Factor Scores
Assign weights to each factor. The composite score ranks the top 100 S&P 500 stocks (by market cap, all major sectors) using z-scored, winsorised signals.
Set Momentum to 3 and all other factors to 1. Click 'Apply Weights' and observe which stocks rise to the top. Then try the opposite: set Value to 3 and Momentum to 0. How does the top-20 list change? This shows how different factor views produce different portfolios.
How Factor Scores Work
Each factor is z-scored (mean 0, std 1) and winsorised at ยฑ3ฯ to remove outliers. The composite score is a weighted sum: Score = ฮฃ wแตข ร zแตข. Adjust the sliders to see how different factor tilts change the stock ranking.
Factor Construction โ Academic Disclosure
Factor scores use a two-tier system: fundamental data from Yahoo Finance is preferred when available, with price-based proxies as fallback. Coverage varies by stock โ some may use fundamentals while others fall back to proxies.
- Value โ primary: inverse P/E ratio (Fama & French, 1992); fallback: negative 12-month price return (mean-reversion proxy).
- Size โ primary: inverse log market capitalisation (Banz, 1981); fallback: inverse share price.
- Quality โ primary: Return on Equity (Novy-Marx, 2013 uses gross profitability; ROE is a related proxy); fallback: trailing Sharpe ratio.
Momentum (12-month price return) and Low Volatility (inverse 252-day volatility) are correctly constructed from price data alone and match their academic definitions. Fundamental data availability depends on Yahoo Finance coverage โ typically 80โ90% of S&P 500 stocks.
The Factor Zoo Problem
Academic researchers have documented over 400 "factors" that appear to predict returns in historical data (Harvey, Liu & Zhu, 2016). The majority are likely false discoveries due to data mining and publication bias. This tool implements five of the most replicated factors: Momentum (Jegadeesh & Titman, 1993), Low Volatility (Ang et al., 2006), Value (Fama & French, 1992), Size (Banz, 1981), and Quality (Novy-Marx, 2013). Even these canonical factors have experienced multi-year drawdown periods and their premiums may be arbitraged away over time.
Reference: Harvey, C. R., Liu, Y., & Zhu, H. (2016). "โฆ and the Cross-Section of Expected Returns." Review of Financial Studies, 29(1), 5โ68.
12-1 month price return (skip last month to avoid short-term reversal). Stocks that have risen tend to keep rising (Jegadeesh & Titman, 1993).
Inverse of 252-day annualised realised volatility. Low-risk stocks earn higher risk-adjusted returns (Ang et al., 2006; Black, 1972).
Return on Equity (ROE) from yfinance fundamentals when available; falls back to excess-return Sharpe ratio. The canonical Quality factor (Novy-Marx, 2013) uses gross profitability (gross profit / total assets).
Earnings Yield (1 / trailing P/E) from yfinance fundamentals when available; falls back to negative 12-month price return. The canonical Value factor (Fama & French, 1992) uses price-to-book ratio.
Inverse log market capitalisation from yfinance when available; falls back to inverse log share price. Smaller firms earn a size premium (Banz, 1981; Fama & French, 1992 SMB factor).