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.

The Dip Index applied across the eleven S&P sector ETFs — a rotation map of how many sectors are participating in a move, and which ones are carrying it.

A single regime score built from volatility, trend and momentum — from crisis and risk-off dips to full risk-on, without stacking three separate indicators.

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.

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.

Price against a six-month average carried six months forward — the gap between current mood and the tone of lagging news, sorted into four states.

One risk reading of the macro backdrop from volatility, credit and the stocks-to-Treasuries ratio — each z-scored against its own trailing year and weighted.

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.

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.

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).

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.

How far price sits below its 200-day and 48-month averages — the tactical and generational capitulation thresholds, shaded while either is active.

A position sizer: volatility-scaled momentum across six horizons, cut back whenever the asset's own volatility runs above normal, and held until the target drifts.

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.

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.

Thirty Bollinger %B horizons stacked into one heatmap ribbon — where the close sits inside every band from 14 to 364 bars, and whether they agree.

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.

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.

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 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.

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.

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.

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.

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.