Asset Pricing Overview

Principles

Definition

Asset pricing is a core field within financial economics that investigates the theoretical and empirical relationship between the market price of a financial asset, the expected future cash flows it is anticipated to generate, and the associated risks. It seeks to develop models and frameworks to explain how financial markets value assets and determine expected returns based on risk and the time value of money.

Ontological type

Core Theories

Risk Factors

Empirical Methods

Key developments

Key Figures

Dynamic Multifactor Foundations era

Kenneth R. French [1] is associated with the Dynamic Multifactor Foundations era, with notable stints at the University of Chicago [3] and the University of Rochester [4] during 1971-1992. His key contributions in this era include linking cross-sectional stock-return patterns to factor loadings and macro state variables, as seen in the papers The Cross‑Section of Expected Stock Returns [6], Expected stock returns and volatility [7], and Dividend yields and expected stock returns [8], which together helped establish early intertemporal and no-arbitrage pricing insights. Eugene F. Fama [2] is linked to Cornell University [5] and the University of Chicago [3] during this era. His key contributions include the cross-sectional pricing framework exemplified by The Cross‑Section of Expected Stock Returns [6] and the relationship between dividend yields and expected stock returns [8], which were pivotal for modeling how investors hedge against changing investment opportunities and for laying groundwork for later asset-pricing tests.

Cross-Sectional Factor Consolidation era

Kenneth R. French [1] is a central figure in asset pricing during the Cross-Sectional Factor Consolidation era, with affiliations at Massachusetts Institute of Technology [3] and Yale University [4]. His key contributions in this era include identifying common risk factors in the returns on stocks and bonds [6] and documenting size and book-to-market factors in earnings and returns [7], which solidified a factor-based framework for pricing and risk premia in cross-sectional tests. Eugene F. Fama [2] is a defining figure in this era, with the University of Chicago [5] as a primary affiliation. His collaborative work on common risk factors in the returns on stocks and bonds [6] and on size and book-to-market factors in earnings and returns [7] helped establish the cross-sectional factor approach and the central role of risk premia in asset pricing.

Cross-Asset Regimes and Machine Learning era

Kenneth R. French[1] is a leading asset-pricing scholar affiliated with Cornell University[3] and Yale University[4] during this era of cross-asset regime-aware pricing. His key contributions include the five-factor asset pricing model[6], which extends prior factor work to better capture cross-asset risk premia and regime-sensitive pricing, and the analysis of size, value, and momentum in international stock returns[7], highlighting pervasive cross-market patterns essential for multi-asset frameworks in this era. Eugene F. Fama[2] is a foundational figure at the University of Chicago[5] during this period. His contributions include co-authoring the five-factor asset pricing model[6] and the study on size, value, and momentum in international stock returns[7], which helped anchor traditional and cross-market pricing foundations in regime-aware, multivariate settings.