The focus of the volatility literature on forecasting and the predominance of the conceptually simpler HAR model over … long memory stochastic volatility models has led to the fact that the actual degree of memory estimates has rarely been … realized volatility and the potential of spurious long memory. In this paper we provide a comprehensive analysis of the memory …

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 …

We propose using the price range, a recently-neglected volatility proxy with a long histoy in finance, in the … estimation of stochastic volatility models. We show both theoretically and empirically that the log range is approximately … Gaussian, in sharp contrast to popular volatility proxies, such as log absolute or squared returns. Hence Gaussian quasi …

nonstationary volatility. In the same article, Xu proposed a set of t-tests for the regression coefficients and claimed that these … only under the exact knowledge of the asymptotic order of the nonstationary volatility. In this paper it is first shown … obtained, that do not depend either on the asymptotic order of the nonstationary volatility, or on the degree of the polynomial …

predict the sector-level S&P500 exchange-traded fund (ETF) volatility. It was found that the predictive content of co-jumps is … volatility forecasting. Additionally, we carried out Monte Carlo experiments designed to examine the relative performances of the …

In this paper, we consider the forecast evaluation of realized volatility measures under cross-section dependence using …-section when forecasting Realized Volatility. Under the null hypothesis of equal predictive accuracy the benchmark model employed …