MTF WaveTrend [CryptoSea]The MTF WaveTrend Indicator is a sophisticated tool designed to enhance market analysis through multi-timeframe WaveTrend calculations. This tool is built for traders who seek to identify market momentum and potential reversals with higher accuracy.
In the example below, we can see all the choosen timeframes agree on bearish momentum.
Key Features
Multi-Timeframe WaveTrend Analysis: Tracks WaveTrend values across multiple timeframes to provide a comprehensive view of market momentum.
Customizable Colour Rules: Offers three different colour rules (Traditional, WT1 0 Rule, WT1 & WT2 0 Rule) to suit various trading strategies.
Timeframe Visibility Control: Allows users to enable or disable specific timeframes, providing flexibility in analysis.
Clear Visual Indicators: Uses color-coded squares and labels to clearly display WaveTrend status across different timeframes.
Candle Colouring Option: Includes a setting for neutral candle coloring to enhance chart readability.
This example shows what can happen when all timeframes start alligning with eachother.
How it Works
WaveTrend Calculation: Computes the WaveTrend oscillator by applying a series of exponential moving averages and scaling calculations.
Multi-Timeframe Data Aggregation: Utilizes the `request.security` function to gather and display WaveTrend values from various timeframes without repainting issues.
Conditional Plotting: Displays visual cues only when higher timeframes align with the selected timeframe, ensuring relevant and reliable signals.
Dynamic Colour Rules: Adjusts the indicator colors based on the chosen rule, whether it's a traditional crossover, WT1 crossing zero, or both WT1 & WT2 crossing zero.
Traditional: Colors are determined by the relationship between WT1 and WT2. If WT1 is greater than WT2, it is bullish (bullColour), otherwise bearish (bearColour).
WT1 0 Rule: Colors are based on whether WT1 is above or below zero. WT1 above zero is bullish (bullColour), below zero is bearish (bearColour).
WT1 & WT2 0 Rule: A more complex rule where both WT1 and WT2 need to be above zero for a bullish signal (bullColour) or both below zero for a bearish signal (bearColour). If WT1 and WT2 are not in agreement, a neutral color (neutralColour) is displayed.
This indicator will make sure that the lowest timeframe you can see data from will be the timeframe you are on. This is to avoid false signals as you cannot display 3 x 5 minute candles whilst looking at the 15 minute candle.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of WaveTrend movements across different timeframes.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with multi-timeframe WaveTrend analysis.
Customized Analysis: Adapts to various trading styles with extensive input settings that control the display and sensitivity of WaveTrend data.
The MTF WaveTrend Indicator by is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
M-oscillator
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.
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
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.
Chande Momentum Oscillator (CMO) Buy Sell Strategy [TradeDots]The "Chande Momentum Oscillator (CMO) Buy Sell Strategy" leverages the CMO indicator to identify short-term buy and sell opportunities.
HOW DOES IT WORK
The standard CMO indicator measures the difference between recent gains and losses, divided by the total price movement over the same period. However, this version of the CMO has some limitations.
The primary disadvantage of the original CMO is its responsiveness to short-term volatility, making the signals less smooth and more erratic, especially in fluctuating markets. This instability can lead to misleading buy or sell signals.
To address this, we integrated the concept from the Moving Average Convergence Divergence (MACD) indicator. By applying a 9-period exponential moving average (EMA) to the CMO line, we obtained a smoothed signal line. This line acts as a filter, identifying confirmed overbought or oversold states, thereby reducing the number of false signals.
Similar to the MACD histogram, we generate columns representing the difference between the CMO and its signal line, reflecting market momentum. We use this momentum indicator as a criterion for entry and exit points. Trades are executed when there's a convergence of CMO and signal lines during an oversold state, and they are closed when the CMO line diverges from the signal line, indicating increased selling pressure.
APPLICATION
Since the 9-period EMA smooths the CMO line, it's less susceptible to extreme price fluctuations. However, this smoothing also makes it more challenging to breach the original +50 and -50 benchmarks.
To increase trading opportunities, we've tightened the boundary ranges. Users can customize the target benchmark lines in the settings to adjust for the volatility of the underlying asset.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Signal Cool Down Period: 5
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
[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.
Custom Signal Oscillator StrategyThe CSO is made to help traders easily test their theories by subtracting the difference between two customizable plots(indicators) without having to search for strategies. The general purpose is to provide a tool to users without coding knowledge.
How to use :
Apply the indicator(s) to test
Go to the CSO strategy input settings and select the desired plots from the added indicators. (The back test will enter long or short depending on the fast signal crosses on the slow signal)
Pull up the strategy tester
Adjust the input settings on the selected indicator(s) to back test
For example, the published strategy is using the basis lines from two Donchian channels with varying length. This can be utilized with multiple overlays on the chart and oscillators that are operating on the same scale with each other. Since chart glows aren't extremely common, a glow option is included to stand out on the chart as the chain operator. A long only option for is also included for versatility.
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.
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.
---
### 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
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!
Volume Weighted Relative Strength Index (VWRSI) [AlgoAlpha]Volume Weighted Relative Strength Index 📈✨
The Volume Weighted Relative Strength Index (VWRSI) by AlgoAlpha enhances traditional RSI by incorporating volume weighting, providing a more nuanced view of market strength. It uses custom range detection to measure consolidation strength, applying dynamic scoring to highlight trend phases. The indicator includes customizable moving averages (SMA, EMA, WMA, VWMA) and color-coded visual cues for uptrends and downtrends. Additionally, it marks significant bullish and bearish trend points with symbols, making it easier to identify potential trading opportunities. This powerful tool helps traders make informed decisions by combining volume, price action, and trend analysis.
✨ Key Features :
📊 Volume-Weighted RSI : Combines RSI with volume for better accuracy.
🔄 Range Detection : Identifies consolidation phases.
🎨 Customizable MAs : Choose from various moving averages.
🔔 Alert Capabilities : Set notifications for trend points.
🚀 How to Use :
🛠 Add Indicator : Add the indicator to favorites, and customize the settings to suite your trading style.
📊 Analyze Market : Watch RSI and range score for trends.
🔔 Set Alerts : Get notified of bullish/bearish points.
✨ How It Works :
The Volume Weighted Relative Strength Index (VWRSI) combines traditional RSI with volume weighting to offer a more comprehensive view of market momentum. It calculates the RSI using the closing price, then weights it by volume to enhance the accuracy of the trend analysis. The indicator also includes a custom range detection feature that evaluates consolidation strength by dynamically scoring the RSI over a specified period. This scoring helps identify phases of strong trends and consolidations. Visual elements like color-coded trend fills and symbols for bullish and bearish points make it easier to spot key market movements and potential trading opportunities.
Stay ahead with VWRSI by AlgoAlpha! 📈💡
RSI ATR Range [SS]Hey everyone,
Over the course of the last year I had a bunch of requests to do something with RSI. I did do an RSI expected move plotter, but the requests were to overhaul RSI and make it better I guess.
So here is my attempt!
This is the RSI ATR plotter. Its similar to my RSI expected move plotter, however, it gives you the ATR ranges associated with the current RSI value. This allows you to conceptualize RSI in a different way. Instead of looking for "oversold" over "overbought", you can actually just see the expected high to open range and the expected open to low range based on the current RSI.
This will allow you to determine such things as:
a) Is it likely to be bullish?
b) Is it likely to be bearish?
c) The average move, in a dollar amount, associated with this RSI.
In addition to presenting RSI in terms of ranges as opposed to the actual RSI value, the indicator will also signal likely reversal areas. Whenever there is a huge spike in RSI and range, whether it be up or down, this generally corresponds to an imminent reversal. The indicator is programmed to recognize this and plot little grey circles to notify you of an impending reversal.
Let's take a look at some reversal examples using NVDA:
In the chart above, we can see that the RSI signaled a reversal. As it was part of a downtrend, the reversal was bullish.
Let's look at a top reversal:
The chart above shows a likely downside reversal.
And some little bounce reversals here and there:
In addition to showing you the ATR range and reversals, the indicator will show you the RSI in a bar graph format:
You won't be able to look for RSI divergences, if you are a believer of those. However, you can definitely visualize them in the ATR ranges which are directly affected by the RSI readings.
Aspects of the indicator:
Bull ranges are displayed in green.
Bear ranges are displayed in red.
When green is present we know its entering or currently in a bullish RSI range:
Inversely, when it starts to shift red, we know we are entering a bearish RSI range:
There is a border that circles the range. It will be green when we are in a bullish range and red when we are in a bearish range. In addition to these 2 signals, the RSI bar chart itself will turn green in bullish ranges, and red in bearish ranges.
Here is bullish:
Here is bearish:
Customizability
You can customize the Source input for the RSI (default is close). As well as the length (default is 14).
The ATR length is defaulted to 500. My suggestion is to leave this be. You can increase it but I would not suggest decreasing it as it may omit some of the RSI ranges from its history.
And that is the indicator my friends! Hope you enjoy!
As always, safe trades!
PROWIN STUDY BASIC CURRENT CANDLE TABLE**PROWIN STUDY BASIC CURRENT CANDLE TABLE**
**Description:**
The PROWIN STUDY BASIC CURRENT CANDLE TABLE indicator provides an insightful analysis of the current candle's volume and its comparative performance against the last 50 candles. This script includes several features designed to help traders understand volume trends and potential market direction.
**Key Features:**
1. **Volume Analysis**:
- Accesses the current candle's volume and compares it with the highest and lowest volumes over the past 50 candles.
- Calculates the average volume between the highest and lowest values for a better perspective.
2. **Candle Trend Identification**:
- Identifies whether the current candle is bullish or bearish by comparing the current close price with the previous close price.
3. **Average Volume Calculation**:
- Computes the average volume of bullish (green) and bearish (red) candles over the last 50 periods.
- Derives an average value between the green and red volume averages.
4. **Volume Slope Calculation**:
- Calculates the difference in volume averages (EMAs) between successive periods to determine the slope.
- Computes the angle of inclination for green, red, and average volume lines in degrees.
5. **Plotting**:
- Plots the average volumes of green and red candles as well as the combined average on the chart.
- Visualizes these metrics with color-coded lines for quick interpretation.
6. **Dynamic Table**:
- Displays a dynamic table on the chart that updates in real-time.
- Shows the angles of inclination for buy (green), sell (red), and average volume (blue) with corresponding background colors.
7. **Customizable Background**:
- Includes an option to set a semi-transparent background color for the chart, enhancing visual clarity.
This indicator is designed to help traders gain deeper insights into market volume dynamics and make more informed trading decisions. Whether you're analyzing short-term movements or long-term trends, the PROWIN STUDY BASIC CURRENT CANDLE TABLE offers valuable data at a glance.
Advanced Stochastic [CryptoSea]The Advanced Stochastic Indicator is a sophisticated tool designed to enhance market analysis through detailed stochastic calculations. This tool is built for traders who seek to identify market divergences and pivot points with higher accuracy.
Key Features
Multi-Layer Stochastic Analysis: Tracks both standard and smoothed stochastic values to provide a granular view of market momentum.
Divergence Detection: Automatically detects both regular and hidden bullish and bearish divergences, offering critical insights into potential market reversals.
Adaptive Oscillator Display: Features customizable display options for the stochastic oscillator, allowing traders to view data in Default, Histogram, or Both modes.
Customizable Lookback Periods: Users can set specific lookback periods for divergence analysis and stochastic calculations, tailoring the tool to fit various trading strategies.
In the example below, there is a bearish divergence above 0. You would first want the stoch to break below the 0 level as a show of strength, this would be an aggressive entry, a higher probability option would be to wait for the stoch to retest and reject from 0 which is what we have a few candles later.
How it Works
Stochastic Calculation: Computes the stochastic oscillator by smoothing the %K line over a user-defined period, then applying a second smoothing for the %D line.
Pivot Point Analysis: Utilizes advanced algorithms to find low and high pivot points based on the oscillator values, crucial for spotting trend reversals.
Colour-Coded Divergence Alerts: Utilizes color codes to highlight divergence signals directly on the chart, aiding in quick visual analysis.
Responsive Threshold Settings: Includes options to adjust the sensitivity of divergence detection, ensuring that only significant divergences are highlighted.
In the example below, we have 2 divergence signals. The first a bullish one which fails to break above 0. The second signal is given above 0 so you would want a retest and a show of strength when the stoch returns to 0 but it fails to hold. Both of these divergence signals are invalidated.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of stochastic movements and divergence.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with pivot point detection and divergence analysis.
Customized Analysis: Adapts to various trading styles with extensive input settings that control the display and sensitivity of oscillator data.
The Advanced Stochastic Indicator by is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
MTF Williams Vix Market Bottoms [CryptoSea]MTF Williams Vix Fix Indicator is a dynamic tool tailored for traders looking to capture market extremes with high precision. This multi-timeframe indicator leverages the concept of the Williams Vix Fix to spot potential reversals before they occur.
Key Features
Multi-Timeframe Analysis: Provides simultaneous visibility across multiple timeframes, enabling traders to assess market conditions comprehensively from a single chart.
Advanced Volatility Detection: Utilizes a modified Vix Fix formula to highlight extreme price deviations, which often precede significant market reversals.
Customizable Settings: Offers extensive input options to tweak the lookback periods, percentile thresholds, and visibility settings, aligning with various trading strategies.
Visual Band Indicators: Features upper bands and range highs that signal potential overbought and oversold conditions, enhancing trading decision-making.
Below, you can see how the indicator performs across different timeframes, providing valuable insights into market behavior.
How it Works
Vix Fix Calculation: Determines the worst-case 'panic' sell-offs in price as a percentage of the high, capturing the emotional extremes of the market.
Statistical Bands: Employs Bollinger bands over the Vix Fix values to define normal and extreme volatility conditions.
Color-Coded Indicators: Uses color differentiation to instantly highlight when readings surpass critical upper band or range high thresholds, signaling key trading opportunities.
For instance, in the analysis provided below, notice how the indicator flags significant market moves, allowing traders to anticipate potential entry or exit points.
Application
Risk Management: Aids in identifying extreme market conditions where prices may revert, helping in effective position sizing and risk management.
Strategic Planning: Enhances strategic trading plans by identifying not only when but also where market extremes may occur, considering multiple timeframes.
Customization: Adapts seamlessly to different market environments with adjustable settings for volatility thresholds and visual display preferences.
The MTF Williams Vix Fix Indicator by is an essential tool for traders aiming to leverage market volatility for optimal entry and exit, ensuring they are well-equipped to handle market extremes with confidence.
Color Stochastic IndicatorThis Pine Script™ indicator, "Color Stochastic Indicator," is designed to visualize the stochastic oscillator with color-coded trends and shaded background levels, providing a clearer understanding of market trends and potential trading signals.
Key Features:
Customizable Parameters:
K Period: The period for the %K line in the stochastic calculation (default: 50).
D Period: The period for the %D line, which is the moving average of %K (default: 13).
Slowing: The slowing factor applied to the stochastic calculation (default: 2).
Smoothing: A factor for additional smoothing of the stochastic values (default: 1.0).
Use Crossover: Option to determine trend based on the crossover of %K and %D lines.
Display Levels: Option to show significant stochastic levels on the chart (0.2, 0.5, 0.8).
Price Field: Selection of the price field used in calculations.
Stoch Width: Line width for the %K line.
Signal Width: Line width for the %D line.
Background Colors:
Upper Level Background: Shaded area between 0.5 and 0.8 with a customizable color.
Lower Level Background: Shaded area between 0.2 and 0.5 with a customizable color.
Color-Coded Trends:
Wait (Gray): Neutral state when no clear trend is detected.
Uptrend (Green): Indicates a potential buying signal.
Downtrend (Red): Indicates a potential selling signal.
Signal Line (Blue): Represents the %D line for clearer signal identification.
Alerts:
Customizable alerts trigger when the trend changes, providing timely notifications for potential trade opportunities.
How It Works:
Stochastic Calculation:
The %K line is calculated based on the selected K Period.
The %D line is a simple moving average (SMA) of the %K line over the D Period.
Additional smoothing is applied to both %K and %D lines using the specified Smoothing factor.
Fisher Transform:
The script applies a Fisher transform to the smoothed %K values, enhancing the clarity of trend signals.
Trend Determination:
If Use Crossover is enabled, the trend is determined based on the crossover of smoothed %K and %D lines.
If Use Crossover is disabled, the trend is determined based on whether the smoothed %K value is above or below 0.5.
Background Shading:
Fixed background colors are applied using hline and fill functions, highlighting the specified levels on the chart (0.2, 0.5, 0.8).
Plotting:
The smoothed %K line is plotted with color coding based on its value relative to the %D line and threshold levels.
The %D line is plotted for reference.
How to Use:
Adding the Indicator:
Copy and paste the provided Pine Script™ code into a new indicator script in TradingView.
Save and add the indicator to your desired chart.
Configuring Parameters:
Adjust the input parameters (K Period, D Period, Slowing, etc.) according to your trading strategy and preferences.
Enable or disable the Use Crossover option based on whether you prefer trend determination by crossover or threshold.
Interpreting Signals:
Observe the color-coded %K line to identify potential buy (green) and sell (red) signals.
Use the shaded background areas to quickly assess overbought (0.5 to 0.8) and oversold (0.2 to 0.5) conditions.
Monitor alerts for trend changes to take timely trading actions.
Alerts Setup:
Set up custom alerts based on the provided alert conditions to receive notifications when the trend changes.
Originality:
This script combines the stochastic oscillator with color-coding and background shading for enhanced visualization.
It introduces a unique Fisher transform application to the smoothed %K values.
The crossover and threshold-based trend determination options provide flexibility for different trading strategies.
Customizable alert messages help traders stay informed about trend changes in real time.
By incorporating these features, the "Color Stochastic Indicator" offers a comprehensive tool for traders seeking to leverage stochastic analysis with improved clarity and actionable insights.
