Question

Identify at least two accounting measures that are used in empirical asset pricing models and explain how these measures can be used to identify assets that are expected to have higher returns in the future.

Answer 1

Accounting measurement is the computation of economic or financial activities in terms of money, hours or other units. An accounting measurement is a unit of some measurable element that is used to compare and evaluate accounting data. Accounting is often quantified in terms of money but can also be recorded in terms of alternative units, number of labor hours, number of jobs created, etc. Different accounting measurements provide different views of the overall health of the corporation. By using a variety of different accounting measurements, a person can gain a more comprehensive view of a company's operations and more easily compare them with those of other companies.

We provide evidence that the empirical performance of the new factor models proposed by Hou, Xue, and Zhang (2015) and Fama and French (2015) depends crucially on how their investment factor is constructed. Specifically, we call attention to the fact that, in both models, the investment factor is based on the measure of growth in total assets from Cooper, Gulen, and Schill (2008) and not on what most researchers would view as traditional measures of corporate investment. For both models, we show that there are large decreases in their ability to price the cross-section of returns when the investment factor is instead constructed using the traditional investment measures, or when it is constructed using arguably more complete measures that account for investment in intangibles. Additionally, we do not find a significant decrease in performance when we replace the asset-growth factor with a factor based on growth in noncash current assets or long-term debt (which cannot be complete measures of investment). Our results challenge the idea that traditional investment models can fully account for the explanatory power of the asset-growth factor used in the Hou, Xue, and Zhang (2015) and Fama and French (2015) models.

the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field.

The final outcome of the study is a significant empirical specification that explains average returns in terms of the covariance risk and accounting accruals where the parameter estimates are robust at all conventional levels. Exogenously, accounting accruals may be interpreted as a measure of the firm-specific information risk faced by investors. The specification suggests that in addition to the systematic risk, the investor prices private information that management conveys via accounting accruals, which is both firm-specific and one that mitigates the information risk. In the spirit of Fama and French (1993; 1995; 2015),

the concluding specification suggests that growth, value, cash flows, and investments are redundant and that a two-factor model of beta and accruals performs as well as the six-factor model estimated by the unrestricted.