We propose a direct and convenient reduced-bias estimator of predictive regression coefficients, assuming that the regressors are Gaussian first-order autoregressive with errors that are correlated with the error series of the dependent variable. For the single-regressormodel, Stambaugh (1999)...

We consider semiparametric estimation of the memory parameter in a modelwhich includes as special cases both the long-memory stochasticvolatility (LMSV) and fractionally integrated exponential GARCH(FIEGARCH) models. Under our general model the logarithms of the squaredreturns can be decomposed...

We study the exposure of the US corporate bond returns to liquidity shocks of stocks and Treasury bonds over the period 1973 - 2007 in a regime - switching model. In one regime, liquidity shocks have mostly insignificant effects on bond prices, whereas in another regime, a rise in illiquidity...

We study the exposure of the U.S. corporate bond returns to liquidity shocks of stocks and treasury bonds over the period 1973-2007 in a regime switching model. In one regime, liquidity shocks have mostly insignificant effect on bond prices, whereas in another regime, a rise in illiquidity...

We study the exposure of the US corporate bond returns to liquidity shocks of stocks and Treasury bonds over the period 1973 - 2007 in a regime - switching model. In one regime, liquidity shocks have mostly insignificant effects on bond prices, whereas in another regime, a rise in illiquidity...

We discuss some of the issues pertaining to modelling and estimating long memory in volatility. Themain focus is on semi parametric estimation of the memory parameter in the long memory stochasticvolatility model. We present the asymptotic properties of the log periodogram regression estimator...