FVG Detector Pro
** FVG Detector Pro - Advanced Fair Value Gap Detector**
This indicator automatically identifies Fair Value Gaps (FVG), also known as "Imbalances" or "Liquidity Voids" on your charts with clear and professional visualization.
** Key Features:**
**Automatic detection** of bullish and bearish FVGs
**Colored boxes** with customizable borders for quick identification
**Center line** in dashed style within each FVG
**Automatic deletion** of filled FVGs (can be disabled)
**Adjustable extension**: infinite or defined number of bars
**Visual labels** "FVG ↑" and "FVG ↓" (can be toggled)
**Built-in alerts** for newly detected FVGs
** Fully Customizable Parameters:**
**Bullish FVG:**
- Box color
- Border color
- Center line color
- Border thickness (1-5)
- Center line thickness (1-5)
**Bearish FVG:**
- Box color
- Border color
- Center line color
- Border thickness (1-5)
- Center line thickness (1-5)
**General Options:**
- Show/hide bullish or bearish FVGs
- Infinite extension or fixed number of bars (1-200)
- Automatically delete filled FVGs
- Show/hide labels
** How to Use This Indicator:**
A Fair Value Gap forms when there's a significant price gap between three consecutive candles, creating an untraded zone. These zones often act as price magnets, as the market tends to return and fill them.
- **Bullish FVG (green)**: Potential support zone
- **Bearish FVG (red)**: Potential resistance zone
Perfect for ICT (Inner Circle Trader) trading, Smart Money Concepts (SMC), and market structure analysis.
** Compatible with all timeframes and all markets**: Forex, Crypto, Stocks, Indices, Commodities.
Kitaran
[AMBAGES] X ProtocolTitle: X Protocol
Description: The X Protocol is an institutional-grade framework designed for traders utilizing Smart Money Concepts (SMC) and ICT methodologies. Rather than providing static overlays, this script functions as a logic engine that filters market noise by requiring confluence between time, price, and cross-asset correlation.
The Purpose of this Integration (The Mashup) Traders often struggle with "chart paralysis" when monitoring multiple timeframes. The X Protocol solves this by integrating disparate elements—MTF Fair Value Gaps, Time Cycles, and SMT Divergences—into a single Confluence Score. The script does not simply plot these indicators; it evaluates their relationship. For example, an Entry Model (like a CISD) is only highlighted if it occurs within a specific HTF POI during a designated Macro time window.
Key Methodology & Features
1. The Confluence Dashboard The heart of the system is a dynamic calculation engine that assigns a real-time score (0–10) based on:
Bias Detector: Evaluates market structure by comparing the current swing points against Higher Timeframe (HTF) PD Arrays.
POI Analysis: Tracks price interaction with Monthly, Weekly, and Daily High/Low levels.
Macro Alignment: Validates setups based on time-of-day algorithmic windows (e.g., London Open, AM/PM Silver Bullet windows).
2. Smart Money Technique (SMT) Scanner The script utilizes a multi-symbol comparison (default: ES, NQ, YM) to detect "cracking" correlations.
Logic: It calculates the divergence between the current ticker and two external tickers. A signal is only plotted when a "Swing High/Low" failure occurs at a key liquidity level, preventing the common issue of constant, irrelevant SMT signals.
3. Algorithmic Time Cycles & DWM
DWM Levels: Plots Previous Daily, Weekly, and Monthly levels using precise pivot-time logic rather than standard daily closes.
Time Cycles: Visualizes 90-minute and 270-minute accumulation/distribution cycles to help traders anticipate volatility shifts.
4. Advanced Entry Models The script visualizes two specific institutional models:
CISD (Change in State of Delivery): Defined here as a specific volume-weighted shift following a liquidity sweep.
IFVG (Inverse Fair Value Gap): Identifies gaps that have been reclaimed and "flipped," acting as a support/resistance anchor.
How to Use
Check Bias: Ensure the Dashboard indicates a Bullish or Bearish lean based on HTF structure.
Wait for POI: Monitor for price to reach a DWM level or HTF FVG.
Monitor SMT: Look for the SMT Divergence indicator to confirm institutional accumulation/distribution.
Execution: Look for a CISD or IFVG print when the Confluence Score is 6 or higher.
Credits & Attribution This script utilizes concepts popularized by Inner Circle Trader (ICT). All logic and calculations for the dashboard, confluence scoring, and SMT scanning were custom-coded by .
Disclaimer: This tool is for analytical purposes only. Trading involves significant risk. Past performance does not guarantee future results.
ADIBABA - 4x EMAThis indicator is based on the Exponential Moving Average (EMA) and is designed to help traders identify trend direction, momentum, and price structure with clarity.
The script provides fully customizable EMA length along with an optional Smoothing EMA (SMS), allowing traders to fine-tune the indicator according to their trading style and market conditions.
It is suitable for intraday, swing, and positional traders and works well across multiple asset classes.
How It Works
• The primary EMA follows price movement and defines the trend
• The smoothing EMA reduces market noise and improves signal quality
• Price above EMA indicates a bullish bias
• Price below EMA indicates a bearish bias
This combination helps filter false signals and provides stronger trend confirmation.
CycleForecasterCycleForecaster is a sophisticated multi-oscillator confluence indicator designed to identify market cycles and potential reversal zones through the combination of five powerful technical oscillators. This indicator has been carefully enhanced for TradingView with modern visual aesthetics and additional features.
⚡ Key Features
🎯 Multi-Oscillator Confluence Engine
Combines RSI, Fisher Transform, CCI, MACD, and Stochastic oscillators
Normalizes all oscillators to a unified scale for accurate comparison
Weighted composite calculation for balanced signal generation
🔄 Adaptive Cycle Detection
Automatically identifies cycle peaks and troughs
Tracks and learns from historical cycle lengths
Forecasts expected future cycle turning points
Dynamic percentile-based threshold calculation
📊 Confluence Scoring System
Counts bullish/bearish signals across all oscillators
Configurable confluence threshold (default: 3/5 oscillators must agree)
Filters noise by requiring multi-indicator confirmation
🎨 Premium Visual Design
5 built-in color themes: Neon, Classic, Ocean, Sunset, Matrix
Gradient fills for intuitive overbought/oversold visualization
Momentum histogram for acceleration/deceleration analysis
Professional real-time information panel
📈 How It Works
Oscillator Normalization: Each oscillator is normalized to a -1 to +1 scale, allowing for direct comparison and combination.
Composite Calculation: A weighted average of all normalized oscillators creates a single composite line that represents the overall market cycle position.
Cycle Detection: The indicator identifies peaks and troughs using configurable thresholds, either through automatic percentile calculation or manual settings.
Forecasting: Based on detected cycles, the indicator calculates average cycle length and projects expected future turning points.
Confluence Confirmation: Signal strength is validated by counting how many individual oscillators agree with the overall reading.
GLI Fed Plumbing Regime (v1.0)GLI Regime Index
Global Liquidity Intelligence for Risk Markets
The GLI Regime Index is a macro-liquidity regime engine that classifies the financial system based on where cash is actually flowing inside the Fed–Treasury plumbing.
Markets do not move on narratives.
They move on liquidity .
GLI measures that liquidity in real time by combining four institutional-grade signals:
• Fed Reverse Repo (RRP) – where excess cash is being parked
• 3-Month Treasury Bills – where short-term money prefers to earn yield
• IORB – the Federal Reserve’s policy floor
• SOFR – the true cost of funding in the system
By comparing these flows, GLI identifies which institution is currently in control of money:
Regime What It Means
FED DOMINANT Abundant reserves, liquidity flowing into risk assets
T-BILL DOMINANT Treasury absorbing liquidity, risk tightening
CASH GLUT Excess money trapped at the Fed (RRP high)
FUNDING STRESS Funding markets under pressure (SOFR > IORB)
NEUTRAL Transition state between regimes
Why this matters
Assets like NVDA, BTC, high-beta tech, and growth stocks don’t trade on earnings — they trade on marginal liquidity.
GLI tells you:
When rallies are supported by real money
When breakouts are likely to fail
When dips are being bought vs distributed
When risk is being quietly withdrawn
How to use it
Apply GLI to any chart.
When the background turns:
Green (Fed Dominant) → Risk assets are structurally supported
Orange (T-Bill Dominant) → Liquidity is draining from risk
Blue (Cash Glut) → Money is stuck at the Fed, rallies struggle
Red (Funding Stress) → Volatility and liquidation risk rise
The built-in Liquidity HUD shows:
RRP usage
Fed vs Treasury dominance
SOFR stress
Rate spreads in real time
No interpretation required.
What GLI is not
GLI is not a technical indicator.
It does not look at price, volume, or momentum .
It looks at the money behind the price .
That’s why it works.
GLI Regime Index (v1.0)GLI Regime Index
Global Liquidity Intelligence for Risk Markets
The GLI Regime Index is a macro-liquidity regime engine that classifies the financial system based on where cash is actually flowing inside the Fed–Treasury plumbing.
Markets do not move on narratives.
They move on liquidity.
GLI measures that liquidity in real time by combining four institutional-grade signals:
• Fed Reverse Repo (RRP) – where excess cash is being parked
• 3-Month Treasury Bills – where short-term money prefers to earn yield
• IORB – the Federal Reserve’s policy floor
• SOFR – the true cost of funding in the system
By comparing these flows, GLI identifies which institution is currently in control of money:
Regime What It Means
FED DOMINANT Abundant reserves, liquidity flowing into risk assets
T-BILL DOMINANT Treasury absorbing liquidity, risk tightening
CASH GLUT Excess money trapped at the Fed (RRP high)
FUNDING STRESS Funding markets under pressure (SOFR > IORB)
NEUTRAL Transition state between regimes
These regimes are not opinions — they are the mechanical state of the dollar system.
Why this matters
Assets like NVDA, BTC, high-beta tech, and growth stocks don’t trade on earnings — they trade on marginal liquidity.
GLI tells you:
When rallies are supported by real money
When breakouts are likely to fail
When dips are being bought vs distributed
When risk is being quietly withdrawn
If you’ve ever wondered why price seems to hit invisible walls,
GLI shows you where those walls come from.
How to use it
Apply GLI to any chart.
When the background turns:
Green (Fed Dominant) → Risk assets are structurally supported
Orange (T-Bill Dominant) → Liquidity is draining from risk
Blue (Cash Glut) → Money is stuck at the Fed, rallies struggle
Red (Funding Stress) → Volatility and liquidation risk rise
The built-in Liquidity HUD shows:
RRP usage
Fed vs Treasury dominance
SOFR stress
Rate spreads in real time
No interpretation required.
What GLI is not
GLI is not a technical indicator.
It does not look at price, volume, or momentum.
It looks at the money behind the price.
That’s why it works.
Vertical line at 6PMVertical line deliniated every 6pm for the asian session trading and backtesting.
US ISM MNO/Business CycleVisual indicator tracking the US ISM Manufacturing New Orders Index across business cycle phases. Features four color-coded zones: Over Expansion (red, ≥60), Expansion (green, 50-60), Contraction (blue, 45-50), and Recession (yellow, <45). Includes reference lines at key thresholds (45, 50, 60) and automated alerts for zone transitions. Useful for monitoring economic cycles and timing investment decisions based on manufacturing sector momentum.
Power Hour Trendlines [LuxAlgo]The Power Hour Trendlines indicator is based on Power Hours detection, and includes up to three displayed trendlines derived from the closing prices of all the bars within the last user-selected Power Hours.
Users can edit the time of Power Hours, choose how many sessions to take into account, enable or disable any trendlines, and change their colors.
🔶 USAGE
The Power Hour is defined as the last hour of the trading session and is set by default from 3:00 p.m. to 4:00 p.m. New York time. During this period, volume and volatility enter the market. Traders using higher timeframes may use this period to enter or exit positions by placing MOC (Market on Close) orders.
This tool works under the hypothesis that prices made during power hours (periods with high trading activity) are more relevant when used for the construction of trendlines.
An initial trendline is fit using linear regression; prices from power hours located above this initial fit are used for the upper trendline, while the ones below the fit are used for the lower one.
As with any trendline, traders can analyze the slope to determine the market's direction:
Positive slope: The market is trending up.
Negative slope: The market is trending down.
No slope: The market is trending sideways.
As we can see in the image, Nasdaq and Bitcoin are clearly in downtrends, gold is clearly in an uptrend, and the euro/U.S. dollar is in a sideways market over the last visible sessions.
As you can see, the trend lines may or may not be parallel to each other. The wider the area, the more volatile the data. The narrower the area, the less volatile the data. Let's look at an example.
In the image, the Dow30 and the euro/U.S. dollar have opposite behaviors. The volatility above the middle trendline is growing in the first case but shrinking in the second. In both cases, the volatility in the bottom area seems steady, so there are no big surprises there.
Traders can adjust the number of sessions for calculations, making the tool ideal for analyzing price behavior over different time frames.
As the image shows, we can clearly see how the market behaves over different time periods. XLY has been moving down over the last 10, 20, and 40 sessions, with a steeper decline over shorter periods. However, it has been moving sideways over the last 70 sessions.
One of the main uses of trendlines is to provide key support and resistance. In the image, SPY is shown with trendlines over the last 20 sessions. These lines provide excellent reference points for trading and observing price behavior in those areas, such as whether prices are accepted or rejected, which may trigger a response from other traders.
🔹 Not Allowed Timeframes
For obvious reasons, timeframes larger than 1H are not allowed. The Power Hour is defined as the last hour of the trading session. The tool will display a warning message if the timeframe is longer than 60 minutes.
🔶 SETTINGS
Power Hour (NY Time): Choose a custom Power Hour in New York time
Sessions Memory: Select how many Power Hours to take into account for calculations.
🔹 Style
Top: Enable or disable the top line and choose the line and background colors.
Middle: Enable or disable the middle line and choose the line color.
Bottom: Enable or disable the bottom line and choose the line and background colors.
Background: Enable or disable the background color for top and bottom lines.
Planetary Retrograde Periods█ PLANETARY RETROGRADE PERIODS
Visualize when planets appear to move backward through the zodiac. This indicator detects and displays retrograde motion for all 8 planets that exhibit apparent retrograde motion from Earth's perspective: Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and Pluto.
Powered by the BlueprintResearch lib_ephemeris library.
█ FEATURES
• 8 Planets Supported — Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and Pluto
• Two-Phase Visualization — Distinguishes first half (speed increasing in retrograde direction) from second half (speed decreasing toward direct motion) with different transparency levels
• Future Projections — Projects upcoming retrograde periods up to 500 bars ahead on any timeframe
• Station Markers — Clear labels for Station Retrograde (℞), Midpoint (½), and Station Direct (D)
• Timezone-Aware Labels — Future date/time labels display in your selected timezone
• Alert Conditions — Set alerts for station retrograde, station direct, or any station point
• Per-Planet Colors — Customize colors for each planet individually
• Speed-Based Detection — More accurate than longitude-based methods
█ HOW TO USE
1. Select a Planet — Choose which planet to track from the dropdown (Mercury through Pluto)
2. Enable Two-Phase Display — Toggle "Show Retrograde Halves" to see first half vs. second half shading
3. Configure Future Projections — Set how many bars ahead to scan (1-500) and enable/disable date labels
4. Set Your Timezone — Choose your timezone for accurate future date/time display
5. Customize Colors — Adjust planet colors, transparency levels, and label text color to match your chart theme
6. Create Alerts — Use TradingView's alert system with the built-in conditions for station points
█ UNDERSTANDING THE DISPLAY
Background Colors:
• First Half of the Planet’s retrograde (lighter shade)
• Second Half of the Planet’s retrograde period (darker shade)
Future Projection Lines:
• ℞ (Station Retrograde) — Yellow dotted line marking when the planet will station retrograde
• ½ (Midpoint) — Shorter line in planet color marking the halfway point of the retrograde period
• D (Station Direct) — Green dotted line marking when the planet will station direct
Labels:
• Top label shows planet symbol and station type
• Bottom label shows projected date and time (optional)
█ ACCURACY
This indicator uses speed-based detection
Timing Accuracy:
• All planets (Mercury through Pluto): Within hours to ±1 day
• Future projections maintain accuracy up to 500 bars on any timeframe
• Spot tested on Daily and Weekly charts with excellent results
For Critical Applications:
Cross-reference with professional ephemeris tools such as JPL Horizons or Swiss Ephemeris for mission-critical timing.
█ TECHNICAL DETAILS
Theory: VSOP87 (Mercury through Neptune), Meeus algorithms (Pluto)
█ REFERENCES
• Meeus, Jean. "Astronomical Algorithms" (2nd Edition, 1998)
• Bretagnon & Francou. "VSOP87 Solutions" — Astronomy and Astrophysics 202 (1988)
VIX/VVIX Regime CandlesVIX / VVIX Regime Candles is a volatility regime indicator designed to provide traders and analysts with a clear understanding of market risk conditions. By analyzing both VIX TVC:VIX (implied volatility) and VVIX CBOE:VVIX (volatility of volatility)—including their absolute levels, directional changes, and interactions—the script classifies the market into nine distinct regimes.
Rather than relying solely on absolute volatility values, this indicator incorporates changes over time and divergences between VIX and VVIX, highlighting potential latent risks that may not be immediately apparent from the VIX alone. Falling VIX and VVIX typically indicate improving conditions, while rising levels or divergence can signal emerging stress.
Methodology
VIX / VVIX Regime Candles combines absolute levels, directional changes, and relative behavior of VIX and VVIX to classify market conditions into nine volatility regimes. The methodology includes the following components:
Data Source and Frequency
Uses daily closing prices for CBOE VIX (implied volatility of S&P 500 options) and VVIX volatility of VIX options). Applies these daily values to any chart timeframe, but regime updates occur once per day.
Threshold-Based Regime Classification
VIX thresholds classify absolute market stress: Very Low, Medium Low, Medium High, High
VVIX thresholds classify volatility of volatility: Low, Medium, High
Thresholds are fully configurable by the user to adapt to different market conditions or asset classes.
Momentum / Change Analysis
Calculates percent change over a configurable lookback period for both VIX and VVIX:
VIX Change = (VIX current - VIX lookback) / VIX lookback
VVIX Change = (VVIX current - VVIX lookback) / VVIX lookback
Determines whether VIX and VVIX are rising, falling, or stable relative to configurable percentage thresholds.
Combined Regime Logic
Integrates level-based and momentum-based signals:
High VIX + High VVIX + rising → Panic
Moderate VIX + rising VIX + elevated VVIX → Storm
Low VIX + rising VVIX → Hidden Risk
Falling VIX and VVIX → Low Risk / Settling or Calm
Includes intermediate regimes such as Preparing for Storm and Calm After Storm, providing early warning or recovery context.
Regime Assignment
Assigns a single integer value (1–9) for the current regime.
Detects regime changes to avoid redundant labeling; labels are only created when a new regime begins, minimizing chart clutter.
Visual Encoding
Bar colors correspond to the active regime.
Labels indicate the regime name and are automatically positioned above or below the candle for readability.
Legend table and VIX/VVIX value table provide users with a full reference to interpret the regime directly on the chart.
Parameter Customization
Users can adjust the following parameters to tailor the indicator to their analysis:
VIX and VVIX Thresholds: Modify the levels used to define very low, medium, and high regimes.
Change Thresholds: Adjust the percentage change required to classify VIX or VVIX as rising or falling.
Lookback Period: Change the number of periods over which VIX and VVIX percentage changes are calculated.
Colors: Customize the colors assigned to each regime for candle coloring and labels.
These settings allow users to adapt the indicator for different market conditions, asset classes, or personal trading strategies.
Intended Use
This indicator is intended for risk assessment and contextual analysis rather than as a direct trading signal. It is useful for:
Evaluating risk-on versus risk-off market environments
Informing position sizing and exposure management
Identifying periods when market conditions are unstable
Macro, swing, and portfolio-level analysis
Important Considerations
VIX and VVIX are daily series, so intraday charts will only reflect updates once per day
Thresholds are customizable, and default values reflect commonly observed market behavior
Access to CBOE:VVIX may depend on the TradingView subscription plan
The indicator should be used in conjunction with additional technical or fundamental analysis
This script is provided for educational and informational purposes only and does not constitute financial advice. Users should exercise appropriate risk management when making trading decisions.
Market Up and Low VolatilityMarket Up and Low Volatility is a trend-filter indicator designed to help traders visually identify periods when an equity index is in an upward trend and market volatility is relatively low. The script combines price trend analysis using exponential moving averages (EMAs) with external volatility confirmation to highlight more favorable risk environments.
Concept and Methodology
This indicator is based on two core ideas:
1. Trend Confirmation Using EMAs
The script calculates a 10-period EMA and a 20-period EMA on the selected index (default: S&P 500).
A bullish trend condition requires:
The 10 EMA to be above the 20 EMA
Both EMAs to be rising compared to their values three bars ago
This helps confirm not just trend direction, but also trend momentum.
2. Volatility Filter Using an External Symbol
The indicator also fetches data from a volatility index (default: VIX).
A user-defined volatility threshold is applied
When volatility is below this threshold, it is treated as a lower-risk market environment
Only when both trend and volatility conditions align does the indicator consider the environment favorable.
Visual Output
The index price is plotted in a separate pane.
The plot dynamically changes color:
Green when all trend and volatility conditions are met
Red when one or more conditions are not met
This color-based approach allows traders to quickly assess market conditions without interpreting multiple indicators.
How to Use
This indicator is intended as a market condition filter, not a standalone buy or sell signal.
It can be used to:
Confirm whether broader market conditions are supportive of long strategies
Avoid trading during periods of elevated volatility or weakening trends
Complement existing entry and exit systems
Users can customize:
The index symbol
The volatility symbol
The volatility threshold
to adapt the indicator to different markets or trading styles.
Notes
Calculations are performed on daily timeframe data, regardless of the chart timeframe. This indicator does not predict future price movement and should be used alongside proper risk management and additional analysis.
Institutional Cycle Intelligence System (Machine Learning) The Institutional Cycle Intelligence System (Machine Learning) represents a paradigmatic shift in the capabilities of retail trading analysis, bridging the substantial divide between standard technical analysis and the rigorous, mathematically intensive domain of quantitative finance. At its core, this system is not merely an indicator but a sophisticated ensemble engine that synthesizes advanced Digital Signal Processing (DSP), spectral analysis, and modern Machine Learning techniques into a singular, cohesive market view. For quantitative analysts and institutional traders, this script serves as a testament to the power of "higher mathematics" applied to the chaotic, non-stationary nature of financial time series data. It moves beyond the lagging nature of time-domain indicators—like moving averages or the RSI—and operates primarily in the frequency domain, attempting to deconstruct price action into its constituent oscillatory components. This approach acknowledges a fundamental truth of market mechanics: that price is a composite signal, a noisy waveform comprised of underlying trends, cyclical harmonics, and stochastic noise. By isolating these components, the system offers a look into the "heartbeat" of market liquidity and institutional accumulation-distribution cycles.
The defining characteristic that elevates this system to an institutional grade is its refusal to rely on a single mathematical model. Financial markets are dynamic systems; they shift between trending, mean-reverting, and chaotic regimes. A model that excels in a clean sine-wave market, like a standard cycle, will fail primarily during strong trends or high-volatility shocks. To solve this, the system employs an "Ensemble Architecture," running seven distinct, high-level mathematical models simultaneously. It creates a "committee of experts," where each algorithm analyzes the market through a different mathematical lens—some statistical, some spectral, and some decompositional. However, the true innovation lies in the integration of a Gradient Boosting Machine (GBM). This is where the concept becomes a game-changer for Pine Script development. The system does not merely average these models; it employs a machine learning layer that dynamically optimizes the weight of each model based on its recent predictive performance. It "learns" which mathematical approach is currently syncing best with the market's behavior and amplifies that signal while dampening the others. This is an application of adaptive filtering and optimization theory that is rarely seen outside of proprietary high-frequency trading desks.
To understand the gravity of the mathematics involved, one must examine the specific algorithms employed, starting with the Ehlers Bandpass Filter and Hilbert Transform. This component is rooted in electrical engineering and signal processing. The Bandpass filter is designed to reject frequencies outside a specific range, effectively stripping away the high-frequency noise (tick-by-tick randomness) and low-frequency trends (macro-economic drift) to isolate the "tradable" cycle. Once isolated, the script applies the Hilbert Transform, a linear operator that produces the analytic representation of the signal. By converting the real-valued price series into the complex plane (creating real and imaginary components), the system can mathematically calculate the instantaneous phase and amplitude of the cycle. This allows for the precise determination of market turning points without the lag associated with traditional smoothing, effectively solving the "phase delay" problem that plagues standard oscillators.
Complementing the classic DSP approach is the MESA (Maximum Entropy Spectral Analysis) model. Standard Fourier analysis assumes that data outside the observation window repeats or is zero, which creates "spectral leakage" and inaccuracies when analyzing short data bursts typical of trading. MESA, however, is based on information theory. It constructs a model that maximizes the entropy (randomness) of the unobserved data, thereby making the fewest assumptions possible about what the market did before or after the sample size. This results in a high-resolution estimation of cycle periods even with limited data points. It is a highly mathematical approach to autoregressive modeling, allowing the system to detect shifting cycle lengths rapidly as market volatility expands or contracts.
The system also integrates the Goertzel Algorithm, a method optimized for detecting specific frequency components within a signal. While a Fast Fourier Transform (FFT) scans the entire frequency spectrum, the Goertzel algorithm acts as a matched filter, surgically interrogating the price data for the presence of specific, pre-defined cycle periods (Short, Medium, and Long). It computes the energy or "power" at these specific frequencies. For a quant, this is akin to tuning a radio receiver to listen specifically for the presence of institutional order flow frequencies. If the "power" at the 20-bar cycle is high, the Goertzel component signals that this specific harmonic is currently driving price action. This selective frequency analysis is computationally efficient and provides a direct measurement of cycle strength, distinguishing between a genuine cycle and random market drift.
Moving into the realm of non-linear and non-stationary analysis, the system employs Empirical Mode Decomposition (EMD). Developed for analyzing data that is neither linear nor stationary—a perfect description of financial markets—EMD does not assume a fixed basis like sine waves. Instead, it uses a recursive "sifting" process to decompose the price into a finite number of Intrinsic Mode Functions (IMFs). The algorithm identifies local maxima and minima, creates upper and lower envelopes using cubic splines, and subtracts the mean of these envelopes from the data. This process is repeated until true oscillatory modes are extracted. EMD is often referred to as the "Hilbert-Huang Transform" in academic literature and is considered one of the most powerful tools for analyzing natural phenomena. By using EMD, the system can adapt to asymmetric cycles (where the rally is fast and the drop is slow) that linear models like the Fourier transform would misinterpret.
The inclusion of Singular Spectrum Analysis (SSA) further deepens the mathematical rigor. SSA is a nonparametric spectral estimation method that combines elements of classical time series analysis, multivariate geometry, and signal processing. Conceptually, it involves embedding the time series into a vector space to form a "trajectory matrix" and then performing a decomposition (similar to Principal Component Analysis or SVD) to separate the series into independent components representing trend, oscillatory signals, and noise. While Pine Script limits the full matrix algebra required for complete SVD, the implementation here utilizes heuristic approximations to achieve the decompositional effect. This allows the system to filter out noise "subspaces," reconstructing a signal that retains the structural integrity of the market movement while discarding the stochastic "fuzz" that leads to false signals.
Wavelet Analysis is utilized to address the "Heisenberg Uncertainty Principle" of signal processing, which states one cannot know the precise frequency and precise time of an event simultaneously. While Fourier analysis loses time resolution to gain frequency resolution, Wavelets use "short" basis functions for high frequencies and "long" basis functions for low frequencies. This Multi-Resolution Analysis (MRA) allows the system to see the forest and the trees simultaneously. It decomposes price energy across different scales, identifying whether volatility is driven by short-term microstructure noise or long-term structural shifts. The calculation of "Wavelet Energy" within the script provides a distinct metric of market state, often preceding explosive moves when energy clusters across multiple timescales.
Finally, the statistical backbone is provided by Autocorrelation. This is the mathematical study of self-similarity. It calculates the correlation of the price series with a lagged version of itself. By scanning through various lags (periods), the algorithm identifies the time shift that produces the highest correlation coefficient. If price correlates highly with itself from 20 bars ago, it confirms a 20-bar cycle memory in the market. This is a purely statistical validation method that serves as a "sanity check" for the more complex spectral models, ensuring that the detected cycles are statistically significant and not artifacts of curve fitting.
The culmination of these seven mathematical titans is the Gradient Boosting Machine (GBM) optimization layer. In the context of Pine Script, this is a revolutionary concept. Traditional indicators have static parameters; they calculate the same way in a crash as they do in a bull run. This system, however, utilizes a simplified machine learning loop. It calculates the "loss" or error of each of the seven models relative to recent price returns. Using a gradient descent-inspired approach, it updates a weight vector, assigning higher influence to models that have been predictive in the recent lookback window and penalizing those that have failed. If the market enters a choppy period where trends vanish, the EMD and Wavelet models (which handle noise well) might gain dominance, while the Trend-following components are suppressed. If the market enters a clean harmonic swing, the Ehlers and Goertzel models will take the lead. This dynamic adaptation makes the system "alive," capable of morphing its internal logic to match the current market regime.
For the quantitative analyst, this system offers a robust framework for algorithmic strategy development. It provides "feature engineering" out of the box—transforming raw price data into normalized, de-trended, and phase-aligned oscillators. The composite signal is not just a line on a chart; it is a probability-weighted vector of market state. The "Zero-Lag" nature of the phase calculations allows for entry and exit precision that moving averages mathematically cannot provide. Furthermore, the decomposition of market movements into Short, Medium, and Long cycles allows for fractal analysis—identifying moments of "Constructive Interference" where all three cycles align in phase, creating high-probability, high-velocity trade setups often associated with institutional order execution.
In conclusion, the Institutional Cycle Intelligence System (Machine Learning) is a tour de force of applied mathematics and computational finance. It transcends the limitations of standard technical analysis by treating the market not as a visual pattern, but as a complex signal processing problem. By leveraging the orthogonality of different mathematical approaches—spectral, statistical, and decompositional—and fusing them through an adaptive machine learning mechanism, it offers a level of insight typically reserved for hedge funds with dedicated quant teams. It demonstrates that Pine Script is no longer just a scripting language for drawing lines, but a viable environment for implementing complex, adaptive, and mathematically rigorous trading systems. It is a tool for those who understand that in the financial markets, the edge lies not in predicting the future, but in deeply understanding the mathematical structure of the present.
Active Market SessionsThis indicator displays non-intrusive colored squares that indicate which market session is currently active. When you hover over each square, it shows the active session and the remaining time before that session closes.
The following colors let you identify the active session at a glance:
London (European Session) = Purple
New York (American Session) = Blue
Sydney (Pacific Session) = Yellow
Tokyo (Asian Session) = Red
You can change the indicator’s position on the chart through the settings. This indicator is also DST-aware and automatically adjusts its behavior based on the current daylight saving time status of each session.
Mashrab | Momentum X-RayStop guessing if a stock is strong or weak. The Momentum X-Ray is a professional Heads-Up Display (HUD) that tells you the truth about a stock in seconds.
Most indicators just look at price. This dashboard looks at the Context:
Relative Strength (The "King of the Hill" Check):
It doesn't just compare stocks to the S&P 500.
It automatically detects the stock's specific industry (e.g., Semiconductors, Regional Banks, Gold Miners) and compares it against its actual peers.
Green = The stock is a Leader (Beating its sector).
Red = The stock is a Laggard (Losing to its sector).
Fundamental Health (The "Engine" Check):
Instantly see Revenue Growth (QoQ and YoY) and Net Profit Margins.
Filters out "junk" stocks that are moving up on hype but have no real business growth.
Volatility Scanner:
Calculates the ADR (Average Daily Range) to help you size your positions correctly.
How to Read the Signals:
Top Table (Momentum): Look for Double Green. If a stock is beating the SPY and its Sector, it is an "Alpha Leader."
Bottom Table (Context): Check the "Industry" row to see exactly which ETF the script is using for comparison (e.g., SMH for Chips, KRE for Banks).
Algonova TrendFlowWhat was previously a (very!) manual process of looking at "UPs" and "DOWNs" to determine which way the market is "flowing" has now been automated! Urban TrendFlow is an immense timesaver for our users as we search for opportunities to go long and short (and especially when we need to sit on our hands and let uncertain markets "find their flow".
Wick Connection Alerts (12M/6M/3M/1M)If you want touch/overlap, pick: Any Range Overlap (High-Low)
If you want wick-to-wick specifically, pick: Wick-to-Wick Zones (now with fewer false signals)
Key Time Window & Kill Zones
📌 Key Time Window & Kill Zones
This indicator highlights important global trading sessions and high-probability execution windows using fixed UTC (GMT+0) timings, which align correctly with IST and all other time zones through TradingView’s internal time conversion.
It is designed to help traders focus on institutional activity periods, avoid low-probability hours, and execute trades only during statistically active market windows for Crypto, Forex And US markets.
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⏱️ Session Timings (All in UTC / GMT+0)
Asia Range — 22:00 – 05:00 (Red) ( NO TRADING ZONE)
• Marks the Asian session consolidation range
• Useful for identifying liquidity highs and lows
• Acts as reference for London and New York liquidity sweeps
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Frankfurt Trap Time — 07:00 – 08:00 (Grey) ( NO TRADING ZONE)
• Commonly produces false breakouts and stop-hunts
• No-trade zone
• Used only to observe potential liquidity traps before London open
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London Kill Zone — 08:00 – 09:00 (Blue) (TRADING ZONE)
• High-volatility window at London open
• Trades are valid only after Frankfurt liquidity is swept
• Suitable for smart-money entries following manipulation
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New York Range — 13:00 – 17:00 (Purple)
• Defines the broader New York session range
• Tradeable only when market structure is trending
• Provides context for NY session price development
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New York Kill Zone (Key Time Window) — 14:00 – 15:00 (Deep Purple) ( KEY TIME WINDOW- TRADING WINDOW)
• Primary execution window
• Best setups form after London or NY open inducement
• Suitable for both reversals and continuations
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NYSE Cash Open — 14:30 – 14:45 (Dark Purple) ( AVOID NEW ENTRIES IN THIS ZONE)
• Exact US cash market opening window
• Increased volatility and decisive price moves
• One of the most important intraday execution periods
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🧠 How to Use
• Use session zones as time-based confirmation, not standalone signals
• Combine with:
o Market structure
o Liquidity sweeps
o Inducement
o Order blocks / supply & demand
• Avoid trading outside the highlighted sessions
• Best suited for intraday and scalping strategies
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⚠️ Important Notes
• All sessions are plotted in UTC (GMT+0)
• Automatically adjust to the user’s chart time zone (including IST)
• This indicator does not generate buy or sell signals
• Intended for educational and analytical purposes only
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BONUS
Two Extra Options To mark your Special Time Zones If you Want.
Skylark Digital Assets Monthly FLPSkylark Digital Assets’ Monthly Financial Liquidity Proxy (FLP) is a monthly, regime-focused macro indicator designed to summarize broad financial conditions into a single, stable signal.
This version is the core Monthly FLP only—intended for straightforward liquidity regime tracking—without the additional seasonal classification logic used in other variants.
What you see
Monthly FLP (confirmed): A consolidated monthly liquidity gauge that is held stable on intramonth bars to avoid “mid-month” distortions. The series is designed to reflect the underlying state of conditions at the monthly level rather than short-term noise.
Optional Monthly FLP EMA: A smoothing/trend filter that helps highlight structural shifts and reduces month-to-month volatility.
Midline reference: A neutral reference level for quick above/below regime interpretation.
How to use it
Macro regime context: Use the Monthly FLP as a higher-timeframe backdrop for understanding when conditions are broadly improving or tightening.
Cycle confirmation: The monthly timeframe reduces noise and is best suited for identifying longer-cycle transitions rather than short-term trades.
Asset overlays: Add the FLP to any chart (crypto, equities, FX, rates, commodities) to compare whether price is moving with or against the broader liquidity regime.
Notes
This script is intended for research and visualization. It is not a trading strategy and does not provide guaranteed signals. Always apply independent confirmation and risk management.
Weekly Financial Liquidity IndexSkylark Digital Assets’ Weekly Financial Liquidity Index (FLI) is an index-style representation of macro financial conditions on the weekly timeframe, built to provide a clean, trendable “liquidity tape” you can overlay on any market.
Rather than plotting conditions as a bounded oscillator, the Weekly FLI converts the weekly liquidity environment into a continuous index series. This makes it easier to compare against price, identify regime persistence, and visualize structural turns without the compression effects of 0–100 indicators.
What you see
Weekly FLI (index line): A continuous index reflecting the direction and persistence of broader financial conditions.
Regime behavior: Sustained advances tend to reflect improving conditions; flattening or sustained pullbacks tend to reflect tightening or deterioration.
Optional trend confirmation (minimal): Optional confirmation markers/filters may be enabled to help highlight structural trend shifts while keeping the chart uncluttered.
How to use it
Overlay context: Keep the Weekly FLI on your chart as a macro backdrop for crypto, equities, FX, rates, or commodities.
Trend alignment: Compare the slope and turns of the FLI to the asset you’re analyzing to see when price is moving with (or against) broader conditions.
Cycle awareness: Weekly FLI is best used for multi-week to multi-month context—ideal for identifying transitions, not short-term entries.
Notes
This indicator is intended for research and visualization only. It does not provide guaranteed signals and should be paired with independent confirmation and risk management.
Weekly Financial Liquidity Proxy + Forward Money IndexSkylark Digital Assets’ Weekly Financial Liquidity Proxy (FLP) + Forward Money Index (FMI) is a regime-focused macro overlay designed to compare broad weekly liquidity conditions with a smoothed forward-conditions signal.
The indicator pairs a weekly liquidity proxy (the “what is happening now” layer) with a forward overlay (the “conditions impulse” layer) that can be shifted ahead in time to visually study how changes in conditions often precede broader regime transitions.
What you see
Weekly FLP (confirmed): A consolidated weekly liquidity regime gauge intended to reflect broad improvements/deteriorations in conditions without relying on single-asset behavior.
Weekly FLP EMA (optional): A trend filter that reduces noise and helps distinguish temporary volatility from structural regime change.
Forward Money Index (FMI) — smoothed only: The FMI is not shown in raw form. Instead, it is displayed using two smoothed versions:
a faster smoothing (short EMA) labeled as the primary FMI, and
a slower smoothing (longer EMA) shown as a dotted companion line for confirmation.
Midline reference: A neutral reference level to simplify interpretation and identify above/below-regime behavior.
How to use it
Macro context overlay: Use FLP to understand whether the broader environment supports risk-on behavior or is tightening.
Forward-impulse comparison: Use the smoothed FMI pair to study early turning points and momentum changes that may foreshadow upcoming shifts in the weekly liquidity regime.
Confirmation logic: When the faster FMI line leads and the slower FMI line follows, conditions are strengthening; when the faster line rolls over and converges toward the slower line, the impulse may be fading.
Notes
Lead/offset controls are provided for research and visualization only. Market regimes can compress or expand lead times, so offsets should be treated as a context lens rather than a fixed forecast.
This script is intended for analysis and education and does not constitute financial advice or a trading strategy.
everythingso basically so basically my script my script you want it you want it add and cop it nwog+fvgs just to remove the other one
