E9 PLRRThe E9 PLRR (Power Law Residual Ratio) is a custom-built indicator designed to evaluate the overvaluation or undervaluation of an asset, specifically by utilizing logarithmic price data and a power law-based model. It leverages a dynamic regression technique to assess the deviation of the current price from its expected value, giving insights into how much the price deviates from its long-term trend.
This indicator is primarily used to detect market extremes and cycles, often used in the analysis of long-term price movements in assets like Bitcoin, where cyclical behavior and significant price deviations are common.
This chart is back from 2019 and shows (From left to right) 2018 Bear market bottom at $3.5k (Dark Blue) , following a peak at 12k (dark red) before the Covid crash back down to EUROTLX:4K (Dark blue)
Key Components
Logarithmic Price Data:
The indicator works with logarithmic price data (ohlc4), which represents the average of open, high, low, and close prices. The logarithmic transformation is crucial in financial modeling, especially when analyzing long-term price data, as it normalizes exponential price growth patterns.
Dynamic Exponent 𝑘:
The model calculates a dynamic exponent k using regression, which defines the power law relationship between time and price. This exponent is essential in determining the expected power law price return and how far the current price deviates from that expected trend.
Power Law Price Return:
The power law price return is computed using the dynamic exponent
k over a defined period, such as 365 days (1 year). It represents the theoretical price return based on a power law relationship, which is used to compare against the actual logarithmic price data.
Risk-Free Rate:
The indicator incorporates an adjustable risk-free rate, allowing users to model the opportunity cost of holding an asset compared to risk-free alternatives. By default, the risk-free rate is set to 0%, but this can be modified depending on the user's requirements.
Volatility Adjustment:
A key feature of the PLRR is its ability to adjust for price volatility. The indicator smooths out short-term price fluctuations using a moving average, helping to detect longer-term cycles and trends.
PLRR Calculation:
The core of the indicator is the calculation of the Power Law Residual Ratio (PLRR). This is derived by subtracting the expected power law price return and risk-free rate from the logarithmic price return, then multiplying the result by a user-defined multiplier.
Color Gradient:
The PLRR values are represented visually using a color gradient. This gradient helps the user quickly identify whether the asset is in an undervalued, fair value, or overvalued state:
Dark Blue to Light Blue: Indicates undervaluation, with increasing blue tones representing a higher degree of undervaluation.
Green to Yellow: Represents fair value, where the price is aligned with the expected power law return.
Orange to Dark Red: Indicates overvaluation, with increasing red tones representing a higher degree of overvaluation.
Zero Line:
A zero line is plotted on the indicator chart, serving as a reference point. Values above the zero line suggest potential overvaluation, while values below indicate potential undervaluation.
Dots Visualization:
The PLRR is plotted using dots, with each dot color-coded based on the PLRR value. This dot-based visualization makes it easier to spot significant changes or reversals in market sentiment without overwhelming the user with continuous lines.
Bar Coloring:
The chart’s bars are colored in accordance with the PLRR value at each point in time, making it visually clear when an asset is potentially overvalued or undervalued.
Indicator Functionality
Cycle Identification : The E9 PLRR is especially useful for identifying cyclical market behavior. In assets like Bitcoin, which are known for their boom-bust cycles, the PLRR can help pinpoint when the market is likely entering a peak (overvaluation) or a trough (undervaluation).
Overvaluation and Undervaluation Detection: By comparing the current price to its expected power law return, the PLRR helps traders assess whether an asset is trading above or below its fair value. This is critical for long-term investors seeking to enter the market at undervalued levels and exit during periods of overvaluation.
Trend Following: The indicator helps users identify the broader trend by smoothing out short-term volatility. This makes it useful for both momentum traders looking to ride trends and contrarian traders seeking to capitalize on market extremes.
Customization
The E9 PLRR allows users to fine-tune several parameters based on their preferences or specific market conditions:
Lookback Period:
The user can adjust the lookback period (default: 100) to modify how the moving average and regression are calculated.
Risk-Free Rate:
Adjusting the risk-free rate allows for more realistic modeling of the opportunity cost of holding the asset.
Multiplier:
The multiplier (default: 5.688) amplifies the sensitivity of the PLRR, allowing users to adjust how aggressively the indicator responds to price movements.
This indicator was inspired by the works of Ashwin & PlanG and their work around powerLaw. Thank you. I hall be working on the calculation of this indicator moving forward to make improvements and optomisations.
Centered Oscillators
E9 MACD
The E9 MACD (Moving Average Convergence Divergence) indicator is a powerful tool used in technical analysis to help traders identify potential buy and sell signals based on price action. It is designed to provide clear visual cues and alerts for trading decisions. Here’s how it applies to price action and its key functionalities:
Key Features and Functionality
MACD Line and Signal Line:
MACD Line: Represents the difference between a fast and a slow moving average of the price. It helps in identifying the momentum of the price movement.
Signal Line: A smoothed average of the MACD Line, used to generate trading signals when the MACD Line crosses above or below it.
Histogram: The histogram shows the difference between the MACD Line and the Signal Line. It visually represents the strength of the trend, with positive values indicating bullish momentum and negative values indicating bearish momentum.
Trend Coloring:
Uptrend: When the MACD Line is above the Signal Line, the bars can be colored green to indicate a potential buying opportunity.
Downtrend: When the MACD Line is below the Signal Line, the bars can be colored red to signal a potential selling opportunity.
Timeframe Flexibility:
The E9 MACD can be adjusted to different timeframes, allowing traders to analyze short-term or long-term trends based on their trading strategy. This flexibility helps in tailoring the indicator’s analysis to different market conditions.
Visual Alerts and Highlights:
The indicator includes options to highlight price bars and background colors when significant crossovers occur, making it easier to spot key trading signals.
Circles can be plotted on the MACD Line to indicate cross events, enhancing visual clarity.
Customizable Appearance:
Traders can customize the appearance of the MACD Line, Signal Line, and Histogram, including color and line width, to suit their personal preferences and improve readability.
Alerts for Trading Signals:
The E9 MACD can generate alerts for crossovers of the MACD Line and Signal Line, helping traders stay informed of potential trading opportunities even when they are not actively monitoring the charts.
Application in Trading
The E9 MACD is particularly useful for:
Identifying potential entry and exit points based on the crossing of the MACD Line and Signal Line.
Gauging the strength of the current trend through the histogram.
Adjusting to different timeframes to align the indicator with various trading strategies, from day trading to long-term investing.
By providing clear visual indicators and alerts, the E9 MACD helps traders make more informed decisions and better understand the momentum and direction of price movements.
GKD-C Wavelet Oscillator [Loxx]The Giga Kaleidoscope GKD-C Wavelet Oscillator is a Confirmation module included in AlgxTrading's "Giga Kaleidoscope Modularized Trading System."
█ GKD-C Wavelet Oscillator, a brief overview
The Wavelet Oscillator is an advanced technical analysis tool that integrates wavelet transformations with the Kalman filter to provide a nuanced understanding of market trends and momentum. At the heart of this oscillator is the Haar wavelet transform, a mathematical technique that breaks down price data into different frequency components. The Haar transform works by analyzing the price series in pairs, calculating the average and difference between adjacent data points, effectively separating the underlying signal (trend) from noise or minor fluctuations. This decomposition allows the oscillator to isolate significant price movements and reconstruct them with greater clarity through the inverse Haar transform. The Kalman filter is then applied to further smooth the signal, refining the data and reducing the impact of short-term volatility.
This process enhances the oscillator's ability to detect subtle shifts in market dynamics that might be missed by conventional indicators. The GKD-C Wavelet Oscillator utilizes these refined signals to generate two types of trading signals: Zero-line crosses, where the oscillator moves above or below a central reference point, indicating potential bullish or bearish momentum, and Signal crosses, where the current oscillator value crosses its previous value, signaling possible trend reversals. These features make the Wavelet Oscillator particularly effective in identifying key turning points in the market, providing traders with a powerful tool for anticipating and responding to changes in price momentum within the GKD trading system. (Read the sections below to learn how traders can test these different signal types using AlgxTrading's GKD trading system.)
GKD-C Wavelet Oscillator in Zero-line crosses mode
GKD-C Wavelet Oscillator in Signal crosses mode
To explain the features included in the GKD-C Wavelet Oscillator, let's first dive into the details of the Giga Kaleidoscope (GKD) Modularized Trading System.
█ Giga Kaleidoscope (GKD) Modularized Trading System
The GKD Trading System is a comprehensive, algorithmic trading framework from AlgxTrading, designed to optimize trading strategies across various market conditions. It employs a modular approach, incorporating elements such as volatility assessment, trend identification through a baseline, multiple confirmation strategies for signal accuracy, and volume analysis. Key components also include specialized strategies for entry and exit, enabling precise trade execution. The system allows for extensive backtesting, providing traders with the ability to evaluate the effectiveness of their strategies using historical data. Aimed at reducing setup time, the GKD system empowers traders to focus more on strategy refinement and execution, leveraging a wide array of technical indicators for informed decision-making.
🔶 Core components of a GKD Algorithmic Trading System
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system. The GKD algorithm is built on the principles of trend, momentum, and volatility. There are eight core components in the GKD trading algorithm:
🔹 Volatility - In the GKD trading system, volatility is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. There are 17+ different types of volatility available in the GKD system including Average True Range (ATR), True Range Double (TRD), Close-to-Close, Garman-Klass, and more.
🔹 Baseline (GKD-B) - The baseline is essentially a moving average and is used to determine the overall direction of the market. The baseline in the GKD trading system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other GKD indicators.
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards or price is above the baseline, then only long trades are taken, and if the baseline is sloping downwards or price is below the baseline, then only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
🔹 Confirmation 1, Confirmation 2, Continuation (GKD-C) - The GKD trading system incorporates technical confirmation indicators for the generation of its primary long and short signals, essential for its operation.
The GKD trading system distinguishes three specific categories. The first category, Confirmation 1, encompasses technical indicators designed to identify trends and generate explicit trading signals. The second category, Confirmation 2, a technical indicator used to identify trends; this type of indicator is primarily used to filter the Confirmation 1 indicator signals; however, this type of confirmation indicator also generates signals*. Lastly, the Continuation category includes technical indicators used in conjunction with Confirmation 1 and Confirmation 2 to generate a special type of trading signal called a "Continuation"
In a full GKD trading system all three categories generate signals. (see the section “GKD Trading System Signals” below)
🔹 Volatility/Volume (GKD-V) - Volatility/Volume indicators are used to measure the amount of buying and selling activity in a market. They are based on the trading Volatility/Volume of the market, and can provide information about the strength of the trend. In the GKD trading system, Volatility/Volume indicators are used to confirm trading signals generated by the various other GKD indicators. In the GKD trading system, Volatility is a proxy for Volume and vice versa.
Volatility/Volume indicators reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by GKD-C confirmation and GKD-B baseline indicators.
🔹 Exit (GKD-E) - The exit indicator in the GKD system is an indicator that is deemed effective at identifying optimal exit points. The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
🔹 Backtest (GKD-BT) - The GKD-BT backtest indicators link all other GKD-C, GKD-B, GKD-E, GKD-V, and GKD-M components together to create a GKD trading system. GKD-BT backtests generate signals (see the section “GKD Trading System Signals” below) from the confluence of various GKD indicators that are imported into the GKD-BT backtest. Backtest types include: GKD-BT solo and full GKD backtest strategies used for a single ticker; GKD-BT optimizers used to optimize a single indicator or the full GKD trading system; GKD-BT Multi-ticker used to backtest a single indicator or the full GKD trading system across up to ten tickers; GKD-BT exotic backtests like CC, Baseline, and Giga Stacks used to test confluence between GKD components to then be injected into a core GKD-BT Multi-ticker backtest or single ticker strategy.
🔹 Metamorphosis (GKD-M)** - The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, GKD-E, or GKD-V slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
*(see the section “GKD Trading System Signals” below)
**(not a required component of the GKD algorithm)
🔶 What does the application of the GKD trading system look like?
Example trading system:
Volatility: Average True Range (ATR) (selectable in all backtests and other related GKD indicators)
GKD-B Baseline: GKD-B Multi-Ticker Baseline using Hull Moving Average
GKD-C Confirmation 1: GKD-C Advance Trend Pressure
GKD-C Confirmation 2: GKD-C Dorsey Inertia
GKD-C Continuation: GKD-C Stochastic of RSX
GKD-V Volatility/Volume: GKD-V Damiani Volatmeter
GKD-E Exit: GKD-E MFI
GKD-BT Backtest: GKD-BT Multi-Ticker Full GKD Backtest
GKD-M Metamorphosis: GKD-M Baseline Optimizer
**all indicators mentioned above are included in the same AlgxTrading package**
Each module is passed to a GKD-BT backtest module. In the backtest module, all components are combined to formulate trading signals and statistical output. This chaining of indicators requires that each module conform to AlgxTrading's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the various indictor types in the GKD algorithm.
🔶 GKD Trading System Signals
🔹 Standard Entry requires a sequence of conditions including a confirmation signal from GKD-C, baseline agreement, price criteria related to the Goldie Locks Zone, and concurrence from a second confirmation and volatility/volume indicators.
🔹 1-Candle Standard Entry introduces a two-phase process where initial conditions must be met, followed by a retraction in price and additional confirmations in the subsequent candle, including baseline, confirmations 1 and 2, and volatility/volume criteria.
🔹 Baseline Entry focuses on signals generated by the GKD-B Baseline, requiring agreement from confirmation signals, specific price conditions within the Goldie Locks Zone, and a timing condition related to the confirmation 1 signal.
🔹 1-Candle Baseline Entry mirrors the baseline entry but adds a requirement for a price retraction and subsequent confirmations in the following candle, maintaining the focus on the baseline's guidance.
🔹 Volatility/Volume Entry is predicated on signals from volatility/volume indicators, requiring support from confirmations, price criteria within the Goldie Locks Zone, baseline agreement, and a timing condition for the confirmation 1 signal.
🔹 1-Candle Volatility/Volume Entry adapts the volatility/volume entry to include a phase of initial signal and agreement, followed by a retracement phase that seeks further agreement from the system's components in the subsequent candle.
🔹 Confirmation 2 Entry is based on the second confirmation signal, requiring the first confirmation's agreement, specific price criteria, agreement from volatility/volume indicators, and baseline, with a timing condition for the confirmation 1 signal.
🔹 1-Candle Confirmation 2 Entry adds a retracement requirement to the confirmation 2 entry, necessitating additional agreements from the system's components in the candle following the signal.
🔹 PullBack Entry initiates with a baseline signal and agreement from the first confirmation, with a price condition related to volatility. It then looks for price to return within the Goldie Locks Zone and seeks further agreement from the system's components in the subsequent candle.
🔹 Continuation Entry allows for the continuation of an active position, based on a previously triggered entry strategy. It requires that the baseline hasn't crossed since the initial trigger, alongside ongoing agreements from confirmations and the baseline.
█ GKD-C Wavelet Oscillator, a deep dive
Now that you have a basic understanding of the GKD trading system. let's dive deeper into the features included in the GKD-C Wavelet Oscillator
🔶 GKD-C Wavelet Oscillator Modes aka "Confirmation Type"
The GKD-C Wavelet Oscillator has 4 modes: Confirmation for confirmation 1 and 2; Continuation; Multi-ticker for multi-ticker confirmation 1 and 2; and Optimizer.
🔹 Confirmation: When in this mode, the GKD-C Wavelet Oscillator generates confirmation 1 and 2 signals. These values can then be exported to a GKD-BT backtest strategy.
Signal Key: L = Long, S = Short
GKD-C Wavelet Oscillator in Confirmation mode
Confirmation Exports
GKD-C Wavelet Oscillator in attached to a GKD-BT backtest strategy
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
🔹 Continuation: When in this mode, the GKD-C Wavelet Oscillator generates continuation signals.
Signal Key: L = Long, S = Short, CL = Continuation Long, CS = Continuation Short
GKD-C Wavelet Oscillator in Continuation mode
Continuation Exports
🔹 Multi-ticker: When in this mode, the GKD-C Wavelet Oscillator generates multi-ticker confirmation 1 and 2. This mode allows users to generate confirmation 1 and 2, and continuation signals for up to 10 different tickers. These values can then be exported to a GKD-BT Multi-ticker backtest.
Signal Key: L = Long, S = Short
GKD-C Wavelet Oscillator in Multi-ticker mode
Multi-ticker Exports
GKD-C Wavelet Oscillator attached to the GKD-BT Multi-ticker SCS Backtest
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
🔹 Optimizer: When in this mode, the GKD-C Wavelet Oscillator generates optimization signals. These signals allow the user to backtest a range of input values. These values are exported to a GKD-BT optimizer backtest.
Signal Key: L = Long, S = Short
GKD-C Wavelet Oscillator in Optimizer mode
Optimizer Inputs and Exports
GKD-C Wavelet Oscillator attacked to the GKD-BT Optimizer SCS Backtest
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
█ Conclusion
The GKD-C Wavelet Oscillator serves as a multi-modal component of the GKD trading system allowing traders to optimize and backtest acorss a range of input parameters and tickers. These features decrease total build time required to create a custom GKD algorithmic trading system by allowing users to spend more time trading and less time guessing.
█ How to Access
You can see the Author's Instructions below to learn how to get access.
Commodity Index For Loop | viResearchCommodity Index For Loop | viResearch
Conceptual Foundation and Innovation
The "Commodity Index For Loop" indicator from viResearch is a momentum-based system designed to measure the deviation of the commodity’s closing price from its moving average (MA), normalized by volatility. This indicator uses a for-loop mechanism to evaluate how frequently the price exceeds or falls below specified thresholds, generating a momentum score. By comparing the price to the moving average and applying a volatility factor, the indicator provides a dynamic view of overbought and oversold conditions. The use of a for-loop helps capture the strength of market moves over a customizable range, offering traders deeper insight into market trends.
This innovative approach allows traders to assess market conditions more accurately, identifying potential trend reversals and momentum shifts with greater precision.
Technical Composition and Calculation
The "Commodity Index For Loop" indicator is built on two main components: the commodity price’s deviation from the moving average and a for-loop-based scoring system. The deviation is calculated by subtracting the simple moving average (SMA) of the close from the current closing price and dividing the result by the product of volatility (expressed as the standard deviation) and a constant factor. This normalizes the deviation, accounting for the inherent volatility in the market.
The for-loop mechanism assesses the deviation over a user-defined range (from a to b). The script counts how many times the deviation exceeds or falls below the thresholds, generating a score that reflects the overall market momentum. This score is then compared to two thresholds, one indicating an uptrend and the other a downtrend, which triggers buy and sell signals.
Features and User Inputs
The "Commodity Index For Loop" script offers several customizable inputs, allowing traders to fine-tune the indicator’s behavior according to their strategies. These include:
Length: Defines the period for the moving average and standard deviation, determining how sensitive the indicator is to price changes. For Loop Range: Allows traders to set the range over which the deviation is evaluated, controlling how the scoring system responds to market conditions. Thresholds: Traders can set custom uptrend and downtrend thresholds, specifying when the score should trigger buy or sell signals. Bar Color Settings: Enables traders to color the bars based on the signals generated by the indicator, providing a clearer visual representation of the trend. Practical Applications
The "Commodity Index For Loop" indicator is ideal for traders looking to analyze momentum and trend shifts in commodity markets. By using the for-loop mechanism, the indicator provides a detailed assessment of market conditions, making it particularly useful for:
Identifying Momentum Shifts: The scoring system evaluates the strength of price movements relative to the moving average, providing early signals of potential momentum reversals. Spotting Overbought and Oversold Conditions: The deviation score helps traders detect extreme price levels, allowing for better timing of market entries and exits. Confirming Trend Direction: The script monitors whether the commodity is in an uptrend or downtrend, improving traders’ ability to stay aligned with the prevailing market trend. Advantages and Strategic Value
The "Commodity Index For Loop" script offers significant value by combining the simplicity of a moving average with the advanced analysis provided by a for-loop scoring system. The indicator’s ability to measure price deviations from the moving average, normalized by volatility, helps traders detect trends while reducing the noise caused by short-term price fluctuations. The customizable thresholds and scoring system provide a flexible tool for analyzing market momentum, making the indicator suitable for various trading strategies.
This indicator is particularly valuable for traders who focus on commodities, as it offers a robust framework for identifying market trends and spotting potential turning points. The combination of momentum analysis and trend detection enhances the accuracy of buy and sell signals, providing greater confidence in trading decisions.
Alerts and Visual Cues
The script includes built-in alert conditions to notify traders when key trend changes occur. A "Commodity Index For Loop Long" alert is triggered when the score crosses above the uptrend threshold, signaling a potential upward trend, while a "Commodity Index For Loop Short" alert signals a possible downward trend when the score falls below the downtrend threshold. Color-coded bar plots and filled zones on the chart provide clear visual cues to help traders interpret market conditions in real-time.
Summary and Usage Tips
The "Commodity Index For Loop | viResearch" indicator is a powerful tool for analyzing market momentum and detecting potential reversals in commodity prices. By combining price deviation from a moving average with a for-loop scoring system, the indicator offers a comprehensive view of market trends. Incorporating this script into your trading strategy can improve your ability to detect momentum shifts, confirm trend direction, and manage risk more effectively. The "Commodity Index For Loop" provides a reliable and customizable solution for traders seeking to refine their technical analysis in commodity markets.
Note: Backtests are based on past results and are not indicative of future performance.
Power MarketPower Market Indicator
Description: The Power Market Indicator is designed to help traders assess market strength and make informed decisions for entering and exiting positions. This innovative indicator provides a comprehensive view of the evolution of Simple Moving Averages (SMA) over different periods and offers a clear measure of market strength through a total score.
Key Features:
Multi-Period SMA Analysis:
Calculates Simple Moving Averages (SMA) for 10 different periods ranging from 10 to 100.
Provides detailed analysis by comparing the current closing price with these SMAs.
Market Strength Measurement:
Assesses market strength by calculating a total score based on the relationship between the closing price and the SMAs.
The total score is displayed as a histogram with distinct colors for positive and negative values.
Smoothed Curve for Better View:
A smoothing of the total score is applied using a 5-period Simple Moving Average to represent the overall trend more smoothly.
Dynamic Information Table:
Real-time display of the maximum and minimum values among the SMAs, as well as the difference between these values, providing valuable insights into the variability of moving averages.
Visual Reference Lines:
Horizontal lines at zero, +50, and -50 for easy evaluation of key score levels.
How to Use the Indicator:
Position Entries: Use high positive scores to identify buying opportunities when market strength is strong.
Position Exits: Negative scores may signal market weakness, allowing you to exit positions or wait for a better opportunity.
Data Analysis: The table helps you understand the variability of SMAs, offering additional context for your trading decisions.
This powerful tool provides an in-depth view of market dynamics and helps you navigate your trading strategies with greater confidence. Embrace the Power Market Indicator and optimize your trading decisions today!
The real breakout indicator CCI + Money Flow + Buy / SellComponents of the indicator
1. CCI (Commodity Channel Index)
The CCI component measures the deviation of the price from its statistical average. It is used to identify overbought or oversold conditions and is integrated into the trend logic to determine potential trend reversals. High values may indicate overbought conditions, while low values could signify oversold situations.
Detailed
The CCI (Commodity Channel Index) used in "The Real Breakout Indicator Hawk" is an enhanced version compared to the traditional CCI, offering several advantages:
1. Weighting and Smoothing Mechanism
In this version, the CCI values are weighted and smoothed using custom parameters (c1, c2, c3), which allows for greater flexibility in adjusting the sensitivity of the CCI to market conditions. This smoothing reduces noise and provides clearer signals compared to the standard CCI, which can be prone to whipsaws in volatile markets.
2. Multi-level Calculation
The indicator uses an array-based approach to calculate multiple variations of CCI values (with p as the parameter for different levels of calculation), which is then combined to create a more robust signal. This multi-level approach allows for capturing different market cycles, unlike the traditional CCI that only uses a single period for calculation.
3. Integration with Moving Averages and Trend Detection
Unlike the original CCI, which is often used in isolation, this version integrates with the trend detection logic by combining it with moving averages and money flow. The enhanced CCI contributes to the broader trend analysis, ensuring that buy/sell signals are not just based on CCI overbought/oversold levels but also validated by moving averages and slope calculations.
4. Trend-Weighted CCI
This version adds weight to recent price action trends, making it more adaptive to current market momentum. The CCI values are influenced by recent high and low prices, adding a trend-following aspect that is missing from the original CCI, which treats all price deviations equally.
This image of EURAD shows for example that when CCI component is green a strong trend is detected which can hold for up to 10 days in this example, ideal for swing trades;
EURAUD 2H
5. Improved Overbought/Oversold Detection
The script incorporates a dynamic overbought/oversold detection zone based on the enhanced CCI. It accounts for market volatility, allowing it to adjust its thresholds (such as the 200 level) more effectively in different market environments. This makes the enhanced CCI better suited for varying market conditions compared to the fixed thresholds of the original CCI.
You can see that the red diamond signal is generated at the absolute top of the price range after which price started to reverse, the detection is based on a cross over value together with Money Flow strength
BTCUSDT 2H
6. Strong Buy/Sell Confirmation
The enhanced CCI works in tandem with other components like Money Flow and Moving Averages to confirm buy or sell signals. This cross-validation makes the indicator less reliant on CCI alone and ensures that the signals generated are stronger and less prone to false positives, which is a common issue with the standalone CCI.
The green diamond buy signal in a strong downtrend is mostly a short retrace of price before continuing down further, yo can use this as an entry signal after the bounce up into an FVG for example. However when price is at a support, meaning price is not moving down further and this occurs this could be a potential reversal signal as shown on the right side on the chart below. FVG is not respected, retested and price continues up.
BTCUSDT 2H
Summary:
In summary, the enhanced CCI in this indicator improves over the original CCI by providing better noise reduction, multi-level analysis, trend integration, and adaptability to different market conditions. These improvements lead to more reliable and actionable trading signals.
2. Money Flow (MF) www.tradingview.com
The Money Flow component tracks the flow of capital in and out of an asset. Positive values indicate strong buying pressure, while negative values show selling pressure. This is smoothed to avoid noise and is used to confirm strong buy or sell conditions.
The Money Flow (MF) in "The Real Breakout Indicator Hawk" measures the flow of capital into or out of an asset, helping to assess the underlying buying or selling pressure in the market.
1. Positive Money Flow (Buying Pressure)
When the MF is positive, it indicates that more money is flowing into the asset, which suggests strong buying interest. This helps confirm that a price increase or breakout to the upside is supported by demand.
2. Negative Money Flow (Selling Pressure)
A negative MF indicates that capital is leaving the asset, reflecting selling pressure. This is a sign that the market is under bearish conditions, and prices are likely to decline or break down.
3. Confirmation of Buy and Sell Signals
The MF is used to confirm buy and sell signals generated by other components of the indicator. When the MF aligns with other bullish signals, it strengthens the buy condition, and similarly, when the MF shows strong selling pressure, it reinforces a sell signal.
4. Filtering Noise
The MF is smoothed to filter out noise, ensuring that only significant movements in buying or selling pressure are considered. This helps avoid false signals and makes the MF a reliable tool for detecting true market strength.
5. Range Sensitivity
The MF operates within defined ranges, ensuring that buy or sell signals are only triggered when the flow of money is strong enough, adding precision to signal generation.
In summary, the Money Flow component is crucial for validating market direction, enhancing signal reliability, and helping traders make more informed decisions based on the underlying capital movement in the market.
3. Moving Averages (MA)
Multiple types of moving averages (SMA, EMA, HMA, etc.) are used to smooth price action and highlight the trend direction. The script supports different types of moving averages, and their slopes are calculated to assist in identifying changes in trend momentum.
The Moving Averages (MA) section of "The Real Breakout Indicator Hawk" plays a critical role in smoothing price data, identifying trends, and generating buy/sell signals. Here’s a breakdown of what it does and how you can use it effectively without diving into the script:
1. Moving Average Types
This section allows the user to choose from different types of moving averages, each with unique characteristics:
SMA (Simple Moving Average): Takes the average of closing prices over a specific period. It’s slower and better suited for detecting long-term trends.
EMA (Exponential Moving Average): Gives more weight to recent prices, making it more responsive to new price action and suitable for short-term trading.
HMA (Hull Moving Average): A smoother and faster moving average, useful for reducing lag in fast-moving markets.
LVMA (Linear Weighted Moving Average): Places the most weight on recent prices, making it even more responsive than EMA.
Alma (Arnaud Legoux Moving Average): A smoother version that reduces noise while maintaining responsiveness to recent price action.
2. Smoothing and Trend Detection
The moving average smooths out price data to remove small fluctuations and focuses on the overall trend. When prices are trading above the moving average, it suggests that the market is in an uptrend. When prices are below the moving average, it indicates a downtrend.
3. Trend Confirmation
The moving average serves as a confirmation tool. When the price crosses above the moving average, it could signal the start of a bullish trend, and when the price crosses below, it may indicate the beginning of a bearish trend.
4. Buy and Sell Signals
Buy Signal: The system detects a buy signal when:
The moving average crosses above 0, indicating a potential upward momentum.
Other indicators like Money Flow and CCI align to confirm the trend.
Sell Signal: A sell signal is triggered when:
The moving average crosses below 0, signaling a potential downtrend.
This signal is further validated by other components such as Money Flow and CCI to reduce false signals.
5. Using Moving Averages in Trading
Crossover Strategy: One of the simplest ways to use moving averages is by employing a crossover strategy. For instance:
When the shorter-term moving average (e.g., 20-period) crosses above a longer-term moving average (e.g., 50-period), this is a bullish crossover, indicating a buy signal.
Conversely, when the shorter-term moving average crosses below the longer-term moving average, this is a bearish crossover, indicating a sell signal.
Trend Following: If you’re trading with the trend, you can use a moving average to stay in the trade as long as the price remains above (for long positions) or below (for short positions) the moving average.
Support and Resistance: Moving averages can also act as dynamic support or resistance levels. For example, in an uptrend, the CCI might bounce off the moving average, offering a good entry point for a long position. In a downtrend, the moving average could act as resistance where prices may reverse, offering a shorting opportunity.
To use the MA section effectively:
Choose the right type of moving average based on your trading style (e.g., use EMA for faster response or SMA for long-term trends).
Watch for crossovers as buy/sell signals, especially in combination with other indicators.
Follow the trend by observing whether the price is above or below the moving average.
Use the moving average as a dynamic support/resistance level to find optimal entry/exit points.
This approach makes the moving average a versatile tool for identifying trends, refining entry and exit points, and confirming overall market direction.
an example when MA crosses below 0, keep in mind that when it it starts curving up and turning green there is a reversal brewing, this could take time...
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4. Buy Signals
Buy signals are generated when the moving average crosses up, and the Money Flow and other trend-based conditions are met, including CCI levels confirming the strength of the breakout. Additionally, slope calculations and other momentum indicators provide extra confirmation for entries.
5. Sell Signals
Sell signals occur when the moving average crosses down, combined with negative Money Flow, confirming downward pressure. Other trend-based conditions, including the CCI, must also align to validate the signal, and slope calculations ensure that momentum is on the sell side.
6. Slope and Trend Detection
The script includes calculations for the slope of price action over a lookback period to measure trend strength and direction. The slope is normalized to help identify when the market is gaining or losing momentum. This slope is used in conjunction with the moving averages and Money Flow to give more accurate trend signals.
The Slope and Trend Detection component in "The Real Breakout Indicator Hawk" is designed to measure the direction and strength of the market’s trend by calculating the slope of the price action over a specific period. This helps to identify whether the market is gaining or losing momentum, and it is a key element in refining buy/sell signals.
Here’s how the Slope and Trend Detection works and how you can use it effectively without diving into the script:
1. Slope Calculation
Slope is essentially the rate of change of the moving average (or price) over a given number of bars. It measures how steeply the price is moving up or down.
The script calculates the slope by measuring the difference between the moving average over a defined number of bars (e.g., 12 bars in this case). A larger slope indicates a stronger trend, while a smaller slope suggests a weaker or consolidating trend.
2. Normalized Slope
The slope is normalized, meaning it is adjusted to fall within a range that makes it easier to compare across different time frames and markets. This normalization helps to gauge whether the slope is strong or weak relative to historical data.
Positive slopes (above 0) indicate an uptrend or rising price momentum, while negative slopes (below 0) indicate a downtrend or falling price momentum.
3. Trend Detection
The slope of the moving average is used to detect the current trend:
If the slope is positive, the market is in an uptrend.
If the slope is negative, the market is in a downtrend.
The stronger the slope (the steeper it is), the stronger the trend. A small slope indicates a weak trend or consolidation.
4. Slope Thresholds
The system uses thresholds to determine the significance of the slope. These thresholds are set as upper and lower bounds:
Upper Threshold: If the slope exceeds this threshold, the trend is considered strong, and it could trigger a buy signal.
Lower Threshold: If the slope falls below this threshold (into the negative range), it indicates a strong downtrend, and it could trigger a sell signal.
These thresholds help filter out weak or false signals that occur in sideways or low-momentum markets.
5. Positive and Negative Slope Arrays
The system keeps track of both positive and negative slopes over a defined lookback period (e.g., 500 bars). By storing these values, it creates a historical context that helps to assess the current slope in relation to past price movements.
It calculates the standard deviation and the average of these slopes to dynamically adjust the thresholds for each market condition, making the trend detection more adaptive to different types of assets or market phases.
6. Using Slope and Trend Detection in Trading
Buy Signal with Positive Slope: When the slope is positive and exceeds a certain threshold, it confirms that the market is in a strong uptrend. This can be used as a signal to enter a long position or add to existing long trades.
Sell Signal with Negative Slope: When the slope turns negative and falls below the lower threshold, it signals a strong downtrend, indicating a potential short-selling opportunity or the time to exit long positions.
Avoiding Flat Markets: If the slope remains close to zero (neither strongly positive nor negative), it suggests a lack of clear trend or a consolidating market. In these conditions, it might be better to avoid taking new trades or use additional filters to confirm signals.
7. Slope-Based Trend Strength Indicator
You can also use the slope as a measure of trend strength:
Strong Trend: When the slope is steep (either positive or negative), it indicates strong momentum, and you can be more confident in holding a trade in that direction.
Weak Trend or Consolidation: When the slope is flat, it indicates weak price momentum, which may signal a period of consolidation or indecision in the market.
8. Visual Representation
The slope is often visually represented as a gradient or line that fluctuates around a central point (usually zero). Positive values are shown in one color (e.g., green for an uptrend), while negative values are shown in another color (e.g., red for a downtrend). This allows traders to quickly identify the current trend direction and its strength.
Summary:
To use Slope and Trend Detection effectively:
Monitor the slope to determine the trend direction (positive = uptrend, negative = downtrend).
Look for thresholds to identify strong trends. For instance, a steep positive slope signals a strong uptrend, while a steep negative slope signals a strong downtrend.
Use slope changes to confirm buy/sell signals. For example, if you receive a buy signal and the slope is positive and increasing, it confirms that momentum is behind the trade.
Avoid low-slope periods when the slope is close to zero, indicating a lack of trend or sideways market conditions.
This approach helps traders stay on the right side of the trend while avoiding periods of low momentum, enhancing the accuracy of trade signals.
7. Banker Fund Flow Trend
This component identifies potential large institutional moves by tracking specific patterns in price and volume data. When the institutional or "banker" entry or exit conditions are met, it highlights these moments with candles and generates alerts.
The Banker Fund Flow Trend in "The Real Breakout Indicator Hawk" helps detect the flow of institutional (or "smart money") into and out of the market by tracking price trends and large player activity. It uses red and yellow candles to signal when institutional money is influencing the market.
Key Points:
Yellow Candles (Banker Entry):
A yellow candle is plotted when institutional money starts flowing into the market.
This signals a potential buy opportunity, as large market players are likely pushing prices upward.
Red Candles (Banker Exit):
A red candle appears when institutional money starts exiting the market.
This is a signal to consider selling or exiting long positions, as institutional selling could drive prices lower.
Usage:
Yellow candles: Use these as signals to enter long trades or add to existing positions, confirming upward momentum driven by institutional buyers.
Red candles: Treat these as signals to exit long trades or consider short positions, as institutional selling may lead to further downside.
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The yellow and red candles provide clear, actionable signals for aligning trades with institutional flows, ensuring you’re following the "smart money."
8. Dynamic Buy/Sell Calculations
A dynamic component is designed to refine the buy and sell signals further based on additional conditions like price patterns, volatility, and Money Flow. This ensures that signals are more responsive to changing market conditions.
The Dynamic Buy/Sell Calculations in "The Real Breakout Indicator Hawk" are designed to refine entry and exit points for trades by using additional conditions beyond simple crossovers. These calculations adapt to the current market conditions, making them more responsive to changes in volatility, trend strength, and momentum.
Key Features:
Dynamic Buy Calculation:
The indicator generates a buy signal when multiple conditions align. These conditions include the money flow (MF) being within a favorable range, the moving average (MA) confirming upward momentum, and the CCI and other trend components indicating strength.
This makes the buy signal more reliable, as it considers multiple aspects of market behavior (price, momentum, and money flow) to avoid false entries.
Dynamic Sell Calculation:
Similarly, the sell signal is triggered when the dynamic conditions indicate downward momentum.
This includes:
The moving average crossing down.
Negative money flow, suggesting selling pressure.
Other trend signals confirming a bearish move.
The dynamic nature of these conditions ensures that sell signals are only generated when there’s a high probability of continued downside movement.
Adaptive to Market Conditions:
The dynamic nature of these calculations means that the buy/sell signals adapt to market changes, like volatility spikes or sudden trend reversals. Instead of relying on static conditions, the system adjusts to current price movements and volatility.
Avoiding Noise:
By adding multiple filters like MF thresholds, slope, and moving averages, the dynamic calculations help reduce false signals that occur in noisy, sideways markets. This helps traders avoid entering trades during periods of low momentum or unclear trends.
How to Use:
Buy Signals: Use these signals to enter long trades when the dynamic conditions align, confirming that upward momentum is strong and backed by institutional flows.
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Aqua marker/cross signals (price manipulation/continuation)
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Sell Signals: Use the sell signals to exit long positions or enter short trades when the market shows signs of bearish momentum, confirmed by multiple conditions like MA crossovers and negative money flow.
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In summary, the Dynamic Buy/Sell Calculations provide a more sophisticated approach to generating trade signals by combining various trend and momentum indicators, helping traders make more informed decisions in different market conditions.
This part of the code is identifying two key trading signals: moments to buy and moments to sell based on the behavior of a calculated trend line.
Buy Condition:
The system looks for a situation where the trend has been moving downward but has started to reverse upward. Specifically, it checks if the trend was declining a little while ago, then stopped falling, and is now starting to rise. If these conditions are met and the trend is still below a certain level, the system considers this a possible time to buy.
Sell Condition:
The opposite happens for selling. The system monitors for a situation where the trend has been moving upward but starts to turn downward. It checks if the trend was rising, leveled off, and now seems to be starting to fall. If these conditions are met and the trend is above a certain level, this could indicate a good time to sell.
Visual Markers:
To help the user easily see these signals on a chart, the system places symbols at specific points. A marker appears on the chart where the conditions for buying or selling are met, allowing the trader to quickly spot potential entry or exit points in the market.
In summary, this logic is designed to detect possible changes in trend direction and signal appropriate times to consider buying or selling, with clear visual markers on the chart for quick identification.
9. Alerts for Buy and Sell
The indicator provides built-in alert conditions for both buy and sell signals. When these conditions are met, the system generates alerts, making it suitable for automated monitoring.
Each of these components works together to detect potential breakout opportunities, trend continuations, and reversals, making the indicator suitable for both short-term and long-term trading strategies.
Swiss Knife [MERT]Introduction
The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format.
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Key Features
Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes.
Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection.
Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score.
Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart.
Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots.
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Explanation of Each Indicator
Moving Average Convergence Divergence (MACD)
- Purpose : Measures the relationship between two moving averages of price.
- Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum.
Awesome Oscillator (AO)
- Purpose : Gauges market momentum by comparing recent market movements to historic ones.
- Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum.
Parabolic SAR (SAR)
- Purpose : Identifies potential reversal points in price direction.
- Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend.
SuperTrend
- Purpose : Determines the prevailing market trend.
- Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line.
Detrended Price Oscillator (DPO)
- Purpose : Removes trend from price to identify cycles.
- Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below.
Relative Strength Index (RSI)
- Purpose : Measures the speed and change of price movements.
- Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum.
Stochastic Oscillator
- Purpose : Compares a particular closing price to a range of its prices over a certain period.
- Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions.
Bollinger Bands (BB)
- Purpose : Measures market volatility and provides relative price levels.
- Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness.
Ichimoku Cloud
- Purpose : Provides support and resistance levels, trend direction, and momentum.
- Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud.
Chande Momentum Oscillator (CMO)
- Purpose : Measures momentum on both up and down days.
- Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum.
Donchian Channels
- Purpose : Identifies volatility and potential breakouts.
- Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout.
Average Directional Index (ADX)
- Purpose : Measures the strength of a trend.
- Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend.
Volume Momentum Indicators (VolMom, CumVolMom, POCMom)
- Purpose : Analyze volume to assess buying and selling pressure.
- Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum.
Fractals
- Purpose : Identify potential reversal points in the market.
- Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend.
Divergence Detection
- Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line).
- Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal.
- Note : This functionality utilizes the library from Divergence Indicator .
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Coloring Scheme
Background Color
- Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes.
- Interpretation :
- Green Shades : Indicate bullish market sentiment.
- Red Shades : Indicate bearish market sentiment.
- Intensity : The strength of the color corresponds to the strength of the sentiment score.
Sentiment Table
- Purpose : Displays the status of each indicator across different timeframes.
- Interpretation :
- Green Cell : The indicator suggests a bullish signal.
- Red Cell : The indicator suggests a bearish signal.
- Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe.
Exponential Moving Averages (EMAs)
- Purpose : Provide dynamic support and resistance levels.
- Colors :
- EMA 10 : Lime
- EMA 20 : Yellow
- EMA 50 : Orange
- EMA 100 : Red
- EMA 200 : Purple
Trendlines
- Purpose : Visual representation of support and resistance levels based on pivot points.
- Interpretation :
- Upward Trendlines : Colored green , indicating support levels.
- Downward Trendlines : Colored red , indicating resistance levels.
- Note : Trendlines are drawn using the library from Simple Trendlines .
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Utility of Market Sentiment
The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by:
Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend.
Identifying Reversals : Divergences and fractals can signal potential turning points.
Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades.
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Divergences
Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal.
- Bullish Divergence : Price makes a lower low, but the indicator makes a higher low.
- Bearish Divergence : Price makes a higher high, but the indicator makes a lower high.
The indicator detects divergences for:
RSI
MACD
Stochastic Oscillator
On-Balance Volume (OBV)
Money Flow Index (MFI)
Accumulation/Distribution Line (A/D Line)
By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly.
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Trendlines
Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points:
- Upward Trendlines (Support) : Connect higher lows, indicating an uptrend.
- Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend.
These trendlines help traders visualize the trend direction and potential breakout or reversal points.
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Super Trend Reversals (ST Reversal)
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders:
Engage Early : Enter the market as reversal momentum builds up.
Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes.
By capturing these reversal points, traders can enhance their trading performance.
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Conclusion
The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions.
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Citations
- Divergence Detection Library : Divergence Indicator by DevLucem
- Trendline Drawing Library : Simple Trendlines by HoanGhetti
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Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions.
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Prime OscilatorPrime Oscilator is a powerful tool designed to help traders track momentum shifts and confirm trends in volatile markets. This oscillator-based tool integrates advanced market analysis techniques to provide a clear picture of momentum and trend direction, helping traders stay in sync with the prevailing market conditions.
Core Features of Prime Oscilator
Oscillator-Based Momentum Tracking: Prime Oscilator operates as a dynamic oscillator that tracks shifts in market momentum by analyzing the relationship between the A/D line and its signal line. This allows traders to identify potential changes in market direction and confirm trend strength.
Trend Confirmation Filter: Prime Oscilator incorporates a long-term trend filter, using a 50-period Simple Moving Average (SMA) to confirm whether the market is trending upward or downward. This helps traders focus on trades that align with the broader market direction.
Adaptive Signal Line: The oscillator’s signal line adjusts dynamically to reflect short-term momentum changes, allowing traders to react quickly to evolving market conditions. This makes the Prime Oscilator highly responsive to both fast-moving and stable markets.
Color-Coded Oscillator Line: The oscillator line changes color based on the current market conditions, providing a visual cue of momentum shifts. The line remains green during upward momentum and red during downward momentum, giving traders an easy way to gauge the market direction.
How Prime Oscilator Works
Prime Oscilator blends the power of trend analysis with momentum tracking to provide a comprehensive view of market conditions. By analyzing the Accumulation/Distribution (A/D) line and comparing it to a dynamic signal line, traders can monitor momentum shifts and confirm trends.
A/D Line Crossover: The indicator uses the relationship between the A/D line and the signal line to detect potential momentum changes. When the A/D line moves relative to the signal line, it reflects shifts in market momentum, allowing traders to follow the direction of the trend.
Trend Filtering: To ensure that momentum is aligned with the broader market direction, Prime Oscilator uses a 50-period SMA as a trend filter. This confirms whether the market is in an uptrend or downtrend and helps traders avoid focusing on short-term fluctuations that go against the prevailing trend.
Why It's Useful for Traders
Prime Oscilator is especially valuable for traders looking for a reliable way to track momentum shifts while aligning their trades with the overall market trend. This reduces noise and ensures that traders focus on opportunities that are in line with broader market movements.
Momentum-Based Trend Analysis: By tracking momentum changes, Prime Oscilator helps traders stay on top of potential market shifts without the noise that comes from traditional indicators.
Clear Visual Feedback: The color-coded oscillator line provides instant feedback on market conditions, allowing traders to focus on decision-making rather than analyzing multiple indicators.
Flexible Across Markets and Timeframes: Whether you are trading in volatile markets or more stable environments, Prime Oscilator adapts to different market conditions, ensuring you always have a clear picture of momentum and trend.
Prime Oscilator is ideal for traders who:
Scalp or trade intraday: Quickly captures momentum shifts in short timeframes.
Swing traders: Identifies potential trend reversals in higher timeframes while confirming momentum strength.
Trend followers: Ensures your trades are aligned with the prevailing market trend by confirming momentum shifts.
By combining momentum analysis with trend direction, Prime Oscilator offers a dynamic view of the market, helping traders navigate changing conditions with ease.
Why It's Worth Paying For
Prime Oscilator provides several unique advantages that make it a valuable tool for traders:
Clear and Actionable Insights: The oscillator-based momentum tracking gives traders a clear understanding of when the market's momentum is shifting, allowing for more informed trading decisions.
No Lagging: Unlike some trend-following indicators, Prime Oscilator reacts dynamically to market changes, helping traders stay aligned with the current market direction.
Adaptable and Flexible: Whether you trade on shorter timeframes or hold longer positions, Prime Oscilator adapts seamlessly to various market conditions. The trend filter ensures that traders remain aligned with broader market trends.
Visual Simplicity: The color-coded oscillator line and background shading provide an easy-to-read way of monitoring market conditions, enabling faster decision-making.
How to Get Access
To gain access to Prime Oscilator , please send me a direct message on TradingView or follow the provided link to request access. Ensure that access requests are made privately so the comments section remains focused on discussions related to the script’s performance and use.
Risk Disclaimer
While Prime Oscilator offers valuable insights into market momentum and trends, it’s important to note the following:
Past performance is not indicative of future results: Prime Oscilator ’s trend and momentum analysis are based on historical data, and no indicator can predict future price movements with certainty.
Market Conditions: The effectiveness of the Prime Oscilator may vary across different market conditions, and traders should always use proper risk management when trading.
Trading Risks: Like any trading tool, Prime Oscilator should be used as part of a comprehensive trading strategy that includes risk management techniques such as stop-loss orders and position sizing.
Ultra Money FlowIntroduction
The Ultra Money Flow script is a technical indicator for analyzing stock trends. It highlights buying and selling power, helping you identify bullish (rising) or bearish (falling) market trends.
Detailed Description
The Ultra Money Flow script calculates and visually displays two main components: Fast and Slow money flow. These components represent short-term and long-term trends, respectively.
Here's how it works:
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Inputs
You can adjust the speed of analysis (Fast Length and Slow Length) and the type of smoothing applied (e.g., Simple Moving Average, Exponential Moving Average).
Choose colors for visualizing the trends, with blue for bullish (positive) and orange for bearish (negative) movements.
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Money Flow Calculation
The script analyzes price changes (delta) over specified periods.
It separates upward price movements (buying power) from downward ones (selling power).
It then calculates the difference between these powers for both Fast and Slow components.
The types of smoothing methods range from traditional ones like the Simple Moving Average (SMA) to advanced ones like the Double Expotential Moving Average (DEMA) or the Triple Exponential Moving Average (TEMA) or the Recursive Moving Average (RMA) or the Weigthend Moving Average (WMA) or the Volume Weigthend Moving Average (VWMA) or Hull Moving Average (HMA).
Very Special ones are the Triple Weigthend Moving Average (TWMA) wich created RedKTrader .
I created the Multi Weigthend Moving Average (MWMA) wich is a simple signal line to the TWMA.
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Divergence
This indicator can show divergence by comparing the direction of price movements with the indicator value.
If the price and the indicator move in opposite directions, you can use these signals to help decide when to buy or sell.
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Auto Scaling
The script adjusts its calculations based on the time frame you are viewing, whether it's minutes, hours, or days, ensuring accurate representation across different time scales.
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Plotting
The script plots the Fast component as a histogram and the Slow component as a line, using the chosen colors to indicate bullish or bearish trends.
The thickness and transparency of these plots give additional clues about the strength of the trend.
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By using this indicator, traders can easily spot shifts in buying and selling power, allowing for better-informed decisions in the market.
Special Thanks
I use the TWMA-Function created from RedKTrader to smooth the values.
Special thanks to him for creating and sharing this function!
MACD Diff SignalWhen the MACD Absolute Histogram is above a threshold (set by nth lowest absolute histogram value in the rolling window) the indicator produces the MACD Histogram level, otherwise it produces 0. This Indicator is good for identifying bullish or bearish momentum.
Custom MACD Oscillator with Bar ColoringCustom MACD Oscillator with Bar Coloring
This custom MACD indicator is a fusion of two powerful MACD implementations, combining the best features of both the MACD Crossover by HPotter and the Multiple Time Frame Custom MACD Indicator by ChrisMoody. The indicator enhances the traditional MACD with customizable options and dynamic bar coloring based on the relationship between the MACD and Signal lines, providing a clear visual representation of momentum shifts in the market.
Key Features:
MACD Oscillator: Built on the core MACD principle, showing the difference between two Exponential Moving Averages (EMA) for momentum tracking.
Signal Line: A Simple Moving Average (SMA) of the MACD, helping to identify potential entry/exit points through crossovers.
Multiple Time Frame Support: Allows users to view MACD and Signal data from different timeframes, giving a broader view of the market dynamics.
Bar Coloring: Bars are colored green when the MACD is above the Signal line (bullish), red when the MACD is below (bearish), and blue during neutral conditions.
Histogram with Custom Colors: A customizable histogram visualizes the difference between the MACD and Signal lines with color-coding to represent changes in momentum.
Cross Dots: Visual markers at points where the MACD crosses the Signal line for easy identification of potential trend shifts.
This indicator is a versatile tool for traders who want to visualize MACD-based momentum and crossover signals in multiple timeframes with clear visual cues on price bars.
Advanced Stochastic ForLoopAdvanced Stochastic ForLoop
OVERVIEW
Advanced Stochastic ForLoop is an improved version of Stochastic it is designed to calculate an array of values 1 or -1 depending if soruce for calculations is above or below basis.
It takes avereage of values over a range of lengths, providing trend signals smothed based on various moving averages in order to get rid of noise.
It offers flexibility with different signal modes and visual customizations.
TYPE OF SIGNALS
-FAST (MA > MA or MA > 0.99)
-SLOW (MA > 0)
-THRESHOLD CROSSING (set by user treshold for both directions)
-FAST THRESHOLD (when theres an change in signal by set margin e.g 0.4 -> 0.2 means bearsih when FT is set to 0.1, when MA is > 0.99 it will signal bullish, when MA < -0.99 it will signal bearish)
Generaly Lime color of line indicates Bullish, Fuchsia indicates Bearish.
This colors are not set in stone so you can change them in settings.
Alerts included when line color is:
-Bullish Trend, line color is lime
-Bearish Trend, line color is fuchsia
Credit
Idea for this script was from one of indicators created by www.tradingview.com
Warning
This indicator can be really noisy depending on the settings, signal mode so it should be used preferably as a part of an strategy not as a stand alone indicator
Remember the lower the timeframe you use the more noise there is.
No single indicator should be used alone when making investment decisions.
Multi-Asset Cross Timeframe Divergence Ind. (MACDI) // AlgoFyreThe Multi-Asset Cross Timeframe Divergence Indicator (MACDI) identifies divergences in momentum like RSI across multiple assets and timeframes. It visually highlights lagging correlated asset momentum divergences, helping traders spot inefficiencies and potential trade opportunities in the following asset.
🔶 KEY FEATURES
🔸Average Momentum Trendline for Each Timeframe
The Average Momentum Trendline feature calculates the average momentum of multiple assets over specified timeframes. It uses smoothed values to determine the momentum trend for each timeframe on the average aggregated momentum of both assets. This trendline helps traders identify the overall direction of the market momentum, providing a clearer picture of potential price movements.
🔸Real-time Divergence Indication and Alert Table
The Real-time Divergence Indications and Alert Table feature visualizes detected divergences between the momentum values of the two assets across different timeframes. It identifies both bullish and bearish divergences, signaling lagging reversals in the the following asset and potential trading opportunities. When a divergence is detected, the system generates real-time visual indications on the chart and in an overview table for traders to act promptly. The alert table provides a comprehensive overview of all detected divergences, making it easier for traders to monitor and respond to market changes.
🔸Color and Size Based Labels on Price Chart based on Divergence Type
The Color and Size Based Labels feature visually represents divergences directly on the price chart. Bullish and bearish divergences are marked with distinct colors and sizes, making them easily identifiable at a glance. Larger labels indicate higher timeframes and thus generally more significance.
🔶 INSTRUCTION GUIDELINES
🔸Identify Divergence Clusters
The more divergences align, the higher the probability of a potential trend reversal in the asset. When multiple multi-timeframe divergences occur in both lower and higher timeframes within a local cluster, the probability of a reversal increases. This is valid for both for bullish and bearish divergences.
🔸Spot Low Probability Divergences
To further increase the probability, analyze the current state of the average momentum trendline. For a bullish reversal, a relatively low level of the average momentum trendline is preferred, whereas for a bearish reversal, a relatively high level is preferred.
🔶 INDIVIDUAL CONFIGURATION
🔸Leading Asset
This input allows the user to select the leading asset for the divergence analysis.
🔸Following Asset
This input allows the user to select the following asset for the divergence analysis.
🔸Higher Timeframe
This input sets the higher timeframe for the analysis.
🔸Lower Timeframe
This input sets the lower timeframe for the analysis.
🔸Show RSI Divergence
This input enables or disables the display of RSI divergence signals.
🔸RSI Length
This input sets the length of the RSI calculation.
🔸RSI Source
This input sets the source data for the RSI calculation (e.g., close price).
🔸RSI Smoothing Length
This input sets the length of the smoothing applied to the RSI values.
🔸Smoothing Method
This input sets the method used for smoothing the RSI values.
🔶 CONCLUSION
The Multi-Asset Cross Timeframe Divergence Indicator (MACDI) is a powerful tool for identifying momentum divergences across multiple assets and timeframes. Its visual cues and customizable table make it easy to use and interpret, providing valuable insights for trading decisions.
Relative Strength and MomentumRelative Strength and Momentum Indicator
Unlock deeper market insights with the Relative Strength and Momentum Indicator—a powerful tool designed to help traders and investors identify the strongest stocks and sectors based on relative performance. This custom indicator displays essential information on relative strength and momentum for up to 15 different symbols, compared against a benchmark index, all within a clear and organized table format.
Key Features:
1. Customizable Inputs: Choose up to 15 symbols to compare, along with a benchmark index, allowing you to tailor the indicator to your trading strategy. The 'Lookback Period' input defines how many weeks of data are analyzed for relative strength and momentum.
2. Relative Strength Calculation: For each selected symbol, the indicator calculates the Relative Strength (RS) against the chosen benchmark. This RS is further refined using an exponential moving average (EMA) to smooth the results, providing a more stable trend overview.
3. Momentum Analysis: Momentum is determined by analyzing the rate of change in relative strength. The indicator calculates a momentum rank for each symbol, based on its relative strength’s improvement or deterioration.
4. Percentile Ranking System: Each symbol is assigned a percentile rank (from 1 to 100) based on its relative strength compared to the others. Similarly, momentum rankings are also assigned from 1 to 100, offering a clear understanding of which assets are outperforming or underperforming.
5. Visual Indicators:
a. Green: Signals improving or stable relative strength and momentum.
b. Red: Indicates declining relative strength or momentum.
c. Aqua: Highlights symbols performing well on both relative strength and momentum—ideal candidates for further analysis.
6. Two Clear Tables:
a. Relative Strength Rank Table: Displays weekly rankings of relative strength for each symbol.
b. Momentum Table: Shows momentum trends, helping you identify which symbols are gaining or losing strength.
7. Color-Coded for Easy Analysis: The tables are color-coded to make analysis quick and straightforward. A green color means the symbol is performing well in terms of relative strength or momentum, while red indicates weaker performance. Aqua marks symbols that are excelling in both areas.
Use Case:
a. Sector Comparison: Identify which sectors or indexes are showing both relative strength and momentum to pick high-potential stocks. This allows you to align with broader market trends for improved trade entries.
b. Stock Selection: Quickly compare symbols within the same sector to find the stronger performers.
Volume Wave Trend ConfirmationUtility of the Indicator
The core utility of this indicator lies in its ability to utilize volume, a less frequently exploited metric in MACD analysis, providing several strategic advantages:
Trend Confirmation: By focusing on volume, the indicator confirms whether movements in price are backed by significant trading activity. A rising MACD line above the signal line, paired with increasing volume, can confirm the strength of an uptrend. Conversely, if the histogram turns negative while the MACD line falls below the signal line during a price drop, it confirms a robust downtrend.
Early Warning Signals: Changes in the histogram and divergences between the MACD and Signal lines can serve as early warnings of potential reversals or slowdowns in market momentum. For instance, a shrinking histogram in an uptrend might suggest that the upward movement is losing steam.
Market Sentiment: The integration of volume into the MACD framework allows the indicator to provide insights into underlying market sentiment. Higher volumes during price movements indicate stronger conviction among traders, making the trend more reliable.
Indicator Functionality
The "Volume Wave Trend Confirmation" indicator is built on the Moving Average Convergence Divergence (MACD) framework, but with a unique twist: it uses the smoothed moving averages (SMA) of trading volumes instead of price. The indicator calculates two specific SMAs of the volume — a shorter 33-period SMA and a longer 100-period SMA — and computes their difference. This difference is then used as the input for the MACD calculation, with typical parameters set at 12, 26, and a signal line of 9.
MACD Line (Blue): Represents the main line, calculated as the difference between the 12-period and 26-period exponential moving averages (EMA) of the volume difference.
Signal Line (Orange): A 9-period EMA of the MACD line, acting as a trigger for buy or sell signals.
Histogram (Blue/Purple): Measures the distance between the MACD line and the Signal line, colored blue when positive (above the Signal line) and purple when negative (below the Signal line).
Gaussian Acceleration ArrayIndicators play a role in analyzing price action, trends, and potential reversals. Among many of these, velocity and acceleration have held a significant place due to their ability to provide insight into momentum and rate of change. This indicator takes the old calculation and tweaks it with gaussian smoothing and logarithmic function to ensure proper scaling.
A Brief on Velocity and Acceleration: The concept of velocity in trading refers to the speed at which price changes over time, while acceleration is the rate of change(ROC) of velocity. Early momentum indicators like the RSI and MACD laid foundation for understanding price velocity. However, as markets evolve so do we as technical analysts, we seek the most advanced tools.
The Acceleration/Deceleration Oscillator, introduced by Bill Williams, was one of the early attempts to measure acceleration. It helped gauge whether the market was gaining or losing momentum. Over time more specific tools like the "Awesome Oscillator"(AO) emerged, which has a set length on the datasets measured.
Gaussian Functions: Named after the mathematician Carl Friedrich Gauss, the Gaussian function describes a bell-shaped curve, often referred to as the "normal distribution." In trading these functions are applied to smooth data and reduce noise, focusing on underlying patterns.
The Gaussian Acceleration Array leverages this function to create a smoothed representation of market acceleration.
How does it work?
This indicator calculates acceleration based the highs and lows of each dataset
Once the weighted average for velocity is determined, its rate of change essentially becomes the acceleration
It then plots multiple lines with customizable variance from the primary selected length
Practical Tips:
The Gaussian Acceleration Array offers various customizable parameters, including the sample period, smoothing function, and array variance. Experiment with these settings to tailor it to preferred timeframes and styles.
The color-coded lines and background zones make it easier to interpret the indicator at a glance. The backgrounds indicate increasing or decreasing momentum simply as a visual aid while the lines state how the velocity average is performing. Combining this with other tools can signal shifts in market dynamics.
VWAP PressureKey Features and Utility:
Intrabar Focus: Unlike standard VWAP, which provides a cumulative average throughout the day, the Intrabar VWAP focuses on volume-weighted price calculations within shorter time frames. This allows traders to see how price and volume interact moment-to-moment, offering a granular view of market sentiment.
Market Pressure Analysis: The indicator examines the difference between a smoothed weighted average price of the close and intrabar price movements. This analysis helps in identifying the market pressure at high volume areas. When the market exhibits high volume at low prices within a bar, it suggests accumulation, whereas high volume at high prices indicates distribution.
Momentum and Pressure Shift Signals: By applying a modified MACD calculation to the smoothed difference, the indicator provides signals on shifts in market pressure. Positive values indicate upward price momentum (buying pressure), while negative values suggest downward momentum (selling pressure).
Market DirectionThe "Market Direction" indicator combines four advanced sub-indicators to provide a comprehensive and multi-dimensional analysis of market trends, momentum, and potential reversals. This innovative approach leverages different aspects of price action, volume, and market sentiment, offering traders an in-depth view of market conditions.
1. Fractal Indicator: Multi-Scale Price Action Analysis
The Fractal Indicator identifies significant highs and lows over six different pivot lengths, offering a nuanced view of price action across multiple timeframes. By comparing distances from current closing prices to these key fractal points, the indicator determines potential trend reversals and market direction. This approach enables traders to adapt their strategies to various market conditions, capturing both short-term fluctuations and long-term trends.
2. Volume MACD Indicator: Enhanced Market Momentum
The Volume MACD Indicator goes beyond traditional MACD analysis by incorporating volume-weighted movement and the structural attributes of candlesticks (such as body length and wicks). This hybrid model offers a more comprehensive understanding of market momentum by integrating both price action and trading volume. The use of Smoothed Moving Averages (SMMA) reduces noise and ensures more stable signals, helping traders focus on sustainable trends and longer-term investment opportunities.
3. Cumulative Volume Momentum Indicator: Volume Dynamics Insight
The Cumulative Volume Momentum Indicator evaluates the momentum of cumulative buying and selling volumes, offering a clear picture of market strength and potential reversals. By comparing the relationship between open, close, high, and low prices, and applying a MACD approach to these volume dynamics, this indicator helps traders identify momentum shifts that often precede price movements. The visualization through histograms adds clarity to bullish and bearish volume momentum, enhancing decision-making in volatile markets.
4. POC-Price Momentum Indicator: Market Depth and Sentiment
The POC-Price Momentum Indicator assesses the difference between the Point of Control (POC) and closing prices, providing insights into underlying market sentiment. Positive differences indicate a buildup of upward momentum, while negative differences suggest a bearish tilt. By calculating moving averages of these differences, the indicator highlights the strength and sustainability of ongoing trends, helping traders align their strategies with the broader market direction.
Unified Rating for Confirming Market Direction
The "Market Direction" indicator consolidates the outputs of these four sub-indicators into a single, aggregated sentiment score. This score helps traders confirm the prevailing market trend by weighing the combined insights from fractal analysis, volume momentum, price action, and POC dynamics. A positive score suggests a bullish market, while a negative score indicates bearish conditions.
Uptrick: Momentum-Volatility Composite Signal### Title: Uptrick: Momentum-Volatility Composite Signal
### Overview
The "Uptrick: Momentum-Volatility Composite Signal" is an innovative trading tool designed to offer traders a sophisticated synthesis of momentum, volatility, volume flow, and trend detection into a single comprehensive indicator. This tool stands out by providing an integrated view of market dynamics, which is critical for identifying potential trading opportunities with greater precision and confidence. Its unique approach differentiates it from traditional indicators available on the TradingView platform, making it a valuable asset for traders aiming to enhance their market analysis.
### Unique Features
This indicator integrates multiple crucial elements of market behavior:
- Momentum Analysis : Utilizes Rate of Change (ROC) metrics to assess the speed and strength of market movements.
- Volatility Tracking : Incorporates Average True Range (ATR) metrics to measure market volatility, aiding in risk assessment.
- Volume Flow Analysis : Analyzes shifts in volume to detect buying or selling pressure, adding depth to market understanding.
- Trend Detection : Uses the difference between short-term and long-term Exponential Moving Averages (EMA) to detect market trends, providing insights into potential reversals or confirmations.
Customization and Inputs
The Uptrick indicator offers a variety of user-defined settings tailored to fit different trading styles and strategies, enhancing its adaptability across various market conditions:
Rate of Change Length (rocLength) : This setting defines the period over which momentum is calculated. Shorter periods may be preferred by day traders who need to respond quickly to market changes, while longer periods could be better suited for position traders looking at more extended trends.
ATR Length (atrLength) : Adjusts the timeframe for assessing volatility. A shorter ATR length can help day traders manage the quick shifts in market volatility, whereas longer lengths might be more applicable for swing or position traders who deal with longer-term market movements.
Volume Flow Length (volumeFlowLength): Determines the analysis period for volume flow to identify buying or selling pressure. Day traders might opt for shorter periods to catch rapid volume changes, while longer periods could serve swing traders to understand the accumulation or distribution phases better.
Short EMA Length (shortEmaLength): Specifies the period for the short-term EMA, crucial for trend detection. Shorter lengths can aid day traders in spotting immediate trend shifts, whereas longer lengths might help swing traders in identifying more sustainable trend changes.
Long EMA Length (longEmaLength): Sets the period for the long-term EMA, which is useful for observing longer-term market trends. This setting is particularly valuable for position traders who need to align with the broader market direction.
Composite Signal Moving Average Length (maLength): This parameter sets the smoothing period for the composite signal's moving average, helping to reduce noise in the signal output. A shorter moving average length can be beneficial for day traders reacting to market conditions swiftly, while a longer length might help swing and position traders in smoothing out less significant fluctuations to focus on significant trends.
These customization options ensure that traders can fine-tune the Uptrick indicator to their specific trading needs, whether they are scanning for quick opportunities or analyzing more prolonged market trends.
### Functionality Details
The indicator operates through a sophisticated algorithm that integrates multiple market dimensions:
1. Momentum and Volatility Calculation : Combines ROC and ATR to gauge the market’s momentum and stability.
2. Volume and Trend Analysis : Integrates volume data with EMAs to provide a comprehensive view of current market trends and potential shifts.
3. Signal Composite : Each component is normalized and combined into a composite signal, offering traders a nuanced perspective on when to enter or exit trades.
The indicator performs its calculations as follows:
Momentum and Volatility Calculation:
roc = ta.roc(close, rocLength)
atr = ta.atr(atrLength)
Volume and Trend Analysis:
volumeFlow = ta.cum(volume) - ta.ema(ta.cum(volume), volumeFlowLength)
emaShort = ta.ema(close, shortEmaLength)
emaLong = ta.ema(close, longEmaLength)
emaDifference = emaShort - emaLong
Composite Signal Calculation:
Normalizes each component (ROC, ATR, volume flow, EMA difference) and combines them into a composite signal:
rocNorm = (roc - ta.sma(roc, rocLength)) / ta.stdev(roc, rocLength)
atrNorm = (atr - ta.sma(atr, atrLength)) / ta.stdev(atr, atrLength)
volumeFlowNorm = (volumeFlow - ta.sma(volumeFlow, volumeFlowLength)) / ta.stdev(volumeFlow, volumeFlowLength)
emaDiffNorm = (emaDifference - ta.sma(emaDifference, longEmaLength)) / ta.stdev(emaDifference, longEmaLength)
compositeSignal = (rocNorm + atrNorm + volumeFlowNorm + emaDiffNorm) / 4
### Originality
The originality of the Uptrick indicator lies in its ability to merge diverse market metrics into a unified signal. This multi-faceted approach goes beyond traditional indicators by offering a deeper, more holistic analysis of market conditions, providing traders with insights that are not only based on price movements but also on underlying market dynamics.
### Practical Application
The Uptrick indicator excels in environments where understanding the interplay between volume, momentum, and volatility is crucial. It is especially useful for:
- Day Traders : Can leverage real-time data to make quick decisions based on sudden market changes.
- Swing Traders : Benefit from understanding medium-term trends to optimize entry and exit points.
- Position Traders : Utilize long-term market trend data to align with overall market movements.
### Best Practices
To maximize the effectiveness of the Uptrick indicator, consider the following:
- Combine with Other Indicators : Use alongside other technical tools like RSI or MACD for additional validation.
- Adapt Settings to Market Conditions : Adjust the indicator settings based on the asset and market volatility to improve signal accuracy.
- Risk Management : Implement robust risk management strategies, including setting stop-loss orders based on the volatility measured by the ATR.
### Practical Examples and Demonstrations
- Example for Day Trading : In a volatile market, a trader notices a sharp increase in the momentum score coinciding with a surge in volume but stable volatility, signaling a potential bullish breakout.
- Example for Swing Trading : On a 4-hour chart, the indicator shows a gradual alignment of decreasing volatility and increasing buying volume, suggesting a strengthening upward trend suitable for a long position.
### Alerts and Their Uses
- Alert Configurations : Set alerts for when the composite score crosses predefined thresholds to capture potential buy or sell events.
- Strategic Application : Use alerts to stay informed of significant market moves without the need to continuously monitor the markets, enabling timely and informed trading decisions.
Technical Notes
Efficiency and Compatibility: The indicator is designed for efficiency, running smoothly across different trading platforms including TradingView, and can be easily integrated with existing trading setups. It leverages advanced mathematical models for normalizing and smoothing data, ensuring consistent and reliable signal quality across different market conditions.
Limitations : The effectiveness of the Uptrick indicator can vary significantly across different market conditions and asset classes. It is designed to perform best in liquid markets where data on volume, volatility, and price trends are readily available and reliable. Traders should be aware that in low-liquidity or highly volatile markets, the signals might be less reliable and require additional confirmation.
Usage Recommendations : While the Uptrick indicator is a powerful tool, it is recommended to use it in conjunction with other analysis methods to confirm signals. Traders should also continuously monitor the performance and adjust settings as needed to align with their specific trading strategies and market conditions.
### Conclusion
The "Uptrick: Momentum-Volatility Composite Signal" is a revolutionary tool that offers traders an advanced methodology for analyzing market dynamics. By combining momentum, volatility, volume, and trend detection into a single, cohesive indicator, it provides a powerful, actionable insight into market movements, making it an indispensable tool for traders aiming to optimize their trading strategies.
Multi-Kernel CCI [BackQuant]Multi-Kernel CCI
Conceptual Foundation and Innovation
It offers a fresh take on the Commodity Channel Index (CCI) by integrating three distinct kernel functions—Exponential Decay, Gaussian Decay, and Cosine Decay—to create a more robust and adaptive momentum indicator. The use of these kernel functions allows the CCI calculation to be more responsive to price changes while smoothing out noise, providing traders with clearer trend signals and reducing false alerts in varying market conditions.
Technical Composition and Calculation
The core of this indicator is a multi-kernel approach to calculating the CCI, where three different decay kernels are applied to the price source. Each kernel provides a unique weighting mechanism for price data over a user-defined lookback period. The result is an average of these three kernel calculations, which serves as the foundation for the CCI calculation. This innovative approach makes the Multi-Kernel CCI more adaptive to different market conditions compared to traditional CCI calculations.
Exponential Decay Kernel: Applies an exponential weighting to recent price data, giving more importance to recent values while smoothing out older data.
Gaussian Decay Kernel: Weights data using a Gaussian function, ensuring smooth transitions between price points and reducing outliers' impact.
Cosine Decay Kernel: Utilizes a cosine function to apply a unique oscillating weight to the data, capturing cyclical market movements more effectively.
Adaptive Thresholding: Like the Adaptive Momentum Oscillator, this indicator adjusts its long and short thresholds dynamically using percentile-based calculations over historical CCI values.
Features and User Inputs The Multi-Kernel CCI offers a wide range of customization options for traders:
Kernel Calculation Length & Alpha: Traders can fine-tune the sensitivity of the CCI by adjusting the length of the kernel calculation and the alpha parameter for the Exponential Decay Kernel.
Adaptive Thresholds: The indicator provides percentile-based thresholds for both long and short signals, allowing traders to dynamically adjust their signals based on historical data.
Extreme Value Detection: This feature highlights extreme overbought and oversold conditions with customizable thresholds and background hues, visually aiding in identifying high-probability reversal zones.
Divergence Detection: The script includes a divergence detection feature, identifying regular and hidden bullish or bearish divergences to help traders spot potential trend reversals.
Practical Applications The Multi-Kernel CCI excels in markets where adaptive trend detection and momentum confirmation are critical. Traders can leverage this tool in several ways:
Adaptive Trend Following: The dynamically adjusting thresholds allow traders to capture trends more effectively while avoiding false signals during consolidations or choppy markets.
Reversal Detection: The multi-kernel approach ensures that reversals are detected with greater precision, particularly in volatile markets where traditional indicators might fail.
Divergence Identification: With built-in divergence detection, the indicator provides traders with an early warning of potential trend reversals, helping to time their entries and exits more effectively.
Advantages and Strategic Value The Multi-Kernel CCI offers several strategic advantages over traditional CCI indicators:
Multi-Kernel Smoothing:
By using multiple decay kernels, this CCI calculation is better suited to detect subtle changes in market momentum, reducing the impact of noise and providing clearer trend signals.
Dynamic Thresholds:
The adaptive percentile-based thresholds ensure that the indicator remains relevant across different market conditions, enhancing signal accuracy.
Visual and Analytical Aids:
With features like extreme value detection and divergence spotting, this indicator equips traders with powerful tools to confirm trend strength and identify potential reversals.
Summary and Usage Tips
The Multi-Kernel CCI is a highly versatile tool for traders seeking a more adaptive and robust momentum indicator. Its multi-kernel foundation provides smoother, more reliable signals, while the adaptive thresholds and divergence detection features help traders refine their entries and exits. The dynamic nature of this indicator makes it ideal for both trend-following and reversal strategies in volatile markets.
Traders should experiment with the kernel calculation length and alpha parameter to align the indicator's sensitivity with their specific trading style and market conditions. Additionally, the adaptive thresholds can be fine-tuned to ensure the CCI captures the most significant trend changes without being overly reactive to short-term fluctuations.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Inverse Fisher Oscillator [BigBeluga]The Inverse Fisher Oscillator is a powerful tool for identifying market trends and potential reversal points by applying the Inverse Fisher Transform to normalized price data. This indicator plots multiple smoothed oscillators, each color-coded to signify their relation to dynamic volatility bands. Additionally, the Butterworth filter is incorporated to further refine trend signals. The Inverse Fisher Oscillator offers traders a visually appealing and insightful approach to trend analysis and market direction detection.
🔵 KEY FEATURES
● Inverse Fisher Oscillator Visualization
Multiple Oscillators : The indicator calculates and plots six different Inverse Fisher Oscillators, each smoothed at increasing levels to provide a layered view of price momentum.
Color-Coded Signals : The oscillator lines are color-coded based on their relation to the volatility bands—green for bullish momentum, red for bearish momentum, and yellow for neutral movements.
● Butterworth Filter Integration
Filtering : The Butterworth filter is applied to mid-line Bands to reduce noise, allowing for clearer trend detection.
// Calculate constants for the Butterworth filter
float piPrd = math.pi / mid_len
float g = math.sqrt(2)
float a1 = math.exp(-g * piPrd)
float b1 = 2 * a1 * math.cos(g * piPrd)
float coef2 = b1
float coef3 = -a1 * a1
float coef1 = (1 - b1 + a1 * a1) / 4
// Source data for the Butterworth filter
float source = ifish // The first inverse Fisher Oscillator is used as the source
// Previous source and butter filter values
var float butter = na // Initialize the 'butter' variable
// Handle null values using the nz function
float prevB1 = nz(butter , source) // Use 'source' as a fallback if butter is null
float prevB2 = nz(butter , source) // Use 'source' as a fallback if butter is null
// Calculate the Butterworth filter value
butter := coef1 * (source + (2 * source ) + source ) + (coef2 * prevB1) + (coef3 * prevB2)
● Numbered Signal Marks
Signal Markers : The indicator plots numbered signals on the chart when an oscillator crosses above the upper volatility band or below the lower volatility band.
Numbered Lines : Numbers correspond to the different oscillators (1-6), helping traders easily identify which smoothing level generated the signal.
Visual Cues : The signals are color-coded—green for bullish crossovers and red for bearish crossunders—providing clear visual cues for trend accumulation phases.
Mid-Line Option : Traders can choose between plotting the Butterworth filter as a dynamic mid-line or simply displaying it as part of the bands.
Volatility Bands : Dynamic volatility bands provide additional context for interpreting the strength and sustainability of trends.
● Dashboard Display
Real-Time Market Trend Overview : The dashboard in the bottom-right corner of the chart displays the market trend based on the Inverse Fisher Oscillator for six different smoothing levels, providing a clear visual summary of market direction.
Direction Symbols : Directional symbols (up, down, or neutral) are displayed in the dashboard, color-coded to represent bullish, bearish, or neutral momentum.
Current Price Display : The dashboard also shows the current price and highlights whether it is above or below the opening price.
🔵 HOW TO USE
● Identifying Trend Reversals
Bullish Reversals : When the oscillators short period lines start to cross above the upper volatility band (green), it indicates potential bullish momentum.
Bearish Reversals : When the oscillator crosses below the lower volatility band (red), it signals potential bearish momentum.
Neutral Signals : When the oscillator remains within the bands (yellow), it suggests that the market is in a neutral or consolidating state. Traders may choose to wait for a clearer trend signal.
● Using the Dashboard for Trend Overview
Market Trend Summary : The dashboard provides a quick overview of market direction across six different smoothing levels. Green arrows indicate bullish momentum, red arrows indicate bearish momentum, and wavy lines suggest neutrality.
Price Context : The dashboard also displays the current price, helping traders quickly assess whether the price is moving in the expected direction relative to their trend analysis.
● Volatility Band Interpretation
Volatility-Based Signals : Pay attention to how the oscillators interact with the volatility bands. Strong trends will often result in oscillators staying above or below the bands, while weaker trends or consolidations will see oscillators hovering within the bands.
🔵 CUSTOMIZATION
Length and Smoothing : Adjust the length and smoothing parameters to fit different market conditions and timeframes.
Bands Multiplier : Customize the multiplier for the volatility bands to make them more or less sensitive to price changes.
Mid-Line Type : Choose whether to display the Butterworth filter as a mid-line or incorporate it into the volatility bands.
Signal Markers : Toggle on or off the number markers for signal crossovers, making it easier to identify key entry and exit points.
🔵 CONCLUSION
The Inverse Fisher Oscillator combines the power of the Inverse Fisher Transform and the Butterworth filter to provide a sophisticated approach to trend and reversal detection. By leveraging volatility-based analysis and visually intuitive signals, this indicator helps traders spot potential entry and exit points with greater clarity. The customizable dashboard display adds further value, offering a real-time summary of market conditions to enhance decision-making. Use this tool in conjunction with other technical analysis methods to develop a well-rounded trading strategy.
Composite Momentum█ Introduction
The Composite Momentum Indicator is a tool we came across that we found to be useful at detecting implied tops and bottoms within quick market cycles. Its approach to analyzing momentum through a combination of moving averages and summation techniques makes it a useful addition to the range of available indicators on TradingView.
█ How It Works
This indicator operates by calculating the difference between two moving averages—one fast and one slow, which can be customized by the user. The difference between these two averages is then expressed as a percentage of the fast moving average, forming the core momentum value which is then smoothed with an Exponential Moving Average is applied. The smoothed momentum is then compared across periods to identify directional changes in direction
Furthermore, the script calculates the absolute differences between consecutive momentum values. These differences are used to determine periods of momentum acceleration or deceleration, aiming to establish potential reversals.
In addition to tracking momentum changes, the indicator sums positive and negative momentum changes separately over a user-defined period. This summation is intended to provide a clearer picture of the prevailing market bias—whether it’s leaning towards strength or weakness.
Finally, the summed-up values are normalized to a percentage scale. This normalization helps in identifying potential tops and bottoms by comparing the relative strength of the momentum within a given cycle.
█ Usage
This indicator is primarily useful for traders who focus on detecting quick cycle tops and bottoms. It provides a view of momentum shifts that can signal these extremes, though it’s important to use it in conjunction with other tools and market analysis techniques. Given its ability to highlight potential reversals, it may be of interest to those who seek to understand short-term market dynamics.
█ Disclaimer
This script was discovered without any information about its author or original intent but was nonetheless ported from its original format that is available publicly. It’s provided here for educational purposes and should not be considered a guaranteed method for market analysis. Users are encouraged to test and understand the indicator thoroughly before applying it in real trading scenarios.
MACD with DPO Strategy by NGExplanation of the MACD with DPO Strategy:
MACD (Moving Average Convergence Divergence):
The MACD is a trend-following indicator that shows the relationship between two moving averages of a price.
In this script:
We calculate the MACD line by subtracting the slow moving average (typically 26-period EMA) from the fast moving average (typically 12-period EMA).
The Signal line is calculated as a 9-period EMA of the MACD line.
The Histogram is the difference between the MACD line and the Signal line, indicating the momentum of the price trend.
Buy Condition: The script generates a buy signal when the MACD histogram crosses from negative to positive (indicating a bullish momentum) and DPO is also positive.
Sell Condition: The script generates a sell signal when the MACD histogram crosses from positive to negative (indicating a bearish momentum) and DPO is also negative.
DPO (Detrended Price Oscillator):
The DPO removes long-term trends from prices, making it easier to identify shorter-term cycles or oscillations.
In this script:
We calculate the DPO by subtracting a shifted simple moving average (SMA) from the close price. The shifting period depends on half the specified period.
We also calculate the DPO SMA as a 30-period EMA of the DPO values.
DPO Color: The DPO line is colored green when the DPO is above zero (indicating upward momentum) and red when it is below zero (indicating downward momentum). The histogram is also colored based on whether the DPO is positive or negative.
Plotting and Alerts:
The script plots the MACD, Signal, and Histogram on the chart.
Additionally, it plots the DPO and its SMA with different colors depending on whether the DPO is above or below zero.
Buy Signal: A green arrow labeled "BUY" is plotted below the bar when both MACD and DPO indicate a bullish condition.
Sell Signal: A red arrow labeled "SELL" is plotted above the bar when both MACD and DPO indicate a bearish condition.
Background colors are used to highlight the chart whenever a buy or sell condition occurs.
The script also includes alerts for both buy and sell signals, allowing users to set notifications when conditions are met.
How to Use:
Identify Buy and Sell Signals:
The script generates a Buy signal when:
The MACD histogram crosses from negative to positive (bullish momentum), and
The DPO is above zero (indicating upward momentum).
The script generates a Sell signal when:
The MACD histogram crosses from positive to negative (bearish momentum), and
The DPO is below zero (indicating downward momentum).
Chart Visualization:
The MACD histogram and Signal line help visualize the momentum and potential trend reversal.
The DPO and DPO SMA help visualize the shorter-term price cycles.
The signals (Buy and Sell) will be plotted on the chart with arrows indicating entry points.
Customization:
You can adjust the MACD and DPO parameters (such as fast_length, slow_length, period_) to fit your trading style or market conditions.
The script can be used in any timeframe depending on your strategy (e.g., intraday trading or longer-term trading).
Example Scenario:
If you're looking for potential buy opportunities, wait for the script to generate a buy signal (green arrow) where the MACD histogram has shifted to positive, and DPO is also in the green (above zero). This signals that both momentum and cycle direction are aligned for a potential upward movement.
Conversely, for sell opportunities, wait for the red arrow where MACD momentum is turning negative and DPO is also negative (below zero), indicating a bearish condition.
This combination of MACD and DPO allows traders to identify stronger and more reliable entry/exit points by confirming the trend with the MACD and detecting shorter-term price cycles with the DPO.
Pulse Oscillator [UAlgo]The "Pulse Oscillator " is a trading tool designed to capture market momentum and trend changes by combining the strengths of multiple well-known technical indicators. By integrating the RSI (Relative Strength Index), CCI (Commodity Channel Index), and Stochastic Oscillator, this indicator provides traders with a comprehensive view of market conditions, offering both trend filtering and precise buy/sell signals. The oscillator is customizable, allowing users to fine-tune its parameters to match different trading strategies and timeframes. With its built-in smoothing techniques and level adjustments, the Pulse Oscillator aims to be a reliable tool for both trend-following and counter-trend trading strategies.
🔶 Key Features
Multi-Indicator Integration: Combines RSI, CCI, and Stochastic Oscillator to create a weighted momentum oscillator.
Why Use Multi-Indicator Integration?
Script uses Multi-Indicator Integration to combine the strengths of different technical indicators—such as RSI, CCI, and Stochastic Oscillator—into a single tool. This approach helps to reduce the weaknesses of individual indicators, providing a more comprehensive and reliable analysis of market conditions. By integrating multiple indicators, we can generate more accurate signals, filter out noise, and enhance our trading decisions.
Customizable Parameters: Allows users to adjust weights, periods, and smoothing techniques, providing flexibility to adapt the indicator to various market conditions.
Trend Filtering Option: An optional trend filter is available to enhance the accuracy of buy and sell signals, reducing the risk of false signals in choppy markets.
Dynamic Levels: The indicator dynamically calculates multiple levels of support and resistance, adjusting to market conditions with customizable decay factors and offsets.
Visual Clarity: The indicator visually represents different levels and trends with color-coded plots and fills, making it easier for traders to interpret market conditions at a glance.
Alerts: Configurable alerts for buy and sell signals, as well as trend changes, enabling traders to stay informed of key market movements without constant monitoring.
🔶 Interpreting the Indicator
Buy Signal: A buy signal is generated when the Slow Line crosses under the Fast Line during an uptrend or when the trend filter is disabled. This indicates a potential bullish reversal or continuation of an upward trend.
Sell Signal: A sell signal occurs when the Slow Line crosses above the Fast Line during a downtrend or when the trend filter is disabled, signaling a potential bearish reversal or continuation of a downward trend.
Trend Change: The indicator detects trend changes when the Fast Line shifts from increasing to decreasing or vice versa, providing early warning of possible market reversals.
Dynamic Levels: The indicator calculates upper and lower levels based on the Fast Line's values. These levels can be used to identify overbought or oversold conditions and potential areas of support or resistance.
🔶 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.
