出版社：Suntory Toyota International Centre for Economics and Related Disciplines
摘要：Asset returns are frequently assumed to be determined by one or more common
factors. We consider a bivariate factor model, where the unobservable common
factor and idiosyncratic errors are stationary and serially uncorrelated, but have
strong dependence in higher moments. Stochastic volatility models for the latent
variables are employed, in view of their direct application to asset pricing models.
Assuming the underlying persistence is higher in the factor than in the errors, a
fractional cointegrating relationship can be recovered by suitable transformation of
the data. We propose a narrow band semiparametric estimate of the factor
loadings, which is shown to be consistent with a rate of convergence, and its finite
sample properties are investigated in a Monte Carlo experiment.
关键词：Fractional cointegration; stochastic volatility; narrow band least
squares; semiparametric analysis.
