Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
在腳本中搜尋"Cycle"
Bitcoin as % Global M2 signalThis script provides signal system:
Buy signal: each time the YoY of the Global M2 rises more than 2.5% while the distance between the bitcoin price as a percentage of the Global M2 is below its yearly SMA.
Sell signal: the distance between the bitcoin price as a percentage of the Global M2 and its yearly SMA is > 0.7
This is a very simple system, but it seems to work pretty well to ride the bitcoin price cycle wave.
The parameters are hard coded but they can be easily changed to test different levels for both the buy and sell signals.
ONE RING 8 MA Bands with RaysCycle analysis tool ...
MAs: Eight moving averages (MA1–MA8) with customizable lengths, types (RMA, WMA, EMA, SMA), and offsets
Bands: Upper/lower bands for each MA, calculated based on final_pctX (Percentage mode) or final_ptsX (Points mode), scaled by multiplier
Rays: Forward-projected lines for bands, with customizable start points, styles (Solid, Dashed, Dotted), and lengths (up to 500 bars)
Band Choices
Manual: Uses individual inputs for band offsets
Uniform: Sets all offsets to base_pct (e.g., 0.1%) or base_pts (e.g., 0.1 points)
Linear: Scales linearly (e.g., base_pct * 1, base_pct * 2, base_pct * 3 ..., base_pct * 8)
Exponential: Scales exponentially (e.g., base_pct * 1, base_pct * 2, base_pct * 4, base_pct * 8 ..., base_pct * 128)
ATR-Based: Offsets are derived from the Average True Range (ATR), scaled by a linear factor. Dynamic bands that adapt to market conditions, useful for breakout or mean-reversion strategies. (final_pct1 = base_pct * atr, final_pct2 = base_pct * atr * 2, ..., final_pct8 = base_pct * atr * 8)
Geometric: Offsets follow a geometric progression (e.g., base_pct * r^0, base_pct * r^1, base_pct * r^2, ..., where r is a ratio like 1.5) This is less aggressive than Exponential (which uses powers of 2) and provides a smoother progression.
Example: If base_pct = 0.1, r = 1.5, then final_pct1 = 0.1%, final_pct2 = 0.15%, final_pct3 = 0.225%, ..., final_pct8 ≈ 1.71%
Harmonic: Offsets are based on harmonic flavored ratios. final_pctX = base_pct * X / (9 - X), final_ptsX = base_pts * X / (9 - X) for X = 1 to 8 This creates a harmonic-like progression where offsets increase non-linearly, ensuring MA8 bands are wider than MA1 bands, and avoids duplicating the Linear choice above.
Ex. offsets for base_pct = 0.1: MA1: ±0.0125% (0.1 * 1/8), MA2: ±0.0286% (0.1 * 2/7), MA3: ±0.05% (0.1 * 3/6), MA4: ±0.08% (0.1 * 4/5), MA5: ±0.125% (0.1 * 5/4), MA6: ±0.2% (0.1 * 6/3), MA7: ±0.35% (0.1 * 7/2), MA8: ±0.8% (0.1 * 8/1)
Square Root: Offsets grow with the square root of the band index (e.g., base_pct * sqrt(1), base_pct * sqrt(2), ..., base_pct * sqrt(8)). This creates a gradual widening, less aggressive than Linear or Exponential. Set final_pct1 = base_pct * sqrt(1), final_pct2 = base_pct * sqrt(2), ..., final_pct8 = base_pct * sqrt(8).
Example: If base_pct = 0.1, then final_pct1 = 0.1%, final_pct2 ≈ 0.141%, final_pct3 ≈ 0.173%, ..., final_pct8 ≈ 0.283%.
Fibonacci: Uses Fibonacci ratios (e.g., base_pct * 1, base_pct * 1.618, base_pct * 2.618
Percentage vs. Points Toggle:
In Percentage mode, bands are calculated as ma * (1 ± (final_pct / 100) * multiplier)
In Points mode, bands are calculated as ma ± final_pts * multiplier, where final_pts is in price units.
Threshold Setting for Slope:
Threshold setting for determining when the slope would be significant enough to call it a change in direction. Can check efficiency by setting MA1 to color on slope temporarily
Arrow table: Shows slope direction of 8 MAs using an Up or Down triangle, or shows Flat condition if no triangle.
Price Position Percentile (PPP)
Price Position Percentile (PPP)
A statistical analysis tool that dynamically measures where current price stands within its historical distribution. Unlike traditional oscillators, PPP adapts to market conditions by calculating percentile ranks, creating a self-adjusting framework for identifying extremes.
How It Works
This indicator analyzes the last 200 price bars (customizable) and calculates the percentile rank of the current price within this distribution. For example, if the current price is at the 80th percentile, it means the price is higher than 80% of all prices in the lookback period.
The indicator creates five dynamic zones based on percentile thresholds:
Extremely Low Zone (<5%) : Prices in the lowest 5% of the distribution, indicating potential oversold conditions.
Low Zone (5-25%) : Accumulation zone where prices are historically low but not extreme.
Neutral Zone (25-75%) : Fair value zone representing the middle 50% of the price distribution.
High Zone (75-95%) : Distribution zone where prices are historically high but not extreme.
Extremely High Zone (>95%) : Prices in the highest 5% of the distribution, suggesting potential bubble conditions.
Mathematical Foundation
Unlike fixed-threshold indicators, PPP uses a non-parametric approach:
// Core percentile calculation
percentile = (count_of_prices_below_current / total_prices) * 100
// Threshold calculation using built-in function
p_extremely_low = ta.percentile_linear_interpolation(source, lookback, 5)
p_low = ta.percentile_linear_interpolation(source, lookback, 25)
p_neutral_high = ta.percentile_linear_interpolation(source, lookback, 75)
p_extremely_high = ta.percentile_linear_interpolation(source, lookback, 95)
Key Features
Dynamic Adaptation : All zones adjust automatically as price distribution changes
Statistical Robustness : Works on any timeframe and any market, including highly volatile cryptocurrencies
Visual Clarity : Color-coded zones provide immediate visual context
Non-parametric Analysis : Makes no assumptions about price distribution shape
Historical Context : Shows how zones evolved over time, revealing market regime changes
Practical Applications
PPP provides objective statistical context for price action, helping traders make more informed decisions based on historical price distribution rather than arbitrary levels.
Value Investment : Identify statistically significant low prices for potential entry points
Risk Management : Recognize when prices reach historical extremes for profit taking
Cycle Analysis : Observe how percentile zones expand and contract during different market phases
Market Regime Detection : Identify transitions between accumulation, markup, distribution, and markdown phases
Usage Guidelines
This indicator is particularly effective when:
- Used across multiple timeframes for confirmation
- Combined with volume analysis for validation of extremes
- Applied in conjunction with trend identification tools
- Monitored for divergences between price action and percentile ranking
Timed Reversion Markers (Custom Session Alerts)This script plots vertical histogram markers at specific intraday time points defined by the user. It is designed for traders who follow time-based reversion or breakout setups tied to predictable market behavior at key clock times, such as institutional opening moves, midday reversals, or end-of-day volatility.
Unlike traditional price-action indicators, this tool focuses purely on time-based triggers, a technique often used in time cycle analysis, market internals, and volume-timing strategies.
The indicator includes eight fully customizable time inputs, allowing users to mark any intraday minute with precision using a decimal hour format (for example, 9.55 for 9:55 AM). Each input is automatically converted into hour and minute format, and a visual histogram marker is plotted once per day at that exact time.
Example use cases:
Mark institutional session opens (e.g., 9:30, 10:00, 15:30)
Time-based mean reversion or volatility windows
Backtest recurring time-based reactions
Highlight algorithmic spike zones
The vertical plots serve as non-intrusive, high-contrast visual markers for scalping setups, session analysis, and decision-making checkpoints. All markers are displayed at the top of the chart without interfering with price candles.
[iQ]PRO Master iQWave SystemWelcome to the PRO Master iQWave System, an exclusive, ndicator crafted for TradingView. This cutting-edge tool harnesses sophisticated mathematical models to deliver precise buy and sell signals, empowering traders with a comprehensive view of market dynamics.
Key Features
Advanced Analytical Framework: Seamlessly integrates state-of-the-art techniques in signal processing, statistical analysis, and market profiling to uncover high-probability trading opportunities.
Holistic Market Insight: Combines proprietary methods for data transformation, frequency-based cycle detection, adaptive trend and seasonality extraction, and moment-driven anomaly identification—offering a multi-dimensional approach to price analysis.
Customizable Precision: With a wide range of user inputs, traders can tailor the system to their unique strategies and adapt it to diverse market conditions, ensuring flexibility across asset classes and timeframes.
Intuitive Visual Feedback: Displays critical insights directly on your chart, including adaptive fits, statistical boundaries, market profile levels, and a clear, actionable signal label—making complex analysis accessible at a glance.
Why Choose PRO Master iQWave System?
Designed for experienced traders, this indicator stands out by blending advanced analytics with practical usability. Whether you're identifying reversals, filtering noise, or gauging market structure, the PRO Master iQWave System equips you with a robust, all-in-one solution. Its proprietary algorithms distill intricate market data into actionable signals, helping you stay ahead of the curve.
Elevate Your Trading
Experience the power of next-level technical analysis. The PRO Master iQWave System is more than an indicator—it's a strategic edge, reserved for those ready to unlock its potential. Take your trading to new heights with this exclusive tool, available only by invitation.
ADvM, of MMiQ
MCDX_SignalThe MCDX indicator (Market Cycle Dynamic Index) is a technical indicator developed by Trung Pham. It is a tool used for analyzing the stock market, often utilized to identify big money flow (Big Money) and evaluate the strength of individual stocks or the overall market.
MCDX is known for its distinctive histogram chart with red and green bars. The red bars typically represent the inflow of big money, while the green bars indicate small money flow or outflows.
Pivot Highs/Lows with Bar CountsWhat does the indicator do?
This indicator adds labels to a chart at swing (a.k.a., "pivot") highs and lows. Each label may contain a date, the closing price at the swing, the number of bars since the last swing in the same direction, and the number of bars from the last swing in the opposite direction. A table is also added to the chart that shows the average, min, and max number of bars between swings.
OK, but how do I use it?
Many markets -- especially sideways-moving ones -- commonly cycle between swing highs and lows at regular time intervals. By measuring the number of bars between highs and lows -- both same-sided swings (i.e., H-H and L-L) and opposite-sided swings (i.e., H-L and L-H) -- you can then project the averages of those bar counts from the last high or low swing to make predictions about where the next swing high or low should occur. Note that this indicator does not make the projection for you. You have to determine which swing you want to project from and then use the bar counts from the indicator to draw a line, place a label, etc.
Example: Chart of BTC/USD
The indicator shows pivot highs and lows with bar counts, and it displays a table of stats on those pivots.
If you focus on the center section of the chart, you can see that prices were moving in a sideways channel with very regular highs and lows. This indicator counts the bars between these pivots, and you could have used those counts to predict when the next high or low may have occurred.
The bar counts do not work as well on the more recent section of the chart because there are no regularly time swings.
RSI w/Hann WindowingThis RSI by John Ehlers of "Yet Another" Improved RSI. Taking advantage of the Hann windowing. As seen on PRC and published by John Ehlers, it has a zero mean and appears smoother than the classic RSI. In his own words " I prefer oscillator-type indicators to have a zero mean. We can achieve this simply by multiplying the classic RSI by 2 so it swings from 0 to 2, and then subtract 1 from the product so the indicator swings from -1 to +1." Ehlers goes on to say " Bear in mind 14 may not be the best length to analysis. So, the best length to use for the RSIH indicator is on the order of the dominant cycle period of the data."
This indicator works well with both bullish and bearish divergences. It also works well with oversold and overbought indications. Shown by the Red zone on top (Overbought) and the green zone on the bottom(oversold). Each which have an adjustable buffer zone. You may need to adjust the length of the RSIH to suit your asset. There are also multiply signal line's to choose from. Also take note of when the RSIH crosses up or down on the signal line.
None of this is financial advice.
MVRVZ - MVRVZ Top and Bottom Indicator for BTC [Logue]Market Value-Realized Value Z-score (MVRVZ) - The MVRV-Z score measures the value of the bitcoin network by comparing the market cap to the realized value and dividing by the standard deviation of the market cap (market cap – realized cap) / std(market cap)). When the market value is significantly higher than the realized value, the bitcoin network is "overvalued". Very high values have signaled cycle tops in the past and low values have signaled bottoms. For tops, the default trigger value is above 6.85. For bottoms, the indicator is triggered when the MVRVZ is below -0.25 (default).
NUPL - Net Unrealized Profit-Loss BTC Tops/Bottoms [Logue]Net Unrealized Profit Loss (NUPL) - The NUPL measures the profit state of the bitcoin network to determine if past transfers of BTC are currently in an unrealized profit or loss state.
Values above zero indicate that the network is in overall profit, while values below zero indicate the network is in overall loss. Highly positive NUPL values indicate overvaluation of the BTC network and relatively negative NUPL values indicate an undervaluation of the BTC network.
For tops: The default setting for tops is based on decreasing "strength" of BTC tops. A decreasing linear function (trigger = slope * time + intercept) was fit to past cycle tops for this indicator and is used as the default to signal macro tops. The user can change the slope and intercept of the line by changing the slope and/or intercept factor. The user also has the option to indicate tops based on a horizontal line via a settings selection. This horizontal line default value is 73. This indicator is triggered for a top when the NUPL is above the trigger value.
For bottoms: Bottoms are displayed based on a horizontal line with a default setting of -13. The indicator is triggered for a bottom when the NUPL is below the bottom trigger value.
LMACD - Logarithmic MACD Weekly BTC Index [Logue]Logarithmic Moving Average Convergence Divergence (LMACD) Weekly Indicator - The LMACD is a momentum indicator that measures the strength of a trend using 12-period and 26-period moving averages. The weekly LMACD for this indicator is calculated by determining the difference between the log (base 10) of the 12-week and 26-week exponential moving averages. Larger positive numbers indicate a larger positive momentum.
For tops: The default setting for tops is based on decreasing "strength" of BTC tops. A decreasing linear function (trigger = slope * time + intercept) was fit to past cycle tops for this indicator and is used as the default to signal macro tops. The user can change the slope and intercept of the line by changing the slope and/or intercept factor. The user also has the option to indicate tops based on a horizontal line via a settings selection. This line default value is 0.125. This indicator is triggered for a top when the LMACD is above the trigger value.
For bottoms: Bottoms are displayed based on a horizontal line with a default setting of -0.07. The indicator is triggered for a bottom when the LMACD is below the bottom trigger value.
MCG - Meme Coin Gains [Logue]Meme Coin Gains. Investor preference for meme coin trading may signal irrational exuberance in the crypto market. If a large spike in meme coin gains is observed, a top may be near. Therefore, the gains of the most popular meme coins (DOGE, SHIB, SATS, ORDI, BONK, PEPE, and FLOKI) were averaged together in this indicator to help indicate potential mania phases, which may signal nearing of a top. Two simple moving averages of the meme coin gains are used to smooth the data and help visualize changes in trend. In back testing, I found a 10-day "fast" sma and a 20-day "slow" sma of the meme coin gains works well to signal tops and bottoms when extreme values of this indicator are reached.
Meme coins were not traded heavily prior to 2020. Therefore, there is only one cycle to test at the time of initial publication. Also, the meme coin space moves fast, so more meme coins may need to be added later. Also, once a meme coin has finished its mania phase where everyone and their mother has heard of it, it doesn't seem to run again (at least with the data up until time of publication). Therefore, the value of this indicator may not be great unless it is updated frequently.
The two moving averages are plotted. For the indicator, top and bottom "slow" sma trigger lines are plotted. The sma trigger line and the periods (daily) of the moving averages can be modified to your own preferences. The "slow" sma going above or below the trigger lines will print a different background color. Plot on a linear scale if you want to view this as similar to an RSI-type indicator. Plot on a log scale if you want to view as similar to a stochastic RSI.
Use this indicator at your own risk. I make no claims as to its accuracy in forecasting future trend changes of Bitcoin or the crypto market.
MCV - Meme Coin Volume [Logue]Meme Coin Volume. Investor preference for meme coin trading may signal irrational exuberance in the crypto market. If a large spike in meme coin volume is observed, a top may be near. Therefore, the volume of the most popular meme coins was added together in this indicator to help indicate potential mania phases, which may signal nearing of a top. A simple moving average of the meme coin volume also helps visualize the trend while reducing the noise. In back testing, I found a 10-day sma of the meme coin volume works well.
Meme coins were not traded heavily prior to 2020. Therefore, there is only one cycle to test at the time of initial publication. Also, the meme coin space moves fast, so more meme coins may need to be added later.
The total volume is plotted along with a moving average of the volume. For the indicator, you are able to change the raw volume trigger line, the sma trigger line, and the period (daily) of the sma to your own preferences. The raw volume or sma going above their respective trigger lines will print a different background color.
Use this indicator at your own risk. I make no claims as to its accuracy in forecasting future trend changes of Bitcoin or the crypto market.
AMDX-XAMDGuided by ICT tutoring and also inspired by the teaching of
Daye', I create this versatile "AMDX" indicator.
A = Accumulation
M = Manipulation
D = Distribution
X = Continuation Or Reversal
This indicator shows a different way of viewing all the Timeframes by dividing them into Quarters, in this context the Trading sessions are divided into a 90m cycle, dividing each time range into Q1-Q2-Q3-Q4, in this way you have a clear vision of what the price is likely to do
True Open Times =
Opening Week - Monday at 6pm
Opening Day - 00:00
Asia -7.30pm
London -01.30
New York -07:30
PM -1.30pm
Session Times =
Q1 Asia 18:00-00:00
Q2 London 00:00-06:00
Q3 New York 06:00-12:00
Q4 PM 12:00-18:00
The user has the possibility to:
- Choose whether to display AMDX W
- Choose whether to display AMDX D
- Choose whether to display AMDX Session
- Choose to show the text in the Box
- Choose to show open levels
The indicator should be used as ICT and 'Daye' show in their concepts.
The indicator divides everything into Quarter ranges and classifies them into Q1-Q2-Q3-Q4 (as in the example above), and each Quarter has its own specific function, and can be used in this way:
If Q1 does an expansion it is likely that Q2 will do a consolidation, Q3 will do a Manipulation and Q4 will do a reversal returning to Q1
-If we are Bullish we buy under Open Session
-If we are Bearish we buy above open session
As in the example below:
If something is not clear, comment below and I will reply as soon as possible.
Recession Indicator (Unemployment Rate)Unemployment rate
percentage of unemployed individuals in an economy among individuals currently in the labour force. It is calcuated as Unemployed IndividualsTotal Labour Force × 100 where unemployed individuals are those who are currently not working but are actively seeking work.
The unemployment rate is one of the primary economic indicators used to measure the health of an economy. It tends to fluctuate with the business cycle, increasing during recessions and decreasing during expansions. It is among the indicators most commonly watched by policy makers, investors, and the general public.
Policy makers and central banks consider how much the unemployment rate has increased during a particular recession to gauge the recession’s impact on the economy and to decide how to tailor fiscal and monetary policies to mitigate its adverse effects. In addition, central banks carefully try to predict the future trend of the unemployment rate to devise long-term strategies to lower it.
This indicator is a representation of yearly rate of change of Unemployment rate. Historically (not always) when ROC(Yearly) of Unemployment rate crossover zero line was a signal of recession or economic contraction.
DR/IDR of Omega by TRSTNThis is an EXPERIMENTAL Script by @TRSTNGLRD derived from the coding of @IAmMas7er's "DR/IDR" Indicator that adds a total of 11 additional DR / IDR Ranges on both lower and higher timeframes.
This script is no-longer being worked on, so I have made it public.
Background:
This Script utilizes the Fibonacci-Doubling Sequence between the range of 18:30pm and 16:55pm NY-Time. Each Cycle is grouped into the following:
Omega/2, Omega/4, Omega/8, and Omega/16
The Mas7er's three original sessions are: Omega/4v1, Omega/4v2, and Omega/8v1
These three Sessions above take rule over all others. If you are looking to back-test this version of the script, please use the Experimental ranges as confirmation for the three above.
Important Notes:
- Please only select Sessions with their respected groups (All of Omega/4, All of Omega/16, etc...) rather than selecting all of them at once.
If you select all of them at once, the ranges will not be correct and cut each other off.
The only exceptions to this rule are the Mas7er's original ranges above.
- If you wish to have multiple groups of Ranges together, please add a second indicator to your chart.
- Omega/16v1 and Omega/16v6 are known to have a high-probability of a Judas Swing (takes out both sides of the range) - Be Cautious!
- Omega/2v1 is a very large DR / IDR range. I am working on shrinking it in size, but have more experimenting to do with different ranges.
- I do not use the experimental ranges with the IDR , only the DR . I have not been able to define probabilities fully yet, but the levels are respected nonetheless.
This script is not supposed to work EXACTLY like the Mas7er's, rather, generally instead.
Please comment and leave your opinion below about which ranges work the best and how you may utilize them.
Thank you!
CyCLOPECyCLOPE - CYCLe OPErator
by Antonio Pace 2022
All right reserved
The script uses time series decomposition tecniques for decompose the price signal into 10 harmonics waves of increasing
period and wavelength, the sum of which is the signal itself, to eliminate background noise and show a cleaner signal.
Also divides the high frequencies (secondary, short period trend) from the primary trend (long period trend),
which is composed of low frequencies, and show both separately.
Find highs and lows and indicate possible trend reversals, and favorable entry or exit points.
T0 is the basic harmonic with period 8 Time Unit (TU) of the current timeframe.
T1 has a double period compared to T0, T2 has a double period compared to T1 and so on.
The script composes the primary trend by adding the First 5 harmonics of the longer period (T7 + T6 + T5 + T4 + T3), therefore of low frequency.
This eliminates the noise (short-term retracements) from the main trend.
Similarly, it reconstructs the secondary trend (a possible retracement of a primary trend) by adding the two harmonics with the high frequency (T2 + T1)
T0 the harmonic with highest frequency it is too noisy for this TimeFrame and is left out.
The script then identifies the maximums and minimums of the primary trend and the secondary trend, indicating possible trend reversal points or favorable entry points in a continuing trend.
The script finds the maxima and minima of the reconstructed signal so as to have as little noise as possible.
The reconstructed signal is shown on the screen. The blue line for the long term trend and the orange line for the short time trend.
If the cloud changes from red to green, it means that a local minimum has formed on the main tred, we are in the presence of a possible bullish inversion.
If the cloud turns from green to red then a local high has formed, a bearish trend reversal may have started.
The line on the cloud represents the subtrend instead.
If the line goes from green to red it has formed a maximum and if it goes from red to green it has formed a minimum.
For instance:
If the line is red and the cloud becomes red we are in the presence of a possible inversion and the beginning of a bearish trend.
I exit the long position and into the short position.
Similarly If the cloud is red and the line is green it means that I have a rising subtrend in a bearish dominate trend.
If the line turns red I have a bearish entry point.
If the cloud turns green the low of the subtrend has also become a low of the main trend, a bullish trend has started.
The script is designed to run on a daily timeframe, but it should work on any timeframe provided there are enough Time Units (1024 TU) in the past.
Minimum usable timeframe: 8h, at shorter timeframes the signal becomes indistinguishable from noise.
when the main trend and the sub-trend have the same magnitude, that is, the line and the cloud have the same size, but different color the noise prevails,
there is no valid information.
Wait for them to become the same color to enter the market again.
Once you have chosen the timeframe and asset on which to operate, select the harmonics to compose the main trend and those to compose the secondary trend
so that the indicator matches as much as possible with the real results.
Looking for the right balance between signal and noise and then continuing to use these settings, for this specific timeframe.
if you don't want have both Long Term and Short Trend trend on screen you can hide the short therm and add is harmonic to LongTime trend
in these case gren cloud indicate long and red color indicate short.
VERY IMPORTANT!
THE LONG TERM TREND DOMINATE OVER THE SHORT TERM TREND EXCEPT WHERE BOTH HAVE SAME MAGNITUDE.
The short term trend describe price retracemet over long term trend,
enter to market only when both have the same color.
Use short therm trend to find maximum or minimum of retracement.
FIND AND USE THE MINIMUM NUMBER OF WAVE PER TREND, THE RISK IS OVER FITTING THE PRICE LINE AND CREATE CONFUSION.
THE SCRIPT WORK BEST FOR DAILY TIMEFRAME AND COME CONFIGURED FOR THIS.
ETH Gravity OscillatorThis indicator is a deviation of a Center of Gravity Oscillator corrected for the diminishing returns of Ethereum.
I've set up this indicator for it to be used on the weekly timeframe . The indicator oscillates between 0 and 10, where 0 indicates oversold conditions and 10 indicates overbought conditions. What is interesting is that it is not particularly ideal for identifying market cycle tops, but generally picks out the most euphoric region in the initial parabolic rally. Good to potentially keep in mind if there is a second bounce to the peak!
The indicator plots in any ETH charts. It paints in all time frames, but Weekly time frame is the correct one to interpret the 'official' read of it.
Made at the request of a kind commenter. If you would like to request different derivations of this script be sure to let me know!
TASC 2025.02 Autocorrelation Indicator█ OVERVIEW
This script implements the Autocorrelation Indicator introduced by John Ehlers in the "Drunkard's Walk: Theory And Measurement By Autocorrelation" article from the February 2025 edition of TASC's Traders' Tips . The indicator calculates the autocorrelation of a price series across several lags to construct a periodogram , which traders can use to identify market cycles, trends, and potential reversal patterns.
█ CONCEPTS
Drunkard's walk
A drunkard's walk , formally known as a random walk , is a type of stochastic process that models the evolution of a system or variable through successive random steps.
In his article, John Ehlers relates this model to market data. He discusses two first- and second-order partial differential equations, modified for discrete (non-continuous) data, that can represent solutions to the discrete random walk problem: the diffusion equation and the wave equation. According to Ehlers, market data takes on a mixture of two "modes" described by these equations. He theorizes that when "diffusion mode" is dominant, trading success is almost a matter of luck, and when "wave mode" is dominant, indicators may have improved performance.
Pink spectrum
John Ehlers explains that many recent academic studies affirm that market data has a pink spectrum , meaning the power spectral density of the data is proportional to the wavelengths it contains, like pink noise . A random walk with a pink spectrum suggests that the states of the random variable are correlated and not independent. In other words, the random variable exhibits long-range dependence with respect to previous states.
Autocorrelation function (ACF)
Autocorrelation measures the correlation of a time series with a delayed copy, or lag , of itself. The autocorrelation function (ACF) is a method that evaluates autocorrelation across a range of lags , which can help to identify patterns, trends, and cycles in stochastic market data. Analysts often use ACF to detect and characterize long-range dependence in a time series.
The Autocorrelation Indicator evaluates the ACF of market prices over a fixed range of lags, expressing the results as a color-coded heatmap representing a dynamic periodogram. Ehlers suggests the information from the periodogram can help traders identify different market behaviors, including:
Cycles : Distinguishable as repeated patterns in the periodogram.
Reversals : Indicated by sharp vertical changes in the periodogram when the indicator uses a short data length .
Trends : Indicated by increasing correlation across lags, starting with the shortest, over time.
█ USAGE
This script calculates the Autocorrelation Indicator on an input "Source" series, smoothed by Ehlers' UltimateSmoother filter, and plots several color-coded lines to represent the periodogram's information. Each line corresponds to an analyzed lag, with the shortest lag's line at the bottom of the pane. Green hues in the line indicate a positive correlation for the lag, red hues indicate a negative correlation (anticorrelation), and orange or yellow hues mean the correlation is near zero.
Because Pine has a limit on the number of plots for a single indicator, this script divides the periodogram display into three distinct ranges that cover different lags. To see the full periodogram, add three instances of this script to the chart and set the "Lag range" input for each to a different value, as demonstrated in the chart above.
With a modest autocorrelation length, such as 20 on a "1D" chart, traders can identify seasonal patterns in the price series, which can help to pinpoint cycles and moderate trends. For instance, on the daily ES1! chart above, the indicator shows repetitive, similar patterns through fall 2023 and winter 2023-2024. The green "triangular" shape rising from the zero lag baseline over different time ranges corresponds to seasonal trends in the data.
To identify turning points in the price series, Ehlers recommends using a short autocorrelation length, such as 2. With this length, users can observe sharp, sudden shifts along the vertical axis, which suggest potential turning points from upward to downward or vice versa.
Vibration BoxFirst Public release of the Vibration Box
WARNING - THESE CYCLES CANNOT PREDICT PERFECT "UP & DOWN" MOTION
There is absolutely no guarantee that these cycles will predict perfect "up & down" motion for the markets
Please be aware that this tool is to be used with a robust risk management system
These cycles are representative of "circle geometry within a square of price & time"
Slowly, I will build up some ideas to go along with this script so that you can learn to apply it to many different markets in many different ways
Those familiar with the work of W.D. Gann should be able to utilize this tool in many different ways
Instructions:
Place the box down with 2 mouse clicks (first is for bottom left corner & second is for top right corner)
NOTE: DUE TO TRADINGVIEW LIMITATIONS
-There is a maximum of 12 divisions for your box/vibration (I will work on increasing this number)
-You MUST choose a coordinate that is within the price action that has already occurred
-You CANNOT initially place the box BEFORE THE FIRST BAR of data
-You CANNOT initially place the box BEYOND THE LAST BAR of data
THEN, ONCE YOU HAVE PLACED THE BOX FOR THE FIRST TIME
YOU CAN MANUALLY ADJUST THE DATES WITHIN THE SETTINGS TO PLACE THE BOX IN ANYWAY YOU WOULD LIKE!
Time Block with Current K-Line TimeThis indicator divides the market into fixed time blocks (daily, three-day, weekly, monthly, and yearly) and displays 1/4, 1/2, and 3/4 dividing lines within each block, indicating key price positions within the block.
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Description:
1. Generally speaking, the duration of a market period is one time block within the corresponding period.
2. Supports display of the current candlestick time, the dividing line for the next block, and a countdown.
3. Multi-time zone support: Shanghai, New York, London, Tokyo, and UTC. Time display automatically adapts to the selected time zone.
4. Time block visualization: Select the time block length based on the observation period and draw dividers at the time block boundaries.
5. Real-time time display: Detailed time of the current candlestick chart (year/month/day, hour:minute, day of the week).
6. Future time prediction: Displays the next time block's start position with a future divider. A countdown function displays the time until the next block, helping to determine the remaining duration of the current trend.
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Use scenarios:
Day trading: Identify trading day boundaries (1-day blocks)
Swing trading: Optimize weekly/monthly time frame transitions (1-week/1-month blocks)
Long-term investment: Observe annual market cycles (1-year blocks)
Cross-time zone trading: Seamlessly switch between major global trading time zones.
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Functions:
- Time block division to observe market cycles
- Draw 1/4, 1/2, and 3/4 dividers to assist in trading decisions
- Current K-line Time Display
- Future Block Divider and Countdown Indicator
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How to Use:
Can be combined with trend lines or other trend-following tools to identify trend-following entry opportunities near the dividing line and follow the main trend.
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本指标将行情划分为固定时间区块（日、三日、周、月、年），并在每个区块内显示1/4、1/2、3/4分割线，标示区块内关键价格位置
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描述：
1. 通常而言，一段行情的持续时间为对应周期下的一个时间区块
2. 支持显示当前K线时间及下一个区块的分割线和倒计时。
3. 多时区支持，支持上海、纽约、伦敦、东京、UTC五大交易时区，自适应所选时区的时间显示
4. 时间区块可视化：根据观测周期选择时间区块长度，在时间区块边界绘制分隔线
5. 实时时间显示：当前K线详细时间（年/月/日 时:分 星期）
6. 未来时间预测，下一个时间区块开始位置显示未来分割线，倒计时功能显示距离下个区块的时间，用于辅助判断当前趋势的剩余持续时间
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使用场景：
日内交易：识别交易日边界（1日区块）
波段交易：把握周/月时间框架转换（1周/1月区块）
长期投资：观察年度市场周期（1年区块）
跨时区交易：无缝切换全球主要交易时区
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功能：
- 时间区块划分，观察行情周期
- 绘制1/4、1/2、3/4分割线，辅助交易判断
- 当前K线时间显示
- 未来区块分割线及倒计时提示
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使用方法：
可结合趋势线或其他趋势跟随工具，在分割线附近寻找顺势进场机会，追随主趋势
CVDD Z-ScoreCumulative Value Days Destroyed (CVDD) - The CVDD was created by Willy Woo and is the ratio of the cumulative value of Coin Days Destroyed in USD and the market age (in days). While this indicator is used to detect bottoms normally, an extension is used to allow detection of BTC tops. When the BTC price goes above the CVDD extension, BTC is generally considered to be overvalued. Because the "strength" of the BTC tops has decreased over the cycles, a logarithmic function for the extension was created by fitting past cycles as log extension = slope * time + intercept. This indicator is triggered for a top when the BTC price is above the CVDD extension. For the bottoms, the CVDD is shifted upwards at a default value of 120%. The slope, intercept, and CVDD bottom shift can all be modified in the script.
Now with the automatic Z-Score calculation for ease of classification of Bitcoin's valuation according to this metric.
Created for TRW.
