The VIX index is not only a volatility index but also a polynomial combination of all possible higher moments in market return distribution under the risk-neutral measure. This paper formulates the VIX as a linear decomposition of four fundamentally different elements: the realized variance...

The paper advances the log-generalized gamma distribution as a suitable generator of conditional skewness. Based on the NYSE composite daily returns an asMA-asQGARCH model along with skewness dynamics is estimated. The results indicate a skewness that varies between sizeable negative skewness...

This paper offers an improvement to the trade-to-trade model for event studies. While the trade-to-trade model of Maynes and Rumsey (1993) addresses the problem of thin trading by eliminating periods in which no trading is recorded, the proposed improvement addresses the influence of zero-value...

This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...

We provide a new framework for modeling trends and periodic patterns in high-frequency financial data. Seeking adaptivity to ever-changing market conditions, we enlarge the Fourier flexible form into a richer functional class: both our smooth trend and the seasonality are non-parametrically...

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)...

We analyze the stock market return predictability for three different periods. We evaluate the conditional variance (CV) and the variance risk premium (VRP) as predictors of stock market returns for which we are using well-established versions of the heterogeneous auto-regressive (HAR) model and...

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...

Prediction of future movement of stock prices has been a subject matter of many research work. There is a gamut of literature of technical analysis of stock prices where the objective is to identify patterns in stock price movements and derive profit from it. Improving the prediction accuracy...

An effective approach for forecasting return volatility via threshold nonlinear heteroskedastic models of the daily asset price range is provided. The return is defined as the difference between the highest and lowest log intra-day asset price. A general model specification is proposed, allowing...