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.
Ciclos
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
Daily Financial Liquidity IndexSkylark Digital Assets’ Daily Financial Liquidity Index (FLI) is a daily, index-style view of macro financial conditions designed to provide a clean “liquidity tape” you can overlay against any asset.
Unlike bounded oscillators, the Daily FLI is structured as a continuous index: it translates daily changes in financial conditions into a smooth, price-like series that can trend, plateau, or roll over as regimes shift. The goal is not to predict a specific asset, but to offer a consistent, comparable reference for risk-on / risk-off conditions across time.
What you see
Daily FLI (index line): A continuous index representation of the underlying liquidity environment.
Regime behavior: Strong, persistent uptrends tend to reflect broadly improving conditions; flattening or drawdowns tend to reflect tightening or deteriorating conditions.
Optional confirmation markers: Minimal, non-intrusive markers can be enabled for additional trend confirmation while keeping the chart clean.
How to use it
Overlay context: Use the FLI as a background “macro state” overlay on crypto, equities, FX, rates, or commodities.
Trend confirmation: Compare the slope and turning points of the FLI to the asset you’re analyzing to identify periods when price is moving with or against broader conditions.
Cycle awareness: The Daily FLI is best interpreted as a regime tool—ideal for multi-week to multi-month context rather than short-term entries.
Notes
This script is intended for research and visual analysis. It is not a trading strategy, does not generate guaranteed signals, and should be used alongside risk management and independent confirmation.
Forward Money Index x Financial Liquidity Proxy Skylark Digital Assets Forward Money Index x Financial Liquidity Proxy is a two-layer liquidity dashboard designed to show broad, slow-moving liquidity conditions alongside a smoothed forward-conditions signal that can be shifted ahead in time for visual comparison.
At its core, the chart has three roles:
Baseline Liquidity Regime (FLP – Monthly, Confirmed)
The primary line represents a consolidated view of monthly liquidity conditions across a diversified set of markets. It’s constructed to behave like a regime gauge—rising during periods where financial conditions are broadly improving and falling during periods where conditions are tightening. Because it uses confirmed monthly values, it avoids the “mid-month repaint” effect and is intended to be interpreted as a stable, end-of-month state.
Trend Filter / Regime Smoother (FLP EMA)
The FLP EMA is a slower companion line that reduces month-to-month noise and helps define whether liquidity is structurally expanding or contracting. In practice, this line is the “signal stabilizer”: it makes longer-cycle transitions clearer, reduces overreaction to single-month spikes, and helps you distinguish between temporary wobble vs true regime shift.
Forward Conditions Overlay (Forward Money Index – Displayed as EMA3 & EMA6 only)
The forward overlay is intentionally not shown in its raw form. Instead, it is used internally and then displayed only through two smooth versions:
a short smoothing (3-month EMA), labeled as the “Forward Money Index (FMI)” in the settings, and
a medium smoothing (6-month EMA), shown as a dotted companion line.
This creates a clean “fast vs slow” forward-conditions pair. The short version reacts sooner and highlights turning points earlier; the longer version confirms whether the shift is persistent. When both are rising together, it suggests strengthening conditions; when the shorter line rolls over and converges down toward the longer line, it indicates that the impulse is fading even if conditions remain elevated.
Lead / Offset behavior (visual forecasting lens)
The FMI pair can be shifted forward by a chosen number of months, allowing you to compare whether shifts in forward conditions tend to precede changes in the broader liquidity proxy. This is not presented as a deterministic forecast; it’s a visual tool to examine phase relationships across cycles. Different environments can compress or expand lead times, so the offset is best treated as a “lens” rather than a fixed law.
Midline reference
A 50 midline provides a neutral reference level so both the proxy and the forward overlay can be interpreted in simple regime terms: above the midline generally corresponds to more favorable conditions, while below corresponds to tighter or weaker conditions.
Why the smoothing matters
By plotting only the 3M and 6M EMA versions of the forward signal, the indicator avoids overemphasizing short-term noise and instead focuses on structural turns—the part of the signal that tends to matter most for multi-month regime interpretation. This makes it useful for:
identifying early inflections that may precede broader liquidity shifts,
confirming whether changes are impulsive (fast line leading) or durable (both lines aligned), and
tracking the decay of an impulse when the fast line begins to fade toward the slow line.
Overall, the chart is meant to function as a monthly macro dashboard: FLP shows where broad liquidity conditions are now, FLP EMA shows the underlying trend regime, and the FMI EMA pair provides a smoothed forward-conditions overlay to help evaluate whether the next regime transition may already be forming.
Planetary IngressDisplays planetary ingresses, the moments when a planet crosses from one zodiac sign into another. This indicator marks historical ingresses directly on your chart and projects upcoming ones with precise date, time, and retrograde status.
Powered by the open-source BlueprintResearch Planetary Ephemeris library , which implements truncated VSOP87 (planets) and ELP2000 (Moon) series for high-accuracy celestial calculations entirely within Pine Script.
█ FEATURES
• All 10 celestial bodies — Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and Pluto
• Geocentric or Heliocentric views — toggle between Earth-centered (standard astrology) and Sun-centered perspectives
• Retrograde indicator — shows ℞ symbol when a planet is in apparent retrograde motion (geocentric only)
• Future ingress projection — displays the following sign change as a dotted vertical line with customizable date/time and timezone
• Color-coded by zodiac sign — 12 fully customizable colors for each sign
• Per-sign visibility controls — easily show/hide specific signs
• Per-sign alerts — get notified when a planet enters selected signs
• Fully customizable labels — adjust size, colors, transparency, and placement
█ HOW TO USE
1. Select your planet from the dropdown
2. Choose Geocentric (traditional) or Heliocentric view
3. Historical ingresses appear as labels above price bars with a planet symbol and a zodiac sign
4. The next future ingress is shown as a dotted vertical line with projected date/time
5. Hover over labels for exact degree position (e.g., "0°Ari00'")
6. Set up alerts via "Alert on Ingress" settings for specific sign entries
█ LIMITATIONS & ACCURACY
This indicator uses optimized, truncated VSOP87 and ELP2000 series tailored for Pine Script performance. It delivers excellent accuracy for trading and analytical purposes, but is not intended for professional astronomical use.
Expected Ingress Timing Accuracy (Geocentric view):
• Sun, Moon, Mercury, Venus, Mars: Within hours to ±1 day
• Jupiter, Saturn: Within ±1–2 days
• Uranus, Neptune: Within ±3–7 days
• Pluto: Within ±1–2 weeks (simplified Meeus method, valid 1900–2100)
Heliocentric view: Inner and faster-moving planets match geocentric accuracy. Outer planets (especially Uranus/Neptune) may occasionally show larger variances (up to ±1 month in rare cases) due to their extremely slow motion amplifying minor truncation effects in the series.
Why outer planets vary more:
Slower planets take weeks or months to cross a single degree. Even minor positional discrepancies from truncated terms can shift ingress timing by days or weeks—most noticeable with the outermost bodies.
Recommendation: For mission-critical timing, always cross-reference with professional tools such as JPL Horizons , Swiss Ephemeris, or Astro.com.
█ ROADMAP
Accuracy improvements are an ongoing priority. The modular library design allows targeted upgrades to individual planets without breaking existing functionality.
Planned Enhancements:
• Higher-precision outer planet calculations (Uranus, Neptune)
• Improved heliocentric outer planet accuracy
• Enhanced Pluto method
• Additional series terms where beneficial
Updates will be released through the BlueprintResearch/lib_ephemeris library—follow for notifications.
█ OPEN SOURCE
This indicator is part of the fully open-source Planetary Ephemeris project. The core ephemeris library is public for study, modification, and reuse in your own scripts:
• BlueprintResearch/lib_ephemeris — Main planetary calculation engine
Licensed under MPL 2.0 — free to use and modify, with changes to the library shared back to the community.
Momentum Burst + Absolute Momentum(TI65) + EP9M)This is a momentum burst indicator popularized by StockBee (hey EGeee). Track the stock absolute momentum for continuation breakout. Last but not least, identify EP9M. It can be Episodic pivot 9M volume breakout as a classic EP (CANSLIM type) for a long term trade or a regular EP9M or EP9M delayed reaction for swing trade. KISS - don't over complicate.
Gold Chop MeterWhat it does
It’s a market quality filter. It does NOT tell you direction.
It tells you when Gold is too compressed/choppy to trust clean expansions.
NORMAL = tradable conditions
CHOP = compressed / messy conditions
NO TRADE (30M BOX) = hard stop (30M is CHOP)
NO TRADE (HTF CHOP) = hard stop (majority of higher TFs are CHOP)
How to read the panel (left → right)
You’ll see:
1H: NORMAL/CHOP | 30M: NORMAL/CHOP | 15M: NORMAL/CHOP | 5M: NORMAL/CHOP | TRADE/NO TRADE
The rules (exact)
If 30M = CHOP → NO TRADE (30M BOX)
This is your strongest filter. Don’t fight it.
If 30M isn’t CHOP, then it checks majority:
Default: 1H + 30M + 15M
If 2 of 3 are CHOP → NO TRADE (HTF CHOP)
If those are not true → it prints TRADE
If 15M is CHOP but 30M is NORMAL, it prints:
“TRADE (CAUTION – 15M CHOP)”
That means: trade smaller, quicker, or wait for cleaner trigger.
Settings you actually need to touch
1) Profile
Auto (by session) = best for most days (it changes the threshold by time window)
NYO / Overnight / London profiles are there if you want to force one behavior.
2) ATR Length (fixed)
Default 4 is good for Gold.
If it’s too sensitive (flips CHOP too often), raise to 5.
If it’s too slow (stays NORMAL when price is dead), drop to 3.
3) Include 5M in majority filter? (default OFF)
OFF = cleaner, less restrictive (recommended)
ON = stricter filter (needs 3 of 4 to be CHOP for “HTF CHOP” but 5M influences the count)
How to use it with your purge strategy (simple playbook)
When it says TRADE
You’re allowed to execute your normal model:
Sweep → displacement / CHoCH → first return → run
When it says TRADE (CAUTION – 15M CHOP)
Still tradable, but:
take A+ only
smaller size
quicker TP, don’t expect runners
demand a cleaner trigger (strong displacement)
When it says NO TRADE
You don’t force entries.
What you do instead:
wait for 30M to flip back to NORMAL
or wait for a clear range break + retest that turns the environment back to expansion
Quick “decision cheat”
30M CHOP? → Stop. No trade.
2/3 HTFs CHOP? → Stop. No trade.
Only 15M CHOP? → Trade, but cautious.
All NORMAL? → Green light.
Multi-Metric Market Regime Detector - [KK]This indicator identifies current market behavioral regimes by synthesizing six complementary analytical methodologies. Rather than generating trading signals, it provides contextual analysis to help traders understand market conditions and adapt their strategies accordingly.
Markets cycle through distinct behavioral states - trending efficiently, consolidating in ranges, compressing before breakouts, or transitioning between states. This tool quantifies these conditions using only price action data (OHLC), enabling traders to filter strategies based on current market structure.
Core Methodology
The indicator combines six independent metrics into a weighted composite classification system:
Efficiency Ratio (30% weight)
Measures the signal-to-noise ratio of price movement by comparing net price displacement to total path traveled. High efficiency indicates clean directional movement; low efficiency indicates choppy, noisy conditions.
Choppiness Index (25% weight)
Quantifies whether the market is trending or consolidating by comparing cumulative True Range to actual price range. Values below 38.2 suggest trending behavior; values above 61.8 suggest range-bound consolidation.
Volatility Analysis (20% weight)
Detects compression and expansion cycles using the relationship between Bollinger Bands and Keltner Channels. Compression phases (squeeze conditions) often precede significant directional moves.
Fractal Efficiency Proxy (10% weight)
Analyzes path complexity by comparing net displacement to cumulative range, providing insight into the smoothness versus randomness of price action.
Market Structure (15% weight)
Examines pivot point sequences to identify structural trends. Higher Highs and Higher Lows indicate bullish structure; Lower Lows and Lower Highs indicate bearish structure.
Wick-to-Body Ratio Analysis (qualitative)
Identifies rejection and indecision patterns by measuring the proportion of candle wicks to bodies, highlighting potential reversal zones or liquidity events.
Regime Classifications
The composite scoring system produces four distinct regime states:
TRENDING : High efficiency, low choppiness, clear directional structure. Favorable conditions for momentum and trend-following strategies.
CHOPPY/RANGE : Low efficiency, high choppiness, mean-reverting behavior. Favorable conditions for range trading and counter-trend setups.
COMPRESSION : Volatility squeeze detected, market coiling. Anticipate expansion; reduce position size until breakout confirmation.
TRANSITION : Mixed signals, conflicting metrics, unclear direction. Recommended to reduce exposure and wait for regime clarity.
Visual Features
Regime-Colored Candles (enabled by default)
Candles are colored according to the current regime state for immediate visual identification. Green indicates trending, gray indicates choppy, orange indicates compression, and yellow indicates transition.
Comprehensive Metrics Table (top right)
Displays real-time values for all six metrics along with individual regime assessments and the final composite classification with score.
Regime Guide Table (middle right)
Quick reference guide showing recommended strategies and actions to avoid for each regime state.
Chart Label ( optional)
Summary label displaying current regime and key metric values.
Background Coloring (optional)
Alternative visualization using background colors instead of candle coloring.
Indicator Plots (optional)
Displays Efficiency Ratio and Choppiness Index with threshold reference lines.
Customization Options
All calculation parameters are adjustable:
- Efficiency Ratio lookback period and thresholds
- Choppiness Index length and classification thresholds
- Volatility analysis parameters (BB/KC multipliers and lengths)
- Pivot detection sensitivity (left/right bars)
- Text size controls for both tables (Tiny to Huge)
- Visual element toggles (candles, background, label, tables, plots)
The indicator automatically detects chart theme (dark/light) and adjusts text colors for optimal readability.
Practical Application
This is a context tool, not a signal generator. Use it to:
- Filter trend-following strategies to trending regimes only
- Identify range-bound conditions for mean-reversion setups
- Anticipate breakout opportunities during compression phases
- Reduce exposure during transitional periods with mixed signals
- Improve risk management by matching position size to regime clarity
The indicator works on all timeframes and instruments using only OHLC data. Higher timeframes generally provide more stable regime classifications.
Alert Conditions
Four alert types are available:
- Efficiency Ratio crosses trend threshold
- Choppiness Index enters range territory
- Volatility squeeze released
- Regime state change detected
Technical Notes
Built with Pine Script v5. Uses up to 500 bars of historical data for stable calculations. All metrics are calculated in real-time with no repainting on confirmed pivots. Compatible with all chart themes through adaptive text coloring.
Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice or trading recommendations. Past performance and theoretical analysis do not guarantee future results. Always conduct independent research and implement appropriate risk management. Trading financial instruments involves substantial risk of loss.
Usage Philosophy
The goal is not to trade more frequently, but to think more clearly about market conditions. Use this tool to develop deeper intuition about market structure and to enforce discipline by avoiding low-probability setups during unfavorable regime conditions.
Nested SMA WaveThe "Nested SMA Wave" is a custom Pine Script (v5) indicator for TradingView that overlays a series of 8 Simple Moving Averages (SMAs) on the price chart. These SMAs use exponentially increasing lengths based on powers of 2, starting from a user-defined base length (default: 25). This creates lengths like 25, 50, 100, 200, 400, 800, 1600, and 3200.
Each SMA is plotted in a distinct color, forming a "wave" of nested lines that fan out from short-term (faster, more responsive) to long-term (slower, smoother). Semi-transparent colored fills (shaded zones) are added between consecutive SMAs, with customizable toggles and transparency levels, creating layered visual bands that highlight the spaces between different trend timescales.
Use Cases
Multi-Timeframe Trend Visualization: The power-of-2 nesting approximates higher timeframe trends on lower timeframes without switching charts. Shorter SMAs react quickly to price changes, while longer ones show major trends, helping identify overall market structure at a glance.
Support/Resistance Identification: Price interacting with the SMA lines or shaded zones can act as dynamic support/resistance. Crossovers between nested SMAs signal potential momentum shifts.
Trend Strength and Alignment: When SMAs are widely spaced and aligned (e.g., all sloping up), it indicates strong trends. Converging or crossing SMAs suggest consolidation or reversals. The shaded zones add depth, making expansions/contractions in volatility or trend power visually obvious.
Ribbon-Style Trading: Similar to moving average ribbons, traders can look for price pulling back to inner zones for entries in the direction of the broader "wave," or use zone breaks for signals.
Customization for Different Assets/Timeframes: Adjust the base length (e.g., smaller for crypto volatility, larger for stocks) and toggle shades to reduce clutter.
This creates a visually rich, rainbow-like overlay that's particularly useful for trend-following strategies on any chart.
Monthly Financial Liquidity Proxy Seasons 2.0The Skylark Digital Assets Monthly Financial Liquidity Proxy (FLP) — Seasons 2.0 converts a long-horizon liquidity signal into a clean, regime-based seasonal map that helps identify where markets likely sit in the broader liquidity cycle.
Core signal: A monthly composite liquidity proxy, normalized so diverse markets can be combined into a single, comparable oscillator.
Smoothing layer: A 12-month EMA is used to reduce noise and emphasize durable regime shifts.
Season regimes (EMA-based):
Winter (Blue): EMA ≤ 49 → tighter liquidity / risk-off tendency.
Spring (Yellow): EMA 50–59 → improving liquidity / transition regime.
Summer (Green): EMA ≥ 60 → abundant liquidity / risk-on tendency.
Fall (Red): triggers on 3 consecutive declining EMA months, only if EMA is ≥ 50 → late-cycle cooling/rollover behavior.
Anti-“blip” logic (Seasons 2.0): A new season is only recognized after it persists for at least 3 months, filtering out 1-month regime flickers.
Visual backfill: Once a season is confirmed (month #3), the script visually backfills the prior months so the regime appears from the start of the run—without changing the underlying confirmation rule.
Net: Monthly FLP Seasons 2.0 is a cycle-context tool—built to highlight durable liquidity regimes and transitions, not to overreact to short-term noise.
Skylark Digital Assets Daily FLP SnapshotThe Skylark Digital Assets Daily Financial Liquidity Proxy (Daily FLP) is a snapshot-style indicator designed to track the market’s current liquidity tone using a single standardized daily reading.
What it measures: A daily composite “liquidity impulse”—whether conditions are broadly tightening or easing across key global risk and rate benchmarks.
How it’s built (high level): It blends multiple major markets into one equal-weighted composite, using a normalized momentum framework so very different assets can be compared on the same scale.
Why “snapshot-safe”: The daily value is computed as a stable daily print (one clean value per day), so it avoids noisy intraday flicker and stays consistent when viewed on different chart timeframes.
How to interpret it:
Higher readings generally align with easier financial conditions / risk-on regimes.
Lower readings generally align with tighter conditions / risk-off regimes.
The Daily FLP is most useful for regime context, not as a standalone trade trigger.
How it’s used: As a macro timing and risk-management overlay—a way to contextualize positioning, confirm broader market shifts, and monitor transitions from tightening to easing (and vice-versa).
Skylark Digital Assets Monthly Financial Liquidity IndexThe Monthly Financial Liquidity Proxy (FLP) is a standardized, oscillator-style measure of broad financial conditions. Seasons 2.0 is the public-facing framework that translates the FLP into four regime “seasons” to help describe where liquidity sits within a recurring cycle.
What “Seasons 2.0” does
Converts the monthly FLP into a clear regime map (Winter / Spring / Summer / Fall).
Uses explicit thresholds + persistence rules to reduce noise and avoid one-month regime “blips.”
Designed for macro framing and cycle context (not a single-indicator trading system).
