About

Quantitative equity rankings
grounded in research.

AlphaPanel is a multi-factor ranking engine that scores US equities on a 0–100 scale. The Smart Score synthesizes signals rooted in well-documented market anomalies — cross-sectional momentum, trend recovery dynamics, and relative strength persistence — each supported by decades of academic and practitioner research.

The model is adaptive. Factor weights shift based on prevailing market structure, giving more influence to trend-following signals in directional regimes and adjusting exposure during periods of elevated dispersion or mean reversion. The goal is a score that stays useful across market environments, not one that's optimized for a single regime.

The universe is filtered to liquid, institutional-grade equities — the kind of stocks you can actually execute on without moving the market. Every signal is validated out-of-sample across bull markets, drawdowns, rate cycles, and sector rotations before it earns a place in the composite.

Research foundation

The Smart Score draws on factor premia that have been studied extensively in financial economics. The core signals include:

1
Cross-sectional momentum

The tendency for recent relative winners to continue outperforming over intermediate horizons. First documented by Jegadeesh and Titman (1993) and confirmed across geographies, asset classes, and time periods. One of the most robust anomalies in empirical finance.

2
Trend recovery dynamics

Stocks that have traveled the farthest from their trailing low points exhibit stronger forward returns than those still near their lows. This signal captures structural recovery and distinguishes between stocks in active uptrends and those grinding sideways — a dimension that standard momentum misses.

3
Relative strength persistence

The observation that leadership tends to cluster and persist over multi-month windows. Stocks that rank highly on composite strength metrics show a measurable tendency to sustain that ranking, creating a window for systematic rebalancing to capture ongoing outperformance.

4
Adaptive factor weighting

Rather than applying static weights, the model evaluates which signals are contributing most effectively in the current environment. In strong trending markets, momentum signals receive higher emphasis. During regime transitions, the model tempers its conviction — reducing exposure to signals that historically degrade during inflection points.

How we build

Out-of-sample first

No signal makes it into production without passing validation on data the model has never seen. If it only works in hindsight, it doesn't ship.

Regime-aware

Markets aren't stationary. The model is tested across expansions, drawdowns, rate hikes, and rotations — and is designed to adapt rather than break.

Minimal complexity

More parameters means more ways to overfit. We keep the factor set lean and intentional. Everything in the model has to justify its inclusion with persistent, independent edge.

Continuous research

The current model is not the final model. We're actively evaluating additional signals, expanded universes including international equities, and alternative weighting schemes.

What AlphaPanel is

A systematic ranking engine built on documented factor premia
A screener for identifying relative strength across 1,000+ equities
A research tool with full backtest transparency including losing periods
An adaptive model that adjusts to changing market structure

What it is not

Financial advice or a recommendation to buy or sell any security
A short-term trading signal or intraday indicator
A guarantee of future performance
A replacement for independent analysis and risk management

FAQ

Built by a team that allocates real capital using this model.

AlphaPanel — Quantitative equity rankings.
Not financial advice·v2.0