A factor table in stock trading is a structured dataset that quantifies various attributes of stocks to help traders and investors make data-driven decisions. These factors are typically categorised into fundamental, technical, macroeconomic, and sentiment-based metrics.

1. Fundamental Factors
These assess a company’s financial health and valuation:

Value Metrics: P/E ratio, P/B ratio, dividend yield.

Profitability: ROE (Return on Equity), ROA (Return on Assets), gross margin.

Leverage & Risk: Debt-to-equity ratio, interest coverage ratio.

2. Technical Factors
These analyse price trends and market behaviour:

Momentum: 12-month price return, RSI (Relative Strength Index).

Volatility: Beta, standard deviation of returns.

Trend Indicators: Moving averages (50-day, 200-day), MACD.

3. Macroeconomic & Industry Factors
External conditions affecting stock performance:

Interest Rates & Inflation: Sensitivity to Fed policy changes.

Sector-Specific Metrics: Oil prices for energy stocks, consumer sentiment for retail.

4. Sentiment & Behavioural Factors
Market psychology and trading activity:

Short Interest Ratio: High short interest may indicate bearish sentiment.

Volume & Liquidity: Average daily trading volume, bid-ask spreads.

Why Factor Tables Matter
By combining these factors, traders can:

Rank stocks based on quantifiable criteria.

Build multi-factor models (e.g., combining value + momentum).

Automate screening for algorithmic trading strategies.

Factor tables are essential for quantitative trading, smart beta ETFs, and risk management, helping traders systematically identify opportunities while minimising biases.