implications from a long-run risk model that allow for both time-varying volatility and volatility uncertainty. We provide new … for the direct estimation of the underlying economic mechanisms, including a new volatility leverage effect, the … persistence of the latent long-run growth component and the two latent volatility factors, as well as the contemporaneous impacts …

empirical regularities in credit markets. Our model captures the empirical level and volatility of credit spreads, generates a …

volatilities as measured by daily range. Long memory features of the range-based volatility estimators of the two series are …

. The theory underlying our estimates are based on in-fill asymptotic arguments for directly identifying the systematic and … idiosyncratic jumps, together with conventional long-span asymptotics and Extreme Value Theory (EVT) approximations for consistently … the high-frequency data together with the day-to-day temporal variation in the volatility are able to explain the “extreme …

possible to generate a volatility-return trade-off in a regression model simply by introducing dynamics in the standardized … disturbance process. Importantly, the volatility in the GARCH-AR model enters the return function in terms of relative volatility …, implying that the risk term can be stationary even if the volatility process is nonstationary. We provide a complete …

variation in the stochastic volatility. On implementing the new estimation procedure with actual high-frequency data for the S …

contribution of this paper is twofold. First, it provides a bivariate asymptotic limit theory for realised variance and realised … asymptotic variance of the estimation bias. Eventually, this leads to a feasible asymptotic theory which is applicable in … practice. Finally, Monte Carlo studies reveal a good finite sample performance of the proposed feasible limit theory. …