This paper presents presents presents a fractionally cointegrated vector autoregression (FCVAR) (FCVAR) (FCVAR) (FCVAR) model to examine to examine to examine to examine to examine to examine to examine various relations between stock returns and downside risk. Evidence from major advanced...

The present study addresses the economic interpretation of stock market volatility. We argue that its character is inherently ambivalent, being considered as an indicator of either information flow or uncertainty.We discriminate between these views by measuring the fraction of price changes that...

Information flows 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...

In this paper we investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact...

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...

As a function of strike and time to maturity the implied volatility estimation is a challenging task in financial econometrics. Dynamic Semiparametric Factor Models (DSFM) are a model class that allows for the estimation of the implied volatility surface (IVS) in a dynamic context, employing...

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-min squared mid-quote returns, average trade sizes, number of...

The basic model for high-frequency data in finance is considered, where an efficient price process is observed under microstructure noise. It is shown that this nonparametric model is in Le Cam's sense asymptotically equivalent to a Gaussian shift experiment in terms of the square root of the...

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...