long/Short Signals
When the combined score drops below the oversold threshold (default is 26), a long signal (▲) is displayed on the chart, indicating a potential buying opportunity.
When the combined score exceeds the overbought threshold (default is 74), a short signal (▼) is shown, signaling a potential sell or short opportunity.
Higher Timeframe Analysis
If enabled, the indicator also plots a line representing the combined score for a higher timeframe. This can be used to align lower timeframe trades with the broader trend of a higher timeframe, providing added confirmation.
Signals for long and short entries are also plotted for the higher timeframe when its combined score reaches overbought or oversold levels.
🔶Purpose of Using Multiple Technical Indicators
The combination of RSI, VZO, MFI, and CCI in the Momentum Nexus Heatmap provides a comprehensive approach to analyzing market momentum by leveraging the unique strengths of each indicator. This multi-indicator method minimizes the limitations of using just one tool, resulting in more reliable signals and a clearer understanding of market conditions.
RSI (Relative Strength Index)
RSI contributes by measuring the strength and speed of recent price movements. It helps identify overbought or oversold levels, signaling potential trend reversals or corrections. Its simplicity and effectiveness make it one of the most widely used indicators in technical analysis, contributing to momentum assessment in a straightforward manner.
VZO (Volume Zone Oscillator)
VZO adds the critical element of volume to the analysis. By assessing whether price movements are supported by significant volume, VZO distinguishes between price changes that are driven by real market conviction and those that might be short-lived. It helps validate the strength of a trend or alert the trader to potential weakness when price moves are unsupported by volume.
MFI (Money Flow Index)
MFI enhances the analysis by combining price and volume to gauge money flow into and out of an asset. This indicator provides insight into the participation of large players in the market, showing if money is pouring into or exiting the asset. MFI acts as a volume-weighted version of RSI, giving more weight to volume shifts and helping traders understand the sustainability of price trends.
CCI (Commodity Channel Index)
CCI contributes by measuring how far the price deviates from its statistical average. This helps in identifying extreme conditions where the market might be overextended in either direction. CCI is especially useful for spotting trend reversals or continuations, particularly during market extremes, and for identifying divergence signals.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
RSI & Volume Impact Analyzer Ver.1.00Description:
The RSI VOL Score indicator combines the Relative Strength Index (RSI) and volume data through a mathematical calculation to assist traders in identifying and confirming potential trend reversals and continuations. By leveraging both momentum (RSI) and volume data, this indicator provides a more comprehensive view of market strength compared to using RSI or volume alone.
How It Works:
This indicator calculates a score by comparing the RSI against its moving average, adjusted by the volume data. The resulting score quantifies market momentum and strength. When the score crosses its signal line, it may indicate key moments where the market shifts between bullish and bearish trends, potentially helping traders spot these changes earlier.
Calculation Methods:
The RSI VOL Score allows users to select between several calculation methods to suit their strategy:
SMA (Simple Moving Average): Provides a balanced smoothing approach.
EMA (Exponential Moving Average): Reacts more quickly to recent price changes, offering faster signals.
VWMA (Volume Weighted Moving Average): Emphasizes high-volume periods, focusing on stronger market moves.
WMA (Weighted Moving Average): Applies greater weight to recent data for a more responsive signal.
What the Indicator Plots:
Score Line: Represents a combined metric based on RSI and volume, helping traders gauge the overall strength of the trend.
Signal Line: A smoothed version of the score that helps traders identify potential trend changes. Bullish signals occur when the score crosses above the signal line, while bearish signals occur when the score drops below.
Key Features:
Trend Identification: The score and signal line crossovers can help confirm emerging bullish or bearish trends, allowing traders to act on upward or downward momentum.
Customizable Settings: Traders can adjust the lengths of the RSI and signal line and choose between different moving averages (SMA, EMA, VWMA, WMA) to tailor the indicator to their trading style.
Timeframe-Specific: The indicator works within the selected timeframe, ensuring accurate trend analysis based on the current market context.
Practical Use Cases:
Trending Markets: In trending markets, this indicator helps confirm bullish or bearish signals by validating price moves with volume. Traders can use the crossover of the score and signal line as a guide for entering or exiting trades based on trend strength.
Ranging Markets: In ranging markets, the indicator helps filter out false signals by confirming if price movements are backed by volume, making it a useful tool for traders looking to avoid entering during weak or uncertain market conditions.
Interpreting the Score and Signal Lines:
Bullish Signal: A bullish signal occurs when the score crosses above the signal line, indicating a potential upward trend in momentum and price.
Bearish Signal: A bearish signal is generated when the score crosses below the signal line, suggesting a potential downward trend or weakening market momentum.
By mathematically combining RSI and volume data into a single trend score, the RSI VOL Score indicator provides traders with a powerful tool for identifying trend shifts early and making more confident trading decisions.
Important Note:
The signals generated by this indicator should be interpreted in conjunction with other analysis tools. It is always advisable to confirm signals before making any trading decisions.
Disclaimer:
This indicator is designed to assist traders in their decision-making process and does not provide financial advice. The creators of this tool are not responsible for any financial losses or trading decisions made based on its signals. Trading involves significant risk, and users should seek professional advice or conduct their own research before making any trading decisions.
Stochastic RMIThe Relative Momentum Index (RMI) is a technical analysis indicator used to analyze the price movements of assets in a financial market. Similar to the RSI (Relative Strength Index), it helps measure the momentum and strength of the asset's price movements over the recent period. However, the RMI offers a "smoother" view, unlike the RSI. This means that there is less "noise" in the indicator.
As is known, the Stochastic RSI indicator is based on the RSI. What I did was to create a stochastic based on the RMI. If you compare this indicator with the "Stochastic RSI", you will see that there is no difference between them, except that the "Stochastic RMI" is more "smooth" and noiseless.
Trend Following Composite Index ( TFCI ) 🏆 Trend Following Composite Index (TFCI) 🏆
Overview 🔎
The Trend Following Composite Index (TFCI) is designed to provide traders with a comprehensive view of market trends by combining several technical indicators in a single, unified tool. Each component brings its unique perspective, and together they create a well-rounded signal that may help traders better understand the current market condition. TFCI simplifies the decision-making process by aggregating these signals into one easy-to-read confidence percentage, allowing traders to quickly gauge whether the market is trending upwards, downwards, or is in a period of indecision.
Combining Multiple Indicators for a Unique Edge 🔀
TFCI integrates six different technical indicators, each tuned to capture distinct aspects of market behavior. Rather than relying on any single indicator, TFCI merges their signals into one, providing a more nuanced and potentially more reliable view of the market. This combination helps reduce the weaknesses inherent in any one indicator, offering a more balanced and holistic trend signal.
RSI Filter: The RSI helps identify potential overbought or oversold conditions, but when used alone, it can generate false signals. In TFCI, the RSI is smoothed and combined with other metrics to avoid reacting to small fluctuations, making the signals more robust.
Kijun-Based Band: This component, inspired by the Kijun-sen line from the Ichimoku system, defines adaptive price bands based on market equilibrium. When combined with a smoothing filter, it provides traders with clear visual cues for potential trend reversals, reducing the guesswork.
Boosted Moving Average: By combining short- and long-term EMAs, this component reacts quickly to price changes, while the "boost" factor enhances its ability to confirm trends early. This combination helps filter out market noise, making it easier to spot genuine trend shifts.
Deviation Condition: This proprietary moving average adjusts dynamically based on volatility, which means it adapts to fast-changing market conditions. By adjusting its sensitivity based on market deviations, it helps smooth out erratic price movements, creating clearer trend signals.
VWTSI (Volume-Weighted Trend Strength Indicator): Volume is an essential factor in confirming trends. This indicator looks at price movements in relation to volume to assess the strength of the trend. By factoring in volatility, it ensures that traders are focusing on the strongest market moves, further enhancing the reliability of the signals.
Supertrend: A volatility-based trailing stop that defines buy and sell points. Its role in TFCI is to help maintain positions during trending markets while avoiding premature exits due to minor pullbacks.
A Streamlined Confidence Signal 🧮
One of the main advantages of TFCI is that it simplifies the multitude of signals into one easy-to-read confidence percentage. The aggregation of multiple indicators means that no single indicator drives the signal; instead, the combined analysis ensures that only when several conditions align do you get a clear trend indication. This reduces false positives and gives traders a more confident view of the overall market direction.
Bullish signals from several components push the percentage higher.
Bearish signals lower the percentage.
A neutral score indicates indecision, signaling a potential range-bound or consolidating market.This consolidated signal allows traders to make quicker decisions without having to interpret several individual indicators, making the tool more user-friendly and practical for daily trading.
Why TFCI’s Combination is Unique and Useful 🔍
What makes TFCI stand out is how each of these indicators works together to offer a more comprehensive view of the market:
Reduced Noise: By combining multiple indicators, TFCI reduces the likelihood of acting on false signals. The integration of smoothing mechanisms and volume-based confirmations further increases signal reliability.
More Balanced Analysis: Using indicators that analyze price, volume, volatility, and trend strength, TFCI provides a balanced view of market conditions. Traders can trust that the signal reflects multiple facets of the market rather than just one aspect, making it more adaptable to different market environments.
Easier to Read: Instead of juggling multiple charts or relying on complex setups, TFCI combines everything into one clear percentage and visual signal. This saves time and reduces the complexity of decision-making.
Tested Across Market Conditions 📅
While no indicator can predict the future, TFCI has been tested in a range of market conditions. Its ability to adapt to different environments (trending, volatile, or range-bound) makes it a versatile tool, though like any technical tool, it should be used alongside other forms of analysis and risk management.
Custom Display Options for Readability 📊
To make TFCI even more versatile, it includes two display modes:
Table Mode: This mode breaks down the signals from each component, showing traders exactly how each element is contributing to the overall confidence score. Ideal for those who want to dig deeper into the details.
Gauge Mode: A simplified visual display, perfect for traders who want a quick, at-a-glance view of market conditions.
Color Blindness Mode 🌈
TFCI also includes several color palettes for traders affected by color blindness, ensuring everyone can easily interpret the signals.
Conclusion 🔒
TFCI brings together multiple technical indicators in a unique way that aims to improve trend detection by providing a balanced and easy-to-read signal. Its proprietary adjustments and combination of price, volume, and volatility indicators offer a comprehensive view of market conditions, making it a valuable tool for traders of all experience levels. However, it is essential to remember that no past performance can guarantee future results.
BRT MACD CustomBRT MACD Custom — Adaptive and Flexible MACD for Multi-Timeframe Analysis
The BRT MACD Custom is an advanced version of the traditional MACD indicator, offering additional flexibility and adaptability for multi-timeframe trading. This custom script allows traders to adjust the calculation parameters for MACD to suit their specific trading strategy, timeframe, and market conditions.
Key Features
Multi-Timeframe Support
Unlike the standard MACD, this indicator lets you choose a specific timeframe (different from the chart timeframe) for calculating MACD values. This feature provides more flexibility in analyzing market trends on multiple timeframes without changing the main chart.
Example: You can analyze MACD on a 15-minute timeframe even when your chart is set to 1-minute, giving you broader market insights.
Customizable EMA and Signal Settings
Users can adjust the fast and slow EMA lengths as well as the signal smoothing to better align with their preferred trading strategies. The script allows switching between the two popular types of moving averages — SMA or EMA — for both the MACD and the signal line.
Volatility-Based Adaptive EMA
The script includes an adaptive mechanism for EMA calculation. When the selected timeframe closes, the indicator dynamically adjusts the calculation, ensuring the MACD values respond quickly to market volatility. This makes the indicator more reactive compared to static MACD implementations.
Shift Options for MACD, Signal, and Histogram
The indicator allows shifting the MACD, signal line, and histogram values by one or more bars. This can be useful for backtesting and simulating strategies where you anticipate future price movements.
Signal Alerts for Long and Short Trades
The script generates visual signals when certain conditions are met, indicating potential long or short trade opportunities. These signals are based on MACD and histogram crossovers:
Long Signal: Triggered when MACD is above the signal line and both are rising.
Short Signal: Triggered when MACD is below the signal line and both are falling.
Custom Plotting
The MACD line, signal line, and histogram are plotted on the chart for easy visualization. The histogram changes colors to reflect positive or negative momentum:
Green shades when MACD is above the signal line.
Red shades when MACD is below the signal line.
Applications in Trading
The BRT MACD Custom is ideal for traders who need flexibility in their technical analysis. Its multi-timeframe capabilities and customizable moving averages make it suitable for day trading, swing trading, and long-term investing across a variety of markets.
Scalping: Use the 1-minute or 5-minute timeframe to identify short-term trends while calculating MACD on a higher timeframe such as 15 or 30 minutes.
Swing Trading: Apply the indicator on 1-hour or 4-hour charts to detect mid-term trends.
Long-Term Investing: Analyze daily or weekly charts with longer EMA periods to confirm market direction before making large investments.
Cubic Bezier Curve RSI [CBCR]Overview :
Introducing the Cubic Bézier Curve RSI – an innovative approach to smoothing the traditional RSI using cubic Bézier curves. This indicator provides traders with a smoother, adaptive version of the RSI that can help filter out noise and better highlight market trends.
Key Features:
Bézier Curve : the script uses cubic Bézier curves to create a smoothed version of the RSI, offering a more visually appealing and potentially more insightful representation of market momentum.
Customizable Settings: Users can adjust the Bézier Curve Length, Impact Factor, and color modes, allowing full customization of the smoothing effect and visualization.
Color-coded Trend Indicator: The smoothed RSI is displayed with colors that indicate potential bullish or bearish trends, helping traders quickly assess market conditions.
Overbought/Oversold Lines: Option to display overbought and oversold levels for better identification of market extremes.
Parameters:
RSI Length: Set the length for the traditional RSI calculation (default is 14).
Bézier Curve Length: Adjust the length of the Bézier curve used to smooth the RSI (default is 20).
Impact Factor: Control the influence of the Bézier smoothed values versus the original RSI values (default is 0.5, ranging from 0.0 to 1.0).
Overbought/Oversold Lines: Option to show overbought (default: 70) and oversold (default: 30) lines for easier identification of extreme conditions.
Color Mode: Choose between "Trend Following" and "Overbought/Oversold" modes for line color indication.
Display Settings: Color customization for bullish and bearish phases allows better visual differentiation.
How It Works:
The CBCR uses four control points derived from historical RSI values over a user-defined length. It then applies the cubic Bezier formula to generate a sequence of points representing a smoothed version of the RSI over this range.
The Bezier curve is recalculated each time a specific number of bars (as defined by the Bezier Curve Length) have passed, helping reduce noise while retaining key trend information.
The result is a smoothed RSI that combines the adaptability of cubic Bezier curves with the familiar oscillation of the RSI, making it potentially more robust for identifying shifts in market sentiment.
Visuals:
Smoothed RSI Line: Plotted on the indicator pane, the line changes color depending on the chosen color mode:
Trend Following Mode: Color changes based on whether the smoothed RSI is above or below the 50-level.
Overbought/Oversold Mode: Color changes based on whether the smoothed RSI is above the overbought level or below the oversold level.
Bullish Color: Configurable (default: cyan).
Bearish Color: Configurable (default: red).
Overbought/Oversold Lines: Horizontal lines at user-defined levels (default: 70 for overbought, 30 for oversold) for easy identification of market extremes.
Usage:
The CBCR can be used like a traditional RSI but with a smoother output that may help traders avoid false signals generated by sudden price spikes. For instance:
Look for crossovers around the 50 level as a signal for changing momentum.
Use the overbought and oversold levels to identify potential reversal zones.
Observe the color change of the line for an immediate visual cue on current sentiment.
