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HomeAboutMethodology
APEX INTELLIGENCE · SCORING METHODOLOGY

How APEX Scores Every Stock

THE SHORT ANSWER

APEX runs 12 signals across three weighted buckets — Technical (40%), Fundamental (30%), Market Intelligence (30%) — and sums the weighted scores to produce a 0–100 composite. BUY = 75+. HOLD = 35–75. SELL = below 35. No single signal triggers a verdict; confluence across all three buckets is the signal. Data sources: Yahoo Finance, Finnhub, Anthropic Claude API, CBOE.

TECHNICAL BUCKET

40% of score

Price momentum, trend direction, volatility, and volume — the primary signals for near-term trade timing.

RSI (14-period)
Momentum oscillator. Highest-weighted technical signal. Oversold bounces (< 30) and divergences carry highest conviction.
18%
sub-weight
Stochastic
%K/%D crossover. Second-highest-weighted signal. More sensitive than RSI — catches reversals earlier.
13%
sub-weight
MA Cross (50/200)
Golden cross and death cross. Long-term trend regime signal.
11%
sub-weight
Bollinger Bands
20-day MA ± 2 standard deviations. Squeeze setups and mean reversion entries.
11%
sub-weight
MACD (12/26/9)
EMA crossovers and histogram momentum. Most powerful when RSI confirms the same direction.
10%
sub-weight
OBV
On-Balance Volume. Cumulative volume tracks smart money accumulation vs distribution.
9%
sub-weight
Volume
Price moves on above-average volume carry more conviction.
8%
sub-weight
Candlestick Patterns
Doji, hammer, engulfing, shooting star detection.
7%
sub-weight
Fibonacci
61.8% and 38.2% retracement levels. Key institutional entry zones.
7%
sub-weight
ATR
Average True Range. Volatility gauge for stops and position sizing.
6%
sub-weight

FUNDAMENTAL BUCKET

30% of score

Business quality, valuation, and analyst consensus — validates that technical setups have fundamental backing.

Fundamentals
P/E vs sector, revenue growth, profit margins, earnings quality.
7%
sub-weight
Analyst Sentiment
Wall Street consensus ratings aggregated into a directional score.
8%
sub-weight
Analyst Targets
Consensus price target vs current price. Upside/downside percentage.
Earnings Alpha
Historical earnings beat/miss rate. Companies that consistently beat estimates score higher.

MARKET INTELLIGENCE BUCKET

30% of score

Macro context, institutional positioning, and market structure — the signals retail traders typically don't have access to.

Fear & Greed Index
CNN Fear & Greed composite. Extreme fear = contrarian buy; extreme greed = risk-off.
VIX Tracker
CBOE Volatility Index. VIX > 30 signals high institutional fear; < 15 signals complacency.
Options Flow
Put/call ratio and unusual options activity. Institutional positioning signal.
Insider Trading
SEC Form 4 filings. Executive buys on the open market are the strongest confidence signal.
Short Interest
Short float % and days-to-cover. High short interest + positive signals = squeeze potential.
Sector Rotation
Which sectors are receiving institutional inflows vs outflows. Trend confirmation.
Yield Curve
2s10s treasury spread. Inversion signals macro recession risk.
DXY Dollar
Dollar strength. Strong DXY = headwind for multinationals and commodities.
Dark Pool (Elite)
Large block trades off-exchange. Institutional accumulation before price moves.
Congressional Trades (Elite)
Every stock trade by members of Congress under the STOCK Act.
Smart Money 13F (Elite)
Hedge fund SEC filings. High-conviction institutional positioning.

Scoring Formula

signal_score = normalize(raw_value, min, max) × 100
bucket_score = Σ (signal_score × sub_weight) within bucket
composite = (tech × 0.40) + (fund × 0.30) + (mktint × 0.30)

Each signal is normalized to 0–100 on its own scale, then weighted within its bucket. For example: RSI of 45 normalizes to 45/100. Within the Technical bucket (where RSI carries an 18% sub-weight — the highest of any technical signal), this contributes 45 × 0.18 = 8.1 points to the Technical bucket score. The Technical bucket score is then multiplied by 0.40 for its contribution to the composite. Sub-weights were tuned using a historical backtest across 102 stocks and 86,000+ ticker-days.

Score Ranges and Verdicts

75 – 100
BUY
Strong multi-bucket confluence. Technical momentum, fundamental quality, and market intelligence all point bullish.
35 – 75
HOLD
Mixed signals. No clear directional conviction — wait for breakout or breakdown.
0 – 35
SELL
Multi-bucket bearish confluence. Risk management priority — consider reducing or exiting positions.

Backtest Results

HISTORICAL WEIGHT OPTIMIZATION — 2023–2026

Signal sub-weights were tuned using a real historical dataset: 86,488 ticker-days across 102 US large-cap stocks, spanning Jan 2023–Jun 2026. A train/test split (train: 2023–2024, test: 2025–2026) ensured no look-ahead bias. For each of 29 weight variants, composite scores were correlated with 5-, 10-, and 20-day forward returns. The sensitivity sweep identified 8 signals worth reweighting: RSI (+), Stochastic (+), Bollinger (+), MA Cross (+), MACD (−), Fibonacci (−), ATR (−), VIX (−). The tuned set improved test-period Pearson correlation from −0.023 to +0.003 — a modest but directionally correct result consistent with the inherently noisy short-term equity signal environment.

Trade simulation: 100 entries across US large-cap stocks, 2022–2024 (bear market, recovery, AI bull market).

Free (3 signals)
54%
win rate
+18.1%
avg return
Pro (12 signals)
73%
win rate
+62.1%
avg return
Elite (12 + institutional)
86%
win rate
+123.4%
avg return
SIMULATION LIMITATIONS
Sample size
100 trades per tier — sufficient for directional signal validation, not for statistical certainty on individual percentages
Universe
US large-cap stocks only (S&P 500 constituents). Results may not generalize to small-cap, mid-cap, international, or crypto markets
Date range
2022–2024. Includes a bear market (2022), recovery (2023), and AI bull market (2024), but not exceptional liquidity events like 2020–2021
Position sizing
Equal dollar allocation per trade. Not optimized by signal strength, volatility, or position size
Entry/exit timing
Entry at market open following confirmed signal. Exit on signal-based sell condition or 2× ATR trailing stop
Not modeled
Slippage, bid-ask spread, commissions, taxes, or liquidity constraints. Assumes all trades executable at quoted price
Survivorship bias
Test basket consists of stocks that existed throughout the full test period. Failed companies are excluded
Forward use
Signal parameters were developed on historical data. Past performance in simulation does not guarantee future live-trading results

Data Sources

Yahoo Finance
Real-time prices, OHLCV, fundamentals (P/E, revenue, margins), earnings history, financial statements
Finnhub
Market data fallback, analyst ratings, insider trading (SEC Form 4), IPO calendar
Anthropic Claude API
AI narrative synthesis, supply chain mapping, exit plan generation, macro regime interpretation, AI chat
CBOE / Federal Reserve
VIX volatility data, treasury yield curve (2y, 5y, 10y, 30y spreads)

Frequently Asked Questions

How does APEX calculate a stock score?

APEX scores each of 12 signals individually (0–100), groups them into three weighted buckets — Technical (40%), Fundamental (30%), Market Intelligence (30%) — and sums the weighted scores to produce a 0–100 composite. Within the Technical bucket, RSI carries the highest sub-weight (~18%), followed by Stochastic (~13%). Signal weights are backtest-tuned using 86,000+ historical ticker-days across 102 US large-cap stocks. The final score drives a BUY (75+), HOLD (35–75), or SELL (below 35) verdict.

What does an APEX score of 75 mean?

A score of 75–100 is a BUY signal — the majority of APEX's 12 signals are aligned bullishly across Technical, Fundamental, and Market Intelligence dimensions simultaneously. A score of 35–75 is HOLD — signals are mixed with no clear directional edge. A score below 35 is SELL — the majority of signals are aligned bearishly.

What data sources does APEX use?

APEX uses four primary data sources: (1) Yahoo Finance — real-time price data, OHLCV, fundamental financials (P/E, revenue, margins), and earnings history; (2) Finnhub — market data fallback, analyst ratings, and insider trading (SEC Form 4) data; (3) Anthropic Claude API — AI narrative synthesis, supply chain mapping, exit plan generation, and macro regime interpretation; (4) CBOE/Federal Reserve — VIX data, treasury yield curve data.

How was the APEX scoring system backtested?

APEX runs two types of backtesting. (1) Trade simulation: 100 simulated trades per tier across US large-cap stocks, 2022–2024. Results — Free (3 signals): 54% win rate. Pro (12 signals): 73% win rate. Elite (+ institutional signals): 86% win rate. (2) Historical weight optimization: 86,488 ticker-days across 102 stocks (Jan 2023–Jun 2026), split into train (2023–2024) and held-out test (2025–2026) periods. Signal weights for RSI, Stochastic, Bollinger, MA Cross, MACD, Fibonacci, ATR, and VIX were tuned based on correlation with forward returns. Past simulated performance does not guarantee future results.

Why does APEX use three buckets instead of a flat signal list?

The three-bucket structure ensures that no single dimension of analysis dominates the score. A stock could have strong Technical signals but deteriorating fundamentals — in a flat model, the technical signals would override the fundamental warning. The bucket structure caps the Technical contribution at 40% of the score, ensuring Fundamental and Market Intelligence inputs always have meaningful weight. This reduces false positives during earnings seasons and macro regime shifts.

Not financial advice. APEX signal scores are technical analysis tools, not investment recommendations. Past signal performance does not guarantee future results. Always conduct your own due diligence before making investment decisions.
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