Comovement of stock market indices increases during volatile periods, and does not come down when the turmoil settles down. This paper explains formation of persistent comovements during high volatility periods with theories from Bayesian learning. My main conclusion is that the correlation that...

This study refers to the earlier work of analysis in the frequency domain. A different definition of causality is made, and its implications to the general idea of causality are discussed. The causality relationship between two monetary aggregates, simple sum and Divisia indices, and their...

This article identifies caveats of using the correlation coefficient between two fractionally integrated time series as a measure of association between them, and compares various procedures for removing the long-range dependence component in the output series of the G7.

This paper investigates the transmission mechanisms of noise and volatility between economies through trade links, and the effects of synchronization on business cycles. We investigate the transmission of outside noise and the fluctuations that the noise generates. We identify conditions under...

The method proposed in this chapter is making use of the bispectrum transformation to estimate the level of integration of a fractionally integrated time series. Bispectrum ransformation transforms the series into a two dimensional frequency space, and thus has higher information content...

This paper investigates the transmission mechanisms of structural shocks and volatility between economies through trade links, and the effects of synchronization on business cycles. We investigate the transmission of outside structural shocks and the fluctuations that the shocks generate. We...

This paper investigates the transmission mechanisms of noise and volatility between economies through trade links, and the effects of synchronization on business cycles. We investigate the transmission of outside noise and the fluctuations that the noise generates. We identify conditions under...