How to use AlphaScreen

From 10,000 tickers to a handful of high-conviction ideas — the funnel, the vocabulary, and a 60-second tour.

The Funnel — how we get to the best stocks

STEP 1 · ~10,000 tickers

Universe Scan

Every listed stock is scored daily for Relative Strength (RS) vs the S&P 500. Full Scanner

STEP 2 · Market check

Regime Gate

Only deploy when the Master Banner says the tape is FAVORABLE. Markets

STEP 3 · RS ≥ 90

Leaders Only

Keep the top decile — stocks outperforming 90% of the market. Sector Rotation confirms where money is rotating. Sector Rotation

STEP 4 · Tight bases

Setup Quality

Low RMV (volatility contraction) + industry strength = coiled springs, not extended chases.

STEP 5 · 5 picks

GEAR-SHIFT 🕹️

One melded engine picks the final few: RS leaders that also clear the breakout-timing gate, held for a 3-week sprint. GEAR-SHIFT

Backtest — GEAR-SHIFT across a full cycle (2019 → today, incl. the COVID crash)

Protocol: a 3-week sprint run continuously from mid-2019 through today across two real crashes — the COVID crash (Feb–Mar 2020) and the 2022 bear — $17k across 5 slots, next-open entries, OTOCO brackets (−8% stop / +35% target), 15-day max hold, on ~490 liquid US large-caps. GEAR-SHIFT = RS leaders gated by the breakout-timing engine. Educational research, not advice — read the caveats below.

StrategyCum. returnCAGRWin rateSharpeMax DD
GEAR-SHIFT 🕹️ + regime defend*+217.4%+17.8%46.7%1.18−17.0%
GEAR-SHIFT 🕹️ (entries always on)+186.9%+16.1%44.2%0.89−24.8%
RS-only (no breakout gate)+252.4%+19.5%40.0%1.11−25.0%
SPY+188.2%−33.7%
VTI+179.0%−35.0%

Cumulative return over ~7 years on a $17k book. *Regime defend = halt new entries when market breadth (% of the universe above its 50-day MA) drops below ~50% — validated 2026-07, rolling out. Simulated backtest, not audited live results.

What the crashes taught us: gating RS leaders through the breakout engine already beats the index with far lower drawdown (−24.8% vs SPY −33.7%). But the real edge in a crash is defending by not deploying: halting new entries when breadth thins turned the COVID crash and 2022 bear from losses into near-breakeven, cut full-cycle drawdown to −17.0%, and lifted the Sharpe to 1.18 — the best on the board. Crucially, it defends by withholding capital, not by selling winners — force-flattening the book on a signal was the worst variant we tested (it amputates the trades that reap the profit).

Caveats: the universe is current large-caps, so delisted losers are absent — survivorship bias flatters returns in the crash windows (recovery capture is overstated), so trust the drawdown/Sharpe improvements more than the headline returns. Treat the strategy ranking as robust and the absolute returns as illustrative.

Why a 44% win rate still makes money

Most GEAR-SHIFT trades lose — and the book still compounds. The reason isn't win rate, it's payoff asymmetry. With a −8% stop and a +35% target, each winner is worth ~4.4× each loser, so the break-even win rate is only:

break-even = 1 / (1 + reward/risk) = 1 / (1 + 4.4) ≈ 19%

At a 44% win rate we're more than double break-even. Worked example — risk 1 unit to make 4.4, ten trades, 4 winners / 6 losers:

  • 4 wins × +4.4 = +17.6
  • 6 losses × −1.0 = −6.0
  • Net = +11.6 — profitable despite 60% of the trades losing.

The four winners dwarf the six losers. That's the trader's maxim "80% of trades are a wash; the 20% reap the profits": the −8% stop minimizes each loss while the +35% target and 15-day exit let winners run. It's the casino inverted — a casino tilts the probability with an even payoff; GEAR-SHIFT accepts a sub-50% probability and tilts the payoff. Both are "the house." The catch: a low win rate means losing streaks, so the whole game is surviving the streaks (tight stops + regime defend) long enough for the fat-tail winners to arrive.

Tuning the entry — how close to buy, how far to run

Two knobs set a low-risk entry: how tight to the 21-EMA you buy, and how far you let a winner run before taking profit. We swept both across the full cycle (2019→today) on the explosive-leader universe. Greener = better risk-adjusted return (Sharpe).

Sharpe ratio — entry band (rows) × reward target (cols) 2R 2.5R 3R 4R reward target (how far you let a winner run) → ±2% 0.89 0.77 0.90 1.00 ±3% 0.97 0.79 0.79 0.84 ±4% 0.90 0.66 0.75 0.77 ±5% 0.88 0.76 0.87 0.91 ±6% 0.68 0.57 0.71 1.05 ±8% 0.47 0.30 0.41 0.54 ← tighter entry to the 21-EMA ◇ SWEET SPOT DRAWDOWN CLIFF

The pattern is unambiguous: enter tight to the 21-EMA (±2–3%) and let winners run to ~4R — Sharpe ≈ 1.0 at roughly 15% drawdown. Loosening the entry past ±6% falls off a drawdown cliff — you start buying names that have already run. (The lone bright cell at ±6%/4R is a fragile outlier, not the robust choice.) The same principle drives GEAR-SHIFT’s exit: buy near support, then let the winner run.

How to read a card — the core concepts

The terms every card uses, in plain language. These same definitions appear as hover tooltips on the stage and setup tags across the site.

Glossary — product terms

RRG (Relative Rotation Graph)
A map of sectors/stocks rotating through Leading → Weakening → Lagging → Improving quadrants vs the benchmark.
Sprint
A time-boxed (3-week) basket of the highest-RS setups. Backtests show the time limit itself adds return — capital never sits in stalled names.
HMM (Hidden Markov Model)
A statistical engine that estimates the probability a stock is entering an "explosive" state; it opens up to 5 positions when strict entry gates pass.
DCR
Daily Closing Range — where price closed within the day's range (100 = at the high). Persistent high DCR signals accumulation.
Market Gate / Master Banner
A go/no-go switch computed from SPY trend + volatility. When closed, engines stop opening new positions.
MPT Barbell
An ETF portfolio mixing low-beta hedges + a core + high-beta growth, rebalanced by rules — diversification with a momentum engine.

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Educational research tool — not investment advice. Markets involve risk of loss.