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.
中心震盪指標
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.
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.
Atlas Trend Multi Flow OscilattorThe Atlas Trend Multi Flow Oscillator is a powerful custom indicator designed to combine multiple key financial metrics—volume flow, money flow, and momentum—into a single, easy-to-read oscillatory output. This indicator helps traders better understand market dynamics by presenting a more comprehensive picture of price movements, market sentiment, and potential reversals.
Key Components:
Volume Flow: This is calculated by comparing the current price (hlcc4) to the VWAP (Volume Weighted Average Price). It helps track how volume relates to price changes.
Money Flow: The money flow multiplier is based on the highs and lows of a given period, giving insight into whether the market is experiencing buying or selling pressure.
Momentum: By averaging the price deviation from its mean, the momentum component measures the rate of price change, helping to identify trends.
Combining Factors: The three components are averaged to create the flow momentum, which is normalized and constrained between a specified upper and lower limit (-500 to 500) for better readability.
Visual Interpretation: The indicator visually signals upward or downward market shifts by changing color based on whether the current value exceeds the previous one (green for up, red for down). Additionally, bands (upper and lower) give traders a visual guide for potential overbought or oversold conditions.
How to Use:
Overbought/Oversold Levels: The indicator uses a range of -500 to 500, with additional bands drawn at 400 and -400, which can be used as potential reversal zones.
Momentum Shifts: Pay attention to color changes, as they suggest shifts in momentum. Green signals rising momentum, while red indicates declining momentum.
Zero Line: Crossing the zero line can signal a trend change, making it a valuable confirmation tool for trading decisions.
This oscillator provides a blend of volume, price action, and momentum, making it suitable for traders who want to capture both trend and reversal signals in various market conditions.
Dynamic Rate of Change OscillatorDynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram
Detailed Description for Publication
The Dynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram is a sophisticated technical analysis tool designed to enhance your understanding of market momentum. Created using Pine Script v5 on the TradingView platform, this indicator integrates multiple Rate of Change (RoC) calculations into a unified momentum oscillator. The resulting data is displayed as a color-coded histogram, providing a clear visual representation of momentum changes.
Key Features and Functionality
Multi-Length RoC Calculation:
Short-term RoC: Calculated over a user-defined period (shortRoCLength), this captures variations in price momentum over a shorter duration, offering insights into the immediate price action.
Long-term RoC: This uses a longer period (longRoCLength) to provide a broader view of momentum, helping to smooth out short-term fluctuations and highlight more established trends.
Mid-term RoC: A weighted average of the short-term and long-term RoCs, the mid-term RoC (midRoCWeight) allows you to balance sensitivity and stability in the oscillator's behavior.
Weighted RoC Calculation:
The indicator calculates a single weighted average RoC by integrating short-term, long-term, and mid-term RoCs. The weighting factor can be adjusted to prioritize different market dynamics according to the trader’s strategy. This flexible approach enables the oscillator to remain applicable across diverse market conditions.
Oscillator Calculation and Smoothing:
The oscillator value is computed by subtracting a 14-period Weighted Moving Average (WMA) from the weighted RoC, which helps to normalize the oscillator, making it more responsive to changes in momentum.
The oscillator is then smoothed using a Simple Moving Average (SMA) over a user-defined period (smoothLength). This process reduces market noise, making the oscillator's signals clearer and easier to interpret.
Color-Coded Histogram:
The smoothed oscillator is displayed as a histogram, which is color-coded to reflect bullish or bearish momentum. You can customize the colors to match your charting style, with green typically representing upward momentum and red representing downward momentum.
The color-coded histogram allows for quick visual identification of momentum changes on the chart, aiding in your market analysis.
Zero-Line Reference:
A horizontal line at the zero level is plotted as a reference point. This zero-line helps in identifying when the histogram shifts from positive to negative or vice versa, which can be useful in understanding momentum shifts.
The zero-line offers a straightforward visual cue, making it easier to interpret the oscillator's signals in relation to market movements.
Customization and Versatility
The Dynamic RoC Oscillator with Histogram is designed with flexibility in mind, making it suitable for a wide range of trading styles, from short-term trading to longer-term analysis. Users have the ability to fine-tune the indicator’s input parameters to align with their specific needs:
Adjustable RoC Periods: Customize the short-term and long-term RoC lengths to match the timeframes you focus on.
Weighted Sensitivity: Adjust the mid-term RoC weight to emphasize different aspects of momentum according to your analysis approach.
Smoothing Options: Modify the smoothing moving average length to control the sensitivity of the oscillator, allowing you to balance responsiveness with noise reduction.
Use Cases
Momentum Analysis: Gain a clearer understanding of momentum changes within the market, which can aid in the evaluation of market trends.
Trend Analysis: The oscillator can help in assessing trends by highlighting when momentum is increasing or decreasing.
Chart Visualization: The color-coded histogram provides a visually intuitive method for monitoring momentum, helping you to more easily interpret market behavior.
Conclusion
The Dynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram is a versatile and powerful tool for traders who seek a deeper analysis of market momentum. With its dynamic calculation methods and high degree of customization, this indicator can be tailored to suit a variety of trading strategies. By integrating it into your TradingView charts, you can enhance your technical analysis capabilities, gaining valuable insights into market momentum.
This indicator is easy to use and highly customizable, making it a valuable addition to any trader’s toolkit. Add it to your charts on the TradingView platform and start exploring its potential to enrich your market analysis.
Cumulative Net Money FlowDescription:
Dive into the financial depth of the markets with the "Cumulative Net Money Flow" indicator, designed to provide a comprehensive view of the monetary dynamics in trading. This tool is invaluable for traders and investors seeking to quantify the actual money entering or exiting the market over a specified period.
Features:
Value-Weighted Calculations: This indicator multiplies the trading volume by the price, offering a money flow perspective rather than just counting shares or contracts.
Custom Timeframe Adaptability: Adjust the timeframe to match your trading strategy, whether you are day trading, swing trading, or looking for longer-term trends.
Cumulative Insight: Tracks and accumulates net money flow to highlight overall market sentiment, making it easier to spot trends in capital movement.
Color-Coded Visualization: Displays positive money flow in green and negative money flow in red, providing clear, visual cues about market conditions.
Utility: "Cumulative Net Money Flow" is particularly effective in revealing the strength behind market movements. By understanding whether the money flow is predominantly buying or selling, traders can better align their strategies with market sentiment. This indicator is suited for various asset classes, including stocks, cryptocurrencies, and forex.
Uptrick: DPO Signal & Zone Indicator
## **Uptrick: DPO Signal & Zone Indicator**
### **Introduction:**
The **Uptrick: DPO Signal & Zone Indicator** is a sophisticated technical analysis tool tailored to provide insights into market momentum, identify potential trading signals, and recognize extreme market conditions. It leverages the Detrended Price Oscillator (DPO) to strip out long-term trends from price movements, allowing traders to focus on short-term fluctuations and cyclical behavior. The indicator integrates multiple components, including a Detrended Price Oscillator, a Signal Line, a Histogram, and customizable alert levels, to deliver a robust framework for market analysis and trading decision-making.
### **Detailed Breakdown:**
#### **1. Detrended Price Oscillator (DPO):**
- **Purpose and Functionality:**
- The DPO is designed to filter out long-term trends from the price data, isolating short-term price movements. This helps in understanding the cyclical patterns and momentum of an asset, allowing traders to detect periods of acceleration or deceleration that might be overlooked when focusing solely on long-term trends.
- **Calculation:**
- **Formula:** `dpo = close - ta.sma(close, smaLength)`
- **`close`:** The asset’s closing price for each period in the dataset.
- **`ta.sma(close, smaLength)`:** The Simple Moving Average (SMA) of the closing prices over a period defined by `smaLength`.
- The DPO is derived by subtracting the SMA value from the current closing price. This calculation reveals how much the current price deviates from the moving average, effectively detrending the price data.
- **Interpretation:**
- **Positive DPO Values:** Indicate that the current price is higher than the moving average, suggesting bullish market conditions and a potential upward trend.
- **Negative DPO Values:** Indicate that the current price is lower than the moving average, suggesting bearish market conditions and a potential downward trend.
- **Magnitude of DPO:** Reflects the strength of momentum. Larger positive or negative values suggest stronger momentum in the respective direction.
#### **2. Signal Line:**
- **Purpose and Functionality:**
- The Signal Line is a smoothed average of the DPO, intended to act as a reference point for generating trading signals. It helps to filter out short-term fluctuations and provides a clearer perspective on the prevailing trend.
- **Calculation:**
- **Formula:** `signalLine = ta.sma(dpo, signalLength)`
- **`ta.sma(dpo, signalLength)`:** The SMA of the DPO values over a period defined by `signalLength`.
- The Signal Line is calculated by applying a moving average to the DPO values. This smoothing process reduces noise and highlights the underlying trend direction.
- **Interpretation:**
- **DPO Crossing Above Signal Line:** Generates a buy signal, suggesting that short-term momentum is turning bullish relative to the longer-term trend.
- **DPO Crossing Below Signal Line:** Generates a sell signal, suggesting that short-term momentum is turning bearish relative to the longer-term trend.
- **Signal Line’s Role:** Provides a benchmark for assessing the strength of the DPO. The interaction between the DPO and the Signal Line offers actionable insights into potential entry or exit points.
#### **3. Histogram:**
- **Purpose and Functionality:**
- The Histogram visualizes the difference between the DPO and the Signal Line. It provides a graphical representation of momentum strength and direction, allowing traders to quickly gauge market conditions.
- **Calculation:**
- **Formula:** `histogram = dpo - signalLine`
- The Histogram is computed by subtracting the Signal Line value from the DPO value. Positive values indicate that the DPO is above the Signal Line, while negative values indicate that the DPO is below the Signal Line.
- **Interpretation:**
- **Color Coding:**
- **Green Bars:** Represent positive values, indicating bullish momentum.
- **Red Bars:** Represent negative values, indicating bearish momentum.
- **Width of Bars:** Indicates the strength of momentum. Wider bars signify stronger momentum, while narrower bars suggest weaker momentum.
- **Zero Line:** A horizontal gray line that separates positive and negative histogram values. Crosses of the histogram through this zero line can signal shifts in momentum direction.
#### **4. Alert Levels:**
- **Purpose and Functionality:**
- Alert levels define specific thresholds to identify extreme market conditions, such as overbought and oversold states. These levels help traders recognize potential reversal points and extreme market conditions.
- **Inputs:**
- **`alertLevel1`:** Defines the upper threshold for identifying overbought conditions.
- **Default Value:** 0.5
- **`alertLevel2`:** Defines the lower threshold for identifying oversold conditions.
- **Default Value:** -0.5
- **Interpretation:**
- **Overbought Condition:** When the DPO exceeds `alertLevel1`, indicating that the market may be overbought. This condition suggests that the asset could be due for a correction or reversal.
- **Oversold Condition:** When the DPO falls below `alertLevel2`, indicating that the market may be oversold. This condition suggests that the asset could be poised for a rebound or reversal.
#### **5. Visual Elements:**
- **DPO and Signal Line Plots:**
- **DPO Plot:**
- **Color:** Blue
- **Width:** 2 pixels
- **Purpose:** To visually represent the deviation of the current price from the moving average.
- **Signal Line Plot:**
- **Color:** Red
- **Width:** 1 pixel
- **Purpose:** To provide a smoothed reference for the DPO and generate trading signals.
- **Histogram Plot:**
- **Color Coding:**
- **Green:** For positive values, signaling bullish momentum.
- **Red:** For negative values, signaling bearish momentum.
- **Style:** Histogram bars are displayed with varying width to represent the strength of momentum.
- **Zero Line:** A gray horizontal line separating positive and negative histogram values.
- **Overbought/Oversold Zones:**
- **Background Colors:**
- **Green Shading:** Applied when the DPO exceeds `alertLevel1`, indicating an overbought condition.
- **Red Shading:** Applied when the DPO falls below `alertLevel2`, indicating an oversold condition.
- **Horizontal Lines:**
- **Dotted Green Line:** At `alertLevel1`, marking the upper alert threshold.
- **Dotted Red Line:** At `alertLevel2`, marking the lower alert threshold.
- **Purpose:** To provide clear visual cues for extreme market conditions, aiding in the identification of potential reversal points.
#### **6. Trading Signals and Alerts:**
- **Buy Signal:**
- **Trigger:** When the DPO crosses above the Signal Line.
- **Visual Representation:** A "BUY" label appears below the price bar in the specified buy color.
- **Purpose:** Indicates a potential buying opportunity as short-term momentum turns bullish.
- **Sell Signal:**
- **Trigger:** When the DPO crosses below the Signal Line.
- **Visual Representation:** A "SELL" label appears above the price bar in the specified sell color.
- **Purpose:** Indicates a potential selling opportunity as short-term momentum turns bearish.
- **Overbought/Oversold Alerts:**
- **Overbought Alert:** Triggered when the DPO crosses below `alertLevel1`.
- **Oversold Alert:** Triggered when the DPO crosses above `alertLevel2`.
- **Visual Representation:** Labels "OVERBOUGHT" and "OVERSOLD" appear with distinctive colors and sizes to highlight extreme conditions.
- **Purpose:** To signal potential reversal points and extreme market conditions that may lead to price corrections or trend reversals.
- **Alert Conditions:**
- **DPO Cross Above Signal Line:** Alerts traders when the DPO crosses above the Signal Line, generating a buy signal.
- **DPO Cross Below Signal Line:** Alerts traders when the DPO crosses below the Signal Line, generating a sell signal.
- **DPO Above Upper Alert Level:** Alerts when the DPO is above `alertLevel1`, indicating an overbought condition.
- **DPO Below Lower Alert Level:** Alerts when the DPO is below `alertLevel2`, indicating an oversold condition.
- **Purpose:** To provide real-time notifications of significant market events, enabling traders to make informed decisions promptly.
### **Practical Applications:**
#### **1. Trend Following Strategies:**
- **Objective:**
- To capture and ride the prevailing market trends by entering trades that align with the direction of the momentum.
- **How to Use:**
- Monitor buy and sell signals generated by the DPO crossing the Signal Line. A buy signal suggests a bullish trend and a potential long trade, while a sell signal suggests a bearish trend and a potential short trade.
- Use the Histogram to confirm the strength of the trend. Expanding green bars indicate strong bullish momentum, while expanding red bars indicate strong bearish momentum.
- **Advantages:**
- Helps traders stay aligned with the market trend, increasing the likelihood of capturing substantial price moves.
#### **2. Reversal Trading:**
- **Objective:**
- To identify potential market reversals
by detecting overbought and oversold conditions.
- **How to Use:**
- Look for overbought and oversold signals based on the DPO crossing `alertLevel1` and `alertLevel2`. These conditions suggest that the market may be due for a reversal.
- Confirm reversal signals with the Histogram. A decrease in histogram bars (from green to red or vice versa) may support the reversal hypothesis.
- **Advantages:**
- Provides early warnings of potential market reversals, allowing traders to position themselves before significant price changes occur.
#### **3. Momentum Analysis:**
- **Objective:**
- To gauge the strength and direction of market momentum for making informed trading decisions.
- **How to Use:**
- Analyze the Histogram to assess momentum strength. Positive and expanding histogram bars indicate increasing bullish momentum, while negative and expanding bars suggest increasing bearish momentum.
- Use momentum insights to validate or question existing trading positions and strategies.
- **Advantages:**
- Offers valuable information about the market's momentum, helping traders confirm the validity of trends and trading signals.
### **Customization and Flexibility:**
The **Uptrick: DPO Signal & Zone Indicator** offers extensive customization options to accommodate diverse trading preferences and market conditions:
- **SMA Length and Signal Line Length:**
- Adjust the `smaLength` and `signalLength` parameters to control the sensitivity and responsiveness of the DPO and Signal Line. Shorter lengths make the indicator more responsive to price changes, while longer lengths provide smoother, less volatile signals.
- **Alert Levels:**
- Modify `alertLevel1` and `alertLevel2` to fit varying market conditions and volatility. Setting these levels appropriately helps tailor the indicator to different asset classes and trading strategies.
- **Color and Shape Customization:**
- Customize the colors and sizes of buy/sell signals, histogram bars, and alert levels to enhance visual clarity and align with personal preferences. This customization helps ensure that the indicator integrates seamlessly with a trader's charting setup.
### **Conclusion:**
The **Uptrick: DPO Signal & Zone Indicator** is a multifaceted analytical tool that combines the power of the Detrended Price Oscillator with customizable visual elements and alert levels to deliver a comprehensive approach to market analysis. By offering insights into momentum strength, trend direction, and potential reversal points, this indicator equips traders with valuable information to make informed decisions and enhance their trading strategies. Its flexibility and customization options ensure that it can be adapted to various trading styles and market conditions, making it a versatile addition to any trader's toolkit.
Xtrender and TSI FusionXtrender and TSI Fusion Indicator
I created this indicator for myself. I was inspired by the indicators created by Bjorgum, Duyck and QuantTherapy and decided to create multiple indicators that either work well combined with their indicators or something new that applies some of their indicator concepts. I decided to share all of the indicator I have created because I believe in learning and earing together as a community. If you guys have any questions or suggestions write them.
Overview: The Xtrender and TSI Fusion Indicator is a powerful tool designed to help traders analyze market momentum, trends, and potential reversals. By combining Xtrender with the True Strength Index (TSI), this indicator provides a comprehensive view of market dynamics, making it easier to identify trading opportunities.
Image: Timeframe is set to daily
Features:
1.Xtrender Analysis:
Short-Term Xtrender: Visualizes short-term momentum using RSI-based calculations on EMA differences. This helps in identifying immediate market trends and pullbacks.
Image above: showcases Short-Term Xtrender
Xtrender T3: A smoothed version of the Xtrender that reduces noise and highlights significant trend changes.
Image above: showcases Xtrender T3 with Xtrender T3 color
2.TSI (True Strength Index):
TSI Value: Measures momentum by comparing price changes over two time periods, offering a clear view of trend strength.
TSI Signal Line: A smoothed version of the TSI value, used to generate buy and sell signals when crossed by the TSI.
Image: showcases TSI Value with TSI Signal Line
TSI Histogram: Shows the difference between the TSI and its signal line, highlighting potential reversals and trend continuations.
Image: showcases TSI Histogram
3.Color Coding and Visual Cues:
Trend Colors: The indicator uses dynamic colors to represent bullish or bearish conditions, making it easy to interpret market sentiment.
Background Color : The background changes color based on TSI signals, further aiding in visual trend analysis.
Image: showcases Background color and Zero line
How to Use
1.Xtrender Analysis:
Short-Term Xtrender: The short-term Xtrender is plotted as columns, changing color based on its direction and value. Green or lime indicates positive momentum, while red or maroon indicates negative momentum.
Xtrender T3: The Xtrender T3 line (black) represents a smoothed version of the short-term Xtrender, providing a clearer picture of the overall trend. The color of this line changes based on the Xtrender's value, helping you spot potential trend changes.
2.TSI (True Strength Index):
TSI Value and Signal Line: The TSI value is plotted as a line, with its color changing based on its relationship to the signal line. A crossover of the TSI above the signal line suggests a potential bullish move, while a crossover below indicates a bearish trend.
TSI Histogram: The histogram represents the difference between the TSI and its signal line. Positive values indicate bullish momentum, while negative values suggest bearish momentum.
3.Background Color:
The background color changes based on the TSI signal, with a greenish hue indicating bullish conditions and a reddish hue indicating bearish conditions. This provides a quick visual reference for market sentiment.
4.Zero Line:
A horizontal gray dotted line at the zero level helps you easily identify when the Xtrender or TSI crosses into positive or negative territory, signaling potential trend shifts.
Image above: Timeframe on daily with the individual elements combined
Example of Use:
•Trend Confirmation: Use the Xtrender and Xtrender T3 to confirm the direction of the trend. If both are aligned with the same color and direction, it increases the probability of a strong trend.
•Momentum Reversals: Watch for TSI crosses and histogram shifts to identify potential reversals. For example, a TSI crossover above its signal line with a corresponding change in the histogram from negative to positive could signal a buying opportunity.
•Pullbacks: Identify pullbacks within a trend by observing temporary shifts in the short-term Xtrender or TSI histogram. Use these signals to enter trades in the direction of the overall trend.
Image above: Showcases, Trend confirmation, reversal and pullbacks on daily timeframe.
Customization:
•TSI Speed: Choose between "Fast" and "Slow" TSI settings based on your trading style. Fast settings are more responsive to price changes, while slow settings offer smoother signals.
•Color Settings: Customize the colors for bullish, bearish, and neutral TSI conditions to match your personal preferences or chart theme.
This indicator is versatile and can be used for various trading strategies, from trend following to momentum trading, making it a valuable tool in any trader's arsenal.
My Scripts/Indicators/Ideas /Systems that I share are only for educational purposes
Uptrick: SMA Pivot Marker### Uptrick: SMA Pivot Marker (SPM) — Extensive Guide
#### Introduction
The **Uptrick: SMA Pivot Marker (SPM)** is a sophisticated technical analysis tool crafted by Uptrick to help traders interpret market trends and identify key price levels where significant reversals might occur. By integrating the principles of the Simple Moving Average (SMA) with pivot point analysis, the SPM offers a comprehensive approach to understanding market dynamics. This extensive guide explores the purpose, functionality, and practical applications of the SPM, providing an in-depth analysis of its features, settings, and usage across various trading strategies.
#### Purpose of the SPM
The **SMA Pivot Marker (SPM)** aims to enhance trading strategies by offering a dual approach to market analysis:
1. **Trend Identification**:
- **Objective**: To discern the prevailing market direction and guide trading decisions based on the overall trend.
- **Method**: Utilizes the SMA to smooth out price fluctuations, providing a clearer picture of the trend. This helps traders align their trades with the market's direction, increasing the probability of successful trades.
2. **Pivot Point Detection**:
- **Objective**: To identify key levels where the price is likely to reverse, providing potential support and resistance zones.
- **Method**: Calculates and marks pivot highs and lows, which are significant price points where previous trends have reversed. These levels are used to predict future price movements and establish trading strategies.
3. **Trend Change Alerts**:
- **Objective**: To notify traders of potential shifts in market direction, enabling timely adjustments to trading positions.
- **Method**: Detects and highlights crossover and crossunder points of the smoothed line, indicating possible trend changes. This helps traders react promptly to changing market conditions.
#### Detailed Functionality
1. **Smoothing Line Calculation**:
- **Simple Moving Average (SMA)**:
- **Definition**: The SMA is a type of moving average that calculates the average of a security’s price over a specified number of periods. It smooths out price data to filter out short-term fluctuations and highlight the longer-term trend.
- **Calculation**: The SMA is computed by summing the closing prices of the chosen number of periods and then dividing by the number of periods. For example, a 20-period SMA adds the closing prices for the past 20 periods and divides by 20.
- **Purpose**: The SMA helps in identifying the direction of the trend. A rising SMA indicates an uptrend, while a falling SMA indicates a downtrend. This smoothing helps traders to avoid being misled by short-term price noise.
2. **Pivot Points Calculation**:
- **Pivot Highs and Lows**:
- **Definition**: Pivot points are significant price levels where a market trend is likely to reverse. A pivot high is the highest price over a certain period, surrounded by lower prices on both sides, while a pivot low is the lowest price surrounded by higher prices.
- **Calculation**: The SPM calculates pivot points based on a user-defined lookback period. For instance, if the lookback period is set to 3, the indicator will find the highest and lowest prices within the past 3 periods and mark these points.
- **Purpose**: Pivot points are used to identify potential support and resistance levels. Traders often use these levels to set entry and exit points, stop-loss orders, and to gauge market sentiment.
3. **Visualization**:
- **Smoothed Line Plot**:
- **Description**: The smoothed line, calculated using the SMA, is plotted on the chart to provide a visual representation of the trend. This line adjusts its color based on the trend direction, helping traders quickly assess the market condition.
- **Color Coding**: The smoothed line is colored green (upColor) when it is rising, indicating a bullish trend, and red (downColor) when it is falling, indicating a bearish trend. This color-coding helps traders visually differentiate between uptrends and downtrends.
- **Line Width**: The width of the line can be adjusted to improve visibility. A thicker line may be more noticeable, while a thinner line might provide a cleaner look on the chart.
- **Pivot Markers**:
- **Description**: Pivot highs and lows are marked on the chart with lines and labels. These markers help in visually identifying significant price levels.
- **Color and Labels**: Pivot highs are represented with green lines and labels ("H"), while pivot lows are marked with red lines and labels ("L"). This color scheme and labeling make it easy to distinguish between resistance (highs) and support (lows).
4. **Trend Change Detection**:
- **Trend Up**:
- **Detection**: The indicator identifies an upward trend change when the smoothed line crosses above its previous value. This crossover suggests a potential shift from a downtrend to an uptrend.
- **Usage**: Traders can interpret this signal as a potential buying opportunity or an indication to review and possibly adjust their trading positions to align with the new uptrend.
- **Trend Down**:
- **Detection**: A downward trend change is detected when the smoothed line crosses below its previous value. This crossunder indicates a potential shift from an uptrend to a downtrend.
- **Usage**: This signal can be used to consider selling opportunities or to reassess long positions in light of the emerging downtrend.
#### User Inputs
1. **Smoothing Period**:
- **Description**: This input determines the number of periods over which the SMA is calculated. It directly affects the smoothness of the line and the sensitivity of trend detection.
- **Range**: The smoothing period can be set to any integer value greater than or equal to 1. There is no specified upper limit, offering flexibility for various trading styles.
- **Default Value**: The default smoothing period is 20, which is a common choice for medium-term trend analysis.
- **Impact**: A longer smoothing period results in a smoother line, filtering out more noise and highlighting long-term trends. A shorter period makes the line more responsive to recent price changes, which can be useful for short-term trading strategies.
2. **Pivot Lookback**:
- **Description**: This input specifies the number of periods used to calculate the pivot highs and lows. It influences the sensitivity of pivot point detection and the relevance of the identified levels.
- **Range**: The pivot lookback period can be set to any integer value greater than or equal to 1, with no upper limit. Traders can adjust this parameter based on their trading timeframe and preferences.
- **Default Value**: The default lookback period is 3, which provides a balance between detecting significant pivots and avoiding excessive noise.
- **Impact**: A longer lookback period generates more stable pivot points, suitable for identifying long-term support and resistance levels. A shorter lookback period results in more frequent and recent pivot points, useful for intraday trading and quick responses to price changes.
#### Applications for Different Traders
1. **Trend Followers**:
- **Using the SMA**: Trend followers utilize the smoothed line to gauge the direction of the market. By aligning trades with the direction of the SMA, traders can capitalize on sustained trends and improve their chances of success.
- **Trend Change Alerts**: The trend change markers alert trend followers to potential shifts in market direction. These alerts help traders make timely decisions to enter or exit positions, ensuring they stay aligned with the prevailing trend.
2. **Reversal Traders**:
- **Pivot Points**: Reversal traders focus on pivot highs and lows to identify potential reversal points in the market. These points indicate where the market has previously reversed direction, providing potential entry and exit levels for trades.
- **Pivot Markers**: The visual markers for pivot highs and lows serve as clear signals for reversal traders. By monitoring these levels, traders can anticipate price reversals and plan their trades to exploit these opportunities.
3. **Swing Traders**:
- **Combining SMA and Pivot Points**: Swing traders can use the combination of the smoothed line and pivot points to identify medium-term trading opportunities. The smoothed line helps in understanding the broader trend, while pivot points provide specific levels for potential swings.
- **Trend Change Alerts**: Trend change markers help swing traders spot new swing opportunities as the market shifts direction. These markers provide potential entry points for swing trades and help traders adjust their strategies to capitalize on market movements.
4. **Scalpers**:
- **Short-Term Analysis**: Scalpers benefit from the short-term signals provided by the SPM. The smoothed line and pivot points offer insights into rapid price movements, while the trend change markers highlight quick trading opportunities.
- **Pivot Points**: For scalpers, pivot points are particularly useful in identifying key levels where price may reverse within a short time frame. By focusing on these levels, scalpers can plan trades with tight stop-loss orders and capitalize on quick price changes.
#### Implementation and Best Practices
1. **Setting Parameters**:
- **Smoothing Period**: Adjust the smoothing period according to your trading strategy and market conditions. For long-term analysis, use a longer period to filter out noise and highlight broader trends. For short-term trading, a shorter period provides more immediate insights into price movements.
- **Pivot Lookback**: Choose a lookback period that matches your trading timeframe. For intraday trading, a shorter lookback period offers quick identification of recent price levels. For swing trading or long-term strategies, a longer lookback period provides more stable pivot points.
2. **Combining with Other Indicators**:
- **Integration with Technical Tools**: The SPM can be used in conjunction with other technical indicators to enhance trading decisions. For instance, combining the
SPM with indicators like RSI (Relative Strength Index) or MACD (Moving Average Convergence Divergence) can provide additional confirmation for trend signals and pivot points.
- **Support and Resistance**: Integrate the SPM’s pivot points with other support and resistance levels to gain a comprehensive view of market conditions. This combined approach helps in identifying stronger levels of support and resistance, improving trade accuracy.
3. **Backtesting**:
- **Historical Performance**: Conduct backtesting with historical data to evaluate the effectiveness of the SPM. Analyze past performance to fine-tune the smoothing period and pivot lookback settings, ensuring they align with your trading style and market conditions.
- **Scenario Analysis**: Test the SPM under various market scenarios to understand its performance in different conditions. This analysis helps in assessing the reliability of the indicator and making necessary adjustments for diverse market environments.
4. **Customization**:
- **Visual Adjustments**: Customize the appearance of the smoothed line and pivot markers to enhance chart readability and match personal preferences. Clear visual representation of these elements improves the effectiveness of the indicator.
- **Alert Configuration**: Set up alerts for trend changes to receive timely notifications. Alerts help traders act quickly on potential market shifts without constant monitoring, allowing for more efficient trading decisions.
#### Conclusion
The **Uptrick: SMA Pivot Marker (SPM)** is a versatile and powerful technical analysis tool that combines the benefits of the Simple Moving Average with pivot point analysis. By providing insights into market trends, identifying key reversal points, and detecting trend changes, the SPM caters to a wide range of trading strategies, including trend following, reversal trading, swing trading, and scalping.
With its customizable inputs, visual markers, and trend change alerts, the SPM offers traders the flexibility to adapt the indicator to different market conditions and trading styles. Whether used independently or in conjunction with other technical tools, the SPM is designed to enhance trading decision-making and improve overall trading performance. By mastering the use of the SPM, traders can gain a valuable edge in navigating the complexities of financial markets and making more informed trading decisions.
Z-Score AggregatorOverview:
This indicator is designed to take multiple other indicators as inputs, calculate their respective Z-scores, and then aggregate these Z-scores to provide a comprehensive measure. By transforming the inputs into Z-scores, this indicator standardizes the data, enabling a more accurate comparison across different indicators, each of which may have different scales and distributions.
This indicator is beneficial for Mean-Reversion style trading and investing as it standardizes indicators and lets them work together in one system.
The Z-score, which represents how many standard deviations an element is from the mean, is a crucial statistical tool in this process. It allows the indicator to normalize the varying data points, ensuring that each indicator's contribution to the aggregate score is proportional to its deviation from the average performance.
Inputs:
Z-score length: How far Back it will take into account the inputs
Number Of Sources: This is to set the number of inputs the indicator uses so it calculates them properly and uses only the number of indicators you want.
Source Inputs: 1-10 inputs (no need to use them all as long as you set the number of used indicators beforehand).
Note:
There are three indicators used in this example which are CCI, RSI and Sharpe Ratio. The indicator calculates their individual Z-scores and takes an average. Because Number Of Sources is set to 3 it only uses the first 3 indicators in use.
