出版社：Suntory Toyota International Centres 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
