We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the size of positive and negative jumps and...

We provide new empirical evidence on volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Leverage and volatility feedback effects of the S&P 500 price and volatility dynamics are examined using recently developed methodologies to...

We investigate price duration variance estimators that have long been neglected in the literature. We show i) how price duration estimators can be used for the estimation and forecasting of the integrated variance of an underlying semi-martingale price process and ii) how they are affected by a)...

The approximate long memory Heterogeneous Autoregressive (HAR) model proposed by Corsi is extended in order to account for leverage effects in the realized volatility process and the long memory of the conditional variance of the HAR residuals. The proposed model is estimated using ten years of...

In assessing drivers of commodity prices and volatility at this stage of the current super-cycle in commodities (year 12 of a projected 25), it is vital to understand that production cost is a fundamental. Moreover, marginal production costs are among the most powerful drivers of commodity...

The accuracy of variance prediction depends on both the specification and the accuracy of parameter estimation. To predict stock return variance in a large and ever-changing universe, this paper proposes to replace the classic time-series dynamics specification per each name with a...

In this research paper ARCH-type models and option implied volatilities (IV) are applied in order to estimate the Value-at-Risk (VaR) of a stock index futures portfolio for several time horizons. The relevance of the asymmetries in the estimated volatility estimation is considered. The empirical...

The paper deals with the problem of estimating the pointwise regularity of the multifractional Brownian motion, assumed as a model of the stock price dynamics. We (a) correct the shifting bias affecting a class of absolute moment-based estimators and (b) build a data-driven algorithm in order to...

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and...

We propose a new approach to model high and low frequency components of equity correlations. Our framework combines a factor asset pricing structure with other specifications capturing dynamic properties of volatilities and covariances between a single common factor and idiosyncratic returns....