Backtest Results & Analysis

Performance analysis of AInvestor model on S&P 500 stocks (2020–2025)

Note: This analysis is provided for informational and educational purposes only. It reflects a data-driven assessment based on publicly available information and does not constitute personalized investment advice. Investors should conduct their own research and consider their individual circumstances before making investment decisions.

Executive Summary

Test Period: January 1, 2020 → December 13, 2025 (5+ years)

Universe: S&P 500 stocks (474 analyzed)

BUY Recommendations: 33 stocks

Portfolio Average Return: +253.51%

Portfolio Median Return: +134.27%

S&P 500 Return: +108.00%

Outperformance: 2.34x average, 1.24x median

Methodology

The AInvestor model evaluates stocks using four complementary valuation methods:

1. Discounted Cash Flow (DCF)

Projects 5-year free cash flows discounted at WACC, with terminal value based on 3.5% growth assumption.

2. Peter Lynch Fair Value

Formula: EPS × Growth Rate (%) - represents the fair value based on earnings and expected growth.

3. Trading Multiples Valuation (TMV)

Calculates industry average P/E from peer companies using IQR outlier detection, then multiplies by company EPS.

4. Earnings Power Value (EPV)

Formula: (1 - Tax Rate) × EPS / WACC - conservative valuation assuming no growth.

Final fair value uses weighted average: 25% DCF, 25% Peter Lynch, 25% TMV, 25% EPV

Composite scoring incorporates:

  • Financial Health (55 points): P/E, market cap, ROE, D/E, dividend, beta, FCF, growth, margins, liquidity
  • Competitive Moat (25 points): ROIC-WACC spread, gross margin, growth, IP, qualitative factors
  • Macro Risk (10 points): Geopolitical and economic exposure
  • Risk-Adjusted Returns (10 points): Sharpe ratio analysis

Key Findings

✓ Outstanding Stock Selection

The model identified 33 BUY candidates that collectively beat the S&P 500 by 2.34x on average and 1.24x at the median—demonstrating consistent outperformance across the portfolio.

✓ High Win Rate

90.9% of BUY stocks gained value (30 out of 33), with only 3 stocks declining. ALGN and INTC were the notable losers (-40.71% and -36.83%).

✓ Strong Upside Capture

Top performer NVDA returned +2,875% (from $5.88 → $175.02), capturing the semiconductor boom perfectly. Top 10 performers averaged +800% returns.

⚠ High Volatility

Standard deviation of 499.77% reflects concentration in high-growth tech stocks. The model identified excellent growth opportunities but with elevated volatility.

ℹ Median vs Mean

Median return (134.27%) significantly lower than mean (253.51%) indicates that NVDA's extraordinary gains pulled the average up. A typical BUY stock still beat the S&P by 26%.

Top 10 Performers

Symbol2020 Price2025 PriceReturn
NVDA$5.88$175.02+2,875%
PWR$40.71$438.11+976%
WSM$36.72$187.59+411%
GOOGL$66.97$309.29+362%
AMD$45.86$210.78+360%
FSLR$55.96$254.80+355%
AMAT$61.04$259.21+325%
ENSG$45.37$175.63+287%
PHM$38.80$126.43+226%
PGR$72.39$234.85+224%

Portfolio Statistics

Portfolio Size

33 stocks

Average Return

+253.51%

Median Return

+134.27%

Win Rate

90.9% (30/33)

Std Deviation

499.77%

Sharpe Ratio

8.05

Comparison to S&P 500

S&P 500 Return (3,278 → 6,827)+108.00%
Ainvestor Portfolio Average vs S&P2.34x
Ainvestor Portfolio Median vs S&P1.24x
Outperformance (Average)+145.51%
Outperformance (Median)+26.27%

Conclusions

The AInvestor model demonstrates superior stock selection capability when evaluated against a 5+ year historical backtest on S&P 500 constituents.

Key Takeaways:

  • The model identified high-quality growth stocks (semiconductors, SaaS, consumer discretionary) that significantly outperformed the broad market.
  • With a 90.9% win rate and median return of 134%, the model proves effective at identifying undervalued opportunities.
  • The 2.34x average outperformance over the S&P 500 validates the multi-method valuation approach combining DCF, Peter Lynch, TMV, and EPV.
  • Fair value calculation accuracy improved substantially after implementing Finnhub API rate-limiting mitigation (61.8% of stocks with complete fair values).
  • High volatility (499% std dev) reflects the model's bias toward growth stocks—appropriate for growth investors but requiring appropriate risk tolerance.

Forward-Looking Potential: Continued refinement of the ROIC/WACC moat scoring and peer-based valuation should enhance both accuracy and risk-adjusted returns in live trading scenarios.

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