Information ows across international financial markets typically occur within hours, making volatility spillover appear contemporaneous in daily data. Such simultaneous transmission of variances is featured by the stochastic volatility model developed in this paper, in contrast to usually...

A small strand of recent literature is occupied with identifying simultaneity in multipleequation systems through autoregressive conditional heteroscedasticity. Since thisapproach assumes that the structural innovations are uncorrelated, any contemporaneousconnection of the endogenous variables...

The present paper embarks on an analysis of interactions between the US and Euroland in the capital, foreign exchange, money and stock markets from 1994 until 2006. Considering influences on financial market volatility, the estimations are carried out in multivariate EGARCH models using...

The present paper analyses interactions between the foreign exchange, money and stock markets in Asian Pacific countries from 1999 till 2006. Considering influences on financial market volatility, the estimations are carried out in multivariate EGARCH models using structural residuals. This...

We give an explicit PDE characterization for the solution of the problemof maximizing the utility of both terminal wealth and intertemporal consumption under model uncertainty. The underlying market model consists of a risky asset, whose volatility and long-term trend are driven by an external...

We introduce a Nelson-Siegel type interest rate term structure model with the underlying yield factors following autoregressive processes revealing time-varying stochastic volatility. The factor volatilities capture risk inherent to the term structure and are associated with the time-varying...

In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as trading costs in an electronic limit order book market. Using data from the Australian Stock Exchange we model 1-minsquared mid-quote returns, average trade sizes, number of...

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be...

Market option prices in last 20 years confirmed deviations from the Black and Scholes (BS) models assumptions, especially on the BS implied volatility. Implied binomialtrees (IBT) models capture the variations of the implied volatility known as \volatility smile". They provide a discrete...

In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a...