An n-variable structural vector auto-regression (SVAR) can be identified (up to shock order) from the evolution of the residual covariance across time if the structural shocks exhibit heteroskedasticity (Rigobon (2003), Sentana and Fiorentini (2001)). However, the path of residual covariances is...

We use a Dixit-Stiglitz setting to show that aggregate productivity fluctuations can be generated through changes in the dispersion of firms' productivity. When the elasticity of substitution among goods is larger than one, an increase in the dispersion raises aggregate productivity because...

We review evidence on the Great Moderation together with evidence about volatility trends at the micro level to develop a potential explanation for the decline in aggregate volatility since the 1980s and its consequences. The key elements are declines in firm-level volatility and aggregate...

Previous studies on spillover effects in future markets have so far confined themselves to static analyses. In this study, we use a newly introduced spillover index to examine dynamic spillovers between spot and futures market volatility, volume of futures trading and open interest in the UK and...

In this study we examine the dynamic structural relationship between oil price shocks and stock market returns and volatility for a sample of both net oil-exporting and net oil-importing countries between 1995:09 and 2013:07. We accomplish that, by extending the Diebold and Yilmaz (2012) dynamic...

This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are...

Joint dynamics of market index returns, volume traded and volatility of stock market returns can unveil different dimensions of market microstructure. It can be useful for precise volatility estimation and understanding liquidity of the financial market. In this study, the joint dynamics is...

Previous studies have investigated the comovements of international equity markets by using correlation, cointegration, common factor analysis, and other approaches. In this paper, we investigate the stochastic structure of major euro and non-euro area stock market series from 1994 to 2006, by...

A new variant of the ARCH class of models for forecasting the conditional variance, to be called the Generalized AutoRegressive Conditional Heteroskedasticity Parkinson Range (GARCH-PARK-R) Model, is proposed. The GARCH-PARK-R model, utilizing the extreme values, is a good alternative to the...

Asset allocation and risk calculations depend largely on volatile models. The parameters of the volatility models are estimated using either the Maximum Likelihood (ML) or the Quasi-Maximum Likelihood (QML). By comparing the out-of-sample forecasting performance of 68 ARCH-type models using...