An all-in-one institutional toolkit that maps market structure, supply and demand zones, hidden liquidity pools and high-probability reversal patterns — built to align your analysis with smart money concepts.

A multi-component trend toolkit built around four independent systems — Bias Magnet, Flux Trend, Surge Waves and Velocity Bands — plus a real-time dashboard, with one-click profiles for scalping, intraday, swing or long-term styles.

An ICT-inspired toolkit that automatically detects and highlights the key areas of potential support and resistance, marking order, breaker, rejection and suspension blocks on the chart.

An ICT-rooted toolkit that detects market imbalances — the inefficiencies price leaves behind — and highlights them as high-probability support, resistance and reversal zones.

A centered momentum tool plotting a single line on a fixed −1 to +1 scale, where 0 marks balance and pushes beyond ±1 highlight stretched conditions — with optional layers for trend bias, participation and divergences.

A statistical breakout and exhaustion indicator that adapts to market conditions using the Student-T Distribution — a single source of truth for shifts in volume-weighted fair value and high-probability reversal points.

A multi-layered momentum engine that cross-references trend, capital flow and machine-learning probabilities — using Ehlers SuperSmoother signal processing and KNN to quantify market conviction instead of relying on a single data point.

An ICT toolkit that identifies daily market behavior templates from session highs and lows, marking previous, current and future daily profile context — with a scanner listing predicted profile scenarios for the current day.

An ICT toolkit that automatically detects weekly profile templates and displays the week's structure with a clear OHLC profile line, a missing-profiles layer for wider scenario coverage and a predicted-profiles scanner.

A market-microstructure suite combining higher-timeframe volume profiles, delta tracking, liquidity mappings and volume anomalies — showing where institutional volume clusters, where imbalances occur and where critical liquidity resides.

An institutional tool that deciphers the Power of 3 — accumulation, manipulation and distribution — bridging lower-timeframe entries with the higher-timeframe narrative so you trade in sync with daily, weekly or monthly expansion.

A full Candle Range Theory workflow: every candle is treated as a tradable range where price sweeps one side, reclaims back inside and distributes toward the opposite side, with the 50% midpoint as an early target.

A multi-timeframe model that pairs higher-timeframe context with lower-timeframe sweeps and CISD shifts, then projects objective liquidity targets and standard deviation levels for rules-based entries, risk and targets.

Detects and validates Swing Failure Patterns — where smart money sweeps liquidity but fails to sustain the move, trapping breakout traders — tracking each pattern from formation through confirmation, success or failure.

An ICT-style reversal model that fades false breakouts — price breaks a prior swing level, runs liquidity, then snaps back inside — packaging sweep, MSS confirmation, confluence and targets into one clean workflow.

An ICT Unicorn Model indicator spotting high-probability reversals: a zigzag structure detects the liquidity grab, a breaker-style structure confirms the formation, and macro time filters keep execution inside institutional windows.

A structured ICT checklist for high-probability longs and shorts: previous day high/low as external liquidity, 1-hour Fair Value Gaps as imbalance zones, and 15-minute MSS/SMT confirmation inside a multi-timeframe framework.

Identifies high-probability setups from core price action — market structure shifts and liquidity sweeps — then manages the trade with ATR-scaled take-profit levels and an adaptive trailing stop band.

Identifies and validates Breaker Block setups in real time — a sweep followed by a structure-breaking reversal that mitigates an old order block — highlighting both the swept liquidity levels and the resulting entry zones.

Links higher-timeframe sweeps with lower-timeframe structure shifts into precise Fair Value Gap entry models — mapping HTF candles, gaps and CE lines directly onto your chart so you never switch timeframes hunting for setups.

Maps institutional price delivery from historical OHLC data, using ICT accumulation, manipulation and distribution patterns to create high-probability support and resistance zones across timeframes and sessions.

A systematic way to read candlestick delivery: maps average manipulation, distribution and time pivots for a chosen timeframe, helping you understand why a candle printed the way it did and where price reaches next.

Maps session-based OHLC statistics into actionable levels — projecting where price commonly pulls (manipulation) and where it expands next (distribution), with timing pivots for each trading session.

Transforms ordinary candles into a macro-level roadmap, statistically projecting manipulation and distribution legs — and the timing pivots that shape delivery — to frame cleaner support and resistance from a data-driven view.

Breaks down each candle's OHLC behavior to show when volatility is expanding, where it clusters and how price is likely to deliver after manipulation-style wicks — making fast-moving conditions easier to read.

Shows how far price sits below its running all-time high as a percentage drawdown — near 0% at the ATH, deeper negatives at historic retracements — framing cycle context, DCA planning and capitulation awareness.

Tracks daily Bitcoin dominance with a configurable moving average and key dominance zones, so you can read when capital is rotating into Bitcoin (BTC-led phases) versus into altcoins (altcoin season conditions).

Compares an asset's Compound Annual Growth Rate to its Maximum Drawdown over the same period — using downside risk rather than volatility to quantify how efficient returns really are for capital preservation.

Measures the slope of the VIX curve with a linear regression across multiple volatility tenors — reading whether markets price complacency (contango) or stress (backwardation) in real time.

A market breadth oscillator that tracks the percentage of assets in a chosen index trading above a selected moving average — spotting broad pullbacks, measuring participation and judging whether moves are broadly supported.

Aggregates global M2 money supply across 19 major economies, converted to USD, and plots the total alongside its year-over-year growth — a clean backdrop of worldwide liquidity for risk assets.

A rules-based framework for long-term investors combining a time-aware moving average, standard deviation bands and anchored VWAPs to spot fair-value magnets, over/under-valuation zones and regime shifts from days to decades.

Quantifies global risk-on versus risk-off conditions in a single score, aggregating 30+ components across equities, fixed income, commodities, FX, volatility and policy proxies — each z-score normalized and custom-weighted.

Normalizes major assets to a base value of 100 from a chosen date, so you can instantly see which markets are leading, lagging or rotating across equities, bonds, cash, credit, commodities, currency and crypto.

Enhances the classic Mayer Multiple with Z-Score normalization — measuring how far price deviates from its 200-day average in standard deviations to spot overextended rallies and deep discounts without subjective judgment.

Compresses statistical deviation into a clean 0–100 oscillator — normalizing distance from a moving average by standard deviation to flag overbought/oversold conditions and snap-back zones around the mean.

Turns raw price swings into a measurable momentum pulse using log returns, colored with an adaptive volatility-based gradient and optional fixed thresholds — making regime shifts, impulse moves and mean-reversion opportunities easy to spot.

Measures monthly-style price speed with a Rate of Change calculation over roughly 30 days — showing how fast price is moving, not just direction, with a zero baseline and an optional overheated burst level.

Plots on-chain MVRV for BTC or ETH with classic reference levels and optional standard deviation bands — spotting historical euphoria and stress conditions to size crypto cycle position.

Measures risk-adjusted performance by comparing returns that exceed a chosen hurdle against those that fall short — a rolling Omega where above 1.0 is favorable and strong regimes often read 1.5–2.0.

Plots return on investment over a fixed window — 1M, 3M, 6M, 1Y or custom days — calculated from daily closes, so trend strength and market rotation can be judged at a glance.

A bird's-eye view of where capital is flowing across the standard US sectors — calculating relative strength and volume, classifying rotation phases and anchoring sectors to the four stages of the economic cycle.

Measures excess return per unit of volatility — how efficiently an asset is rewarded for the risk it takes — with configurable return models, annualization and smoothing for a decision-ready read.

Plots the cyclically adjusted P/E ratio anchored to 10 years of inflation-adjusted earnings, visualizing fair-value zones, extreme overvaluation peaks and generational buying opportunities across 140+ years of history.

Like Sharpe, but only downside volatility counts — measuring excess return per unit of downside deviation relative to a minimum acceptable return, with percentile or fixed-level views.

A standardized Z-score oscillator blending price deviation, relative volume weighting and adaptive volatility scaling to flag deep undervaluation (accumulation) and excessive euphoria (distribution).

Converts price into a rolling Z-score — distance from the mean in standard deviations — and displays it as a smooth color-graded wave, with sigma tiers optionally converted into live price levels.

A Tom DeMark-inspired oscillator measuring demand by comparing intra-period extremes to previous levels — focusing on highs and lows rather than closes to catch overextended trends and reversal points.

Maps Bitcoin's key valuation zones by comparing price against its Realized Price — derived from realized market cap divided by supply — with bands, an MVRV-style oscillator and valuation-based signals.

Measures the divergence between the true growth of global money supply and a selected market index — blending central bank M2 data with optional Fed net liquidity to flag deep value zones when liquidity outpaces price.

Analyzes volatility as a series of distinct regimes rather than a single oscillator — classifying states, tracking persistence and validating with bond volatility and credit spreads to output a dynamic trading bias.

Visualizes an asset's historical monthly performance as a calendar heatmap — highlighting seasonal trends and long-term performance with up to 30 years of data and automatic year-to-date calculations.

Compares average historical monthly performance across a broad basket of assets — identifying cross-asset seasonal trends with quarterly grouping and multiple calculation modes.

A modular dashboard tracking the market dynamics of major US spot Bitcoin ETFs — consolidating daily flow data into institutional capital momentum with multiple formats and an intelligent scoring system.

A multi-metric composite oscillator gauging whether capital is flowing toward Bitcoin or altcoins — aggregating four independent metrics into a single noise-reduced 0–100 index.

Gauges market volatility and risk by applying a Z-Score normalization to the VIX over a configurable lookback — flagging statistical extremes of fear (overbought) and complacency (oversold).

An institutional-grade allocation model synthesizing five market pillars — regime, risk, valuation, sentiment and macro — into a dynamic 0–100% equity weighting, with automated crisis detection to de-risk in extreme conditions.

A modular dashboard tracking capital rotation across major US SPDR sector ETFs — consolidating daily inflow and outflow data to identify sector leadership and risk appetite in the broader market.

Measures the symmetry of an asset's return distribution by comparing extreme positive returns to extreme negative ones — revealing hidden tail risk that volatility-based indicators often miss.

A statistical oscillator measuring how far price has deviated from its historical baseline using a rolling Z-Score — highlighting overextended conditions ripe for reversion to the mean.

Analyzes the option-adjusted spread between High Yield and Investment Grade corporate bonds, standardized into a Z-Score, to flag credit stress and macro risk-on/risk-off regimes before they fully appear in equities.

Aggregates 12 technical factors — momentum, trend direction, volume and volatility — into a single visual heatmap with a conviction dashboard, instead of cluttering the chart with a dozen separate indicators.