Conventional GARCH modeling formulates an additive-error mean equation for daily return and an autoregressive moving-average specification for its conditional variance, without much consideration on the effects of intra-daily data. Using Engle’s multiplicative-error model (MEM) formulation,...

The aim of this paper is to assess to what extent intraday data can explain and predict end-of-the-day volatility. Using a realized volatility measure as proposed by Andersen, T., T. Bollerslev, F. Diebold, and P. Labys. 2001. The distribution of realized exchange rate volatility. Journal of the...

ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility clustering and asymmetry characterize the logarithmic realized volatility of both the indices. The ARFIMAX model with time-varying conditional heteroskedasticity is the best...

Within the industrial metals industry, there has been a great deal of interest surrounding trends in metals market volatility over time. This paper uses a rolling AR(1)-GARCH(1,1) model to estimate and forecast the volatility processes for daily returns on the futures prices of two important...

In this paper we analyse if the implied volatility (IMV) is an unbiased predictor for the realised volatility (REV) of the underlying asset (future contracts). For this aim we use the daily data from Ibex-35 future option market (years 2000 to 2003). From the option prices we obtain a series of...

Statistical volatility models rely on the assumption that the shape of the conditional distribution is fixed over time and that it is only the volatility that varies. The recently proposed conditional autoregressive value at risk (CAViaR) models require no such assumption, and allow quantiles to...

Multifractal processes are a relatively new tool of stock market analysis. Their power lies in the ability to take multiple orders of autocorrelations into account explicitly. In the first part of the paper we discuss the framework of the Lux model and refine the underlying phenomenological...

A rapidly growing literature has documented important improvements in volatility measurement and forecasting performance through the use of realized volatilities constructed from high frequency returns coupled with relatively simple reduced-form time series modeling procedures. Building on...