Instability of Predictability of Asset Returns
نویسندگان
چکیده
This paper studies a time-varying coefficient predictive regression model, which takes account of the endogeneity and nearly integrated and integrated state variables. A local linear approach is used to estimate the time-varying coefficients. The asymptotic distributions of these estimates are established for α-mixing time series and the uniform convergence with a rate is also investigated. Further, we show that convergence rates for the intercept and slope functions are different. Due to the different convergence rates, we propose a two stage estimation procedure to obtain the optimal estimates of intercept and slop functions respectively. Finally, a Monte Carlo experiment and an empirical study are investigated to show the usefulness of the proposed theory and estimation procedures.
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