Ilan Cooper

A Global Macroeconomic Risk Model for Value, Momentum, and Other Asset Classes

Value and momentum returns and combinations of them are explained by their loadings on global macroeconomic risk factors across both countries and asset classes. These loadings describe why value and momentum have positive return premia and why they are negatively correlated. The global macroeconomic risk factor model also performs well in summarizing the cross section of various additional asset classes. The findings identify the source of the common variation in expected returns across asset classes and countries suggesting that markets are integrated.

The Factor Structure of Time-Varying Discount Rates

Discount rate variation is driven by a short run business cycle component and a longer run trend component. This leads to state variable hedging of these two components and ICAPM logic implies a three factor model for expected returns. One factor represents cash flow news and the two other factors represent short term and long term discount rate news. News about both these discount rate components is important in describing the cross section of stock returns. Consistent with the predictions of leading asset pricing models, long run discount rate news is priced consistently across different samples and specifications and commands a higher risk premium than short run discount rate news.

Risk Aversion Sensitive Real Business Cycles

Technology choice allows for substitution of production across states of nature and depends on state dependent risk aversion. In equilibrium, endogenous technology choice can counter a persistent negative productivity shock with an increase in investment. An increase in risk aversion intensifies transformation across states, which directly leads to higher investment volatility. In our model and the data, the conditional volatility of investment correlates negatively with the price-dividend ratio and predicts excess stock market returns. In addition, the same mechanism generates predictability of consumption and produces fluctuations in the risk-free rate.

Factor Dispersion and Cross-sectional Risk Premia

I propose a new risk-based explanation of momentum by deriving a simple two-factor asset pricing model, which contains the market return and stock return dispersion as risk factors. This model offers a large fit for portfolios sorted on momentum and industry momentum, with cross-sectional R^2 estimates around 80%. Past losers are more positively correlated with return dispersion, which earns a negative price of risk, and hence the lower risk premia earned by those stocks. The model compares favorably with some of the most popular multifactor models in the literature, and also helps explaining the earnings momentum and profitability anomalies.

Multifactor Models and the APT: Evidence from a Broad Cross-Section of Stock Returns

We examine the consistency of several prominent multifactor models from the asset pricing literature with the Arbitrage Pricing Theory (APT) framework. We follow the APT-related literature and estimate the common factor structure from a cross-section containing 420 equity portfolios (associated with 42 major CAPM anomalies) by employing the asymptotic principal components method. Our benchmark model contains six statistical factors and clearly dominates (both in economic and statistical terms) most of the empirical multifactor models. These results represent a critical challenge to the current workhorse models in terms of explaining large-scale portfolio equity risk premia and achieving consistency with the APT.

New Evidence on Conditional Factor Models

We estimate conditional multifactor models over a large cross-section of stock returns associated with 25 alternative CAPM anomalies. Using conditioning information significantly improves the performance of the multifactor models of Hou, Xue, and Zhang (2015, HXZ) and Fama and French (2015, 2016). Both models have a similar global fit, yet HXZ clearly dominates other models in terms of pricing the extreme portfolio deciles and the cross-sectional dispersion in equity risk premia. Thus, the asset pricing implications of alternative investment and profitability factors differ significantly in the large cross-section of stocks. The HML factor is largely redundant when using conditioning information.

The Cross-Section of Industry Investment Returns

Firm level characteristics explain the cross section of investment returns of industry portfolios that include listed and unlisted firms. Moreover, common asset pricing models explain the cross-sectional variation of characteristic-based investment returns which include listed and unlisted firms. Assuming that managers of unlisted fi rms are less likely to be affected by investor misvaluation and are less likely to overinvest, our results are consistent with a rational interpretation of the role of characteristics. Given a portfolio characteristic, there are no systematic differences in expected investment returns for listed and unlisted fi rms suggesting their cost of equity are unrelated to whether a rm is listed or unlisted.