Aeon FluxAeon Flux visualizes rolling cumulative realized volatility, as a signal-generating leading indicator.
'Realized volatility' is shorthand for the metric's true output: entropy . The uniformity (or lack of uniformity) of price and volume distributions over a rolling cumulative period, normalized across the asset's full history.
Entropy = x⋅log2(x)−(1−x)⋅log2(1−x)
AEON FLUX VISUALIZES TIME CYCLES
Aeon Flux distills any asset's cyclical pendulum-like behavior, from bull to bear and vice versa, in a visualization that surfaces and isolates the pendulum shift.
As such, Aeon Flux may be the first metric to automate visualization of time cycles.
Time cycles are a soft science and esoteric concept in markets: an opinion, hard to prove or disprove.
They're ultimately just cycles of accumulation & distribution, that tend to recur at rough consistent intervals.
(Aeon Flux does not measure accumulation & distribution directly, those forces are merely implied.)
ENTROPY AS A LEADING INDICATOR
The transitions between state (from bullish to bearish & vice versa) are often good swing entries & exits, across a wide range of high cap risk markets.
ENTROPY AS A DISTRIBUTION MONITOR
Aeon Flux has a track record of detecting higher timeframe macro distribution on the BTC Index.
The signal: two cycles in a row of lower highs, where the cycle high (the highest oscillator print achieved that cycle) is lower than the previous cycle's high.
Invalidation: if the second cycle in a row of lower highs touches the green AND red target areas on its way up, that demonstrates robust volatility, and the distribution signal is invalidated.
ALERTS & NOTIFICATIONS
Alerts are enabled for swing long & short signals. Automating alerts to monitor distribution are a potential enhancement for future iterations of the script.
Pesquisar nos scripts por "Cycle"
Bitcoin Macro Trend Map [Ox_kali]
## Introduction
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The “Bitcoin Macro Trend Map” script is designed to provide a comprehensive analysis of Bitcoin’s macroeconomic trends. By leveraging a unique combination of Bitcoin-specific macroeconomic indicators, this script helps traders identify potential market peaks and troughs with greater accuracy. It synthesizes data from multiple sources to offer a probabilistic view of market excesses, whether overbought or oversold conditions.
This script offers significant value for the following reasons:
1. Holistic Market Analysis : It integrates a diverse set of indicators that cover various aspects of the Bitcoin market, from investor sentiment and market liquidity to mining profitability and network health. This multi-faceted approach provides a more complete picture of the market than relying on a single indicator.
2. Customization and Flexibility : Users can customize the script to suit their specific trading strategies and preferences. The script offers configurable parameters for each indicator, allowing traders to adjust settings based on their analysis needs.
3. Visual Clarity : The script plots all indicators on a single chart with clear visual cues. This includes color-coded indicators and background changes based on market conditions, making it easy for traders to quickly interpret complex data.
4. Proven Indicators : The script utilizes well-established indicators like the EMA, NUPL, PUELL Multiple, and Hash Ribbons, which are widely recognized in the trading community for their effectiveness in predicting market movements.
5. A New Comprehensive Indicator : By integrating background color changes based on the aggregate signals of various indicators, this script essentially creates a new, comprehensive indicator tailored specifically for Bitcoin. This visual representation provides an immediate overview of market conditions, enhancing the ability to spot potential market reversals.
Optimal for use on timeframes ranging from 1 day to 1 week , the “Bitcoin Macro Trend Map” provides traders with actionable insights, enhancing their ability to make informed decisions in the highly volatile Bitcoin market. By combining these indicators, the script delivers a robust tool for identifying market extremes and potential reversal points.
## Key Indicators
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Macroeconomic Data: The script combines several relevant macroeconomic indicators for Bitcoin, such as the 10-month EMA, M2 money supply, CVDD, Pi Cycle, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons (Full description bellow).
Open Source Sources: Most of the scripts used are sourced from open-source projects that I have modified to meet the specific needs of this script.
Recommended Timeframes: For optimal performance, it is recommended to use this script on timeframes ranging from 1 day to 1 week.
Objective: The primary goal is to provide a probabilistic solution to identify market excesses, whether overbought or oversold points.
## Originality and Purpose
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This script stands out by integrating multiple macroeconomic indicators into a single comprehensive tool. Each indicator is carefully selected and customized to provide insights into different aspects of the Bitcoin market. By combining these indicators, the script offers a holistic view of market conditions, helping traders identify potential tops and bottoms with greater accuracy. This is the first version of the script, and additional macroeconomic indicators will be added in the future based on user feedback and other inputs.
## How It Works
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The script works by plotting each macroeconomic indicator on a single chart, allowing users to visualize and interpret the data easily. Here’s a detailed look at how each indicator contributes to the analysis:
EMA 10 Monthly: Uses an exponential moving average over 10 monthly periods to signal bullish and bearish trends. This indicator helps identify long-term trends in the Bitcoin market by smoothing out price fluctuations to reveal the underlying trend direction.Moving Averages w/ 18 day/week/month.
Credit to @ryanman0
M2 Money Supply: Analyzes the evolution of global money supply, indicating market liquidity conditions. This indicator tracks the changes in the total amount of money available in the economy, which can impact Bitcoin’s value as a hedge against inflation or economic instability.
Credit to @dylanleclair
CVDD (Cumulative Value Days Destroyed): An indicator based on the cumulative value of days destroyed, useful for identifying market turning points. This metric helps assess the Bitcoin market’s health by evaluating the age and value of coins that are moved, indicating potential shifts in market sentiment.
Credit to @Da_Prof
Pi Cycle: Uses simple and exponential moving averages to detect potential sell points. This indicator aims to identify cyclical peaks in Bitcoin’s price, providing signals for potential market tops.
Credit to @NoCreditsLeft
NUPL (Net Unrealized Profit/Loss): Measures investors’ unrealized profit or loss to signal extreme market levels. This indicator shows the net profit or loss of Bitcoin holders as a percentage of the market cap, helping to identify periods of significant market optimism or pessimism.
Credit to @Da_Prof
PUELL Multiple: Assesses mining profitability relative to historical averages to indicate buying or selling opportunities. This indicator compares the daily issuance value of Bitcoin to its yearly average, providing insights into when the market is overbought or oversold based on miner behavior.
Credit to @Da_Prof
MRVR Z-Scores: Compares market value to realized value to identify overbought or oversold conditions. This metric helps gauge the overall market sentiment by comparing Bitcoin’s market value to its realized value, identifying potential reversal points.
Credit to @Pinnacle_Investor
Hash Ribbons: Uses hash rate variations to signal buying opportunities based on miner capitulation and recovery. This indicator tracks the health of the Bitcoin network by analyzing hash rate trends, helping to identify periods of miner capitulation and subsequent recoveries as potential buying opportunities.
Credit to @ROBO_Trading
## Indicator Visualization and Interpretation
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For each horizontal line representing an indicator, a legend is displayed on the right side of the chart. If the conditions are positive for an indicator, it will turn green, indicating the end of a bearish trend. Conversely, if the conditions are negative, the indicator will turn red, signaling the end of a bullish trend.
The background color of the chart changes based on the average of green or red indicators. This parameter is configurable, allowing adjustment of the threshold at which the background color changes, providing a clear visual indication of overall market conditions.
## Script Parameters
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The script includes several configurable parameters to customize the display and behavior of the indicators:
Color Style:
Normal: Default colors.
Modern: Modern color style.
Monochrome: Monochrome style.
User: User-customized colors.
Custom color settings for up trends (Up Trend Color), down trends (Down Trend Color), and NaN (NaN Color)
Background Color Thresholds:
Thresholds: Settings to define the thresholds for background color change.
Low/High Red Threshold: Low and high thresholds for bearish trends.
Low/High Green Threshold: Low and high thresholds for bullish trends.
Indicator Display:
Options to show or hide specific indicators such as EMA 10 Monthly, CVDD, Pi Cycle, M2 Money, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons.
Specific Indicator Settings:
EMA 10 Monthly: Options to customize the period for the exponential moving average calculation.
M2 Money: Aggregation of global money supply data.
CVDD: Adjustments for value normalization.
Pi Cycle: Settings for simple and exponential moving averages.
NUPL: Thresholds for unrealized profit/loss values.
PUELL: Adjustments for mining profitability multiples.
MRVR Z-Scores: Settings for overbought/oversold values.
Hash Ribbons: Options for hash rate moving averages and capitulation/recovery signals.
## Conclusion
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The “Bitcoin Macro Trend Map” by Ox_kali is a tool designed to analyze the Bitcoin market. By combining several macroeconomic indicators, this script helps identify market peaks and troughs. It is recommended to use it on timeframes from 1 day to 1 week for optimal trend analysis. The scripts used are sourced from open-source projects, modified to suit the specific needs of this analysis.
## Notes
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This is the first version of the script and it is still in development. More indicators will likely be added in the future. Feedback and comments are welcome to improve this tool.
## Disclaimer:
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Please note that the Open Interest liquidation map is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
Wyckoff Phases OscillatorThe "Wyckoff Phases Oscillator" is a script designed for the TradingView platform. It's an indicator that provides traders with an oscillator-based visual representation of the Wyckoff Market Cycle. The oscillator doesn't overlay the price chart but instead appears in a separate panel beneath it.
How it works:
The script operates based on two input parameters: length and timeFrame. The length parameter, set by default to 21, determines the period used for various calculations within the script. On the other hand, timeFrame, set by default to "1", specifies the timeframe for which the script will gather and analyze data.
The script requests security information such as closing prices (higherClose), volume (higherVolume), highest prices (higherHigh), and lowest prices (higherLow) from the ticker symbol (syminfo.tickerid) within the defined timeframe.
Two exponential moving averages (ema1 and ema2) are calculated based on the closing prices, with lengths of 5 and 9 respectively.
A Rate of Change (ROC) is calculated based on the closing prices and the defined length.
An average volume (avgVolume) is calculated using a simple moving average (SMA) based on the volume and the defined length.
The script defines conditions for institutional buying and selling.
Institutional buying is determined when the closing price is greater than the lowest price and the volume is greater than the average volume.
Institutional selling is determined when the closing price is less than the highest price and the volume is greater than the average volume.
The script also defines conditions for the four phases of the Wyckoff Market Cycle: Accumulation, Markup, Distribution, and Markdown. Each phase has specific conditions based on the closing prices, EMA values, ROC, and institutional buying or selling conditions.
The script then assigns oscillator values based on the Wyckoff phase:
Accumulation is assigned a value of 1
Markup is assigned a value of 2
Distribution is assigned a value of 3
Markdown is assigned a value of 4
These oscillator values are plotted as colored circles, with different colors representing different phases. The color values are specified in RGB format.
Finally, the script plots horizontal lines as references for each of the four phases using the hline function. These lines are labeled and color-coded to match the corresponding oscillator circles. The lines have a linewidth of 1 and are solid in style.
If the oscillator moves from level 1 (Accumulation) to level 2 (Markup), this could indicate a potential bullish trend, as the market moves from a phase of accumulation to a phase of increasing prices.
Conversely, if the oscillator moves from level 3 (Distribution) to level 4 (Markdown), this could signal a potential bearish trend, signaling that the market has moved from a phase of distribution to a phase of declining prices.
While the Wyckoff Phases Oscillator can provide valuable insights on its own, it can also be used in conjunction with other technical analysis tools and indicators. For example, you might use it alongside a volume indicator to confirm signals, or with support and resistance levels to identify potential entry and exit points.
Retrograde Motion - Future Projections: [Blueprint_So9]█ Retrograde Motion with Future Projections
Overview
This indicator visualizes planetary retrograde motion both historically and into the future across any timeframe up to 500 bars. Whether you’re reviewing past retrograde cycles or anticipating upcoming ones, this tool provides a clear and customizable view for analysis.
What is Retrograde?
Retrograde motion occurs when a planet appears to reverse direction from Earth’s perspective. This optical illusion, caused by relative planetary orbits, has long been studied for its potential timing relevance in financial and psychological cycles. Retrogrades are often associated with review, reversal, or disruption phases.
🔹 Key Features
Historical and Future Projection
Track retrograde cycles both in hindsight and into upcoming dates, allowing you to draw potential zones of interest before they arrive.
Split-Half Retrograde Visualization
Each retrograde period is divided into two halves, clearly highlighting the 50% midpoint. Users can view either the full retrograde duration or focus on each half separately for more granular analysis.
Multi-Timeframe Compatibility
Built to function seamlessly across all timeframes.
Planet Selection
Choose which planetary retrograde cycle to display.
Custom Visual Options
Toggle between full retrograde overlays or half-cycle shading. Background color transparency can be adjusted.
Original Logic: Future Projection Integration
This tool is one of the first to implement forward-looking retrograde cycle projections with midpoint segmentation.
This indicator uses planetary data from the Astrolib library by @BarefootJoey
MastersCycleSignal(Mastersinnifty)Overview
MastersCycleSignal is a high-precision market timing and projection indicator for trend-following and swing traders.
It combines an adaptive cycle detection algorithm, forward-looking sine wave projections, dynamic momentum confirmation, and Gann Square of 9-based geometric targets into a complete structured trading framework.
The script continuously analyzes price oscillations to detect dominant cycles, projects expected price behavior with future-facing sine approximations, and generates buy/sell signals once confirmed by adaptive momentum filtering.
Upon confirmation, it calculates mathematically consistent Gann-based target levels and risk-managed stop-loss suggestions.
Users also benefit from auto-extending targets as price action unfolds — helping traders anticipate rather than react to market shifts.
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Uniqueness
MastersCycleSignal stands apart through a unique fusion of techniques:
- Dynamic Cycle Detection
- Detects dominant cycles using a cosine correlation maximization method between detrended price (close minus SMA) and theoretical cosine curves, dynamically recalibrated across a sliding window.
- Sine Wave Future Projection
- Smooths and projects future price paths by approximating a forward sine wave based on the real-time detected dominant cycle.
- Adaptive Momentum Filtering
- Volatility is scaled by divergence between normalized returns and a 5-period EMA, further adjusted by an RSI(2) factor.
- This makes buy/sell signal confirmation robust against noise and false breakouts.
- Gann-Based Target Computation
- Uses a square-root transformation of price, incremented by selectable Gann Square of 9 degrees, for calculating progressive and dynamically expanding price targets.
- Auto-Extending Targets
- As price achieves a projected target, the system automatically draws subsequent new targets based on the prior target differential — providing continuous guidance in trending conditions.
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Usefulness
MastersCycleSignal is built to help traders:
- Identify early trend reversals through cycle shifts.
- Forecast probable price paths in advance.
- Plan systematic target and stop-loss zones with geometric accuracy.
- Reduce guesswork in trend-following and swing trading.
- Maintain structured discipline across intraday, swing, and positional strategies.
It works seamlessly across stocks, indices, forex, commodities, and crypto markets — on any timeframe.
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How to Use
- Attach the indicator to your desired chart.
- When a Buy Signal or Sell Signal appears (green or red markers):
- Use the attached stop-loss labels to manage risk.
- Monitor the automatically plotted target lines for partial exits or full profits.
- The orange projected sine wave illustrates the expected future market path.
- Customization Options:
- Cycle Detection Length — adjust to fine-tune cycle sensitivity.
- Projection Length — modify the forward distance of sine wave forecast.
- Gann Square of 9 Degrees — personalize target increments.
- Toggle Signals and Target visibility as needed.
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Disclaimer
- MastersCycleSignal uses no future data or lookahead bias.
- All projections are based on geometric extrapolations from historical price action — not guaranteed predictions.
- Trading involves risks, and historical cycle behavior may differ in future conditions.
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
Revolution SMA-EMA DivergenceThis is an MACD inspired indicator and it analyzes the difference between the SMA and EMA using the same time period. Unlike the MACD, it can give you a better understanding of the overall trend. Values above 0 is bullish and below 0 bearish. It consists of two cycles: Black histogram - the long-term cycle and orange histogram - the short-term cycle, as well as timing signal (red line).
Bitcoin Halving Rainbow + S2F Model PriceOverview
The rainbow price line:
This script creates a colorful view of Bitcoin's price action, where different colors indicate the time until the next halving date. The color scale in the top right highlights what each main color group represents in terms of days until the next halving. Using historical data, the simple indication of days until the next halving has somewhat accurately predicted potential bottoms and tops of market cycles. Comparing current colors to previous cycles provides a rough view of where BTC is in its current cycle and what to expect going forward until the next halving date.
In addition to the colored price action, I have incorporated the stock-to-flow model price for Bitcoin.
The stock-to-flow (S2F) model price:
The stock-to-flow ratio is a calculation that aims to estimate how many years are required to produce the current stock of an asset, based on the current production rate. When applied to Bitcoin, we simply divide the total amount of bitcoins in circulation by the amount of bitcoins mined in a certain timeframe. Once we have this value, we can calculate a model price based on the stock-to-flow ratio. This S2F model price uses a 463-day moving average. Preston Pysh came up with this number as he believed Bitcoin cycles happen in three phases: bull run, correction, and a reversion to the mean. He estimated there are about 200,000 blocks per cycle, three phases per cycle, and ~144 blocks per day. Dividing all three gets us 463. I have removed 1,000,000 coins from this calculation to account for Satoshi's coins.
The process I took to plot this model price (credit to PlanB for originally creating this calculation):
-Declare constant variables for the halving period, starting block reward, and the number of coins Satoshi owns.
-Fetch the block index by using the request.security() function.
-Determine the number of halvings that have occurred by dividing the block index by the halving period.
-Calculate the current block reward by multiplying the initial block reward by 0.5 raised to the power of the number of halvings.
-Calculate the number of blocks mined per period (day or week) and derive the stock (total bitcoins in circulation minus Satoshi's coins) and flow (annual block rewards) from it.
-Calculate the S2F ratio by dividing the stock by the flow.
-Calculate the S2F model price by applying a mathematical formula (ModelPrice = exp(-1.84) * S2F to the power of 3.36) along with a 463-day moving average.
** Please note, due to the use of the 463-day MA, the first ~400 days of the S2F model price is not entirely accurate.
In addition to the above, I have added vertical lines on each halving date, along with labels that have a tooltip if you hover over them, which will show more information about that particular halving.
Important tips:
-This script has been designed to work on the 1-Day timeframe but can also work on the 1-Week timeframe. Any other timeframe will not accurately plot all the information due to the way I have developed the script.
-This script is best used on the ticker I have posted this on, "INDEX:BTCUSD". It can also work on "BLX" or "BITSTAMP:BTCUSD".
-Hide candles when using the script to just show the halving rainbow (hover over the symbol name in the top left and press the eye icon).
-Right-click the price scale and select "Scale price chart only" to get a better view of the plots.
-Right-click the price scale and select "Logarithmic."
-I will update the script as time goes on to show future halvings along with adjusting the next halving date as we get closer (if it changes).
Settings Menu:
Tooltips are included explaining what the settings do, but here's a quick summary:
-'Show Vertical Halving Lines?': Default is true. This allows the user to remove the vertical lines shown on each halving date.
-'Show Halving Labels?': Default is true. This allows the user to remove the info labels shown on each halving date.
-'Halving Line and Label Color': Default is white. This allows the user to change the color of the halving lines and labels to better fit their chart layout.
-'Show Stock to Flow Model Price?': Default is true. This allows the user to remove the S2F model price.
-'Stock to Flow Model Price Color': Default is white. This allows the user to change the color of the S2F model price to better fit their chart layout.
-'Draw Color Table?': Default is true. This allows the user to remove the color table in the top right of the chart.
-'Distance rainbow is away from actual price action': Default is 0 (Plots over candles). This allows the user to adjust where the halving rainbow is plotted if they would like to also see candles on the chart. (Use any value under 0.9)
Feel free to message me or comment on the post with any questions or issues!
Much more to come!
Thanks for reading, enjoy!
Triangulation : Statistically Approved ReversalsA lot of calculation, but a simple and effective result displayed on the chart.
It automatically identifies a very favorable period for a price reversal, by analyzing the daily and intraday price action statistics from the maximum of the most recent bars from the historical data. No repainting. Alerts can be set.
The statistical study is done in real time for each instrument. The probabilities therefore vary over time and adapt to the latest information collected by the indicator.
The time range of the data study can be changed by simply changing the UT :
- 30m = 3.5 last months feed statistics
- 15m = 52 last days feed statistics
- 5m = 17 last days feed statistics (recommanded)
HOW TO USE
This indicator informs when we are in a time period strongly favorable to reversal.
==> Crossing probabilities of different kinds, in price and in time => Triangulation of top and bottom !
HOW It WORK :
fractal statistics on high and low formation.
hour's probabilities of making the high/low of the day are crossed with day's probabilities of making the high/low of the week.
First for the day, we study:
- value of the probability compared to the average probabilities
- value of the coefficient between the high probability and the low probability
which we then refine for the hour, with the same calculation.
Result: bright color for a day + hour with high probability, weak color if the probability is low but remains the only possible bias. Between these two possibilities, intermediate colors are possible - just like looking for shorts if the day is bullish, if it is a high probability hour!
This color is displayed in the background, only if we are forming the high of the day for tops, and the low of the day for bottoms - detected with a stochastic.
All probabilities are studied in real time for the current asset.
We will call this signal "killstats", for "killzones statistics"
fractal statistics on the probability of closure under specific predefined levels according to 36 cycles.
the probabilities of several cycles are studied, for example:
NY session versus London and Asian sessions, London session compared to its opening, NY session compared to its opening, "algorithmic cycles" ( 1h30), Opening of NY compared to its intersection with London..
Each cycle producing a probability of closing with respect to the opening price of each period. The periods are : (Etc/UTC)
15-18h / 15-16h / 9-13h / 14-17h / 18-22h / 10-12h / 9-10h30 / 10h30-12h / 12-13h30 / 13h30-15h / 15h-16h30 / 16h30-18h
The cycles can be superimposed, which allows to support or attenuate a signal for the key periods of the day: 9am-12pm, and 3pm-6pm. The period of the day covered by the study of cycles is 9h-22h.
Result : ==> a straight line with a half bell. Colors = almost transparent for 53% probability (low), and very intense for a high probability (75%). The line displayed corresponds to the opening price, which we are supposed to close within the time limit - before the end of the period, where the line stops.
If the price goes in the opposite direction to the one predicted by the statistics, then a background connects the price to the close level to be respected.
if direction and close is respected, nothing is displayed : there is no opportunity, no divergence between statistics and actual price moves.
By unchecking the "light mode", you can see each close level displayed on the chart, with the corresponding probability and the number of times the cycle was detected. The color varies from intense for a high probability (75%), to light for a low probability (53%)
We will call this signal "cyclic anomalies"
By default, as shown in the indicator presentation image, the "intersection only" option is checked: only the intersection between 1) killstats and 2) cyclic anomalies is displayed. (filter +-30% of killstats signals)
MORE INFORMATIONS
/!\ : during a backtest, it is necessary to refresh the studied data to benefit from the real time signals, and for that you have to use the replay mode. if "Backtesting informations?"is checked, labels are displayed on the graph to warn of the % distortion of the signals. I recommend using the replay mode every 250 candles, and every 1000 candles for premium accounts, to have real signals.
- Alerts can be set for killzone, or intersections ( As in presentation picture)
- The ideal use is in m5. It can trigger several times a day, sometimes in opposite directions, and sometimes not trigger for several days.
- Premium account have 20k candles data, and not 5k => signals may vary depending on your tradingview subscription.
Ehlers Adaptive Relative Strength Index (RSI) [Loxx]Ehlers Adaptive Relative Strength Index (RSI) is an implementation of RSI using Ehlers Autocorrelation Periodogram Algorithm to derive the length input for RSI. Other implementations of Ehers Adaptive RSI rely on the inferior Hilbert Transformer derive the dominant cycle.
In his book "Cycle Analytics for Traders Advanced Technical Trading Concepts", John F. Ehlers describes an implementation for Adaptive Relative Strength Index in order to solve for varying length inputs into the classic RSI equation.
What is an adaptive cycle, and what is the Autocorrelation Periodogram Algorithm?
From his Ehlers' book mentioned above, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average (KAMA) and Tushar Chande’s variable index dynamic average (VIDYA) adapt to changes in volatility. By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic, relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator.This look-back period is commonly a fixed value. However, since the measured cycle period is changing, as we have seen in previous chapters, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the autocorrelation periodogram algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is Adaptive RSI?
From his Ehlers' book mentioned above, page 137:
"The adaptive RSI starts with the computation of the dominant cycle using the autocorrelation periodogram approach. Since the objective is to use only those frequency components passed by the roofing filter, the variable "filt" is used as a data input rather than closing prices. Rather than independently taking the averages of the numerator and denominator, I chose to perform smoothing on the ratio using the SuperSmoother filter. The coefficients for the SuperSmoother filters have previously been computed in the dominant cycle measurement part of the code."
Happy trading!
Quarterly Theory ICT 05 [TradingFinder] Doubling Theory Signals🔵 Introduction
Doubling Theory is an advanced approach to price action and market structure analysis that uniquely combines time-based analysis with key Smart Money concepts such as SMT (Smart Money Technique), SSMT (Sequential SMT), Liquidity Sweep, and the Quarterly Theory ICT.
By leveraging fractal time structures and precisely identifying liquidity zones, this method aims to reveal institutional activity specifically smart money entry and exit points hidden within price movements.
At its core, the market is divided into two structural phases: Doubling 1 and Doubling 2. Each phase contains four quarters (Q1 through Q4), which follow the logic of the Quarterly Theory: Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal.
These segments are anchored by the True Open, allowing for precise alignment with cyclical market behavior and providing a deeper structural interpretation of price action.
During Doubling 1, a Sequential SMT (SSMT) Divergence typically forms between two correlated assets. This time-structured divergence occurs between two swing points positioned in separate quarters (e.g., Q1 and Q2), where one asset breaks a significant low or high, while the second asset fails to confirm it. This lack of confirmation—especially when aligned with the Manipulation and Accumulation phases—often signals early smart money involvement.
Following this, the highest and lowest price points from Doubling 1 are designated as liquidity zones. As the market transitions into Doubling 2, it commonly returns to these zones in a calculated move known as a Liquidity Sweep—a sharp, engineered spike intended to trigger stop orders and pending positions. This sweep, often orchestrated by institutional players, facilitates entry into large positions with minimal slippage.
Bullish :
Bearish :
🔵 How to Use
Applying Doubling Theory requires a simultaneous understanding of temporal structure and inter-asset behavioral divergence. The method unfolds over two main phases—Doubling 1 and Doubling 2—each divided into four quarters (Q1 to Q4).
The first phase focuses on identifying a Sequential SMT (SSMT) divergence, which forms when two correlated assets (e.g., EURUSD and GBPUSD, or NQ and ES) react differently to key price levels across distinct quarters. For example, one asset may break a previous low while the other maintains structure. This misalignment—especially in Q2, the Manipulation phase—often indicates early smart money accumulation or distribution.
Once this divergence is observed, the extreme highs and lows of Doubling 1 are marked as liquidity zones. In Doubling 2, the market gravitates back toward these zones, executing a Liquidity Sweep.
This move is deliberate—designed to activate clustered stop-loss and pending orders and to exploit pockets of resting liquidity. These sweeps are typically driven by institutional forces looking to absorb liquidity and position themselves ahead of the next major price move.
The key to execution lies in the fact that, during the sweep in Doubling 2, a classic SMT divergence should also appear between the two assets. This indicates a weakening of the previous trend and adds an extra layer of confirmation.
🟣 Bullish Doubling Theory
In the bullish scenario, Doubling 1 begins with a bullish SSMT divergence, where one asset forms a lower low while the other maintains its structure. This divergence signals weakening bearish momentum and possible smart money accumulation. In Doubling 2, the market returns to the previous low and sweeps the liquidity zone—breaking below it on one asset, while the second fails to confirm, forming a bullish SMT divergence.
f this move is followed by a bullish PSP and a clear market structure break (MSB), a long entry is triggered. The stop-loss is placed just below the swept liquidity zone, while the target is set in the premium zone, anticipating a move driven by institutional buyers.
🟣 Bearish Doubling Theory
The bearish scenario follows the same structure in reverse. In Doubling 1, a bearish SSMT divergence occurs when one asset prints a higher high while the other fails to do so. This suggests distribution and weakening buying pressure. Then, in Doubling 2, the market returns to the previous high and executes a liquidity sweep, targeting trapped buyers.
A bearish SMT divergence appears, confirming the move, followed by a bearish PSP on the lower timeframe. A short position is initiated after a confirmed MSB, with the stop-loss placed
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include : Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Labels : Displays dynamic labels (e.g., “Q2”, “Bullish SMT”, “Sweep”) at relevant points.
Show Lines : Draws connection lines between key pivot or divergence points.
Color Settings : Allows customization of colors for bullish and bearish elements (lines, labels, and shapes)
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequenc y:
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
Doubling Theory is a powerful and structured framework within the realm of Smart Money Concepts and ICT methodology, enabling traders to detect high-probability reversal points with precision. By integrating SSMT, SMT, Liquidity Sweeps, and the Quarterly Theory into a unified system, this approach shifts the focus from reactive trading to anticipatory analysis—anchored in time, structure, and liquidity.
What makes Doubling Theory stand out is its logical synergy of time cycles, behavioral divergence, liquidity targeting, and institutional confirmation. In both bullish and bearish scenarios, it provides clearly defined entry and exit strategies, allowing traders to engage the market with confidence, controlled risk, and deeper insight into the mechanics of price manipulation and smart money footprints.
Detrended Rhythm Oscillator (DRO)How to detect the current "market beat" or market cycle?
A common way to capture the current dominant cycle length is to detrend the price and look for common rhythms in the detrended series. A common approach is to use a Detrended Price Oscillator (DPO). This is done in order to identify and isolate short-term cycles.
A basic DPO description can be found here:
www.tradingview.com
Improvements to the standard DPO
The main purpose of the standard DPO is to analyze historical data in order to observe cycle's in a market's movement. DPO can give the technical analyst a better sense of a cycle's typical high/low range as well as its duration. However, you need to manually try to "see" tops and bottoms on the detrended price and measure manually the distance from low-low or high-high in order to derive a possible cycle length.
Therefore, I added the following improvements:
1) Using a DPO to detrend the price
2) Indicate the turns of the detrended price with a ZigZag lines to better see the tops/bottoms
3) Detrend the ZigZag to remove price amplitude between turns to even better see the cyclic turns ("rhythm")
4) Measure the distance from last detrended zigzag pivot (high-high / low-low) and plot the distance in bars above/below the turn
Now, you can clearly see the rhythm of the dataset indicated by the Detrended Rhythm Oscillator including the exact length between the turns. This makes the procedure to "spot" turns and "measure" distance more simple for the trader.
How to use this information
The purpose is to check if there is a common rhythm or beat in the underlying dataset. To check that, look for recurring pattern in the numbers. E.g. if you often see the same measured distance, you can conclude that there is a major dominant cycle in this market. Also watch for harmonic relations between the numbers. So in the example above you see the highlighted cluster of detected length of around 40,80 and 120. There three numbers all have a harmonic relation to 40.
Once you have this cyclic information, you can use this number to optimize or tune technical indicators based on the current dominant cycle length. E.g. set the length parameter of a technical indicator to the detected harmonic length with the DRO indicator.
Example Use-Case
You can use this information to set the input for the following free public open-source script:
Disclaimer
This is not meant to be a technical indicator on its own and the derived cyclic length should not be used to forecast the next turn per se. The indicator should give you an indication of the current market beat or dominant beats which can be use to further optimize other oscillator or trading related settings.
Options & settings
The indicator allows to plot different versions. It allows to plot the original DPO, the DRO with ZigZag lines, the DRO with detrended ZigZag lines and length labels on/off. You can turn on or off these version in the indicator settings. So you can tweak it visually to your own needs.
Gabriel's Global Market CapGabriel's Global Market Cap is a comprehensive financial indicator designed to track and analyze the total market capitalization across multiple asset classes. It incorporates various financial markets, including stocks, bonds, real estate, cryptocurrencies, commodities, derivatives, private equity, insurance, OTC markets, and natural resources, to provide a holistic view of global market dynamics.
This indicator integrates Ehlers' Adaptive Dominant Cycle Detection and a custom VIX formula to adjust market values based on volatility and volume fluctuations, allowing for a more refined understanding of market conditions.
Key Features
✅ Multi-Market Analysis – Tracks 10+ global financial sectors, each represented by a key ETF or index.
✅ Normalization & Readability – Converts market cap values into an easy-to-read format (Millions, Billions, Trillions, Quadrillions).
✅ Volatility & Volume Adjustments – Optional VIX-based smoothing and relative volume adjustment for more dynamic readings.
✅ Ehlers’ Cycle Detection – Utilizes dominant cycle length detection to uncover market rhythms and cyclic behavior.
✅ Risk Thresholds & Background Coloring – Identifies overbought and oversold conditions with cyclic bands and background shading.
✅ Customizable Inputs – Users can toggle different market categories on/off for focused analysis.
✅ Interactive Data Table – Displays real-time values for each asset class in a structured table format.
Market Categories & Data Sources
📈 Global Stock Market – iShares MSCI ACWI ETF (ACWI)
💰 Global Bond Market – Vanguard Total World Bond ETF (BNDW)
🏡 Real Estate Market – iShares Global REIT ETF (REET)
₿ Cryptocurrency Market – Total Crypto Market Cap (CRYPTOCAP:TOTAL)
🌾 Commodities Market – Invesco DB Commodity Index Fund (DBC)
📊 Derivatives Market – CME Group (CME)
🏦 Private Equity & VC – ProShares Global Listed Private Equity ETF (PEX)
🛡️ Insurance Market – SPDR S&P Insurance ETF (KIE)
💹 OTC Markets – OTC Markets Group (OTCM)
⛽ Natural Resources – iShares Global Energy ETF (IXC)
Technical Enhancements
1️⃣ Custom Volatility Index (VIX) Calculation (Work In Progress)
Adjusts asset values based on volatility conditions using Ehlers' Cycle Detection.
Higher VIX reduces market cap, while lower VIX stabilizes it.
2️⃣ Adaptive Market Normalization
Converts absolute market values into a relative strength scale (0-100) for better visual analysis.
Uses historical min/max values to adjust dynamically.
3️⃣ Cyclic Analysis & Overbought/Oversold Levels
Detects hidden market rhythms & time cycles.
Calculates upper and lower risk bands based on dominant cycle length.
Applies background shading for visualizing low or high risk periods.
Customization Options
🔧 Enable/Disable Market Categories – Select which asset classes to track.
📊 Toggle VIX & Volume Smoothing – Adjust how market cap reacts to volatility & volume.
🎨 Cyclic Risk Bands – Highlight overbought/oversold conditions with dynamic background colors.
Visual Elements
📉 Market Cap Trends – Each category is plotted with a unique color.
🌎 Total Global Value (TGV) – A combined index representing all selected markets.
🎨 Background Coloring – Indicates high/low risk periods.
📋 Real-Time Data Table – Displays normalized & raw market cap values in an easy-to-read format.
Practical Applications
📊 Macroeconomic Analysis – Track global liquidity and investment shifts across asset classes.
💹 Volatility & Risk Assessment – Identify high-risk market conditions based on cyclic behavior.
📈 Cross-Market Comparisons – See which sectors are leading or lagging in value growth.
🔍 Crypto & Stock Market Trends – Analyze how traditional and digital assets correlate.
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.
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.
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.
Bitcoin Power Law Clock [LuxAlgo]The Bitcoin Power Law Clock is a unique representation of Bitcoin prices proposed by famous Bitcoin analyst and modeler Giovanni Santostasi.
It displays a clock-like figure with the Bitcoin price and average lines as spirals, as well as the 12, 3, 6, and 9 hour marks as key points in the cycle.
🔶 USAGE
Giovanni Santostasi, Ph.D., is the creator and discoverer of the Bitcoin Power Law Theory. He is passionate about Bitcoin and has 12 years of experience analyzing it and creating price models.
As we can see in the above chart, the tool is super intuitive. It displays a clock-like figure with the current Bitcoin price at 10:20 on a 12-hour scale.
This tool only works on the 1D INDEX:BTCUSD chart. The ticker and timeframe must be exact to ensure proper functionality.
According to the Bitcoin Power Law Theory, the key cycle points are marked at the extremes of the clock: 12, 3, 6, and 9 hours. According to the theory, the current Bitcoin prices are in a frenzied bull market on their way to the top of the cycle.
🔹 Enable/Disable Elements
All of the elements on the clock can be disabled. If you disable them all, only an empty space will remain.
The different charts above show various combinations. Traders can customize the tool to their needs.
🔹 Auto scale
The clock has an auto-scale feature that is enabled by default. Traders can adjust the size of the clock by disabling this feature and setting the size in the settings panel.
The image above shows different configurations of this feature.
🔶 SETTINGS
🔹 Price
Price: Enable/disable price spiral, select color, and enable/disable curved mode
Average: Enable/disable average spiral, select color, and enable/disable curved mode
🔹 Style
Auto scale: Enable/disable automatic scaling or set manual fixed scaling for the spirals
Lines width: Width of each spiral line
Text Size: Select text size for date tags and price scales
Prices: Enable/disable price scales on the x-axis
Handle: Enable/disable clock handle
Halvings: Enable/disable Halvings
Hours: Enable/disable hours and key cycle points
🔹 Time & Price Dashboard
Show Time & Price: Enable/disable time & price dashboard
Location: Dashboard location
Size: Dashboard size
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.
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! 📈
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.
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.
