  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.
