Arbitrage Pricing Theory and Multi-Factor Models › Summary

This chapter developed the Arbitrage Pricing Theory framework and its practical implementation through multi-factor models. The key concepts covered include:

APT provides a general equilibrium-free framework for asset pricing. By assuming a factor structure for returns and imposing no-arbitrage conditions, APT derives a linear relationship between expected returns and factor exposures without requiring CAPM's restrictive assumptions.

Multi-factor models explain returns through multiple systematic risk sources. The Fama-French factors (market, size, value, profitability, investment) and momentum have become standard tools for understanding return variation and evaluating performance.

Factor loadings are estimated through time-series regression. Regressing asset excess returns on factor returns yields estimates of systematic risk exposures and alpha. Cross-sectional regression provides estimates of factor risk premia.

Factor models enable risk decomposition and attribution. Total portfolio risk splits into systematic (factor) and idiosyncratic components. This decomposition supports risk budgeting, performance attribution, and portfolio construction.

Factor premia vary over time and may not persist. Historical evidence shows meaningful factor premia, but individual periods can differ dramatically from long-term averages. Whether premia reflect risk compensation, behavioral biases, or data mining remains debated.

The next chapter on Portfolio Performance Measurement will build on these concepts, showing how to evaluate investment returns after accounting for factor exposures and risk taken.