Regime Classifier Oscillator (AiBitcoinTrend)The Regime Classifier Oscillator (AiBitcoinTrend) is an advanced tool for understanding market structure and detecting dynamic price regimes. By combining filtered price trends, clustering algorithms, and an adaptive oscillator, it provides traders with detailed insights into market phases, including accumulation, distribution, advancement, and decline.
This innovative tool simplifies market regime classification, enabling traders to align their strategies with evolving market conditions effectively.
👽 What is a Regime Classifier, and Why is it Useful?
A Regime Classifier is a concept in financial analysis that identifies distinct market conditions or "regimes" based on price behavior and volatility. These regimes often correspond to specific phases of the market, such as trends, consolidations, or periods of high or low volatility. By classifying these regimes, traders and analysts can better understand the underlying market dynamics, allowing them to adapt their strategies to suit prevailing conditions.
👽 Common Uses in Finance
Risk Management: Identifying high-volatility regimes helps traders adjust position sizes or hedge risks.
Strategy Optimization: Traders tailor their approaches—trend-following strategies in trending regimes, mean-reversion strategies in consolidations.
Forecasting: Understanding the current regime aids in predicting potential transitions, such as a shift from accumulation to an upward breakout.
Portfolio Allocation: Investors allocate assets differently based on market regimes, such as increasing cash positions in high-volatility environments.
👽 Why It’s Important
Markets behave differently under varying conditions. A regime classifier provides a structured way to analyze these changes, offering a systematic approach to decision-making. This improves both accuracy and confidence in navigating diverse market scenarios.
👽 How We Implemented the Regime Classifier in This Indicator
The Regime Classifier Oscillator takes the foundational concept of market regime classification and enhances it with advanced computational techniques, making it highly adaptive.
👾 Median Filtering: We smooth price data using a custom median filter to identify significant trends while eliminating noise. This establishes a baseline for price movement analysis.
👾 Clustering Model: Using clustering techniques, the indicator classifies volatility and price trends into distinct regimes:
Advance: Strong upward trends with low volatility.
Decline: Downward trends marked by high volatility.
Accumulation: Consolidation phases with subdued volatility.
Distribution: Topping or bottoming patterns with elevated volatility.
This classification leverages historical price data to refine cluster boundaries dynamically, ensuring adaptive and accurate detection of market states.
Volatility Classification: Price volatility is analyzed through rolling windows, separating data into high and low volatility clusters using distance-based assignments.
Price Trends: The interaction of price levels with the filtered trendline and volatility clusters determines whether the market is advancing, declining, accumulating, or distributing.
👽 Dynamic Cycle Oscillator (DCO):
Captures cyclic behavior and overlays it with smoothed oscillations, providing real-time feedback on price momentum and potential reversals.
Regime Visualization:
Regimes are displayed with intuitive labels and background colors, offering clear, actionable insights directly on the chart.
👽 Why This Implementation Stands Out
Dynamic and Adaptive: The clustering and refit mechanisms adapt to changing market conditions, ensuring relevance across different asset classes and timeframes.
Comprehensive Insights: By combining price trends, volatility, and cyclic behaviors, the indicator provides a holistic view of the market.
This implementation bridges the gap between theoretical regime classification and practical trading needs, making it a powerful tool for both novice and experienced traders.
👽 Applications
👾 Regime-Based Trading Strategies
Traders can use the regime classifications to adapt their strategies effectively:
Advance & Accumulation: Favorable for entering or holding long positions.
Decline & Distribution: Opportunities for short positions or risk management.
👾 Oscillator Insights for Trend Analysis
Overbought/oversold conditions: Early warning of potential reversals.
Dynamic trends: Highlights the strength of price momentum.
👽 Indicator Settings
👾 Filter and Classification Settings
Filter Window Size: Controls trend detection sensitivity.
ATR Lookback: Adjusts the threshold for regime classification.
Clustering Window & Refit Interval: Fine-tunes regime accuracy.
👾 Oscillator Settings
Dynamic Cycle Oscillator Lookback: Defines the sensitivity of cycle detection.
Smoothing Factor: Balances responsiveness and stability.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
在腳本中搜尋"Cycle"
Wall Street Cheat Sheet IndicatorThe Wall Street Cheat Sheet Indicator is a unique tool designed to help traders identify the psychological stages of the market cycle based on the well-known Wall Street Cheat Sheet. This indicator integrates moving averages and RSI to dynamically label market stages, providing clear visual cues on the chart.
Key Features:
Dynamic Stage Identification: The indicator automatically detects and labels market stages such as Disbelief, Hope, Optimism, Belief, Thrill, Euphoria, Complacency, Anxiety, Denial, Panic, Capitulation, Anger, and Depression. These stages are derived from the emotional phases of market participants, helping traders anticipate market movements.
Technical Indicators: The script uses two key technical indicators:
200-day Simple Moving Average (SMA): Helps identify long-term market trends.
50-day Simple Moving Average (SMA): Aids in recognizing medium-term trends.
Relative Strength Index (RSI): Assesses the momentum and potential reversal points based on overbought and oversold conditions.
Clear Visual Labels: The current market stage is displayed directly on the chart, making it easy to spot trends and potential turning points.
Usefulness:
This indicator is not just a simple mashup of existing tools. It uniquely combines the concept of market psychology with practical technical analysis tools (moving averages and RSI). By labeling the psychological stages of the market cycle, it provides traders with a deeper understanding of market sentiment and potential future movements.
How It Works:
Disbelief: Detected when the price is below the 200-day SMA and RSI is in the oversold territory, indicating a potential bottom.
Hope: Triggered when the price crosses above the 50-day SMA, with RSI starting to rise but still below 50, suggesting an early uptrend.
Optimism: Occurs when the price is above the 50-day SMA and RSI is between 50 and 70, indicating a strengthening trend.
Belief: When the price is well above the 50-day SMA and RSI is between 70 and 80, showing strong bullish momentum.
Thrill and Euphoria: Identified when RSI exceeds 80, indicating overbought conditions and potential for a peak.
Complacency to Depression: These stages are identified based on price corrections and drops relative to moving averages and declining RSI values.
Best Practices:
High-Time Frame Focus: This indicator works best on high-time frame charts, specifically the 1-week Bitcoin (BTCUSDT) chart. The longer time frame provides a clearer picture of the overall market cycle and reduces noise.
Trend Confirmation: Use in conjunction with other technical analysis tools such as trendlines, Fibonacci retracement levels, and support/resistance zones for more robust trading strategies.
How to Use:
Add the Indicator: Apply the Wall Street Cheat Sheet Indicator to your TradingView chart.
Analyze Market Stages: Observe the dynamic labels indicating the current stage of the market cycle.
Make Informed Decisions: Use the insights from the indicator to time your entries and exits, aligning your trades with the market sentiment.
This indicator is a valuable tool for traders looking to understand market psychology and make informed trading decisions based on the stages of the market cycle.
Market HackThis indicator is intended to only be used in any timeframe between the 1 minute and the 15 minute. If greater than 15 minute, or less than 1 minute, then the table will disappear!
Furthermore, this is a very simple table containing 4 varying emojis:
🔱- This is a gold crossing, indicative of bullish momentum.
💀 - This is a death crossing, indicative of bearish momentum.
🟩 - This represents a bullish cycle, which reinforces the currently active bullish momentum.
🟥 - This represents a bearish cycle, which supports an active bearish momentum.
In summary, 🔱🟩 is perfect confirmation for CALL entry, but even better when at minimum the 1m and 3m care confirmed. Similarly, 💀🟥 confirms an upcoming entry for a PUT. Bear in mind, this indicator is not meant for any financial advice and is only meant to present market direction, or at least a few specific tickers' direction with the market.
Clock&Flow MM+InfoThis script is an indicator that helps you visualize various moving averages directly on the price chart and gain some additional insights.
Here's what it essentially does:
Displays Different Moving Averages: You can choose to see groups of moving averages with different periods, set to nominal cyclical durations. You can also opt to configure them for instruments traded with classic or extended trading hours (great for Futures), and they'll adapt to your chosen timeframe.
Colored Bands: It allows you to add colored bands to the background of the chart that change weekly or daily, helping you visualize time cycles. You can customize the band colors.
Information Table: A small table appears in a corner of the chart, indicating which cycle the moving averages belong to (daily, weekly, monthly, etc.), corresponding to the timeframe you are using on the chart.
Customization: You can easily enable or disable the various groups of moving averages or the colored bands through the indicator's settings.
It's a useful tool for traders who use moving averages to identify trends and support/resistance levels, and who want a quick overview of market cycles.
Questo script è un indicatore che aiuta a visualizzare diverse medie mobili direttamente sul grafico dei prezzi e a ottenere alcune informazioni aggiuntive.
In pratica, fa queste cose:
Mostra diverse medie mobili: Puoi scegliere di vedere gruppi di medie mobili con periodi diversi impostati sulle durate cicliche nominali. Puoi scegliere se impostarle per uno strumento quotato con orario di negoziazione classico o esteso (ottimo per i Futures) e si adattano al tuo timeframe).
Bande colorate: Ti permette di aggiungere delle bande colorate sullo sfondo del grafico che cambiano ogni settimana o ogni giorno, per aiutarti a visualizzare i cicli temporali. Puoi scegliere il colore delle bande.
Tabella informativa: In un angolo del grafico, compare una piccola tabella che indica a quale ciclo appartengono le medie mobili (giornaliero, settimanale, mensile, ecc.) e corrispondono in base al timeframe che stai usando sul grafico.
Personalizzazione: Puoi facilmente attivare o disattivare i vari gruppi di medie mobili o le bande colorate tramite le impostazioni dell'indicatore.
È uno strumento utile per i trader che usano le medie mobili per identificare trend e supporti/resistenze, e che vogliono avere un colpo d'occhio sui cicli di mercato.
MeanRevert Matrix [StabTrading]MeanRevert Matrix is a sophisticated trading tool designed to detect when prices significantly deviate from their historical averages, signalling potential market trends and reversals.
Leveraging complex algorithms that incorporate human emotions and mean reversion theory, this indicator is the first stage in a comprehensive system for identifying market entry points. Its versatility allows it to be applied across all charts and timeframes, providing traders with clear visual cues for trend analysis and decision-making.
This indicator is purposefully straightforward, allowing traders to observe how the different algorithms work in confluence. The MeanRevert Matrix can be customized to fit individual trading styles, particularly in terms of aggressiveness, making it adaptable to various market conditions. Working in tandem with the FloWave Oscillator, it offers an additional layer of confluence, ensuring that trading signals are more reliable.
💡 Features
Reversal Zones - These zones are integral to the MeanRevert Matrix, highlighting areas where trader emotions and money flow suggest potential longer-term reversals. The lighter shaded zones indicate early-stage reversals, while darker shades signal stronger reversal potential. This feature is designed to help traders anticipate market shifts and prepare for them accordingly.
Localized Mean Reversion Signals - These signals are triggered when the price deviates significantly from the mean, unaffected by longer-term price movements. This localized algorithm helps traders focus on short-term market fluctuations without being influenced by broader trends.
Yellow Signals - These signals identify isolated overbought or oversold conditions. While they often indicate reversal points, they can also signal the beginning of accelerated buying or selling, giving traders early warning of potential market shifts.
Trading Style Customization - The MeanRevert Matrix allows traders to tailor their strategy by adjusting the indicator’s aggressiveness. A more aggressive setting will produce more frequent reversal signals, offering flexibility based on the trader’s risk tolerance and market outlook.
Noise Eliminator - This feature helps traders filter out market noise or manipulation by increasing the noise value. By removing unwanted or misleading signals, it ensures that traders are acting on the most reliable data.
📈 Implementing the System
Step 1 - Begin by observing the localized blue trend to identify reversal points below the mean. Green or red signals within this trend indicate that the price remains within the current market parameters, suggesting that a reversal may occur more quickly. Yellow signals, however, indicate that the trend is likely to continue, so it’s advisable to wait for clearer reversal zones to develop. To avoid misleading signals, consider using higher noise values.
Step 2 - Wait for the reversal zone algorithm to indicate a potential market reversal by showing either light or dark red/green colour. A lighter zone suggests that the overall trend is beginning to reverse, while a darker zone indicates a higher likelihood of reversal.
Step 3 - Once a reversal zone is identified, monitor the trend line for signals that the price is moving significantly away from the mean. This indicates a strong localized price movement that is poised for a reversal. At this stage, you can reduce the noise value and increase the aggressiveness of the trading style to capture more reversal signals.
🛠️ Usage/Practice
In the example above, the indicator is set with neutral aggression for buy signals and lower aggression for sell signals, reflecting the current bull market cycle
Red Reversal Zone - A bearish reversal zone emerges, followed by a darker bearish zone, indicating an increased probability of a trend reversal. The red signals show price reversion from the localized mean, but the absence of yellow signals suggests the reversion isn't abnormally aggressive, making this a good area to consider a short position.
Strong Reversal Opportunity - Similar to point 1, but this time a green signal appears within the bullish dark green zone, highlighting a strong reversal potential. Subsequent red signals suggest opportunities to take profits as the trend faces resistance.
Opportunity to Strengthen Long Position - Once again, the indicator shows a bullish reversal zone without yellow signals. This suggests an area of increased resistance at this price point, offering traders another chance to increase their long positions before the market enters the long bull cycle.
Excessive Buying Pressure - The price has deviated significantly from the mean, triggering a yellow signal. This indicates excessive buying pressure, suggesting the trend is likely to continue upward. Although not an immediate bearish area, the red sell signals suggest it could be a time to conservatively take partial profits.
Trend Weakening - As the trend slows down, bearish zones appear, indicating potential reversal points. As the market shows signs of losing upward momentum, this suggests an opportunity to reduce their long exposure or enter a short trade and take advantage of the correction in the bull cycle.
Potential for Additional Long Position - Despite the earlier sell signals, the overall uptrend remains strong. This presents an opportunity either to add to the long position or to take profits from a previous sell position. The strength of the upward trend suggests that the market may continue higher.
Abnormal Upward Momentum - Similar to points 4 and 5, the yellow signals indicate abnormal price action with aggressive upward momentum. As the trend corrects to a normal range, the price hitting a resistance level is confirmed by the appearance of red reversal zones, suggesting a potential pullback.
Sideways Market Signals - In a sideways market, the indicator shows signals that remain within the normal mean reversion range. These signals are not abnormal and suggest potential entry points for trades within a sideways market, indicating periods where the market lacks strong directional momentum.
🔶 Conclusion
With its seamless integration into various charts and timeframes, the MeanRevert Matrix stands as a reliable and adaptable tool, essential for navigating the complexities of modern markets. By following the implementation guidelines and leveraging its features, traders have the potential to effectively anticipate market movements and optimize their entry and exit points.
We developed this indicator to help traders enhance their understanding of market trends and achieve their trading objectives with greater precision.
Cyclic RegressionCyclic Regression is a new concept that uses Digital Signal Processing (DSP) to determine the regression of past and future cycles. This is a unique method of regression which has the ability to forecast into the future.
There are several ways to use this tool.
Firstly, it follows similar rules to moving averages and can be used to filter entries. Long entries should be considered when price action is above the line or the line direction is upwards. The opposite is applied for shorts, a downward direction or price action is below.
The regression line is also a strong SR (Support and Resistance) or trend line so traders can expect big moves when this line is broken or a pullback is made after the break.
Each new direction of regression signifies a new cycle so traders can plan for a possible big move when reaching the end of the line.
The Settings are not your typical length or lookback options:
The main modifier is the "Response" input, with this the frequency response for the signal processing can be adjusted. By default it is set at 5000 but this can be boosted to something like 10000 to tune it to bigger cycles.
The other modifiers include sensitivity which will fine tune the response, this can be use with in conjunction with threshold option which adjusts the threshold of the useable response.
There is also the ability to add an external sources to the signal using the source input box. This allows traders to include other sources of data such as volume or RSI.
TASC 2022.11 Phasor Analysis█ OVERVIEW
TASC's November 2022 edition Traders' Tips includes an article by John Ehlers titled "Recurring Phase Of Cycle Analysis". This is the code that implements the phasor analysis indicator presented in this publication.
█ CONCEPTS
The article explores the use of phasor analysis to identify market trends.
An ordinary rotating phasor diagram is a two-dimensional vector, anchored to the origin, whose rotation rate corresponds to the cycle period in the price data stream. Similarly, Ehlers' phasor is a representation of angular phase rotation along the course of time. Its angle reflects the current phase of the cycle. Angles -180, -90, +90 and +180 degrees correspond to the beginning, valley, peak and end of the cycle, respectively.
If the observed cycle is very long, the market can be considered trending . In his article, John Ehlers defined trending behavior to occur when the derived instantaneous cycle period value is greater that 60 bars. The author also introduced guidelines for long and short entries in a trending state. Depending on the tuning of the indicator period input, a long entry position may occur when the phasor angle is around the approximate vicinity of −90 degrees, while a short entry position may occur when the phasor angle will be around the approximate vicinity of +90 degrees. Applying these definitive guidelines, the author proposed a state variable that is indicated by +1 for a trending long position, 0 for cycling, and −1 for a trending short position (or out).
The phasor angle, the cycle period, and the state variable are made available with three selectable display modes provided for this TradingView indicator.
█ CALCULATIONS
The calculations are carried out as follows.
First, the price data stream is correlated with cosine and sine of a fixed cycle period. This produces two new data streams that correspond to the projections of the frequency domain phasor diagram to the horizontal (so-called real ) and vertical (so-called imaginary ) axis respectively. The wavelength of the cycle period input should be set for the midrange vicinities of the phasor to coincide with the peaks and valleys of the charted price data.
Secondly, the phase angle of the phasor is easily computed as the arctangent of the ratio of the imaginary component to the real component. The difference between the current phasor values and its last is then employed to calculate a derived instantaneous period and market state. This computation is then repeated successively for each individual bar over the entire duration of the data set.
ICTProTools | ICT Insight - Momentum Structures🚀 INTRODUCTION
The Momentum Structures Indicator builds upon the principles of ICT (Inner Circle Trader) and Smart Money Concepts (SMC) to give traders a clearer view of market dynamics. These methods reveal how institutional trading activity shapes price movements, particularly through different types of market liquidity.
The indicator is designed to provide traders with advanced insights into market dynamics by focusing on key price imbalances and higher-timeframe structures . By combining these elements, the indicator allows users to analyze price behavior across multiple timeframes, helping them anticipate potential liquidity pools and price reversals. The emphasis on price imbalances and liquidity zones makes it a versatile tool for both intraday and longer-term strategies, providing critical insights for understanding market cycles and potential turning points.
💎 FEATURES
Imbalance Bar Colors / Zones
Imbalances are fundamental components of the ICT methodology, highlighting areas where price accelerates, creating gaps that may indicate a lack of liquidity . These voids often point to potential reversal or continuation zones in the price action.
An imbalance typically arises when supply and demand are out of balance, resulting in a gap between price levels. Traders keep a close eye on these gaps, as they could present opportunities to enter trades when the price revisits them , as they suggest a strong institutional interest.
We can notice two types of imbalances… A Fair Value Gap (FVG) usually forms from three consecutive candles, defining the space between the wicks of the first and last candle. Conversely, a Volume Imbalance (VI) occurs when a gap appears between the opening and closing prices of two consecutive candles. When these imbalances align with FVGs, they offer a well-rounded framework for assessing market strength.
By analyzing both FVGs and VIs together, traders can gain valuable insight into potential price movements and better evaluate the likelihood of continuation or reversal.
This chart illustrates the Fair Value Gaps (FVG) and Volume Imbalances (VI) within the GBPUSD price action. The FVG Bar Color and FVG Zone represent the same Fair Value Gaps, and similarly, the VI Bar Color and VI Zone display the same Volume Imbalances. They highlight areas where rapid price movements have created gaps in the market. These gaps indicate potential zones for trade entries or exits as the price may return to fill them. As we can see on the chart, the major part of imbalances created has already been filled. They constitute really interesting Point of Interest (POI).
The 50% FVG line marks the midpoint of the gap, which is often considered an important level for price action. A clear example appears in the Bearish FVG on the top left, where price first filled it below the midline, creating a small reaction. The price then liquidated this "fake mitigation" by moving just above the midline before beginning its significant downward movement. This demonstrates the crucial role of imbalances and how precisely price interacts with them.
Traders can use this information to identify potential buying or selling opportunities based on the interaction of price with these gaps and volume imbalances, aiding in the development of their trading strategies.
PO3 Candles (Power of Three)
The Power of Three is a critical concept in the ICT methodology that analyzes Higher Timeframe (HTF) candles focusing on the opening price, high wick, low wick, and closing price. This framework helps traders understand the current market cycle, in three phases , and its trading implications.
Accumulation Phase: In this initial phase, the price consolidates around the opening price as the market gathers liquidity. This often signals that larger players are positioning for the next move.
Manipulation Phase: Represented by the candle wicks, this phase indicates the extreme points where liquidity grabs often occur. Observing these wicks helps traders identify the end of the accumulation phase and potential turning points.
Distribution Phase: The candle body reflects a decisive price movement in one direction , following accumulation and manipulation. Traders align with the direction of this phase to capture the “real candle move”.
Our indicator provides you with the valuable capability to integrate the True Day Range, as defined by ICT. This concept, rooted in institutional logic, defines a trading day as starting at 00:00 New York time. You can customize it to match your trading style and analysis needs.
You can also overlay imbalances (FVG and VI) directly onto PO3 Candles, seamlessly combining imbalance detection with high-timeframe price action. This approach gives you a sharper market perspective, uncovering potential turning points with greater clarity.
In summary, PO3 Candles help traders assess the market structure and identify cycle positions on HTF candles, enabling them to make more strategic trading decisions, which allows for better entry and exit timing, avoiding traps, and seizing the best opportunities to capture significant market moves.
This chart illustrates the application of the Power of Three concept to EURUSD price action, highlighting key phases of market behavior.
In this example, we observe the Daily candles, where a significant Bullish imbalance appears from previous days, forming a Fair Value Gap (FVG). Additionally, there’s a small Volume Imbalance (VI) at the candle's opening, signaling liquidity that the price needs to fill.
Now, focusing on the Weekly candle, we can clearly identify its phases. First, there's an accumulation phase around the opening price, which, as shown by the Daily candles, took some time to develop. Then, the manipulation phase occurs, signaled by the upper wick of the Weekly candle, which liquidates the previously created accumulation. It’s time to look for a potential selling position... Finally, the price falls, beginning to form its bearish body and completing the real move of the week.
This framework allows traders to better understand the market structure and make informed decisions based on the current cycle.
Standard Deviation (STD)
The Standard Deviation (STD) is a concept within the ICT methodology that focuses on identifying periods of consolidation within the market. Specifically, it examines the Central Bank Dealers Range (CBDR) , which occurs between 13:00 and 23:00 New York time. During this period, the market often exhibits consolidation , creating an environment where price action stabilizes before making significant moves.
This consolidation forms the basis of the Standard Deviation (STD) concept. This is based on the idea that the volatility observed during this consolidation phase can be used to anticipate future market volatility. Once this consolidation is identified, the STD framework duplicates the established range both above and below the consolidation area.
As price approaches these duplicated levels, it offers traders critical information on where to anticipate potential reactions. If the price nears the upper boundary of the consolidation, it suggests a potential reversal point, indicating an opportunity to consider selling. Conversely, if the price approaches the lower boundary, it may signal an opportunity to look for buying positions . This duplication could enable traders to determine potential high and low points for the trading day or week for example.
Finally, the Standard Deviation (STD) concept provides a valuable framework for identifying potential key reaction points in the market by leveraging consolidation within the CBDR. By duplicating these ranges, traders can anticipate significant price movements and refine their strategies.
This chart illustrates the Standard Deviation (STD) concept applied to EURUSD price action. The highlighted areas in blue indicate high duplications and low duplications derived from the consolidation identified during the Central Bank Dealing Range (CBDR), marked by the dark gray rectangle.
The high duplications represent potential resistance levels, suggesting areas where the price may encounter selling pressure, while the low duplications signify potential support levels, indicating where buying interest could emerge.
The annotations emphasize how price reacts at these duplicated levels, showing the critical role of the STD in determining where price movements may stall or reverse. In this example, the price responded perfectly to both an upward and a downward duplication, confirming that these levels could represent the day's high and low, an observation validated here. This highlights the precision of price movements, with the price stopping exactly at the full duplication levels (but we can not that the price could also have paused at the midline levels, indicated by the dashed gray lines).
This visualization helps traders anticipate potential reactions and align their strategies with market dynamics, ensuring informed decision-making based on established price behavior.
✨ SETTINGS
Imbalance Bar Colors / Zones: Choose to display FVGs, VIs, or both, with customizable color settings. Choose to extend zones or set them to be removed when mitigated.
PO3 Candles: Customize the PO3 Candles for different timeframes (Daily, Weekly, Monthly), including the calculation Mode (Classic or True Day Range) and timezone associated, and set your body, border, and wick preferred colors. The Imbalance Bar Color and FVG Zones can also be displayed on these HTF candles, as they are configured in their settings.
STD: Select the timeframe on which to base it and configure the number of duplications and midline settings. You can also define the time range and timezone related to consolidation detection, giving you control over when and where the STD should apply.
🎯 CONCLUSION
The Momentum Structures Indicator combines the core principles of ICT and Smart Money Concepts to provide traders with advanced tools for understanding market dynamics. By focusing on key elements like imbalances and liquidity zones, it offers a comprehensive framework for analyzing price behavior. This indicator empowers traders to identify key market phases, anticipate potential reversals, and refine their entry and exit points with precision. While its features provide a valuable edge, it’s essential to remember that none should be used on its own and many more factors go into being a profitable trader.
Economic Seasons [Daveatt]Ever wondered what season your economy is in?
Just like Mother Nature has her four seasons, the economy cycles through its own seasons! This indicator helps you visualize where we are in the economic cycle by tracking two key metrics:
📊 What We're Tracking:
1. Interest Rates (USIRYY) - The yearly change in interest rates
2. Inflation Rate (USINTR) - The rate at which prices are rising
The magic happens when we normalize these values (fancy math that makes the numbers play nice together) and compare them to their recent averages. We use a lookback period to calculate the standard deviation and determine if we're seeing higher or lower than normal readings.
🔄 The Four Economic Seasons & Investment Strategy:
1. 🌸 Goldilocks (↑Growth, ↓Inflation)
"Not too hot, not too cold" - The economy is growing steadily without overheating.
BEST TIME TO: Buy growth stocks, technology, consumer discretionary
WHY: Companies can grow earnings in this ideal environment of low rates and stable prices
2. 🌞 Reflation (↑Growth, ↑Inflation)
"Party time... but watch your wallet!" - The economy is heating up.
BEST TIME TO: Buy commodities, banking stocks, real estate
WHY: These sectors thrive when inflation rises alongside growth
3. 🌡️ Inflation (↓Growth, ↑Inflation)
"Ouch, my purchasing power!" - Growth slows while prices keep rising.
BEST TIME TO: Rotate into value stocks, consumer staples, healthcare
WHY: These defensive sectors maintain pricing power during inflationary periods
4. ❄️ Deflation (↓Growth, ↓Inflation)
"Winter is here" - Both growth and inflation are falling.
BEST TIME TO: Focus on quality bonds, cash positions, and dividend aristocrats
WHY: Capital preservation becomes key; high-quality fixed income provides safety
🎯 Strategic Trading Points:
- BUY AGGRESSIVELY: During late Deflation/early Goldilocks (the spring thaw)
- HOLD & ACCUMULATE: Throughout Goldilocks and early Reflation
- START TAKING PROFITS: During late Reflation/early Inflation
- DEFENSIVE POSITIONING: Throughout Inflation and Deflation
⚠️ Warning Signs to Watch:
- Goldilocks → Reflation: Time to reduce growth stock exposure
- Reflation → Inflation: Begin rotating into defensive sectors
- Inflation → Deflation: Quality becomes crucial
- Deflation → Goldilocks: Start building new positions
The blue dot shows you where we are right now in this cycle.
The red arrows in the middle remind us that this is a continuous cycle - one season flows into the next, just like in nature!
💡 Pro Tip: The transitions between seasons often provide the best opportunities - but also the highest risks. Use additional indicators and fundamental analysis to confirm these shifts.
Remember: Just like you wouldn't wear a winter coat in summer, you shouldn't use a Goldilocks strategy during Inflation! Time your trades with the seasons. 🎯
Happy Trading! 📈
WD Gann: Close Price X Bars Ago with Line or Candle PlotThis indicator is inspired by the principles of WD Gann, a legendary trader known for his groundbreaking methods in time and price analysis. It helps traders track the close price of a security from X bars ago, a technique that is often used to identify key price levels in relation to past price movements. This concept is essential for Gann’s market theories, which emphasize the relationship between time and price.
WD Gann’s analysis often revolved around specific numbers that he considered significant, many of which correspond to squared numbers (e.g., 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521, 1600, 1681, 1764, 1849, 1936). These numbers are believed to represent natural rhythms and cycles in the market. This indicator can help you explore how past price levels align with these significant numbers, potentially revealing key price zones that could act as support, resistance, or reversal points.
Key Features:
- Historical Close Price Calculation: The indicator calculates and displays the close price of a security from X bars ago (where X is customizable). This method aligns with Gann's focus on price relationships over specific time intervals, providing traders with valuable reference points to assess market conditions.
- Customizable Plot Type: You can choose between two plot types for visualizing the historical close price:
- Line Plot: A simple line that represents the close price from X bars ago, ideal for those who prefer a clean and continuous representation.
- Candle Plot: Displays the close price as a candlestick chart, providing a more detailed view with open, high, low, and close prices from X bars ago.
- Candle Color Coding: For the candle plot type, the script color-codes the candles. Green candles appear when the close price from X bars ago is higher than the open price, indicating bullish sentiment; red candles appear when the close is lower, indicating bearish sentiment. This color coding gives a quick visual cue to market sentiment.
- Customizable Number of Bars: You can adjust the number of bars (X) to look back, providing flexibility for analyzing different timeframes. Whether you're conducting short-term or long-term analysis, this input can be fine-tuned to suit your trading strategy.
- Gann Method Application: WD Gann's methods involved analyzing price action over specific time periods to predict future movements. This indicator offers traders a way to assess how the price of a security has behaved in the past in relation to a chosen time interval, a critical concept in Gann's theories.
How to Use:
1. Input Settings:
- Number of Bars (X): Choose the number of bars to look back (e.g., 100, 200, or any custom period).
- Plot Type: Select whether to display the data as a Line or Candles.
2. Interpretation:
- Using the Line plot, observe how the close price from X bars ago compares to the current market price.
- Using the Candles plot, analyze the full price action of the chosen bar from X bars ago, noting how the close price relates to the open, high, and low of that bar.
3. Gann Analysis: Integrate this indicator into your broader Gann-based analysis. By looking at past price levels and their relationship to significant squared numbers, traders can uncover potential key levels of support and resistance or even potential reversal points. The historical close price can act as a benchmark for predicting future market movements.
Suggestions on WD Gann's Emphasis in Trading:
WD Gann’s trading methods were rooted in several key principles that emphasized the relationship between time and price. These principles are vital to understanding how the "Close Price X Bars Ago" indicator fits into his overall analysis:
1. Time Cycles: Gann believed that markets move in cyclical patterns. By studying price levels from specific time intervals, traders can spot these cycles and predict future market behavior. This indicator allows you to see how the close price from X bars ago relates to current market conditions, helping to spot cyclical highs and lows.
2. Price and Time Squaring: A core concept in Gann’s theory is that certain price levels and time periods align, often marking significant reversal points. The squared numbers (e.g., 1, 4, 9, 16, 25, etc.) serve as potential key levels where price and time might "square" to create support or resistance. This indicator helps traders spot these historical price levels and their potential relevance to future price action.
3. Geometric Angles: Gann used angles (like the 45-degree angle) to predict market movements, with the belief that prices move at specific geometric angles over time. This indicator gives traders a reference for past price levels, which could align with key angles, helping traders predict future price movement based on Gann's geometry.
4. Numerology and Key Intervals: Gann paid particular attention to numbers that held significance, including squared numbers and numbers related to the Fibonacci sequence. This indicator allows traders to analyze price levels based on these key numbers, which can help in identifying potential turning points in the market.
5. Support and Resistance Levels: Gann’s methods often involved identifying levels of support and resistance based on past price action. By tracking the close price from X bars ago, traders can identify past support and resistance levels that may become significant again in future market conditions.
Perfect for:
Traders using WD Gann’s methods, such as Gann angles, time cycles, and price theory.
Analysts who focus on historical price levels to predict future price action.
Those who rely on numerology and geometric principles in their trading strategies.
By integrating this indicator into your trading strategy, you gain a powerful tool for analyzing market cycles and price movements in relation to key time intervals. The ability to track and compare the historical close price to significant numbers—like Gann’s squared numbers—can provide valuable insights into potential support, resistance, and reversal points.
Disclaimer:
This indicator is based on the methods and principles of WD Gann and is for educational purposes only. It is not intended as financial advice. Trading involves significant risk, and you should not trade with money that you cannot afford to lose. Past performance is not indicative of future results. The use of this indicator is at your own discretion and risk. Always do your own research and consider consulting a licensed financial advisor before making any investment decisions.
Retracement Painpoints - Robinhodl21Description:
Retracement Painpoints is crafted to delve into the psychology of markets, particularly assets that are heavily driven by profit expectations and hype cycles. This tool excels when applied to assets experiencing strong hype phases. By visualizing downturns, you can assess which pullbacks are mere pauses in the hype cycle and which ones might signal the end of a trend or precede more significant declines. This insight allows you to identify critical points where market sentiment shifts, helping you make more informed trading decisions.
Main Features:
Focuses on assets influenced by hype and strong profit expectations. Helps distinguish between normal retracements and potential trend reversals.
Trend Detection Methods: Moving Average (MA): Utilizes a customizable MA period to determine market trends. Delta to All-Time High (ATH): Analyzes the percentage distance from the ATH to define trend direction. No Trend Detection: Allows for neutral analysis without trend bias.
Statistical Drawdown Analysis: Identifies local minima in drawdowns to calculate statistically significant levels. Option to calculate statistics based on trend direction (bullish/bearish). Adjustable variables for fine-tuning statistical levels.
Visualization: Plots drawdown curves with color-coding based on trend direction. Displays calculated statistical levels on the chart to highlight potential pain points.
Usage:
Set Parameters: Trend Detection Method: Choose your preferred method (MA, Delta to ATH, or None). MA Period: Define the period for the moving average (default: 420). Delta to ATH (%): Set the threshold for distance to ATH (default: 30%). Neutral Zone Delta to ATH (%): Define the neutral market zone (default: 60%). Stat Variables 1 & 2: Adjust these to select the desired statistical drawdown levels. Minimum Drawdown Threshold (%): Set the minimum drawdown to consider in analysis (default: 10%).
Interpretation: Drawdown Curve: Monitor percentage declines from local maxima. The color indicates the current trend direction: Green: Uptrend. Red: Downtrend. Gray: Neutral or no trend detection. Statistical Levels: Use the displayed levels as potential support or resistance zones, reflecting key psychological levels in the market.
Strategic Application: Identify crucial areas where the price has historically reversed. Assess whether a downturn is a typical retracement within a hype cycle or a sign of a more significant decline. Combine this tool with other technical analysis methods to enhance your trading strategy. Adjust settings based on market conditions and personal trading preferences.
Notes: The indicator is based on historical data and should not be used as the sole basis for trading decisions. It's recommended to test the indicator across various markets and timeframes. Past performance is not indicative of future results.
Created by Robinhodl
3Commas dollar cost averaging (DCA) QFL IndicatorAs investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex indicator based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The indicator script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry alerts. During price action development an asset value can go lower and in this way the script will perform safety entries alerts at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action alert.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements. These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The indicator supports traditional and cryptocurrency spot, futures , options and marginal trading exchanges. It works accurately with BTC , USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The indicator can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
The difference between core script and this interpretation is that this strategy is specially designed for 3Commas bots
How to use?
1. Apply indicator to a trading pair your are interested in using 1H timeframe chart
2. Configure the indicator: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView custom alert using the indicator settings to trigger on a condition you are interested in
4. The indicator will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
3Commas Dollar cost averaging trading system (DCA)As investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex trading system based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The strategy script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry actions. During price action development an asset value can go lower and in this way the script will perform safety entries at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The strategy supports traditional and cryptocurrency spot, futures , options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The strategy can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
The difference between core script and this interpretation is that this strategy is specially designed for 3Commas bots
How to use?
1. Apply strategy to a trading pair your are interested in using 1H timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
Dollar cost averaging (DCA) QFL IndicatorAs investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex indicator based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The indicator script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry alerts. During price action development an asset value can go lower and in this way the script will perform safety entries alerts at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action alert.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements. These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The indicator supports traditional and cryptocurrency spot, futures, options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The indicator can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
Advantages of this indicator:
The indicator has custom alert settings for each strategy action
The indicator can be used with 3Commas, Cryptohopper, Alertatron or Zignaly bots
The indicator is sustainable to market slumps and can be used for long-term trading
The indicator provides a large number of entries which is good for diversification
Can be applied to any market and quote currency
Easy to configure user interface settings
How to use?
1. Apply indicator to a trading pair your are interested in using 1H timeframe chart
2. Configure the indicator: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView custom alert using the indicator settings to trigger on a condition you are interested in
4. The indicator will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
Dollar cost averaging trading system (DCA)As investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex trading system based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The strategy script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry actions. During price action development an asset value can go lower and in this way the script will perform safety entries at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The strategy supports traditional and cryptocurrency spot, futures, options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The strategy can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
Advantages of this script:
Strategy has high net profit of 255% at backtests
Backtests show high accuracy around 75%
Low Drawdowns of around 14% at backtests
Strategy is sustainable to market slumps and can be used for long-term trading
The strategy provides a large number of entries which is good for diversification
Can be applied to any market and quote currency
Easy to configure user interface settings
How to use?
1. Apply strategy to a trading pair your are interested in using 1H timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
[GYTS] Filters ToolkitFilters Toolkit indicator
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- 1. INTRODUCTION --------- 🌸
💮 Overview
The GYTS Filters Toolkit indicator is an advanced, interactive interface built atop the high‐performance, curated functions provided by the FiltersToolkit library . It allows traders to experiment with different combinations of filtering methods -— from smoothing low-pass filters to aggressive detrenders. With this toolkit, you can build custom indicators tailored to your specific trading strategy, whether you're looking for trend following, mean reversion, or cycle identification approaches.
🌸 --------- 2. FILTER METHODS AND TYPES --------- 🌸
💮 Filter categories
The available filters fall into four main categories, each marked with a distinct symbol:
🌗 Low Pass Filters (Smoothers)
These filters attenuate high-frequency components (noise) while allowing low-frequency components (trends) to pass through. Examples include:
Ultimate Smoother
Super Smoother (2-pole and 3-pole variants)
MESA Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA)
BiQuad Low Pass Filter
ADXvma (Adaptive Directional Volatility Moving Average)
A2RMA (Adaptive Autonomous Recursive Moving Average)
Low pass filters are displayed on the price chart by default, as they follow the overall price movement. If they are combined with a high-pass or bandpass filter, they will be displayed in the subgraph.
🌓 High Pass Filters (Detrenders)
These filters do the opposite of low pass filters - they remove low-frequency components (trends) while allowing high-frequency components to pass through. Examples include:
Butterworth High Pass Filter
BiQuad High Pass Filter
High pass filters are displayed as oscillators in the subgraph below the price chart, as they fluctuate around a zero line.
🌑 Band Pass Filters (Cycle Isolators)
These filters combine aspects of both low and high pass filters, isolating specific frequency ranges while attenuating both higher and lower frequencies. Examples include:
Ehlers Bandpass Filter
Cyber Cycle
Relative Vigor Index (RVI)
BiQuad Bandpass Filter
Band pass filters are also displayed as oscillators in a separate panel.
🔮 Predictive Filter
Voss Predictive Filter: A special filter that attempts to predict future values of band-limited signals (only to be used as post-filter). Keep its prediction horizon short (1–3 bars) for reasonable accuracy.
Note that the the library contains elaborate documentation and source material of each filter.
🌸 --------- 3. INDICATOR FEATURES --------- 🌸
💮 Multi-filter configuration
One of the most powerful aspects of this indicator is the ability to configure multiple filters. compare them and observe their combined effects. There are four primary filters, each with its own parameter settings.
💮 Post-filtering
Process a filter’s output through an additional filter by enabling the post-filter option. This creates a filter chain where the output of one filter becomes the input to another. Some powerful combinations include:
Ultimate Smoother → MAMA: Creates an adaptive smoothing effect that responds well to market changes, good for trend-following strategies
Butterworth → Super Smoother → Butterworth: Produces a well-behaved oscillator with minimal phase distortion, John Ehlers also calls a "roofing filter". Great for identifying overbought/oversold conditions with minimal lag.
A bandpass filter → Voss Prediction filter: Attempts to predict future movements of cyclical components, handy to find peaks and troughs of the market cycle.
💮 Aggregate filters
Arguably the coolest feature: aggregating filters allow you to combine multiple filters with different weights. Important notes about aggregation:
You can only aggregate filters that appear on the same chart (price chart or oscillator panel).
The weights are automatically normalised, so only their relative values matter
Setting a weight to 0 (zero) excludes that filter from the aggregation
Filters don't need to be visibly displayed to be included in aggregation
💮 Rich visualisation & alerts
The indicator intelligently determines whether a filter is displayed on the price chart or in the subgraph (as an oscillator) based on its characteristics.
Dynamic colour palettes, adjustable line widths, transparency, and custom fill between any of enabled filters or between oscillators and the zero-line.
A clear legend showing which filters are active and how they're configured
Alerts for direction changes and crossovers of all filters
🌸 --------- 4. ACKNOWLEDGEMENTS --------- 🌸
This toolkit builds on the work of numerous pioneers in technical analysis and digital signal processing:
John Ehlers, whose groundbreaking research forms the foundation of many filters.
Robert Bristow-Johnson for the BiQuad filter formulations.
The TradingView community, especially @The_Peaceful_Lizard, @alexgrover, and others mentioned in the code of the library.
Everyone who has provided feedback, testing and support!
Stage AnalysisStage Analysis was created by Stan Weinstein, and helps traders to identify where a stock/etf/index is in its Price Cycle.
The Price Cycle was introduced by Richard D. Wyckoff in the early 1900s, where he noted that stocks repeatedly go through a cycle of Accumulation, Markup, Distribution and Markdown. Stan Weinstein’s Stage Analysis method modified the Wyckoff Price Cycle, and converted it into four stages, which are:
Stage 1 = Accumulation
Stage 2 = Markup
Stage 3 = Distribution
Stage 4 = Markdown
Stage Analysis indicator:
Stan Weinstein had different definitions for the four stages – Stage 1: The Basing Area, Stage 2: The Advancing Phase, Stage 3: The Top Area, Stage 4: The Declining Phase. But for the purposes of the Stage Analysis indicator, you’ll note that we’ve combined Stage 1 and Stage 3, as they share numerous technical characteristics, and in our opinion, still require some discretionary judgement to determine whether they are showing accumulation or distribution characteristics.
So, we believe that neutral better describes them from a purely technical aspect, as being in Stage 3 doesn’t necessarily mean the top area, as it can still make a Stage 2 continuation breakout to new highs, instead of breaking down into Stage 4. Just as a Stage 1 basing pattern, can still make a further Stage 4 continuation breakdown, and won’t necessarily breakout into a Stage 2 advance. Hence, we display both Stage 1 and Stage 3 as Neutral, to help remove the perceived bias associated with Stage 3 and Stage 1.
So, in the indicator the Stages are displayed as three different colored backgrounds:
Blue = Stage 1 / Stage 3: Neutral
Green = Stage 2: Uptrend
Red = Stage 4: Downtrend
Stage 1 / Stage 3: Neutral (Blue background)
Stage 1 shows signs of a potential accumulation base structure developing and begins with a close above the 30-week simple moving average, when the stock is still below its (usually declining) 40-week MA as well, following a Stage 4 downtrend, and then remains in Stage 1 until either it breaks out into a Stage 2 uptrend, or returns to a Stage 4 downtrend once more. Although, there are often multiple failed breakout and breakdown attempts, which change the Stage briefly to Stage 2 or Stage 4, before reverting back into Stage 1, as the base broadens out.
The initial move into Stage 1 can occur in numerous different ways. Sometimes following a powerful rebound rally from the 52-week lows to above the 30-week MA, and at other times, after a basing period first, while the stock is still in Stage 4, and then only briefly moving into Stage 1, before breaking out into a new Stage 2 uptrend. But with all ways, there is a notable Change of Character compared to the previous Stage 4 downtrend, as supply and demand moves towards equilibrium, and the stock starts to build a more significant sideways range/base structure.
Stage 3 is the exact opposite of Stage 1, and instead of accumulation. Signs of distribution begin to appear when a stock is getting later in a Stage 2 Uptrend, with the stock first closing below its 30-week MA, and then starting to build a more significant sideways range/base structure, than the minor structures that formed when it was still trending higher in Stage 2.
It begins with a change of behaviour (i.e. a bigger correction than seen during the rest of Stage 2, that takes it below its 30-week, but still above its (usually rising) 40-week MA, and then that often broadens out into a sideways structure, with multiple swings above and below the 30-week MA, with tests of the highs and lows of the developing structure. Which can see it briefly revert to Stage 2, with failed breakout attempts at the highs (Upthrusts), or Stage 4, with failed breakdown attempts at the lows of the structure (Shakeouts or Springs).
So, Stage 1 and Stage 3 are both more neutral periods between the Stage 2 (Uptrend) and Stage 4 (Downtrend).
Stage 2: Uptrend (Green Background)
Stage 2 is the most important Stage for traders looking to buy stocks with the Stage Analysis method, and begins with a breakout from the prior Stage 1 base, but can also occur more suddenly from a V-bottom pattern or earnings gaps. In which case, it will move directly from a Stage 4 downtrend into a Stage 2 uptrend.
The move to Stage 2 requires certain technical aspects to be present, including a close above its near-term range (we use a 13-week range based on weekly closes), as well as its 200-day MA (40-week MA), and for our proprietary Stage Analysis Technical Attributes (SATA)* score to be at a least a SATA 6 of 10. And so, the change from Stage 1 to Stage 2 will often occur while the stock is still within a “broader” base structure, as the quarterly range is continually shifting, and doesn’t consider technical levels prior to that period.
The breakout point as Stage 2 begins is the Stage Analysis methods favoured entry zone for investors, as it marks the change from the Stage 1 basing period into the more dynamic Stage 2 uptrend (chart changes to green)
A secondary investor entry point can often form soon after the Stage 2 breakout, as the momentum fades from the initial rally, and it pulls back towards the breakout level, before finding support and swinging back higher into the advancing phase. So, the Stage Analysis indicator can be used to determine this secondary entry point by dropping down to an intraday timeframe – such as the 30-minute chart, and waiting for a Stage 2 breakout attempt on that much shorter timescale.
The Trader method entry points also form during the Stage 2 advance, and occur at the Stage 2 continuation breakout points of the more minor re-accumulation bases that form as the Stage 2 advance progresses higher.
Stage 4: Downtrend (Red Background)
Stage 4 is the opposite of Stage 2, and marks the beginning of a potential downtrend, as the distributional forces from Stage 3 gain control, and the stock attempts to move lower.
Stage 4 is the most important Stage for traders looking to short stocks with the Stage Analysis method, and as with Stage 2, it can also begin more suddenly following a sudden sharp decline or an earnings gap lower etc, that knifes through the key MAs and quarterly range.
The move to Stage 4 also requires certain technical aspects to be present, including a close below its near-term range (we use a 13-week range based on weekly closes), as well as its 200-day MA (40-week MA), and for our proprietary Stage Analysis Technical Attributes (SATA) score to be a maximum of a SATA 3 of 10, as if the SATA score is higher than 3, then it will still be considered as Stage 3 (blue) until that drops to a SATA 3 or lower.
The initial short entry point in Stage 4 occurs at the breakdown from Stage 3 to Stage 4 (chart changes to red), and as with Stage 2, a secondary entry point can form, but in Stage 4 it is on a potential pullback towards the breakdown level that then reverses lower once more. So, the Stage Analysis indicator can be used to determine this secondary entry point by dropping down to an intraday timeframe – such as the 30-minute chart, and waiting for a Stage 4 breakdown attempt on that much shorter timescale.
The Trader method short entry points also form during the Stage 4 decline, and occur at the Stage 4 continuation breakdown points of the more minor re-distribution bases that form as the Stage 4 decline progresses lower.
Recommended Chart Setup:
Weekly
Logarithmic scale
Recommended Indicators:
10 – Simple Moving Average
30 – Simple Moving Average
40 – Simple Moving Average (optional)
Mansfield Relative Strength (Original Version) (optional)
Stage Analysis Technical Attributes (SATA) (optional)
The Stages are intended to be used on the Weekly timeframe with a Logarithmic scale primarily, with a 10-week MA, 30-week MA and 40-week MA. But Stage Analysis can be used across multiple timeframes. So, for shorter-term swing traders, the 195-min (2bars/day), 2-hour, 1-hour, 30-min charts etc are often used with the same relative chart settings. But note that the lower the timeframe, the more noise that you’ll get, so you should always refer back to the weekly Stage to trade with the major trend.
Customise the Stage Analysis indicator
Edit colours of the Stages
Show/Hide Stages
Reference:
*Stage Analysis Technical Attributes (SATA)
The Stage Analysis Technical Attributes (SATA) scoring system is our proprietary tool which measures 10 of the key components that we look for in the Stage Analysis method to help to determine the Stage, and is made up of the following components:
Breakouts and Breakdowns
Price / Moving Averages
Relative Strength versus the S&P 500
Momentum
Volume
Overhead Resistance
Combining the SATA score with the price elements described in the Stages descriptions above, provides a Stage Analysis indicator that is faithful to Stan Weinstein's Stage Analysis method, and truly unique from other more simplistic automated versions of the Stages that you might find elsewhere.
Disclaimer: This indicator is for informational and educational purposes only. We accept no liability for any loss which may arise from the use of this indicator. All trading decisions are your own, and should be researched thoroughly, with appropriate risk management in place.
We are not affiliated with Stan Weinstein, and this is our own unique interpretation of the Stage Analysis method, based on our long experience with it.
Financial Astrology Indexes ML Daily TrendDaily trend indicator based on financial astrology cycles detected with advanced machine learning techniques for some of the most important market indexes: DJI, UK100, SPX, IBC, IXIC, NI225, BANKNIFTY, NIFTY and GLD fund (not index) for Gold predictions. The daily price trend is forecasted through planets cycles (angular aspects, speed phases, declination zone), fast cycles are based on Moon, Mercury, Venus and Sun and Mid term cycles are based on Mars, Vesta and Ceres . The combination of all this cycles produce a daily price trend prediction that is encoded into a PineScript array using binary format "0 or 1" that represent sell and buy signals respectively. The indicator provides signals since 2021-01-01 to 2022-12-31, the past months signals purpose is to support backtesting of the indicator combined with other technical indicator entries like MAs, RSI or Stochastic . For future predictions besides 2022 a machine learning models re-train phase will be required.
When the signal moving average is increasing from 0 to 1 indicates an increase of buy force, when is decreasing from 1 to 0 indicates an increase in sell force, finally, when is sideways around the 0.4-0.6 area predicts a period of buy/sell forces equilibrium, traders indecision which result in a price congestion within a narrow price range.
We also have published same indicator for Crypto-Currencies research portfolio:
DISCLAIMER: This indicator is experimental and don’t provide financial or investment advice, the main purpose is to demonstrate the predictive power of financial astrology. Any allocation of funds following the documented machine learning model prediction is a high-risk endeavour and it’s the users responsibility to practice healthy risk management according to your situation.
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
FloWave Oscillator [StabTrading]The FloWave Oscillator is a powerful trading tool designed to identify market trends and reversals by analysing reversal zones based on momentum and fear algorithms.
Serving as the first stage in a comprehensive trading system, it is intentionally straightforward, allowing traders to clearly see potential entry points across all charts and timeframes.
By inputting their own market sentiment, traders can customize the algorithm to align with their trading style. This flexibility helps traders navigate complex market environments with greater precision, whether they are seeking to capitalize on short-term opportunities or ride longer-term trends.
💡 Features
Reversal Zones - The FloWave Oscillator identifies key reversal zones driven by momentum and fear dynamics. Lighter green zones signal the initial stages of a potential reversal, while darker green zones indicate that a trend flip is imminent.
Trading Style Customization - The indicator allows traders to adjust their trading style with sensitivity settings ranging from Very Aggressive to Very Conservative. This flexibility lets traders tailor the indicator to their preferred time horizon—whether they seek to scalp short-term opportunities or capture long-term reversals.
🔥 Sensitivity Settings
Very Aggressive/Aggressive - These settings increase the indicator's sensitivity, generating more frequent signals, ideal for traders focused on short-term gains or those navigating choppy markets.
Neutral - Offers a balanced approach, combining both aggressive and conservative elements. It's a starting point for traders to evaluate performance before adjusting to more specific styles.
Conservative/Very Conservative - These settings reduce signal frequency, focusing on stronger, more reliable reversals. Best suited for long-term traders aiming to minimize risk and avoid premature market entries or exits.
🛠️ Usage/Practice
In the above example we’ll analysis how the indicator accurately predicts both the tops and bottoms of a market cycle.
Top of the Bull Market - The trendline initially shows two light red reversal zones, signalling a potential weakening in the upward momentum. As the trend progresses, a dark red zone emerges, confirming that a more substantial trend reversal to the downside is likely. This sequence provides an early warning, allowing traders to prepare for a possible market shift.
First Bull Signal - In the following phase, the indicator mirrors the previous action but in the opposite direction, identifying a reversal towards the upside. This behaviour demonstrates the indicator's ability to adapt to changing market conditions.
Bottom of the Bear Market - As the market continues its downward trajectory, the indicator presents two dark green reversal zones, highlighting areas where the selling pressure may be easing. These dark green zones offer three distinct opportunities to dollar-cost average (DCA) into the asset, allowing traders to build or enhance their positions during the end of the bear cycle. The indicator’s sensitivity in this phase ensures that traders can navigate the bearish market with confidence.
Continuation of Bull Cycle - In this segment, the indicator does not display any dark green reversal zones, implying that the uptrend remains robust. The absence of these zones suggests that the upward momentum is likely to continue, providing traders with another opportunity to add to their long positions. This scenario underscores the indicator’s capacity to identify when a trend is strong enough to warrant additional investment.
Potential Correction in an Uptrend - A light red zone appears, signalling a possible correction within the ongoing uptrend. However, the absence of a dark red zone indicates that the correction may be minor and that the overall trend is still upward. Traders might view this as a conservative point to take some profits off the table, managing risk while staying aligned with the broader bull market.
Bearish Signal - Eventually, a dark red reversal zone emerges, indicating that the trend has lost its upward momentum. This signal serves as a strong indicator that the uptrend may be concluding, prompting traders to consider exiting their positions or taking a more defensive stance. As the market enters a sideways phase, the trader can switch to a more aggressive trading style, seeking opportunities to scalp within the range while navigating the flat market conditions.
In this example, we demonstrate how to identify scalp trading opportunities by combining the Very Conservative and Very Aggressive settings. The key strategy is to use the Very Conservative trend to confirm the validity of reversal zones identified by the Very Aggressive setting.
The VC trend doesn’t indicate a buy reversal zone, but it shows an upward divergence. This suggests that the reversal buy zone on the VA chart is a potential entry point due to the supportive VC trend.
Multiple sell zones appear on the VA chart, but the VC trend shows a strong and steady uptrend. This suggests that we should wait for confirmation from the VC trend before considering a sell position, as the market is still moving upward strongly.
The VA chart shows several buy zones, but the VC trend indicates a strong downtrend, and no buy zone appears on the conservative setting. This suggests waiting for the next VA buy zone, confirmed by an upward divergence on the VC trend, before entering a trade.
Similar to Point 3 but in the opposite direction, the VA chart shows sell zones, but the VC trend indicates caution. The strategy would be to wait for confirmation from the VC trend before making a move.
🔶Conclusion
When used in conjunction with other indicators like the MeanRevert Matrix, the FloWave Oscillator becomes an integral part of a comprehensive trading system. It helps traders make informed decisions by providing clear signals that are aligned with the current market sentiment and broader economic trends. By following the implementation guidelines and adjusting the indicator settings as market conditions change, traders can effectively enhance their trading performance.
ZigCycleBarCount [MsF]Japanese below / 日本語説明は英文の後にあります。
Based on "ZigZag++" indicator by DevLucem. Thanks for the great indicator.
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This indicator that displays the candle count (bar count) at the peaks of Zigzag .
It also displays the price of the peaks.
You can easily count candles (bars) from peak to peak. Helpful for candles (bars) in cycle theory.
This logic of the indicator is based from the mt4 zigzag indicator .
Parameter:
Depth = depth (price range)
Backstep = Period
Deviation ＝ Percentage of how much the price has wrapped around the previous line.
Example:
Depth = 12
Backstep = 3
Deviation = 5
In this case, the price range is updated by 12 pips or more (Depth), and after 3 or more candlesticks line up (Backstep), if the price deviates from the previous line by 5% or more (Deviation), a peak is added.
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Zigzagの頂点にローソクカウント（バーカウント）を表示するインジケータです。
頂点の価格も表示します。
頂点から頂点までのローソク（バー）を容易にカウントすることができます。
サイクル理論のローソク（バー）に役立ちます。
Zigzagロジック自体はMT4のzigzagインジケータを流用しています。
＜パラメータ＞
Depth＝深さ（値幅）
Backstep＝期間
Deviation＝価格がどれだけ直前のラインの折り返したかの割合
例：
Depth＝12
Backstep＝3
Deviation＝5
この場合、値幅を12pips以上更新し（Depth）、ローソク足が3本以上並んだ後（Backstep）、価格が直前のラインの5％以上折り返せば（Deviation）、頂点を付けます。
＜表示オプション＞
Label_Style = "TEXT"…テキスト表示、"BALLOON"…吹き出し表示
MTF Fractal Bias Confluence DetectorMTF Fractal Bias Confluence Detector
This indicator, the MTF Fractal Bias Confluence Detector, is based on the idea that the market exhibits fractal behaviour. The origin of the idea traces back to 1963, when Benoit Mandelbrot analyzed the fluctuations in cotton prices over a time series starting in 1900, discovering that price changes exhibited scale-invariant patterns. This means that the curve representing daily price changes mirrored the shape of monthly price changes, highlighting the fractal nature of market behaviour. When applied to swing points across multiple timeframes (MTF), this concept suggests that swing points demonstrate similar patterns regardless of the timeframe being analyzed. These self-similar fractal structures provide traders with insights into market reversals and trends, making them a powerful tool for multi-timeframe analysis.
A Swing Point is made up of three main parts: a move away from the last Break level; forming a peak (pivot point) with a Fakeout of the peak (explained through an example later); and a subsequent move away from it. These swing points recur across all timeframes as part of cyclical momentum patterns, meaning each swing point gives rise to a new cycle of market movement. Due to the fractal nature of the market, larger cycles encompass multiple smaller ones.
The theory behind the Fractal Bias Confluence Detector utilizes the idea that the market movements are fractal in nature and illustrates how such swing points can be identified across MTFs. To do so, we examine the Peak Fakeouts within these cycles, as they form. It is not possible to know in advance how long each of these moves will last, but a Swing Point will often occur with a Peak Fakeout. Therefore, the most critical element is to identify the Peak Fakeout.
The snapshot below captures a Peak Fakeout, as discussed earlier.
Similarly, the following snapshot shows various possible breakdowns of Higher Time Frame (HTF) cycles into smaller Lower Time Frame (LTF) movements. The chart contains a white table(not part of the indicator and shown for illustration purposes only).
To further illustrate. Consider the combination of Time Frames (TF) from the 2nd row (from the above snapshot). Cycle TF (1M), Setup TF (1W), Momentum TF (1D) etc.
Price movements in the 1M TF highlight the direction in which HTF traders are pushing the market. Often, when markets have broken out of a level, they tend to form a peak and can then pull back towards the prior breakout level. Once the pullback is beyond the last breakout level, in the opposite direction, we may say the peak formation is created, and directional bias has changed. This is also called Peak Fakeout. Due to the fractal nature of the market, Swing Points on the HTF will often constitute multiple Swing Points on the LTF, though they are not always in sync. However, after such peak formation, there is a high probability that the price might move away from the peak for at least 1 candle (in the cycle TF). This theory illustrates that once a new cycle is in play, we can then look at 1W (Setup TF) to look for possible in-sync movements, at least within that 1 candle of the HTF. Repeating the same for further lower TFs, we may arrive at a confluence of Fractal Bias and see how the movements in LTF are driven by the HTF momentum.
Another example within the chart:
Note: The above examples are just for illustration purposes, and other permutations and combinations of movements across multiple TFs are also possible.
This indicator aims to help users identify such fractal-bias-confluences, so that they can leverage the fractal nature of the market to get a holistic view. To do so, the indicator displays how the market has moved across multiple time frames, with respect to different historical levels.
Features:
1. The bias summary table
The following snapshot depicts the bias summary table at the bottom right of the chart.
1.1. Workings: The table will display, for various TFs, in the first four (starting from "current" to Prev ) rows, one of the following.
"F/H" , " Acronym for the failed break of the previous high",
"F/L" , " Acronym for the failed break of the previous low",
"B/H" , " Acronym for the break of the previous high",
"B/L" , " Acronym for the break of the previous low",
"IN" , " Acronym for an inside candle (never broke high or low of perv candle)",
"OT" , " Acronym for an outside candle (broke both high and low of previous candle and closing price is in between previous high and low)".
Note: these acronyms are customizable according to the user's choice of terminology in any language, as shown in the snapshot below.
1.1.1 In the above snapshot, the 1st row, called "Current", shows how the current candle is evolving with respect to the previous one. The "previous" row shows how the previous candle closed with respect to the pre-previous one. The next two rows represent the bias of the pre-previous and pre-pre-previous in a similar manner. By default, the bias is updated in real-time, even for the already closed historical candles. For example, if the previous 4H candle closed as a B/H and the current price then comes below the pre-previous 4H candle high, then the bias of the previous candle will get updated to F/H. This informs the user that the break above the pre-previous high has failed. However, the user has the option to turn this off. The information in these four rows shows the user how the market is moving currently and how it evolved before reaching the current price levels.
Note: The calculation done by the indicator is to keep track of how the price is moving with respect to the last candle levels in real-time. This means if the price first goes above the previous high and then goes below the previous low, the indicator is equipped to display what happened in the most recent time. The snapshot below shows the option to turn on/off such updates in the bias summary table.
Note: While the bias summary table is turned on, the user also has the option to turn off Prev and Prev rows, as shown in the snapshot below.
1.1.2 The 2nd to last row, called CL/CS(Consecutive Long/Short), shows whether consecutive (2+) breaks of high/low happened or not in one direction without taking out the previous candle's range in the opposite direction. When conditions are met, it will show the number of times the price has been pushed in one direction (in the above manner), followed by "L" for long and "S" for short, for each TF, for example, "4L". It gets updated in real-time for each push in the same direction. Furthermore, a good analogy of "4L" on an HTF is 4 consecutive Break of Structure (BOS) (in the same direction) on LTF, without a Change of Character (CHoCH). Another example would be Stacey Burke's 3 consecutive rises that can be mapped in the indicator, if the conditions are met for "3L" for a given TF.
1.1.3 The last row, FRC/FGC, stands for the first red/green candle. It shows whether the last candle of a TF has closed as green (i.e., close>open) after posting two red candles (i.e., close<open). This helps understand possible short-term retracements in price movements.
1.2 Customizability
1.2.1 We provide a wide range of customizable options, including multiple time frames to choose from for each type of TFs. This is shown in the snapshot below.
1.2.2 All the acronyms on the summary table are customizable and can be user-defined, including text, background color and transparency. This is shown in the snapshot below.
2. High-low lines
2.1 We also show the high and low of various TFs, including the current high and low lines (which are updated in real-time. This can be observed in one of the previous snapshots.
2.2 Previous high, low and close lines can be extended (for Cycles, Setups and Momentum TFs). Their style and thickness are also customizable. This can be observed in one of the previous snapshots.
Note: The user has the option to turn all the lines off. Sub-options include turning off the current line only. Changing the color, thickness, and transparency of the lines. This can be observed in one of the previous snapshots.
3. Last known Break / Failed Break lines.
3.1 We also depict the last known Break and Failed break lines for the user to have all the important levels at their disposal. This can be observed in one of the previous snapshots.
Note: The user has the option to turn this on/off.
4. Magnifier Box
4.1 We have provided the user to look at thirty 1m candles inside a magnifier box while they are in a higher TF chart.
The user has the option to turn this on/off.
5. Moving Averages (MA)
We have also grouped some built-in MA options for the user to utilize along with other elements of the indicator to help them get another layer of confluence.
The user has the option to turn this on/off.
Disclaimer:
The indicator leverages pre-existing theories of market movements. These can be found in decades-old published materials (like books, journals, public lectures accessible over popular video-sharing websites, etc.). As such, we do not claim to have any exclusive rights over the underlying theories. There are many analogous theories and nomenclatures that users can map onto this indicator. Users may also use the indicator in combination with other indicators.
1. Educational Use Only
The "MTF Fractal Bias Confluence Detector" is provided for educational purposes only. It does not constitute an offer, or an obligation, or a guarantee, of profitable trades or loss prevention.
2. No Financial Advice
This tool should not be viewed as financial advice for either trading or investment(s).
3. User Responsibility
Users alone bear all risks associated with any decisions they make using this tool. Past performance does not guarantee future results.
By using the "MTF Fractal Bias Confluence Detector," you acknowledge that you have read, understood and accepted this disclaimer in its entirety.
EMD Oscillator (Zeiierman)█ Overview
The Empirical Mode Decomposition (EMD) Oscillator is an advanced indicator designed to analyze market trends and cycles with high precision. It breaks down complex price data into simpler parts called Intrinsic Mode Functions (IMFs), allowing traders to see underlying patterns and trends that aren’t visible with traditional indicators. The result is a dynamic oscillator that provides insights into overbought and oversold conditions, as well as trend direction and strength. This indicator is suitable for all types of traders, from beginners to advanced, looking to gain deeper insights into market behavior.
█ How It Works
The core of this indicator is the Empirical Mode Decomposition (EMD) process, a method typically used in signal processing and advanced scientific fields. It works by breaking down price data into various “layers,” each representing different frequencies in the market’s movement. Imagine peeling layers off an onion: each layer (or IMF) reveals a different aspect of the price action.
⚪ Data Decomposition (Sifting): The indicator “sifts” through historical price data to detect natural oscillations within it. Each oscillation (or IMF) highlights a unique rhythm in price behavior, from rapid fluctuations to broader, slower trends.
⚪ Adaptive Signal Reconstruction: The EMD Oscillator allows traders to select specific IMFs for a custom signal reconstruction. This reconstructed signal provides a composite view of market behavior, showing both short-term cycles and long-term trends based on which IMFs are included.
⚪ Normalization: To make the oscillator easy to interpret, the reconstructed signal is scaled between -1 and 1. This normalization lets traders quickly spot overbought and oversold conditions, as well as trend direction, without worrying about the raw magnitude of price changes.
The indicator adapts to changing market conditions, making it effective for identifying real-time market cycles and potential turning points.
█ Key Calculations: The Math Behind the EMD Oscillator
The EMD Oscillator’s advanced nature lies in its high-level mathematical operations:
⚪ Intrinsic Mode Functions (IMFs)
IMFs are extracted from the data and act as the building blocks of this indicator. Each IMF is a unique oscillation within the price data, similar to how a band might be divided into treble, mid, and bass frequencies. In the EMD Oscillator:
Higher-Frequency IMFs: Represent short-term market “noise” and quick fluctuations.
Lower-Frequency IMFs: Capture broader market trends, showing more stable and long-term patterns.
⚪ Sifting Process: The Heart of EMD
The sifting process isolates each IMF by repeatedly separating and refining the data. Think of this as filtering water through finer and finer mesh sieves until only the clearest parts remain. Mathematically, it involves:
Extrema Detection: Finding all peaks and troughs (local maxima and minima) in the data.
Envelope Calculation: Smoothing these peaks and troughs into upper and lower envelopes using cubic spline interpolation (a method for creating smooth curves between data points).
Mean Removal: Calculating the average between these envelopes and subtracting it from the data to isolate one IMF. This process repeats until the IMF criteria are met, resulting in a clean oscillation without trend influences.
⚪ Spline Interpolation
The cubic spline interpolation is an advanced mathematical technique that allows smooth curves between points, which is essential for creating the upper and lower envelopes around each IMF. This interpolation solves a tridiagonal matrix (a specialized mathematical problem) to ensure that the envelopes align smoothly with the data’s natural oscillations.
To give a relatable example: imagine drawing a smooth line that passes through each peak and trough of a mountain range on a map. Spline interpolation ensures that line is as smooth and close to reality as possible. Achieving this in Pine Script is technically demanding and demonstrates a high level of mathematical coding.
⚪ Amplitude Normalization
To make the oscillator more readable, the final signal is scaled by its maximum amplitude. This amplitude normalization brings the oscillator into a range of -1 to 1, creating consistent signals regardless of price level or volatility.
█ Comparison with Other Signal Processing Methods
Unlike standard technical indicators that often rely on fixed parameters or pre-defined mathematical functions, the EMD adapts to the data itself, capturing natural cycles and irregularities in real-time. For example, if the market becomes more volatile, EMD adjusts automatically to reflect this without requiring parameter changes from the trader. In this way, it behaves more like a “smart” indicator, intuitively adapting to the market, unlike most traditional methods. EMD’s adaptive approach is akin to AI’s ability to learn from data, making it both resilient and robust in non-linear markets. This makes it a great alternative to methods that struggle in volatile environments, such as fixed-parameter oscillators or moving averages.
█ How to Use
Identify Market Cycles and Trends: Use the EMD Oscillator to spot market cycles that represent phases of buying or selling pressure. The smoothed version of the oscillator can help highlight broader trends, while the main oscillator reveals immediate cycles.
Spot Overbought and Oversold Levels: When the oscillator approaches +1 or -1, it may indicate that the market is overbought or oversold, signaling potential entry or exit points.
Confirm Divergences: If the price movement diverges from the oscillator's direction, it may indicate a potential reversal. For example, if prices make higher highs while the oscillator makes lower highs, it could be a sign of weakening trend strength.
█ Settings
Window Length (N): Defines the number of historical bars used for EMD analysis. A larger window captures more data but may slow down performance.
Number of IMFs (M): Sets how many IMFs to extract. Higher values allow for a more detailed decomposition, isolating smaller cycles within the data.
Amplitude Window (L): Controls the length of the window used for amplitude calculation, affecting the smoothness of the normalized oscillator.
Extraction Range (IMF Start and End): Allows you to select which IMFs to include in the reconstructed signal. Starting with lower IMFs captures faster cycles, while ending with higher IMFs includes slower, trend-based components.
Sifting Stopping Criterion (S-number): Sets how precisely each IMF should be refined. Higher values yield more accurate IMFs but take longer to compute.
Max Sifting Iterations (num_siftings): Limits the number of sifting iterations for each IMF extraction, balancing between performance and accuracy.
Source: The price data used for the analysis, such as close or open prices. This determines which price movements are decomposed by the indicator.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
