results show that asymmetric models generally outperform symmetric ones, indicating that a correlation between volatility and … returns plays an important role for volatility forecasting. Additionally, models utilizing a logarithmic transformation of the …

This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous … autoregressive model (HAR) framework. We show that periodicity inflates the variance of the realized volatility and biases jump …

This paper proposes an ex post volatility estimator, called mixed interval realized variance (MIRV), that uses high … theoretical properties of the new volatility estimator are illustrated and compared with those of the two currently dominant … realized measures: realized volatility and realized range. A simulation study adds to this comparison and highlights some …

The main problem in pricing variance, volatility, and correlation swaps is how to determine the evolution of the … by so-called pseudo-statistics, namely, the pseudo-variance, -covariance, -volatility, and -correlation. The main … paper, we will demonstrate how to value different types of swaps (variance, volatility, covariance, and correlation swaps …

samples collected at random intervals, which are set by the clock running inversely proportional to the market volatility. Our …

assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an …

We present a new theory of homogeneous volatility (and variance) estimators for arbitrary stochastic processes. The …