KNN OscillatorOverview
The KNN Oscillator is an advanced technical analysis tool designed to help traders identify potential trend reversals and market momentum. Using the K-Nearest Neighbors (KNN) algorithm, this oscillator normalizes KNN values to create a dynamic and responsive indicator. The oscillator line changes color to reflect the market sentiment, providing clear visual cues for trading decisions.
Key Features
Dynamic Color Oscillator: The line changes color based on the oscillator value – green for positive, red for negative, and grey for neutral.
Advanced KNN Algorithm: Utilizes the K-Nearest Neighbors algorithm for precise trend detection.
Normalized Values: Ensures the oscillator values are normalized to align with the stock price range, making it applicable to various assets.
Easy Integration: Can be easily added to any TradingView chart for enhanced analysis.
How It Works
The KNN Oscillator leverages the K-Nearest Neighbors algorithm to calculate the average distance of the nearest neighbors over a specified period. These values are then normalized to match the stock price range, ensuring they are comparable across different assets. The oscillator value is derived by taking the difference between the normalized KNN values and the source price. The line's color changes dynamically to provide an immediate visual indication of the market's state:
Green: Positive values indicate upward momentum.
Red: Negative values indicate downward momentum.
Grey: Neutral values indicate a stable or consolidating market.
Usage Instructions
Trend Reversal Detection: Use the color changes to identify potential trend reversals. A shift from red to green suggests a bullish reversal, while a shift from green to red indicates a bearish reversal.
Momentum Analysis: The oscillator's value and color help gauge market momentum. Strong positive values (green) indicate strong upward momentum, while strong negative values (red) indicate strong downward momentum.
Market Sentiment: The dynamic color changes provide an easy-to-understand visual representation of market sentiment, helping traders make informed decisions quickly.
Confirmation Tool: Use the KNN Oscillator in conjunction with other technical indicators to confirm signals and improve the accuracy of your trades.
Scalability: Applicable to various timeframes and asset classes, making it a versatile tool for all types of traders.
震盪指標
ADX and SADX, SDIThe indicator aims to analyze and visualize the Average Directional Index (ADX) and its smoothed versions, along with directional indicators (DI) to help traders identify trend strength and potential buy/sell signals.
Indicator Settings:
The indicator is named "ADX and SADX, SDI" and is set to display prices with a precision of 2 decimal places.
Users can customize the ADX smoothing length, DI length, ADX smoothing period, and DI smoothing period through input variables.
Directional Movement (DM) Calculation:
The function dirmov calculates the positive and negative directional movements (DM) and the smoothed values of the positive directional index (DI+) and negative directional index (DI-).
This is done using the average true range (ATR) to normalize the DM values.
Average Directional Index (ADX) Calculation:
The function adx calculates the ADX, which measures the strength of a trend.
It uses the DI+ and DI- values to compute the ADX value.
Smoothed ADX and DI Calculation:
The ADX values are further smoothed using a simple moving average (SMA).
The DI difference is also smoothed and used to determine the trend direction.
Buy and Sell Signals:
A buy signal is generated when the DI+ crosses above DI- and the smoothed DI difference is increasing.
A sell signal is generated when the DI- crosses above DI+ and the smoothed DI difference is decreasing.
Plotting:
The ADX, smoothed ADX, smoothed DI difference (SPM), DI+, and DI- values are plotted on the chart.
Horizontal lines are drawn to indicate threshold levels (e.g., level 22).
Background and bar colors change based on buy (lime) and sell (maroon) signals to visually indicate these conditions.
Purpose of the Code:
This Pine Script code is used to create a custom indicator on TradingView that helps traders identify the strength and direction of a trend. The Average Directional Index (ADX) is used to measure trend strength, while the Directional Indicators (DI+ and DI-) are used to determine the direction of the trend. The smoothed versions of these indicators (SADX and SDI) provide additional confirmation and smoothing to reduce noise and false signals. Traders can use the buy and sell signals generated by this indicator to make informed trading decisions based on the trend strength and direction.
Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
RSI Sector analysis
Screening tool that produces a table with the various sectors and their RSI values. The values are shown in 3 rows, each with a user-defined length, and can be averaged out and displayed as a single value. The chart is color coded as well. Each ETF representing a sector can be looked at individually, with the top holdings in each preprogrammed, but users can define their own if they wish. The left most ticker is the "benchmark"; SPY is the benchmark for the various sectors, and the ETF is the benchmark for the tickers within.
Symbols are color coded: light blue text indicates that a symbol has greater RSI values in all three timeframes than the benchmark (the leftmost symbol). Orange text indicates that a symbol has a lower RSI value for all three timeframes. In the first row, light blue text indicates the largest RSI increase from the third row to the first row. Orange text indicates the largest RSI decrease from the third row to the first row.
A blue highlight indicates that the value is the highest among the tickers, excluding the benchmark, and an orange highlight indicates that the value is the lowest among the tickers, also excluding the benchmark. A blue highlight on the ticker indicates that it has the highest average value of the 3 rows, and a orange highlight on the ticker indicates that it has the lowest average value of the 3 rows.
DeQuex Algo BISTIntroduction:
The DeQuex Algo is an advanced technical analysis tool designed to help traders identify high-probability entry and exit points in the Borsa Istanbul (BIST) market. This updated version incorporates an adaptive MACD to reduce false signals and improve the overall reliability of the indicator.
Key Features:
1. Adaptive MACD: The script utilizes an adaptive MACD that dynamically adjusts to market volatility, reducing the occurrence of false signals often associated with traditional MACD implementations.
2. RSI Confirmation: In addition to the adaptive MACD, the DeQuex Algo also considers RSI readings to provide stronger confirmation for buy and sell signals.
3. Signal Types:
- Buy Signal: Triggered when the adaptive MACD crosses above its signal line.
- Sell Signal: Triggered when the adaptive MACD crosses below its signal line.
- Strong Buy Signal: Triggered when both the adaptive MACD and RSI cross above their respective thresholds, indicating a high-probability bullish setup.
- Strong Sell Signal: Triggered when both the adaptive MACD and RSI cross below their respective thresholds, indicating a high-probability bearish setup.
4. Price Bar Highlighting: The script color-codes price bars to provide a visual representation of the current trend. Green bars indicate an uptrend, red bars indicate a downtrend, and purple bars signify a period of consolidation or uncertainty. This feature allows traders to quickly assess the market context at a glance.
5. Customizable Alerts: Users can enable alerts for each signal type, ensuring they never miss a potential trading opportunity.
6. Dynamic Support and Resistance: The DeQuex Algo incorporates dynamic support and resistance levels based on market volatility. These levels are plotted using an innovative approach that combines Donchian channels with a Kalman filter for smoother, more reliable zones.
7. User-Friendly Inputs: The script provides a range of input parameters, allowing traders to fine-tune the indicator's sensitivity and adapt it to their preferred trading style and timeframe.
How to Use:
1. Add the DeQuex Algo indicator to your TradingView chart.
2. Customize the input parameters as desired, or use the default settings.
3. Enable alerts for your preferred signal types.
4. Look for buy and sell signals based on the adaptive MACD and RSI readings, paying attention to the color-coded price bars for additional context.
5. Consider the dynamic support and resistance levels when planning your entries, exits, and stop-loss placements.
Please note that while the DeQuex Algo is designed to identify high-probability setups, no indicator is perfect, and false signals may still occur. Always use proper risk management and consider other factors, such as market sentiment and fundamental analysis, when making trading decisions.
We hope that the DeQuex Algo will be a valuable addition to your trading toolbox, and we welcome any feedback or suggestions for further improvement.
Best regards,
BrandonJames1337
TR:
İşte güncellenmiş DeQuex Algo göstergeniz için önerilen bir açıklama:
Giriş:
DeQuex Algo, yatırımcıların Borsa İstanbul (BIST) piyasasında yüksek olasılıklı giriş ve çıkış noktalarını belirlemelerine yardımcı olmak için tasarlanmış gelişmiş bir teknik analiz aracıdır. Bu güncellenmiş sürüm, yanlış sinyalleri azaltmak ve göstergenin genel güvenilirliğini artırmak için uyarlanabilir bir MACD içerir.
Temel Özellikler:
1. Uyarlanabilir MACD: Komut dosyası, piyasa oynaklığına dinamik olarak ayarlanan ve genellikle geleneksel MACD uygulamalarıyla ilişkili yanlış sinyallerin oluşumunu azaltan uyarlanabilir bir MACD kullanır.
2. RSI Onayı: Uyarlanabilir MACD'ye ek olarak DeQuex Algo, alım ve satım sinyalleri için daha güçlü onay sağlamak üzere RSI okumalarını da dikkate alır.
3. Sinyal Türleri:
- Alış Sinyali: Uyarlanabilir MACD sinyal çizgisinin üzerine çıktığında tetiklenir.
- Satış Sinyali: Uyarlanabilir MACD sinyal çizgisinin altından geçtiğinde tetiklenir.
- Güçlü Alış Sinyali: Hem uyarlanabilir MACD hem de RSI kendi eşiklerinin üzerine çıktığında tetiklenir ve yüksek olasılıklı bir yükseliş düzenine işaret eder.
- Güçlü Satış Sinyali: Hem uyarlanabilir MACD hem de RSI kendi eşiklerinin altına düştüğünde tetiklenir ve yüksek olasılıklı bir düşüş düzenine işaret eder.
4. Fiyat Çubuğu Vurgulama: Komut dosyası, mevcut eğilimin görsel bir temsilini sağlamak için fiyat çubuklarını renk kodlarıyla kodlar. Yeşil çubuklar yükseliş trendini, kırmızı çubuklar düşüş trendini ve mor çubuklar ise konsolidasyon veya belirsizlik dönemini gösterir. Bu özellik, yatırımcıların piyasa bağlamını bir bakışta hızlı bir şekilde değerlendirmelerine olanak tanır.
5. Özelleştirilebilir Uyarılar: Kullanıcılar her sinyal türü için uyarıları etkinleştirerek potansiyel bir alım satım fırsatını asla kaçırmamalarını sağlayabilir.
6. Dinamik Destek ve Direnç: DeQuex Algo, piyasa oynaklığına dayalı dinamik destek ve direnç seviyeleri içerir. Bu seviyeler, daha yumuşak ve daha güvenilir bölgeler için Donchian kanallarını Kalman filtresiyle birleştiren yenilikçi bir yaklaşım kullanılarak çizilir.
7. Kullanıcı Dostu Girişler: Komut dosyası, yatırımcıların göstergenin hassasiyetini ince ayarlamalarına ve tercih ettikleri ticaret tarzına ve zaman dilimine uyarlamalarına olanak tanıyan bir dizi giriş parametresi sağlar.
Nasıl Kullanılır:
1. DeQuex Algo göstergesini TradingView grafiğinize ekleyin.
2. Giriş parametrelerini istediğiniz gibi özelleştirin veya varsayılan ayarları kullanın.
3. Tercih ettiğiniz sinyal türleri için uyarıları etkinleştirin.
4. Ek bağlam için renk kodlu fiyat çubuklarına dikkat ederek uyarlanabilir MACD ve RSI okumalarına dayalı alım ve satım sinyallerini arayın.
5. Girişlerinizi, çıkışlarınızı ve stop-loss yerleşimlerinizi planlarken dinamik destek ve direnç seviyelerini göz önünde bulundurun.
DeQuex Algo yüksek olasılıklı kurulumları belirlemek için tasarlanmış olsa da, hiçbir göstergenin mükemmel olmadığını ve yine de yanlış sinyallerin oluşabileceğini lütfen unutmayın. Alım satım kararları verirken her zaman uygun risk yönetimini kullanın ve piyasa duyarlılığı ve temel analiz gibi diğer faktörleri göz önünde bulundurun.
DeQuex Algo'nun ticaret araç kutunuza değerli bir katkı sağlayacağını umuyor ve daha fazla iyileştirme için her türlü geri bildirim veya öneriyi memnuniyetle karşılıyoruz.
Saygılarımla,
BrandonJames1337
Directional Movement Index DEThis script uses the existing built-in DMI indicator but adds two lines indicating strength of the ADX trend. The original author J. Welles Wilder, indicated a ADX trending strongly above 25 (yellow by default), and ADX trending weaker at a threshold of 20 or below (dashed yellow by default).
The default colours have been changed so that ADX is yellow, +DI is green, and -DI is red.
Calculation
Calculating the DMI can actually be broken down into two parts. First, calculating the +DI and -DI, and second, calculating the ADX. To calculate the +DI and -DI you need to find the +DM and -DM (Directional Movement). +DM and -DM are calculated using the High, Low and Close for each period. You can then calculate the following:
Current High - Previous High = UpMove
Previous Low - Current Low = DownMove
If UpMove > DownMove and UpMove > 0, then +DM = UpMove, else +DM = 0
If DownMove > Upmove and Downmove > 0, then -DM = DownMove, else -DM = 0
Once you have the current +DM and -DM calculated, the +DM and -DM lines can be calculated and plotted based on the number of user defined periods.
+DI = 100 times Exponential Moving Average of (+DM / Average True Range)
-DI = 100 times Exponential Moving Average of (-DM / Average True Range)
Now that -+DX and -DX have been calculated, the last step is calculating the ADX.
ADX = 100 times the Exponential Moving Average of the Absolute Value of (+DI - -DI) / (+DI + -DI)
The basics
DMI has a value between 0 and 100 and is used to measure the strength of the current trend. +DI and -DI are then used to measure direction. When combined, the indicator can provide some valuable insight. A general interpretation would be that during a strong trend (ADX above 25 but dependent on the analyst's interpretation), when the +DI is above the -DI, then a Bullish Market is defined. When -DI is above +DI, then a Bearish Market is at hand.
One thing to be considered is that what DMI values determine, strength or a potential signal, is up to the trader's interpretation. Acceptable values may change depending on the financial instrument being examined, therefore some historical analysis of the instrument in question would be prudent. A technical analyst can make better decisions based on what has occurred in historical examples.
All credit goes to the original script .
Modern Trend IdentifierThis is an update by Lightangel112 to Trendilo (Open-Source).
Thanks @ Lightangel112
The Modern Trend Identifier (MTI) is a sophisticated technical analysis tool designed for traders and analysts seeking to accurately determine market trends. This indicator leverages the Arnaud Legoux Moving Average (ALMA) to smooth price data and calculate percentage changes, providing a clearer and more responsive trend analysis. MTI is engineered to highlight trend direction with visual cues, fill areas between the indicator and its bands, and color bars based on trend direction, making it a powerful tool for identifying market momentum and potential reversals.
Capabilities
Smoothing and Trend Calculation:
Utilizes ALMA to smooth price data, reducing noise and providing a clearer view of the trend.
Calculates percentage changes in price over a user-defined lookback period.
Dynamic Range Adjustment:
Normalizes the ALMA percentage change values to ensure they stay within a -100 to 100 range.
Uses a combination of linear and smoothstep compression to handle extreme values without losing sensitivity.
Trend Direction and Highlighting:
Determines the trend direction based on the relationship between the smoothed ALMA percentage change and dynamically adjusted RMS (Root Mean Square) bands.
Colors the trend line to visually indicate whether the market is in an uptrend, downtrend, or neutral state.
Dynamic Threshold Calculation:
Calculates dynamic thresholds using percentile ranks to adapt to changing market conditions.
Visualization Enhancements:
Fills areas between the ALMA percentage change line and its RMS bands to provide a clear visual indication of the trend strength.
Offers the option to color price bars based on the identified trend direction.
Customizable Settings:
Provides extensive customization options for lookback periods, smoothing parameters, ALMA settings, band multipliers, and more.
Allows users to enable or disable various visual enhancements and customize their appearance.
Use Cases
Trend Identification:
MTI helps traders identify the current market trend, whether it's bullish, bearish, or neutral. This can be particularly useful for trend-following strategies.
Momentum Analysis:
By highlighting areas of strong momentum, MTI enables traders to spot potential breakouts or breakdowns. This can be useful for both entry and exit decisions.
Support and Resistance Levels:
The dynamic threshold bands can act as support and resistance levels. Traders can use these levels to set stop-loss and take-profit orders.
Divergence Detection:
MTI can help in identifying divergences between price and the indicator, which can signal potential trend reversals. This is useful for traders looking to capitalize on trend changes.
Risk Management:
The fill areas and colored bars provide clear visual cues about trend strength and direction, aiding in better risk management. Traders can adjust their positions based on the strength of the trend.
Backtesting:
The extensive customization options allow traders to backtest different settings and parameters to optimize their trading strategies for various market conditions.
Multiple Timeframes:
MTI can be applied to multiple timeframes, from intraday charts to daily, weekly, or monthly charts, making it a versatile tool for traders with different trading styles.
Example Scenarios
Day Trading:
A day trader can use MTI on a 5-minute chart to identify intraday trends. By adjusting the lookback period and smoothing parameters, the trader can quickly spot potential entry and exit points based on short-term momentum changes.
Swing Trading:
A swing trader might apply MTI to a 4-hour chart to identify medium-term trends. The dynamic thresholds can help in setting appropriate stop-loss levels, while the trend direction highlighting aids in making informed decisions about holding or exiting positions.
Position Trading:
For a position trader using a daily chart, MTI can help identify the overarching trend. The trader can use the fill areas and bar coloring to assess the strength of the trend and make decisions about entering or exiting long-term positions.
Market Analysis:
An analyst could use MTI to study historical price movements and identify patterns. By examining how the indicator reacted to past market conditions, the analyst can gain insights into potential future price movements.
In summary, the Modern Trend Identifier (MTI) is a versatile and powerful tool that enhances trend analysis with advanced smoothing techniques, dynamic adjustments, and comprehensive visual cues. It is designed to meet the needs of traders and analysts across various trading styles and timeframes, providing clear and actionable insights into market trends and momentum.
Updated with the following:
Additions and Enhancements in MTI
Grouped Inputs with Descriptive Tooltips:
Inputs are organized into groups for better clarity.
Each input parameter includes a descriptive tooltip.
Dynamic Threshold Calculation:
Added dynamic threshold calculation using percentile ranks to adapt to changing market conditions.
Normalization and Compression:
Added normalization factor to ensure plots are within -100 to 100 range.
Introduced smoothstep function for smooth transition and selectively applied linear and smoothstep compression to values outside -80 to 100 range.
Enhanced Visualization:
Highlighted trend direction with RGB colors.
Enhanced fill areas between the ALMA percentage change line and its RMS bands.
Colored price bars based on the identified trend direction.
RMS Lines Adjustment:
Dynamically adjusted RMS calculation without strict capping.
Ensured RMS lines stay below fill areas to maintain clarity.
Descriptive and Organized Code:
Enhanced code clarity with detailed comments.
Organized code into logical sections for better readability and maintenance.
Key Differences and Improvements.
Input Customization:
Trendilo: Inputs are simple and ungrouped.
MTI: Inputs are grouped and include tooltips for better user guidance.
Trend Calculation:
Trendilo: Uses ALMA and calculates percentage change.
MTI: Enhanced with normalization, compression, and dynamic threshold calculation.
Normalization and Compression:
Trendilo: No normalization or compression applied.
MTI: Normalizes values to -100 to 100 range and applies smoothstep compression to handle extreme values.
Dynamic RMS Adjustment:
Trendilo: Simple RMS calculation.
MTI: Dynamically adjusted RMS calculation to ensure clarity in visualization.
Visual Enhancements:
Trendilo: Basic trend highlighting and filling.
MTI: Enhanced visual cues with RGB colors, dynamic threshold bands, and improved fill areas.
Code Clarity:
Trendilo: Functional but lacks detailed comments and organization.
MTI: Well-organized, extensively commented code for better readability and maintainability.
[GYTS-Pro] Flux Composer🧬 Flux Composer (Professional Edition)
🌸 Confluence indicator in GoemonYae Trading System (GYTS) 🌸
The Flux Composer is a powerful tool in the GYTS suite that is designed to aggregate signals from multiple Signal Providers, apply advanced decaying functions, and offer customisable and advanced confluence mechanisms. This allows making informed decisions by considering the strength and agreement ("when all stars align") of various input signals.
🌸 --------- TABLE OF CONTENTS --------- 🌸
1️⃣ Main Highlights
2️⃣ Flux Composer’s Features
Multi Signal Provider support
Advanced decaying functions
Customisable Flux confluence mechanisms
Actionable trading experience
Filtering options
User-friendly experience
Upgrades compared to Community Edition
3️⃣ User Guide
Selecting Signal Providers
Connecting Signal Providers to the Flux Composer
Understanding the Flux
Tuning the decaying functions
Choosing Flux confluence mechanism
Choosing sensitivity
Utilising the filtering options
Interpreting the Flux for trading signals
4️⃣ Limitations
🌸 ------ 1️⃣ --- MAIN HIGHLIGHTS --- 1️⃣ ------ 🌸
- Signal aggregation : Combines signals from multiple different 📡 Signal Providers, each of which can be tuned and adjusted independently.
- Decaying function : Utilises advanced decaying functions to model the diminishing effect of signals over time, ensuring that recent signals have more weight. In addition to the decaying effect, the "quality" of the original signals (e.g. a "strong" GDM from WaveTrend 4D ) are accounted for as well.
- Flux confluence mechanism : The aggregation of all decaying functions form the "Flux", which is the core signal measurement of the Flux Composer. Multiple mechanisms are available for creating the Flux and effectively using it for actionable trading signals.
- Visualisation : Provides detailed visualisation options to help users understand and tune the contributions of individual Signal Providers and their decaying functions.
- Backtesting : The 🧬 Flux Composer is a core component of the TradingView suite of the 🌸 GoemonYae Trading System (GYTS) 🌸. It connects multiple 📡 Signal Providers, such as the WaveTrend 4D, and processes their signals to produce a unified "Flux". This Flux can then be used by the GYTS "🎼 Order Orchestrator" for backtesting and trade automation.
🌸 ------ 2️⃣ --- FLUX COMPOSER'S FEATURES --- 2️⃣ ------ 🌸
Let's delve into more details...
💮 1. Multi Signal Provider support
Using the name of the GYTS "🎼 Order Orchestrator" as an analogy: Imagine a symphony where each instrument plays its own unique part, contributing to the overall harmony. The Flux Composer operates similarly, integrating multiple Signal Providers to create a comprehensive and robust trading signal -- the "Flux". Currently, it supports up to four streams from the WaveTrend 4D's ’s Gradient Divergence Measure (GDM) and another four streams from the Quantile Median Cross (QMC). These can be either four "Professional Edition" Signal Providers or eight "Community Editions".
Note that the GDM includes 2 different continuous signals and the QMC 3 different continuous signals (from different frequencies). This means that the Community Edition can handle 2*2 + 2*3 = 10 different continuous signals and the Professional Edition as much as 20.
As GYTS evolves, more Signal Providers will be added; at the moment of releasing the Flux Composer, only WaveTrend 4D is publicly available.
💮 2. Advanced decaying functions
A trading signal can be relevant today, less relevant tomorrow, and irrelevant in a week's time. In other words, its relevance diminishes, or decays , over time. The Flux Composer utilises decaying functions that ensure that recent signals carry more weight, while older signals fade away. This is crucial for accurate signal processing. The intensity and decay settings allow for precise control, allowing emphasising certain signals based on their strength and relevance over time. On top of that, unlike binary signals ("buy now"), the Flux Composer utilises the actual values from the Signal Providers, differentiating between the exact quality of signals, and thus offering a detailed representation of the trading landscape. We will illustrate this in a further section.
💮 3. Customisable Flux confluence mechanisms
Another core component of the Flux Composer is the ability of intelligently combining the decaying functions. It offers four sophisticated confluence mechanisms: Amplitude Compression, Accentuated Amplitude Compression, Trigonometric, and GYTSynthesis. Each mechanism has its unique way of processing the Flux, tailored to different trading needs. For instance, the Amplitude Compression method scales the Flux based on recent values, much like the Stochastic Oscillator, while the Trigonometric method uses smooth functions to reduce outliers’ impact. The GYTSynthesis is a proprietary method, striking a balance between signal strength and discriminative power.
We'll discuss this in more detail in the User Guide section.
💮 4. Actionable trading experience
While the mathematical abilities might seem overwhelming, the goal of the Flux Composer is to transform complex signal data into actionable trading signals. When the Flux reaches certain thresholds, it generates clear bullish or bearish signals, making it easy for traders to interpret. The inclusion of upper and lower thresholds (UT and LT) helps in identifying strong signals visually and should be a familiar behaviour similar to how many other indicators operate. Furthermore, the Flux Composer can plot trading signals directly on the oscillator, showing triangle shapes for buy or sell signals. This visual aid is complemented by the possibility to setup TradingView alerts.
💮 5. Filtering options
The Professional Edition also offers filtering options to possibly further improve the quality of Flux signals. Signal streams can be divided into “Signal Flux” and “Filter Flux.” The Filter Flux acts as a gatekeeper, ensuring that only signals meeting the Filter's criteria (which consist of similar UT/LT thresholds) are considered for trading. This dual-layer approach enhances the reliability of trading signals, reducing the chances of false positives.
💮 6. User-friendly experience
GYTS is all about sophisticated, robust methods but also "elegance". One of the interpretations of the latter, is that the users' experience is very important. Despite the Flux Composer's mathematical underpinnings, it offers intuitive settings that with omprehensive tooltips to help with a smooth setup process. For those looking to fine-tune their signals, the Flux Composer allows the visualisation of individual decaying functions. This feature helps users understand the impact of each setting and make informed adjustments. Additionally, the background of the chart can be coloured to indicate the trading direction suggested by the Filter Flux, providing an at-a-glance overview of market conditions.
💮 7. Upgrades compared to Community Edition
Number of signal streams -- At the moment of writing, the Professional Edition works with 4x GDM and 4x QMC signal streams from WaveTrend 4D Signal Provider , while Community Edition (CE) Flux Composer (FC) only works with 2x GDM and 2x QMC signal streams.
Flux confluence mechanism -- CE includes the Amplitude Compression and Trigonometric confluence mechanisms, while the Pro Edition also includes the Accentuated Amplitude Compression and the GYTSynthesis mechanisms.
Signal streams as filters -- The Pro Edition can use Signal Providers as filters.
🌸 ------ 3️⃣ --- USER GUIDE --- 3️⃣ ------ 🌸
💮 1. Selecting Signal Providers
The Flux Composer’s foundation lies in its Signal Providers. When starting with the Flux Composer, using a single Signal Provider can already provide significant value due to the nature of decaying functions. For instance, the WaveTrend 4D signal provider includes up to 5 signal types (GDM and QMC in different frequencies) in a single direction (long/short). Moreover, the various confluence mechanisms that enhance the resulting Flux result in improved discrimination between weak and strong signals. This approach is akin to ensemble learning in machine learning, where multiple models are combined to improve predictive performance.
While using a single Signal Provider is beneficial, the true power of the Flux Composer is realised with multiple Signal Providers. Here are two general approaches to selecting Signal Providers:
Diverse Behaviours
Use Signal Providers with different behaviours, such as WaveTrend 4D on various assets/timeframes or entirely different Signal Providers. This approach leverages diversification to achieve robustness, rooted in the principle that varied sources enhance the overall signal quality. To explain this with an analogy, this strategy aligns with the theory of diversification in portfolio management, where combining uncorrelated assets reduces overall risk. Similarly, combining uncorrelated signals can mitigate the risk of signal failure. A practical example can be integrating a mean-reversion signal with a trend-following signal -- these can balance each other out, providing more stable outputs over different market conditions.
Enhancing a Single Provider
If you consider a particular Signal Provider highly effective, you could improve its robustness by using multiple instances with slight variations. These variations could include different sources (e.g., close, HL2, HLC3), data providers (same asset across different brokers/exchanges), or parameter adjustments. This method mirrors Monte Carlo simulations, often used in risk management and derivative pricing, which involve running many simulations with varied inputs to estimate the probability of different outcomes. By applying similar principles, the strategy becomes less susceptible to overfitting, ensuring the signals are not overly dependent on specific data conditions.
💮 2. Connecting Signal Providers to the Flux Composer
Moving on to practicalities: how do you connect Signal Providers with the Flux Composer? You may have noticed that when you open the drawdown of a data source in a TradingView indicator (with "open", "high", "low", etc.), you also see names from other indicators on your chart. We call these "streams", and the Signal Providers are designed such that they output this stream in a way that the Flux Composer can interpret it. Thus, to connect a Signal Provider with the Flux Composer, you should first have that Signal Provider on your chart. Obviously you should set it up an a way that it seems to provide good signals. After that, in the Data Stream dropdown in the Flux Composer, you can select the stream that is outputted by your Signal Provider. This will always be with a prefix of "🔗 STREAM" (after the Signal Provider's indicator name). See the chart below.
There is one important nuance: when you have multiple (similar) Signal Providers on your chart, it may be hard to select the correct data stream in the Flux Composer as the names of the streams keep repeating when you use identical indicators. So be sure to be attentive as you might end up using the same signals multiple times.
Also, the Signal Providers have an "Indicator name" parameter (and another parameter to repeat this name) that is handy to use when you have multiple Signal Providers on your screen. It is handy to give names that describe the unique settings of that Signal Provider so you can better differentiate what you are looking at on your screen.
💮 3. Understanding the Flux
Let's understand how the Signal Provider's signals are processed. In the chart below, you see we have one Signal Provider (WaveTrend 4D) connected to the Flux Composer and that it gives a bearish QMC signal. The Flux Composer converts this into a decaying function. You can show these functions per Signal Provider when the option "Show decaying function of Signal Provider" is enabled (as it is in the chart).
In our opinion, of crucial importance is the ability to process the quality of signals, rather than just any signal. In mathematical terms, we are interested in continuous signals as these provide a spectrum of values. These signals can reflect varying degrees of market sentiment or trend strength, offering richer information than binary signals, which offer only two states (e.g., buy/sell). Especially in the context of the Flux Composer, where you aggregate multiple signals, it makes a big difference whether you combine 10 weak signals or 10 strong signals. To illustrate this principle, look at the chart below where there are 4 signals of different strengths. As you can see, each of the signals affects the Flux with different intensities.
💮 4. Tuning the decaying functions
As previously mentioned, the decaying functions are a way to give more importance to recent signals while allowing older ones to fade away gradually. This mimics the natural way we assess information, giving more weight to recent events. The decaying functions in the Flux Composer are highly customisable while remaining easy to use. You can adjust the initial intensity , which sets the starting strength of a signal, and the decay rate, which determines how quickly this signal diminishes over time. Let's look at specific examples.
If we add 3 Flux Composers on the chart, connect the same Signal Provider, keep all settings the same with one exception, we get the chart below. Here we have changed the "intensity" parameter of the specific signal. As you can see, the decaying functions are different. The intensity determines the initial strength of the decayed function. Adjusting the intensity allows you to emphasise certain signal types based on their perceived reliability or importance.
Let's now keep the intensity the same ("normal"), but change the "decay" parameter. As you can see in the image below, the decay controls how quickly the signal’s strength diminishes over time. By adjusting the decay, you can model the longevity of the signal’s impact. A faster decay means the signal loses its influence quickly, while a slower decay means it remains relevant for a longer period.
So how do multiple signals interact? You can see this as a simple "stacking of decaying functions" (although there is more to it, see next section). In the chart below we different strenghts of signals and different decay rates to illustrate how the Flux is constructed.
Hopefully this helps with developing some intuition how signals are converted to decaying functions, how you can control them, and how the Flux is constructed. When tuning these parameters, use the visualisation options to see how individual decaying functions contribute to the overall Flux. This helps in understanding and refining the parameters to achieve the desired trading signal behaviour.
💮 5. Choosing Flux confluence mechanism
While we mentioned that the Flux is a "stacking of individual decaying functions", in the back-end, that is not exactly that simple. Like previously mentioned, for GYTS, "elegance" is very important. One of the interpretations is "user friendliness" and the Flux confluence mechanism is one of the essential developments for this characteristic. The Flux confluence mechanism is critical in synthesising the aggregated signals into the Flux. The choice of mechanism affects how the signals are combined and the resulting trading signals. The Professional Edition offers four distinct mechanisms, each with its strengths.
The Amplitude Compression mechanism is intuitive, scaling the Flux based on recent values, intuitively not unlike the method of the well-known Stochastic Oscillator. The Accentuated Amplitude Compression method takes this a step further, giving more weight to strong Flux values. The Trigonometric mechanism smooths the Flux and reduces the impact of outliers, providing a balanced approach. Finally, the GYTSynthesis mechanism, a proprietary approach, balances signal strength and discriminative power, making it easier to tune and generalise.
It's difficult to convey the workings of the Flux confluence mechanism in a chart, but let's take the opportunity to show how the Flux would look like when connecting both one WaveTrend 4D Signal Provider signals to four Flux Composers with default settings, except the Flux confluence mechanism:
You may notice subtle differences between the four methods. They react differently to different values and their overall shape is slightly be different. The Amplitude Compression is more "pointy" and GYTSynthesis doesn't react to low values. There are many nuances, especially in combination with tuning the sensitivity and upper/lower threshold (UT/LT) parameters.
💮 6. Choosing sensitivity
Speaking of the sensitivity , this parameters fine-tunes how responsive the Flux is to the input signals. Higher sensitivity results in more pronounced responses, leading to more frequent trading signals. Lower sensitivity makes the Flux less responsive, resulting in fewer but potentially more reliable signals.
You might think that changing the upper/lower threshold (UT/LT) parameters would be equivalent, but that's not the case. The sensitivity In case of the Amplitude Compression mechanisms, changing the sensitivity would change the relative Flux shape over time, and with the Trigonometric and GYTSynthesis mechanisms, the Flux shape itself (independent of time) would change. In other words, these are all good parameters for tuning.
💮 7. Utilising the filtering options
When choosing the signal stream of a Signal Provider, you can also change the default "Signal" category of that Signal Provider to a "Filter". In the example below, two Signal Providers are connected; the second is set as a filter. You can see that a second row of a Flux is shown in the Flux Composer (this visualisation can be disabled), corresponding with the signals of the second Signal Provider.
Logically, only when the Filter Flux gives a signal in a certain direction, signals from the regular Signal Flux are registered. Generally speaking, for this use case it is handy to set the thresholds for the Filter Flux low and possibly to decrease the decay rate so that the filtering is active for a long enough time.
💮 8. Interpreting the Flux for trading signals
Lastly, the Signal Flux gives buy and sell signals when it crosses the upper/lower thresholds (UT/LT), when the filter allows it (if enabled). This can be visualised with the triangles as you may have seen in the charts in the previous sections. For people using TradingView's alerts -- these would work too out of the box. And finally, for backtesting and possibly trade automation, we will have the GYTS "🎼 Order Orchestrator" that connects with the Flux Composer.
🌸 ------ 4️⃣ --- LIMITATIONS --- 4️⃣ ------ 🌸
Only 🌸 GYTS 📡 Signal Providers are supported, as there is a specific method to pass continuous (non-binary) data in the data stream
At the moment of release, only the WaveTrend 4D Signal Provider is available. Other Signal Providers will be gradually released.
[GYTS-CE] Flux Composer🧬 Flux Composer (Community Edition)
🌸 Confluence indicator in GoemonYae Trading System (GYTS) 🌸
The Flux Composer is a powerful tool in the GYTS suite that is designed to aggregate signals from multiple Signal Providers, apply customisable decaying functions, and offer customisable and advanced confluence mechanisms. This allows making informed decisions by considering the strength and agreement ("when all stars align") of various input signals.
🌸 --------- TABLE OF CONTENTS --------- 🌸
1️⃣ Main Highlights
2️⃣ Flux Composer’s Features
Multi Signal Provider support
Advanced decaying functions
Customisable Flux confluence mechanisms
Actionable trading experience
User-friendly experience
3️⃣ User Guide
Selecting Signal Providers
Connecting Signal Providers to the Flux Composer
Understanding the Flux
Tuning the decaying functions
Choosing Flux confluence mechanism
Choosing sensitivity
Interpreting the Flux for trading signals
4️⃣ Limitations
🌸 ------ 1️⃣ --- MAIN HIGHLIGHTS --- 1️⃣ ------ 🌸
- Signal aggregation : Combines signals from multiple different 📡 Signal Providers, each of which can be tuned and adjusted independently.
- Decaying function : Utilises advanced decaying functions to model the diminishing effect of signals over time, ensuring that recent signals have more weight. In addition to the decaying effect, the "quality" of the original signals (e.g. a "strong" GDM from WaveTrend 4D with GDM ) are accounted for as well.
- Flux confluence mechanism : The aggregation of all decaying functions form the "Flux", which is the core signal measurement of the Flux Composer. Multiple mechanisms are available for creating the Flux and effectively using it for actionable trading signals.
- Visualisation : Provides detailed visualisation options to help users understand and tune the contributions of individual Signal Providers and their decaying functions.
- Backtesting : The 🧬 Flux Composer is a core component of the TradingView suite of the 🌸 GoemonYae Trading System (GYTS) 🌸. It connects multiple 📡 Signal Providers, such as the WaveTrend 4D, and processes their signals to produce a unified "Flux". This Flux can then be used by the GYTS "🎼 Order Orchestrator" for backtesting and trade automation.
🌸 ------ 2️⃣ --- FLUX COMPOSER'S FEATURES --- 2️⃣ ------ 🌸
Let's delve into more details...
💮 1. Multi Signal Provider support
Using the name of the GYTS "🎼 Order Orchestrator" as an analogy: Imagine a symphony where each instrument plays its own unique part, contributing to the overall harmony. The Flux Composer operates similarly, integrating multiple Signal Providers to create a comprehensive and robust trading signal -- the "Flux". Currently, it supports up to two streams from the WaveTrend 4D’s Gradient Divergence Measure (GDM) and another two streams from the WaveTrend 4D's Quantile Median Cross (QMC) .
Note that the GDM includes 2 different continuous signals and the QMC 3 different continuous signals (from different frequencies). This means that the Community Edition can handle 2*2 + 2*3 = 10 different continuous signals.
As GYTS evolves, more Signal Providers will be added; at the moment of releasing the Flux Composer, only WaveTrend 4D with GDM and with QMC are publicly available.
💮 2. Advanced decaying functions
A trading signal can be relevant today, less relevant tomorrow, and irrelevant in a week's time. In other words, its relevance diminishes, or decays , over time. The Flux Composer utilises decaying functions that ensure that recent signals carry more weight, while older signals fade away. This is crucial for accurate signal processing. The intensity and decay settings allow for precise control, allowing emphasising certain signals based on their strength and relevance over time. On top of that, unlike binary signals ("buy now"), the Flux Composer utilises the actual values from the Signal Providers, differentiating between the exact quality of signals, and thus offering a detailed representation of the trading landscape. We will illustrate this in a further section.
💮 3. Customisable Flux confluence mechanisms
Another core component of the Flux Composer is the ability of intelligently combining the decaying functions. It offers two sophisticated confluence mechanisms: Amplitude Compression and Trigonometric. Each mechanism has its unique way of processing the Flux, tailored to different trading needs. The Amplitude Compression method scales the Flux based on recent values, much like the Stochastic Oscillator, while the Trigonometric method uses smooth functions to reduce outliers’ impact We'll discuss this in more detail in the User Guide section.
💮 4. Actionable trading experience
While the mathematical abilities might seem overwhelming, the goal of the Flux Composer is to transform complex signal data into actionable trading signals. When the Flux reaches certain thresholds, it generates clear bullish or bearish signals, making it easy for traders to interpret. The inclusion of upper and lower thresholds (UT and LT) helps in identifying strong signals visually and should be a familiar behaviour similar to how many other indicators operate. Furthermore, the Flux Composer can plot trading signals directly on the oscillator, showing triangle shapes for buy or sell signals. This visual aid is complemented by the possibility to setup TradingView alerts.
💮 5. User-friendly experience
GYTS is all about sophisticated, robust methods but also "elegance". One of the interpretations of the latter, is that the users' experience is very important. Despite the Flux Composer's mathematical underpinnings, it offers intuitive settings that with omprehensive tooltips to help with a smooth setup process. For those looking to fine-tune their signals, the Flux Composer allows the visualisation of individual decaying functions. This feature helps users understand the impact of each setting and make informed adjustments.
🌸 ------ 3️⃣ --- USER GUIDE --- 3️⃣ ------ 🌸
💮 1. Selecting Signal Providers
The Flux Composer’s foundation lies in its Signal Providers. When starting with the Flux Composer, using a single Signal Provider can already provide significant value due to the nature of decaying functions. For instance, the WaveTrend 4D signal provider includes up to two GDM and three QMC signals in a single direction (long/short). Moreover, the various confluence mechanisms that enhance the resulting Flux result in improved discrimination between weak and strong signals. This approach is akin to ensemble learning in machine learning, where multiple models are combined to improve predictive performance.
While using a single Signal Provider is beneficial, the true power of the Flux Composer is realised with multiple Signal Providers. Here are two general approaches to selecting Signal Providers:
Diverse Behaviours
Use Signal Providers with different behaviours, such as WaveTrend 4D on various assets/timeframes or entirely different Signal Providers. This approach leverages diversification to achieve robustness, rooted in the principle that varied sources enhance the overall signal quality. To explain this with an analogy, this strategy aligns with the theory of diversification in portfolio management, where combining uncorrelated assets reduces overall risk. Similarly, combining uncorrelated signals can mitigate the risk of signal failure. A practical example can be integrating a mean-reversion signal with a trend-following signal -- these can balance each other out, providing more stable outputs over different market conditions.
Enhancing a Single Provider
If you consider a particular Signal Provider highly effective, you could improve its robustness by using multiple instances with slight variations. These variations could include different sources (e.g., close, HL2, HLC3), data providers (same asset across different brokers/exchanges), or parameter adjustments. This method mirrors Monte Carlo simulations, often used in risk management and derivative pricing, which involve running many simulations with varied inputs to estimate the probability of different outcomes. By applying similar principles, the strategy becomes less susceptible to overfitting, ensuring the signals are not overly dependent on specific data conditions.
💮 2. Connecting Signal Providers to the Flux Composer
Moving on to practicalities: how do you connect Signal Providers with the Flux Composer? You may have noticed that when you open the drawdown of a data source in a TradingView indicator (with "open", "high", "low", etc.), you also see names from other indicators on your chart. We call these "streams", and the Signal Providers are designed such that they output this stream in a way that the Flux Composer can interpret it. Thus, to connect a Signal Provider with the Flux Composer, you should first have that Signal Provider on your chart. Obviously you should set it up an a way that it seems to provide good signals. After that, in the Data Stream dropdown in the Flux Composer, you can select the stream that is outputted by your Signal Provider. This will always be with a prefix of "🔗 STREAM" (after the Signal Provider's indicator name). See the chart below.
There is one important nuance: when you have multiple (similar) Signal Providers on your chart, it may be hard to select the correct data stream in the Flux Composer as the names of the streams keep repeating when you use identical indicators. So be sure to be attentive as you might end up using the same signals multiple times.
Also, the Signal Providers have an "Indicator name" parameter (and another parameter to repeat this name) that is handy to use when you have multiple Signal Providers on your screen. It is handy to give names that describe the unique settings of that Signal Provider so you can better differentiate what you are looking at on your screen.
💮 3. Understanding the Flux
Let's understand how the Signal Provider's signals are processed. In the chart below, you see we have one Signal Provider (WaveTrend 4D) connected to the Flux Composer and that it gives a bearish QMC signal. The Flux Composer converts this into a decaying function. You can show these functions per Signal Provider when the option "Show decaying function of Signal Provider" is enabled (as it is in the chart).
In our opinion, of crucial importance is the ability to process the quality of signals, rather than just any signal. In mathematical terms, we are interested in continuous signals as these provide a spectrum of values. These signals can reflect varying degrees of market sentiment or trend strength, offering richer information than binary signals, which offer only two states (e.g., buy/sell). Especially in the context of the Flux Composer, where you aggregate multiple signals, it makes a big difference whether you combine 10 weak signals or 10 strong signals. To illustrate this principle, look at the chart below where there are 4 signals of different strengths. As you can see, each of the signals affects the Flux with different intensities.
💮 4. Tuning the decaying functions
As previously mentioned, the decaying functions are a way to give more importance to recent signals while allowing older ones to fade away gradually. This mimics the natural way we assess information, giving more weight to recent events. The decaying functions in the Flux Composer are highly customisable while remaining easy to use. You can adjust the initial intensity , which sets the starting strength of a signal, and the decay rate, which determines how quickly this signal diminishes over time. Let's look at specific examples.
If we add 3 Flux Composers on the chart, connect the same Signal Provider, keep all settings the same with one exception, we get the chart below. Here we have changed the "intensity" parameter of the specific signal. As you can see, the decaying functions are different. The intensity determines the initial strength of the decayed function. Adjusting the intensity allows you to emphasise certain signal types based on their perceived reliability or importance.
Let's now keep the intensity the same ("normal"), but change the "decay" parameter. As you can see in the image below, the decay controls how quickly the signal’s strength diminishes over time. By adjusting the decay, you can model the longevity of the signal’s impact. A faster decay means the signal loses its influence quickly, while a slower decay means it remains relevant for a longer period.
So how do multiple signals interact? You can see this as a simple "stacking of decaying functions" (although there is more to it, see next section). In the chart below we use different "intensity" and "decay" parameters to discuss how the Flux is created.
Hopefully this helps with developing some intuition how signals are converted to decaying functions, how you can control them, and how the Flux is constructed. When tuning these parameters, use the visualisation options to see how individual decaying functions contribute to the overall Flux. This helps in understanding and refining the parameters to achieve the desired trading signal behaviour.
💮 5. Choosing Flux confluence mechanism
While we mentioned that the Flux is a "stacking of individual decaying functions", in the back-end, that is not exactly that simple. Like previously mentioned, for GYTS, "elegance" is very important. One of the interpretations is "user friendliness" and the Flux confluence mechanism is one of the essential developments for this characteristic. The Flux confluence mechanism is critical in synthesising the aggregated signals into the Flux. The choice of mechanism affects how the signals are combined and the resulting trading signals. The Community Edition offers two distinct mechanisms, each with its strengths.
The Amplitude Compression mechanism is intuitive, scaling the Flux based on recent values, intuitively not unlike the method of the well-known Stochastic Oscillator. On the other hand, the Trigonometric mechanism smooths the Flux and reduces the impact of outliers, providing a balanced approach. It's difficult to convey the workings of the Flux confluence mechanism in a chart, but let's take the opportunity to show how the Flux would look like when connecting both GDM and QMC signals to two Flux Composers with default settings, except the Flux confluence mechanism:
You can notice that the upper Flux Converter (FC) triggered two signals while the other FC triggered only one. There are more nuances, especially in combination with tuning the sensitivity and upper/lower threshold (UT/LT) parameters.
💮 6. Choosing sensitivity
Speaking of the sensitivity , this parameters fine-tunes how responsive the Flux is to the input signals. Higher sensitivity results in more pronounced responses, leading to more frequent trading signals. Lower sensitivity makes the Flux less responsive, resulting in fewer but potentially more reliable signals.
You might think that changing the upper/lower threshold (UT/LT) parameters would be equivalent, but that's not the case. The sensitivity In case of the Amplitude Compression mechanism, changing the sensitivity would change the relative Flux shape over time, and with the Trigonometric mechanism, the Flux shape itself (independent of time) would change. In other words, these are all good parameters for tuning.
💮 8. Interpreting the Flux for trading signals
Lastly, the Signal Flux gives buy and sell signals when it crosses the upper/lower thresholds (UT/LT) This can be visualised with the triangles as you may have seen in the charts in the previous sections. For people using TradingView's alerts -- these would work out of the box. And finally, for backtesting and possibly trade automation, we will have the GYTS "🎼 Order Orchestrator" that connects with the Flux Composer.
🌸 ------ 4️⃣ --- LIMITATIONS --- 4️⃣ ------ 🌸
Only 🌸 GYTS 📡 Signal Providers are supported, as there is a specific method to pass continuous (non-binary) data in the data stream
At the moment of release, only WaveTrend 4D with GDM and with QMC are available. Other Signal Providers will be gradually released.
Trend Momentum Strength Indicator, Built for Pairs TradingOverview:
This script combines multiple indicators to provide a comprehensive analysis of both trend strength and trend momentum. It is tailored specifically for pairs trading strategies but can also be used for other trading strategies.
Benefit of Comprehensive Analysis:
Having an indicator that evaluates both trend strength and trend momentum is crucial for traders looking to make informed decisions. It allows traders to not only identify the direction and intensity of a trend but also gauge the momentum behind it. This dual capability helps in confirming potential trade opportunities, whether for entering trades with strong trends or considering reversals during overbought or oversold conditions. By integrating both aspects into one tool, traders can gain a holistic view of market dynamics, enhancing their ability to time entries and manage risk effectively.
Features:
* Trend Strength:
Enhanced ADX Formula: The script includes modifications to the standard ADX formula along with DI+ and DI- to provide more responsive trend strength readings.
Directional Indicators: DI+ (green line) indicates positive directional movement, while DI- (red line) indicates negative directional movement.
Trend Momentum:
Modified Stochastic Indicators: The script uses %K and %D indicators, modified and combined with ADX to give a clear indication of trend momentum.
Momentum Strength: This helps determine the strength and direction of the momentum.
Trading Signals:
Combining Indicators: The script combines ADX, DI+, DI-, %K, and %D to generate comprehensive trading signals.
Optimal Entry Points: Designed to identify optimal entry points for trades, particularly in pairs trading.
Colored Area at Bottom:
This area provides two easy-to-read functions:
Color:
Green: Upward momentum (ratio above 1)
Red: Downward momentum (ratio below 1)
Height:
Higher in green: Stronger upward momentum
Lower in red: Stronger downward momentum
Legend:
Green Line: DI+ (Positive)
Red Line: DI- (Negative)
Black Line: ADX
How to Read This Indicator:
1) Trend Direction:
DI+ above DI-: Indicates an upward trend.
DI- above DI+: Indicates a downward trend.
2) Trend Strength:
ADX below 20: Indicates a neutral trend.
ADX between 20 and 25: Indicates a weak trend.
ADX above 25: Indicates a strong trend.
Trading Signals in Pairs Trading:
Neutral Trend: Ideal for pairs trading when no strong trend is detected.
Overbought/Oversold: Uses %K and %D to identify overbought/oversold conditions that support trade decisions.
Entry Signals: Green signals for long positions, red signals for short positions, based on combined criteria of neutral trend strength and supportive momentum.
Application in Pairs Trading:
Neutral trend: In pairs trading strategies, where neutral movement is often sought, this indicator provides signals that are especially relevant during periods of neutral trend strength and supportive momentum, aiding traders in identifying optimal entry
Risk Management: Combining signals from ADX, DI+, DI-, %K, and %D helps traders make more informed decisions regarding entry points, enhancing risk management.
Example Chart (The indicator is on the upper right corner):
Clean Presentation: The chart only includes the necessary elements to demonstrate the indicator’s functionality.
Demonstrates: Overbought/oversold conditions, upward/downward/no momentum, and trading signals with/without specific scenarios.
Fusion MFI RSIHello fellas,
This superb indicator summons two monsters called Relative Strength Index (RSI) and Money Flow Index (MFI) and plays the Yu-Gi-Oh! card "Polymerization" to combine them.
Overview
The Fusion MFI RSI Indicator is an advanced analytical tool designed to provide a nuanced understanding of market dynamics by combining the Relative Strength Index (RSI) and the Money Flow Index (MFI). Enhanced with sophisticated smoothing techniques and the Inverse Fisher Transform (IFT), this indicator excels in identifying key market conditions such as overbought and oversold states, trends, and potential reversal points.
Key Features (Brief Overview)
Fusion of RSI and MFI: Integrates momentum and volume for a comprehensive market analysis.
Advanced Smoothing Techniques: Employs Hann Window, Jurik Moving Average (JMA), T3 Smoothing, and Super Smoother to refine signals.
Inverse Fisher Transform (IFT) Enhances the clarity and distinctiveness of indicator outputs.
Detailed Feature Analysis
Fusion of RSI and MFI
RSI (Relative Strength Index): Developed by J. Welles Wilder Jr., the RSI measures the speed and magnitude of directional price movements. Wilder recommended using a 14-day period and identified overbought conditions above 70 and oversold conditions below 30.
MFI (Money Flow Index): Created by Gene Quong and Avrum Soudack, the MFI combines price and volume to measure trading pressure. It is typically calculated using a 14-day period, with over 80 considered overbought and under 20 as oversold.
Application in Fusion: By combining RSI and MFI, the indicator leverages RSI's sensitivity to price changes with MFI's volume-weighted confirmation, providing a robust analysis tool. This combination is particularly effective in confirming the strength behind price movements, making the signals more reliable.
Advanced Smoothing Techniques
Hann Window: Traditionally used to reduce the abrupt data discontinuities at the edges of a sample, it is applied here to smooth the price data.
Jurik Moving Average (JMA): Known for preserving the timing and smoothness of the data, JMA reduces market noise effectively without significant lag.
T3 Smoothing: Developed to respond quickly to market changes, T3 provides a smoother response to price fluctuations.
Super Smoother: Filters out high-frequency noise while retaining important trends.
Application in Fusion: These techniques are chosen to refine the output of the combined RSI and MFI values, ensuring the indicator remains responsive yet stable, providing clearer and more actionable signals.
Inverse Fisher Transform (IFT):
Developed by John Ehlers, the IFT transforms oscillator outputs to enhance the clarity of extreme values. This is particularly useful in this fusion indicator to make critical turning points more distinct and actionable.
Mathematical Calculations for the Fusion MFI RSI Indicator
RSI (Relative Strength Index)
The RSI is calculated using the following steps:
Average Gain and Average Loss: First, determine the average gain and average loss over the specified period (typically 14 days). This is done by summing all the gains and losses over the period and then dividing each by the period.
Average Gain = (Sum of Gains over the past 14 periods) / 14
Average Loss = (Sum of Losses over the past 14 periods) / 14
Relative Strength (RS): This is the ratio of average gain to average loss.
RS = Average Gain / Average Loss
RSI: Finally, the RSI is calculated using the RS value:
RSI = 100 - (100 / (1 + RS))
MFI (Money Flow Index)
The MFI is calculated using several steps that incorporate both price and volume:
Typical Price: Calculate the typical price for each period.
Typical Price = (High + Low + Close) / 3
Raw Money Flow: Multiply the typical price by the volume for the period.
Raw Money Flow = Typical Price * Volume
Positive and Negative Money Flow: Compare the typical price of the current period to the previous period to determine if the money flow is positive or negative.
If today's Typical Price > Yesterday's Typical Price, then Positive Money Flow = Raw Money Flow; Negative Money Flow = 0
If today's Typical Price < Yesterday's Typical Price, then Negative Money Flow = Raw Money Flow; Positive Money Flow = 0
Money Flow Ratio: Calculate the ratio of the sum of Positive Money Flows to the sum of Negative Money Flows over the past 14 periods.
Money Flow Ratio = (Sum of Positive Money Flows over 14 periods) / (Sum of Negative Money Flows over 14 periods)
MFI: Finally, calculate the MFI using the Money Flow Ratio.
MFI = 100 - (100 / (1 + Money Flow Ratio))
Fusion of RSI and MFI
The final Fusion MFI RSI value could be calculated by averaging the IFT-transformed values of RSI and MFI, providing a single oscillator value that reflects both momentum and volume-weighted price action:
Fusion MFI RSI = (MFI weight * MFI) + (RSI weight * RSI)
Suggested Settings and Trading Rules
Original Usage
RSI: Wilder suggested buying when the RSI moves above 30 from below (enter long) and selling when the RSI moves below 70 from above (enter short). He recommended exiting long positions when the RSI reaches 70 or higher and exiting short positions when the RSI falls below 30.
MFI: Quong and Soudack recommended buying when the MFI is below 20 and starts rising (enter long), and selling when it is above 80 and starts declining (enter short). They suggested exiting long positions when the MFI reaches 80 or higher and exiting short positions when the MFI falls below 20.
Fusion Application
Settings: Use a 14-day period for this indicator's calculations to maintain consistency with the original settings suggested by the inventors.
Trading Rules:
Enter Long Signal: Consider entering a long position when both RSI and MFI are below their respective oversold levels and begin to rise. This indicates strong buying pressure supported by both price momentum and volume.
Exit Long Signal: Exit the long position when either RSI or MFI reaches its respective overbought threshold, suggesting a potential reversal or decrease in buying pressure.
Enter Short Signal: Consider entering a short position when both indicators are above their respective overbought levels and begin to decline, suggesting that selling pressure is mounting.
Exit Short Signal: Exit the short position when either RSI or MFI falls below its respective oversold threshold, indicating diminishing selling pressure and a potential upward reversal.
How to Use the Indicator
Select Source and Timeframe: Choose the data source and the timeframe for analysis.
Configure Fusion Settings: Adjust the weights for RSI and MFI.
Choose Smoothing Technique: Select and configure the desired smoothing method to suit the market conditions and personal preference.
Enable Fisherization: Optionally apply the Inverse Fisher Transform to enhance signal clarity.
Customize Visualization: Set up gradient coloring, background plots, and bands according to your preferences.
Interpret the Indicator: Use the Fusion value and visual cues to identify market conditions and potential trading opportunities.
Conclusion
The Fusion MFI RSI Indicator integrates classical and modern technical analysis concepts to provide a comprehensive tool for market analysis. By combining RSI and MFI with advanced smoothing techniques and the Inverse Fisher Transform, this indicator offers enhanced insights, aiding traders in making more informed and timely trading decisions. Customize the settings to align with your trading strategy and leverage this powerful tool to navigate financial markets effectively.
Best regards,
simwai
---
Credits to:
@loxx – T3
@everget – JMA
@cheatcountry – Hann Window
Persistent Homology Based Trend Strength OscillatorPersistent Homology Based Trend Strength Oscillator
The Persistent Homology Based Trend Strength Oscillator is a unique and powerful tool designed to measure the persistence of market trends over a specified rolling window. By applying the principles of persistent homology, this indicator provides traders with valuable insights into the strength and stability of uptrends and downtrends, helping to inform better trading decisions.
What Makes This Indicator Original?
This indicator's originality lies in its application of persistent homology , a method from topological data analysis, to financial markets. Persistent homology examines the shape and features of data across multiple scales, identifying patterns that persist as the scale changes. By adapting this concept, the oscillator tracks the persistence of uptrends and downtrends in price data, offering a novel approach to trend analysis.
Concepts Underlying the Calculations:
Persistent Homology: This method identifies features such as clusters, holes, and voids that persist as the scale changes. In the context of this indicator, it tracks the duration and stability of price trends.
Rolling Window Analysis: The oscillator uses a specified window size to calculate the average length of uptrends and downtrends, providing a dynamic view of trend persistence over time.
Threshold-Based Trend Identification: It differentiates between uptrends and downtrends based on specified thresholds for price changes, ensuring precision in trend detection.
How It Works:
The oscillator monitors consecutive changes in closing prices to identify uptrends and downtrends.
An uptrend is detected when the closing price increase exceeds a specified positive threshold.
A downtrend is detected when the closing price decrease exceeds a specified negative threshold.
The lengths of these trends are recorded and averaged over the chosen window size.
The Trend Persistence Index is calculated as the difference between the average uptrend length and the average downtrend length, providing a measure of trend persistence.
How Traders Can Use It:
Identify Trend Strength: The Trend Persistence Index offers a clear measure of the strength and stability of uptrends and downtrends. A higher value indicates stronger and more persistent uptrends, while a lower value suggests stronger and more persistent downtrends.
Spot Trend Reversals: Significant shifts in the Trend Persistence Index can signal potential trend reversals. For instance, a transition from positive to negative values might indicate a shift from an uptrend to a downtrend.
Confirm Trends: Use the Trend Persistence Index alongside other technical indicators to confirm the strength and duration of trends, enhancing the accuracy of your trading signals.
Manage Risk: Understanding trend persistence can help traders manage risk by identifying periods of high trend stability versus periods of potential volatility. This can be crucial for timing entries and exits.
Example Usage:
Default Settings: Start with the default settings to get a feel for the oscillator’s behavior. Observe how the Trend Persistence Index reacts to different market conditions.
Adjust Thresholds: Fine-tune the positive and negative thresholds based on the asset's volatility to improve trend detection accuracy.
Combine with Other Indicators: Use the Persistent Homology Based Trend Strength Oscillator in conjunction with other technical indicators such as moving averages, RSI, or MACD for a comprehensive analysis.
Backtesting: Conduct backtesting to see how the oscillator would have performed in past market conditions, helping you to refine your trading strategy.
Statistical RSI Pivot Reversal Indicator [UAlgo]🔶 Idea
The "Statistical RSI Pivot Reversal Indicator " is designed to enhance traditional RSI analysis by incorporating statistical methods to identify potential reversal points more accurately. The core concept is to detect frequently occurring pivot points in the RSI data, which can indicate strong support or resistance levels. By analyzing the most frequent RSI values at these pivots, the script provides traders with clearer signals for potential market reversals, helping to improve the timing of entry and exit points in their trading strategies.
🔶 Key Features
Enhanced RSI Analysis:
This script calculates the Relative Strength Index (RSI) based on user-defined parameters and identifies pivot points in the RSI data. By analyzing these pivots, it detects the most frequently occurring RSI values at support and resistance levels.
Signal Filtering Options:
Filter buy and sell signals based on whether the RSI is in overbought (above 70) or oversold (below 30) conditions, enhancing the reliability of signals.
Visual and Alert Features:
Visual Signals: The script plots the RSI, the most frequent high and low RSI values, and buy/sell signals on the chart.
Alerts: Set up custom alerts for buy and sell conditions, ensuring you never miss a trading opportunity.
🔶 Disclaimer
The "Statistical RSI Pivot Reversal Indicator " script is intended for educational and informational purposes only.
It does not constitute financial advice or investment recommendations.
Trading financial instruments involves risk, and it is possible to lose more than your initial investment. Past performance is not indicative of future results.
FaikValThe "FaikVal" indicator is a powerful tool designed to help traders analyze relative price movements between a base asset and up to three comparison assets. This indicator uses exponential moving averages (EMA) and normalization techniques to identify potential overbought and oversold situations.
Functions and Applications:
Comparison of Price Ratios: The indicator calculates the ratio of the closing price of the base asset to the closing prices of three user-defined comparison assets. This allows for direct comparative analysis and helps identify relative strengths and weaknesses.
EMA Calculations: Two EMAs are calculated for each price ratio (with configurable periods). The difference between these two EMAs serves as the basis for further calculations.
Normalization: The calculated values are normalized over a defined period, helping to smooth out extreme values and facilitate analysis. This normalization transforms the values onto a scale from -100 to 100.
Optional Smoothing: Optional smoothing of the normalized values can be enabled to further reduce short-term fluctuations and generate clearer signals.
Visual Signals: The indicator plots three lines (one for each comparison ratio), representing the normalized values. Additionally, horizontal lines are displayed at +60, -60, and 0 to mark overbought and oversold zones as well as neutral areas.
Customizability: Users can adjust the periods of the EMAs, the length of the normalization period, and the smoothing period. They can also specify which of the three indicators should be displayed.
Applications:
Relative Strength Analysis: Identify whether the base asset is performing stronger or weaker compared to other markets or instruments.
Trend Confirmation: Confirm existing trends by analyzing the movements of the base asset relative to the comparison assets.
Overbought and Oversold Signals: Use the displayed values and horizontal lines to identify potential market turning points and determine entry or exit points.
!!! It works best on the weekly and daily chart for swing trading. It is a set up tool, to determin weather you should go long or short and not a market timing tool. For timing you could use concepts like trend and supply and demand!!!
The "FaikVal" indicator offers versatile and detailed analysis, making it particularly useful for traders seeking deeper insights into relative price strength and weakness.
intellect_city - World Cycle - Ath & Atl - Logarithmic - Signal.Indicator Overview
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for signal purchases of sales, there is also a strategic one from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
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Описание на русском:
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Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для сигнальных покупок продаж, есть также и стратегический от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
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Beschreibung - Deutsch
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Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Signal – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator dient zur Signalisierung von Käufen oder Verkäufen, es gibt auch einen strategischen Indikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
Multiple Oscillator Conditions Final [siulian] v2This tool is created to gather multiple oscilators condition under the same umbrela and back-test your idea.
Basically the only intention of this tool is to used in combination with a back-tester indicator ( or manually ) where you get the entry based on the cumulative signals provided by this tool.
For example you can to combine RSI , MACD, CCI, Keltner Channels or whatever indicator you think it might give you an edge for an entry signal.
You can combine up to 7 indicators either by comparing them with a static value or with another indicator (for example you can compare RSI with RSI MA, Volume with Volume MA, etc)
There are two lines which will be printed.
1) Result(blue line) - it will print 1 when all the condition are met ( the same can be used for back-testing tools)
2) Condition Met count(yellow line) - which will count how many conditions from the ones selected are triggered ( for example you have 6 indicators that are matching the conditions and you still want to take a trade even if the condition number 7 is not met)
Alarms can be setup to check if more than defined conditions are present.
As a demo in the above image i have put several condition in order to possible catch bottoms.
Please understand this is just an example on how to integrate multiple condition into a single entity and should not be used as is.
1) price should close below KC
2) CCI < - 100
3) RSI < 30
4) Vol > Vol MA
Past performance do not guarantee future performance.
Advanced Awesome Oscillator [CryptoSea]Advanced AO Analysis Indicator
The Advanced AO Analysis indicator is a sophisticated tool designed to evaluate the Awesome Oscillator (AO) in search of regular and hidden divergences that signal potential price reversals. By tracking the intensity and duration of the AO's movements, this indicator aids traders in pinpointing critical points in price action.
Key Features
Divergence Detection: Identifies both regular and hidden bullish and bearish divergences, providing early signs of potential market reversals.
Customizable Lookback Periods: Allows users to set specific lookback windows to define the strength and relevance of detected divergences.
Adaptive Oscillator Display: Features customizable display options for the AO, enabling users to view data in different modes suited to their analysis needs.
Alert System: Includes configurable alerts to notify users of potential divergence formations, helping traders respond promptly.
How it Works
AO Calculation: Computes the AO as the difference between short-term and long-term moving averages of the midpoints of bars, highlighting momentum shifts.
Pivot Point Analysis: Utilizes advanced algorithms to find low and high pivot points based on the oscillator values, crucial for spotting trend reversals.
Range Validation: Verifies that divergences occur within a predefined range from pivot points, ensuring their validity and strength.
Visualisation: Plots AO values and potential divergences directly on the chart, aiding in quick visual analysis.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of AO movements and divergence.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with pivot point detection and divergence analysis.
Behavioural Insight: Offers insights into market dynamics and sentiment by analyzing the depth and duration of AO cycles above and below zero.
The Advanced AO Analysis indicator equips traders with a powerful analytical tool for studying the Awesome Oscillator in-depth, enhancing their ability to spot and act on divergence-based trading opportunities in the cryptocurrency markets.
Williams %R OB/OS Candle Coloring### Description for TradingView Publication
**Title:** Williams %R OB/OS Candle Coloring
**Description:**
This Pine Script indicator enhances the visibility of market conditions by changing the color of the candlesticks based on the Williams %R values. It helps traders quickly identify overbought and oversold conditions without the need to display the Williams %R line or any additional bands.
**How It Works:**
- The script calculates the Williams %R value using a specified lookback period (default is 14 days).
- It then compares the Williams %R value against predefined overbought and oversold levels.
- **Overbought Condition:** When the Williams %R value is greater than the upper band level (-20 by default), the candlestick color changes to blue.
- **Oversold Condition:** When the Williams %R value is less than the lower band level (-80 by default), the candlestick color changes to yellow.
**How to Use:**
1. **Input Parameters:**
- **Length:** The lookback period for calculating Williams %R (default is 14).
- **Upper Band Level:** The threshold for overbought conditions (default is -20).
- **Lower Band Level:** The threshold for oversold conditions (default is -80).
2. **Candlestick Coloring:**
- Blue candles indicate potential overbought conditions.
- Yellow candles indicate potential oversold conditions.
This indicator is designed to provide a visual cue directly on the price chart, making it easier for traders to spot extreme market conditions at a glance.
**Concepts Underlying the Calculation:**
Williams %R, developed by Larry Williams, is a momentum indicator that measures overbought and oversold levels. It compares the current closing price to the highest high and lowest low over a specified period. By using color-coded candles, traders can quickly assess market conditions and make informed decisions without the need to interpret an additional indicator line.
This script is particularly useful for traders who prefer a clean chart but still want to leverage the insights provided by the Williams %R indicator.
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### ภาษาไทย:
**คำอธิบาย:**
สคริปต์ Pine Script ตัวนี้ช่วยเพิ่มการมองเห็นสภาวะตลาดโดยการเปลี่ยนสีของแท่งเทียนตามค่าของ Williams %R ช่วยให้เทรดเดอร์สามารถระบุสภาวะการซื้อเกินและขายเกินได้อย่างรวดเร็วโดยไม่ต้องแสดงเส้น Williams %R หรือเส้นระดับเพิ่มเติมใดๆ
**วิธีการทำงาน:**
- สคริปต์คำนวณค่าของ Williams %R โดยใช้ช่วงเวลาที่กำหนด (เริ่มต้นที่ 14 วัน)
- จากนั้นเปรียบเทียบค่าของ Williams %R กับระดับการซื้อเกินและขายเกินที่กำหนดไว้
- **สภาวะการซื้อเกิน:** เมื่อค่าของ Williams %R มากกว่าระดับ Upper Band (-20 เริ่มต้น) สีของแท่งเทียนจะเปลี่ยนเป็นสีน้ำเงิน
- **สภาวะการขายเกิน:** เมื่อค่าของ Williams %R น้อยกว่าระดับ Lower Band (-80 เริ่มต้น) สีของแท่งเทียนจะเปลี่ยนเป็นสีเหลือง
**วิธีการใช้งาน:**
1. **ค่าพารามิเตอร์:**
- **Length:** ช่วงเวลาที่ใช้คำนวณ Williams %R (เริ่มต้นที่ 14)
- **Upper Band Level:** ระดับการซื้อเกิน (เริ่มต้นที่ -20)
- **Lower Band Level:** ระดับการขายเกิน (เริ่มต้นที่ -80)
2. **การเปลี่ยนสีแท่งเทียน:**
- แท่งเทียนสีน้ำเงินระบุถึงสภาวะการซื้อเกิน
- แท่งเทียนสีเหลืองระบุถึงสภาวะการขายเกิน
อินดิเคเตอร์นี้ถูกออกแบบมาเพื่อให้สัญญาณภาพตรงบนกราฟราคาช่วยให้เทรดเดอร์สามารถมองเห็นสภาวะตลาดได้อย่างชัดเจนและทำการตัดสินใจได้ง่ายขึ้น
**แนวคิดที่อยู่เบื้องหลังการคำนวณ:**
Williams %R ที่พัฒนาโดย Larry Williams เป็นอินดิเคเตอร์โมเมนตัมที่วัดระดับการซื้อเกินและขายเกิน มันเปรียบเทียบราคาปิดปัจจุบันกับราคาสูงสุดและต่ำสุดในช่วงเวลาที่กำหนด โดยใช้แท่งเทียนที่มีการเปลี่ยนสี เทรดเดอร์สามารถประเมินสภาวะตลาดและทำการตัดสินใจได้อย่างรวดเร็วโดยไม่ต้องตีความเส้นอินดิเคเตอร์เพิ่มเติม
สคริปต์นี้มีประโยชน์โดยเฉพาะสำหรับเทรดเดอร์ที่ต้องการกราฟที่สะอาดแต่ยังต้องการใช้ข้อมูลเชิงลึกจากอินดิเคเตอร์ Williams %R
Enhanced Reversal DetectionScript Description:
The "Enhanced Reversal Detection" indicator is a powerful tool designed to identify potential market reversals across various financial instruments. It incorporates a sophisticated algorithm that analyzes price action along with key technical indicators such as the Relative Strength Index (RSI), Bollinger Bands, and Moving Average (MA).
How to Use:
Adjustable Parameters: The indicator offers a range of adjustable parameters to cater to different trading preferences and market conditions.
RSI Length: Adjusts the length of the RSI calculation to fine-tune sensitivity.
Overbought Level: Sets the threshold for identifying overbought conditions on the RSI scale.
Oversold Level: Sets the threshold for identifying oversold conditions on the RSI scale.
Bollinger Bands Length: Determines the length of the Bollinger Bands calculation.
Bollinger Bands Multiplier: Adjusts the standard deviation multiplier for the Bollinger Bands, influencing band width.
Moving Average Length: Defines the length of the Moving Average calculation to capture trend direction.
Min Bars Between Signals: Sets the minimum number of bars required between consecutive reversal signals.
ADX Length: Adjusts the length of the Average Directional Index (ADX) calculation.
ADX Threshold: Defines the threshold value for ADX, serving as a filter for reversal signals.
Signal Generation: The indicator generates signals for both bullish and bearish reversals based on predefined criteria. A bullish reversal signal is triggered when the closing price exceeds the lower Bollinger Band and RSI falls below the oversold threshold. Conversely, a bearish reversal signal occurs when the closing price falls below the upper Bollinger Band and RSI surpasses the overbought threshold.
Alerts: Traders can opt to receive alerts for bullish and bearish reversal signals, enabling them to stay informed of potential trading opportunities even when away from the platform.
Publication Readiness:
To ensure readiness for publication in the TradingView public library, the script has been meticulously crafted and documented:
The code is extensively commented to provide clear explanations of parameters, calculations, and signal generation logic.
Best coding practices have been followed to enhance readability and maintainability.
Rigorous testing has been conducted to validate the accuracy and reliability of signal generation across various market conditions.
The script adheres to TradingView's guidelines and policies for script publication, ensuring compliance with platform standards and user expectations.
With its comprehensive features and user-friendly design, the "Enhanced Reversal Detection" indicator is poised to become a valuable asset for traders seeking to identify high-probability reversal opportunities in the financial markets.
Cosine Kernel Regressions [QuantraSystems]Cosine Kernel Regressions
Introduction
The Cosine Kernel Regressions indicator (CKR) uses mathematical concepts to offer a unique approach to market analysis. This indicator employs Kernel Regressions using bespoke tunable Cosine functions in order to smoothly interpret a variety of market data, providing traders with incredibly clean insights into market trends.
The CKR is particularly useful for traders looking to understand underlying trends without the 'noise' typical in raw price movements. It can serve as a standalone trend analysis tool or be combined with other indicators for more robust trading strategies.
Legend
Fast Trend Signal Line - This is the foreground oscillator, it is colored upon the earliest confirmation of a change in trend direction.
Slow Trend Signal Line - This oscillator is calculated in a similar manner. However, it utilizes a lower frequency within the cosine tuning function, allowing it to capture longer and broader trends in one signal. This allows for tactical trading; the user can trade smaller moves without losing sight of the broader trend.
Case Study
In this case study, the CKR was used alongside the Triple Confirmation Kernel Regression Oscillator (KRO)
Initially, the KRO indicated an oversold condition, which could be interpreted as a signal to enter a long position in anticipation of a price rebound. However, the CKR’s fast trend signal line had not yet confirmed a positive trend direction - suggesting that entering a trade too early and without confirmation could be a mistake.
Waiting for a confirmed positive trend from the CKR proved beneficial for this trade. A few candles after the oversold signal, the CKR's fast trend signal line shifted upwards, indicating a strong upward momentum. This was the optimal entry point suggested by the CKR, occurring after the confirmation of the trend change, which significantly reduced the likelihood of entering during a false recovery or continuation of the downtrend.
This is one of the many uses of the CKR - by timing entries using the fast signal line , traders could avoid unnecessary losses by preventing premature entries.
Methodology
The methodology behind CKR is a multi-layered approach and utilizes many ‘base’ indicators.
Relative Strength Index
Stochastic Oscillator
Bollinger Band Percent
Chande Momentum Oscillator
Commodity Channel Index
Fisher Transform
Volume Zone Oscillator
The calculated output from each indicator is standardized and scaled before being averaged. This prevents any single indicator from overpowering the resulting signal.
// ╔════════════════════════════════╗ //
// ║ Scaling/Range Adjustment ║ //
// ╚════════════════════════════════╝ //
RSI_ReScale (_res ) => ( _res - 50 ) * 2.8
STOCH_ReScale (_stoch ) => ( _stoch - 50 ) * 2
BBPCT_ReScale (_bbpct ) => ( _bbpct - 0.5 ) * 120
CMO_ReScale (_chandeMO ) => ( _chandeMO * 1.15 )
CCI_ReScale (_cci ) => ( _cci / 2 )
FISH_ReScale (_fish1 ) => ( _fish1 * 30 )
VZO_ReScale (_VP, _TV ) => (_VP / _TV) * 110
These outputs are then fed into a customized cosine kernel regression function, which smooths the data, and combines all inputs into a single coherent output.
// ╔════════════════════════════════╗ //
// ║ COSINE KERNEL REGRESSIONS ║ //
// ╚════════════════════════════════╝ //
// Define a function to compute the cosine of an input scaled by a frequency tuner
cosine(x, z) =>
// Where x = source input
// y = function output
// z = frequency tuner
var y = 0.
y := math.cos(z * x)
Y
// Define a kernel that utilizes the cosine function
kernel(x, z) =>
var y = 0.
y := cosine(x, z)
math.abs(x) <= math.pi/(2 * z) ? math.abs(y) : 0. // cos(zx) = 0
// The above restricts the wave to positive values // when x = π / 2z
The tuning of the regression is adjustable, allowing users to fine-tune the sensitivity and responsiveness of the indicator to match specific trading strategies or market conditions. This robust methodology ensures that CKR provides a reliable and adaptable tool for market analysis.
Relative Momentum Index with Laguerre FilterThe Relative Momentum Index
The Relative Momentum Index (RMI) is an oscillator that is a variation of the Relative Strength Index (RSI), but incorporates momentum over a variable lookback period rather than just consecutive price changes, which can help identify reversals and filter out noise.
It measures the momentum of price changes over a specified period, rather than just the magnitude of price changes like the RSI does.
It counts up and down days from the current closing price relative to the closing price a certain number of days ago (e.g. 5 days ago), instead of just comparing consecutive daily closes like the RSI
It is calculated by taking the ratio of the average upward price changes to the average downward price changes over a given period, where each change is measured from the close X days ago (X is the “momentum” period)
Like the RSI, the RMI oscillates between 0 and 100, with readings above 70 considered overbought and below 30 oversold.
In trending markets, the RMI tends to remain in overbought or oversold territory for extended periods. In trading ranges, it oscillates more predictably between the overbought and oversold levels.
The RMI is generally considered better than the RSI at identifying potential reversal points, as it incorporates a momentum factor rather than just strength.
It can be used in a similar way to the RSI for trade signals, such as buying when it rises above 30 from below, or selling when it falls below 70 from above
The Laguerre filter
A Laguerre filter is a type of infinite impulse response (IIR) filter used for smoothing signals or data. The Laguerre filter provides a way to apply variable smoothing to a signal by adjusting its pole position, allowing you to control the balance between smoothness and lag based on your preferences. It is an alternative to simple moving averages that can better preserve the shape of the original signal.
Adaptive Trend Lines [MAMA and FAMA]Updated my previous algo on the Adaptive Trend lines, however I have added new functionalities and sorted out the settings.
You can now switch between normalized and non-normalized settings, the colors have also been updated and look much better.
The MAMA and FAMA
These indicators was originally developed by John F. Ehlers (Stocks & Commodities V. 19:10: MESA Adaptive Moving Averages). Everget wrote the initial functions for these in pine script. I have simply normalized the indicators and chosen to use the Laplace transformation instead of the hilbert transformation
How the Indicator Works:
The indicator employs a series of complex calculations, but we'll break it down into key steps to understand its functionality:
LaplaceTransform: Calculates the Laplace distribution for the given src input. The Laplace distribution is a continuous probability distribution, also known as the double exponential distribution. I use this because of the assymetrical return profile
MESA Period: The indicator calculates a MESA period, which represents the dominant cycle length in the price data. This period is continuously adjusted to adapt to market changes.
InPhase and Quadrature Components: The InPhase and Quadrature components are derived from the Hilbert Transform output. These components represent different aspects of the price's cyclical behavior.
Homodyne Discriminator: The Homodyne Discriminator is a phase-sensitive technique used to determine the phase and amplitude of a signal. It helps in detecting trend changes.
Alpha Calculation: Alpha represents the adaptive factor that adjusts the sensitivity of the indicator. It is based on the MESA period and the phase of the InPhase component. Alpha helps in dynamically adjusting the indicator's responsiveness to changes in market conditions.
MAMA and FAMA Calculation: The MAMA and FAMA values are calculated using the adaptive factor (alpha) and the input price data. These values are essentially adaptive moving averages that aim to capture the current trend more effectively than traditional moving averages.
But Omar, why would anyone want to use this?
The MAMA and FAMA lines offer benefits:
The indicator offers a distinct advantage over conventional moving averages due to its adaptive nature, which allows it to adjust to changing market conditions. This adaptability ensures that investors can stay on the right side of the trend, as the indicator becomes more responsive during trending periods and less sensitive in choppy or sideways markets.
One of the key strengths of this indicator lies in its ability to identify trends effectively by combining the MESA and MAMA techniques. By doing so, it efficiently filters out market noise, making it highly valuable for trend-following strategies. Investors can rely on this feature to gain clearer insights into the prevailing trends and make well-informed trading decisions.
This indicator is primarily suppoest to be used on the big timeframes to see which trend is prevailing, however I am not against someone using it on a timeframe below the 1D, just be careful if you are using this for modern portfolio theory, this is not suppoest to be a mid-term component, but rather a long term component that works well with proper use of detrended fluctuation analysis.
Dont hesitate to ask me if you have any questions
Again, I want to give credit to Everget and ChartPrime!
Code explanation as required by House Rules:
fastLimit = input.float(title='Fast Limit', step=0.01, defval=0.01, group = "Indicator Settings")
slowLimit = input.float(title='Slow Limit', step=0.01, defval=0.08, group = "Indicator Settings")
src = input(title='Source', defval=close, group = "Indicator Settings")
input.float: Used to create input fields for the user to set the fastLimit and slowLimit values.
input: General function to get user inputs, like the data source (close price) used for calculations.
norm_period = input.int(3, 'Normalization Period', 1, group = "Normalized Settings")
norm = input.bool(defval = true, title = "Use normalization", group = "Normalized Settings")
input.int: Creates an input field for the normalization period.
input.bool: Allows the user to toggle normalization on or off.
Color settings in the code:
col_up = input.color(#22ab94, group = "Color Settings")
col_dn = input.color(#f7525f, group = "Color Settings")
Constants and functions
var float PI = math.pi
laplace(src) =>
(0.5) * math.exp(-math.abs(src))
_computeComponent(src, mesaPeriodMult) =>
out = laplace(src) * mesaPeriodMult
out
_smoothComponent(src) =>
out = 0.2 * src + 0.8 * nz(src )
out
math.pi: Represents the mathematical constant π (pi).
laplace: A function that applies the Laplace transform to the source data.
_computeComponent: Computes a component of the data using the Laplace transform.
_smoothComponent: Smooths data by averaging the current value with the previous one (nz function is used to handle null values).
Alpha function:
_computeAlpha(src, fastLimit, slowLimit) =>
mesaPeriod = 0.0
mesaPeriodMult = 0.075 * nz(mesaPeriod ) + 0.54
...
alpha = math.max(fastLimit / deltaPhase, slowLimit)
out = alpha
out
_computeAlpha: Calculates the adaptive alpha value based on the fastLimit and slowLimit. This value is crucial for determining the MAMA and FAMA lines.
Calculating MAMA and FAMA:
mama = 0.0
mama := alpha * src + (1 - alpha) * nz(mama )
fama = 0.0
fama := alpha2 * mama + (1 - alpha2) * nz(fama )
Normalization:
lowest = ta.lowest(mama_fama_diff, norm_period)
highest = ta.highest(mama_fama_diff, norm_period)
normalized = (mama_fama_diff - lowest) / (highest - lowest) - 0.5
ta.lowest and ta.highest: Find the lowest and highest values of mama_fama_diff over the normalization period.
The oscillator is normalized to a range, making it easier to compare over different periods.
And finally, the plotting:
plot(norm == true ? normalized : na, style=plot.style_columns, color=col_wn, title = "mama_fama_diff Oscillator Normalized")
plot(norm == false ? mama_fama_diff : na, style=plot.style_columns, color=col_wnS, title = "mama_fama_diff Oscillator")
Example of Normalized settings:
Example for setup:
Try to make sure the lower timeframe follows the higher timeframe if you take a trade based on this indicator!
Multi Timeframe Relative Strength Index {DCAquant}Overview
The Multi Timeframe Relative Strength Index (MTF RSI) is a powerful technical analysis tool designed to provide insights into market momentum and potential trend reversals across multiple timeframes. Leveraging the Relative Strength Index (RSI) formula, this indicator offers traders a comprehensive view of market sentiment and identifies overbought and oversold conditions.
Key Features
RSI Calculation:
Utilizes the standard RSI calculation formula to measure the magnitude of recent price changes and assess the strength of market trends.
Employs a user-defined length parameter to customize the sensitivity of the RSI calculation based on trading preferences.
Multiple Timeframe Analysis:
Allows traders to analyze RSI values across up to six different timeframes, ranging from minutes to days, providing a holistic perspective on market dynamics.
Calculates RSI values independently for each selected timeframe, enabling comparison and trend identification.
Threshold Levels:
Defines overbought and oversold levels to highlight potential reversal points in market trends.
Offers flexibility in adjusting threshold levels based on individual risk tolerance and trading strategies.
Neutral Zone:
Establishes upper and lower neutral thresholds to identify periods of consolidation or sideways movement in price.
Helps traders distinguish between trending and ranging market conditions for more accurate analysis.
Moving Average Smoothing:
Provides the option to apply moving average smoothing to aggregated RSI values for enhanced clarity and reduced noise.
Enables smoother visualization of RSI trends, facilitating easier interpretation for traders.
Visual Representation:
Plots the aggregated MTF RSI values on the price chart, allowing traders to visually assess market momentum and potential reversal points.
Utilizes color-coded backgrounds to indicate Long, Short, or Neutral conditions for quick identification.
Dynamic Table Display:
Displays trading signals alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table format.
Offers flexibility in table placement and size to accommodate user preferences.
How to Use:
Parameter Configuration:
Adjust the length parameter to fine-tune the sensitivity of the RSI calculation based on the desired timeframe and trading strategy.
Define overbought and oversold levels to identify potential reversal points in market trends.
Customize upper and lower neutral thresholds to differentiate between trending and ranging market conditions.
Interpretation:
Monitor the aggregated MTF RSI values plotted on the price chart for signals of overbought or oversold conditions.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable trading insights.
Trading Strategy:
Consider entering Long positions when the aggregated MTF RSI is above the upper neutral threshold, indicating potential bullish momentum.
Evaluate Short opportunities when the aggregated MTF RSI falls below the lower neutral threshold, signaling possible bearish momentum.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management:
Combine MTF RSI analysis with robust risk management strategies, including stop-loss and take-profit levels, to manage trading risks effectively.
Practice prudent risk management and trade within your risk tolerance to minimize potential losses.
Disclaimer
Trading in financial markets involves risk, and past performance is not indicative of future results. The use of the MTF RSI indicator does not guarantee profits or prevent losses. Traders should conduct their own analysis, exercise caution, and seek advice from qualified financial professionals before making trading decisions.
Bollinger Bands with RSI and Volume confirmationThe 'Bollinger Bands with RSI and Volume Confirmation' is an invite-only indicator designed to identify potential buy and sell signals by combining Bollinger Bands, RSI, and volume. This combination aims to provide a clearer picture of market conditions and potential price movements. The indicator is optimized for use on 15-minute timeframes.
Key Features:
1. Bollinger Bands:
- Parameters: The length (default: 20 periods) and the multiplier (default: 2.0) can be adjusted to suit different trading strategies.
- Visualization: The indicator plots the upper, lower, and basis (middle) bands on the 15-minute price chart. It also includes higher timeframe (1-hour) Bollinger Bands.
2. Relative Strength Index (RSI):
- Calculation: The RSI length (default: 21 periods) and source can be customized. The indicator provides an option to choose between SMA and EMA for smoothing the RSI.
3. Volume Confirmation:
- Analysis: The volume moving average length (default: 20 periods) helps confirm signals. Buy and sell signals are only considered valid if the current volume confirms them.
How it Works:
Buy Signal:
- Timeframe and Data Integration: This indicator is used exclusively on the 15-minute chart. It integrates Bollinger Bands data from both the 15-minute and 1-hour charts to enhance the accuracy of bullish or bearish market conditions.
- Bollinger Bands Confluence: When the price reaches the lower band of both the 15-minute and 1-hour Bollinger Bands, it often indicates a stronger oversold condition and a potential support level. This confluence suggests a higher likelihood of a price reversal or bounce back toward the middle or upper band. However, it can also confirm strong bearish momentum.
- RSI Confirmation: To filter out false signals and ensure that the price is likely to move back up rather than continuing downwards, the RSI is used for additional confirmation. The buy signal is only considered if the RSI becomes bullish and crosses above its moving average (RSI-based MA).
- Volume Confirmation: To further validate the potential buy signal, the market volume is analyzed. The indicator checks if there is sufficient volume to support a price reversal. Only if all these conditions align—confluence of Bollinger Bands, bullish RSI, and confirming volume—a buy signal is generated.
- Signal Confirmation Period: The indicator allows a period for all these conditions to align, ensuring a robust and reliable buy signal.
Example Buy Signal:
Sell Signal:
- Timeframe and Data Integration: As with the buy signal, the sell signal is used exclusively on the 15-minute chart. It integrates Bollinger Bands data from both the 15-minute and 1-hour charts to improve the accuracy of bearish market conditions.
- Bollinger Bands Confluence: When the price reaches the upper band of both the 15-minute and 1-hour Bollinger Bands, it often indicates a stronger overbought condition and a potential resistance level. This confluence suggests a higher likelihood of a price reversal downward. However, it can also confirm strong bullish momentum.
- RSI Confirmation: To avoid false signals and ensure that the price is likely to move down rather than continuing upwards, the RSI is used for additional confirmation. The sell signal is only considered if the RSI indicates bearishness and crosses below its moving average (RSI-based MA).
- Volume Confirmation: To validate the potential sell signal, the market volume is analyzed. The indicator checks if there is sufficient volume to support a price reversal downward. Only if all these conditions align—confluence of Bollinger Bands, bearish RSI, and confirming volume—a sell signal is generated.
- Signal Confirmation Period: The indicator allows a period for all these conditions to align, ensuring a robust and reliable sell signal.
Here is an example:
Alerts:
- The indicator includes alert conditions for both buy and sell signals, notifying traders when conditions are met. In order to activate the alerts you must go to TradingView's alerts section and enable buy/sell alerts for an asset.
This indicator uses a multi-faceted approach to signal generationt:
1. Bollinger Bands: This technical analysis tool is used to measure market volatility and identify potential overbought and oversold conditions. By plotting the Bollinger Bands on both 15-minute and 1-hour timeframes, the indicator can detect significant price levels where market reactions are likely.
2. RSI (Relative Strength Index): RSI is utilized to measure the speed and change of price movements. By incorporating an option to choose between SMA and EMA for smoothing, the indicator offers flexibility to adapt to various market conditions. RSI crossing its moving average provides additional confirmation of potential reversals.
3. Volume Analysis: Volume is a critical component in confirming the validity of price movements. The indicator analyzes volume by calculating a moving average (default: 20 periods) to determine if there is sufficient market activity to support the identified signals.
Concepts Underlying Calculations:
- Confluence of Indicators: The primary concept behind this indicator is the confluence of multiple technical indicators. By requiring alignment between Bollinger Bands, RSI, and volume, the indicator filters out false signals and increases the probability of successful trades.
- Timeframe Analysis: Integrating data from multiple timeframes (15-minute and 1-hour) provides a more comprehensive view of market conditions, helping to identify significant support and resistance levels.
- Signal Validation: Each potential signal is subjected to a validation process involving RSI and volume analysis. This ensures that only high-probability signals are generated, reducing the risk of entering trades based on weak or unreliable signals.
This indicator was developed to streamline market analysis and provide a more efficient trading experience. By integrating multiple indicators into a single tool, traders can quickly observe market conditions and make informed decisions without the need to manually check each indicator on separate timeframes. This saves time and provides a clearer sense of how the market is moving, enhancing the overall trading strategy.
Disclaimer:
Trading involves substantial risk and is not suitable for every investor. Past performance is not indicative of future results. Always do your own research and consult with a professional financial advisor before making any trading decisions.
