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...

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...

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...

This paper examines the questions of whether and how feudal rulers were able to credibly commit to preserving monetary stability, and of which consequences their decisions had for the efficiency of financial markets. The study reveals that princes were usually only able to commit to issuing a...

The Chinese stock market features an interesting history of divided market segments: domestic (A), foreigners' (B) and overseas (H). This puts forth questions of market integration as well as cross-divisional information transmission. We address these issues in a structural DCC framework, an...

Using structural VARs, I find that external shocks are an important source of macroeconomic fluctuations in emerging markets. Furthermore, U.S. monetary policy shocks affect quickly and strongly interest rates and the exchange rate in a typical emerging market. The price level and real output in...

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 moving...

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...

In recent policy debates some have argued that expansionary monetary policy in Japan can increase real output in Japan and in Japan's neighbors, while others have warned that it is a beggar-thy-neighbor policy. In this paper we estimate structural vector autoregressions to assess the effects of...

We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven...