The Accumulation of Human and Nonhuman Capital, 1948-84

A Bayesian asset-pricing test is developed that is easily computed in closed-form from the standard F-statistic. Given a set of candidate traded factors, we show how this test can be adapted to permit an analysis of Bayesian model comparison, i.e., the computation of model probabilities for the collection of all possible pricing models that are based on subsets of the given factors. We find that the recent q-factor model is superior to the Fama-French three-factor model augmented by profitability and net investment factors, but both models are dominated by five or six-factor models that include a momentum factor and value and profitability factors that are updated monthly. Thus, although the standard value factor is redundant, our tests show that a version that incorporates more timely price information is not.

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Comparing Asset Pricing Models

Common risk factors in the returns on stocks : empirical evidence from Singapore.

https://hal.archives-ouvertes.fr/hal-01878923/document

A six-factor asset pricing model

Nonfinancial performance measures, such as environmental, social, and governance (ESG) measures, are potentially leading indicators of companies’ financial performance. In the study reported here, ...

https://www.tandfonline.com/doi/pdf/10.1080/0015198X.2019.1654299

Corporate Governance, ESG, and Stock Returns around the World

The present study introduce the human capital component to the Fama and French five-factor model proposing an equilibrium six-factor asset pricing model. The study employs an aggregate of four sets of portfolios mimicking size and industry with varying dimensions. The first set consists of three set of six portfolios each sorted on size to B/M, size to investment, and size to momentum. The second set comprises of five index portfolios, third, a four-set of twenty-five portfolios each sorted on size to B/M, size to investment, size to profitability, and size to momentum, and the final set constitute thirty industry portfolios. To estimate the parameters of six-factor asset pricing model for the four sets of variant portfolios, we use OLS and Generalized method of moments based robust instrumental variables technique (IVGMM). The results obtained from the relevance, endogeneity, overidentifying restrictions, and the Hausman's specification, tests indicate that the parameter estimates of the six-factor model using IVGMM are robust and performs better than the OLS approach. The human capital component shares equally the predictive power alongside the factors in the framework in explaining the variations in return on portfolios. Furthermore, we assess the t-ratio of the human capital component of each IVGMM estimates of the six-factor asset pricing model for the four sets of variant portfolios. The t-ratio of the human capital of the eighty-three IVGMM estimates are more than 3.00 with reference to the standard proposed by Harvey et al. (2016). This indicates the empirical success of the six-factor asset-pricing model in explaining the variation in asset returns.

https://hal.archives-ouvertes.fr/hal-01660135/document

Dissecting anomalies and dynamic human capital: The global evidence

The nexus of anomalies-stock returns-asset pricing models: The international evidence

The study examines the troika of financial liberalisation–volatility–information asymmetry to explore the linkage between financial liberalisation and return volatility across the globe. The financial liberalisation phenomenon was studied across three phases: liberalisation, post-liberalisation, and liberalisation plus post-liberalisation. The results indicate that volatility surged during the liberalisation phase for emerging economies, whereas it significantly declined during the post-liberalisation period. A declining pattern of volatility was observed during the post-liberalisation phase for developed economies. The conditional and unconditional volatility measures were highest during the liberalisation phase for emerging economies, whereas both the volatility measures were higher during the combined liberalisation phase for developed economies. There was evidence of negative asymmetric shock that lowered the volatility in emerging economies, in developed economies, and at the aggregate level.

Rahul Roy

Papers

A six-factor asset pricing model

A six-factor asset pricing model

Dissecting anomalies and dynamic human capital: The global evidence

The nexus of anomalies-stock returns-asset pricing models: The international evidence

A tripartite inquiry into financial liberalisation–volatility–information asymmetry nexus: Global panel approach