This paper establishes the link of microstructure and macroeconomic factors with the timevarying conditional correlation of foreign exchange and excess equity returns. By using the proposed DCC model with exogenous variables, capital flows and interest rate differentials are shown to be significant determinants of this correlation which is inclusive of the short-run variation of both asset retu...

In this paper we introduce a multivariate generalized autoregressive conditional heteroskedastic (GARCH) class of models with time-varying eigenvalues. The dynamics the eigenvalues is derived for cases underlying Gaussian and Student’s t-distributed innovations based on general theory dynamic score by Creal, Koopman Lucas (2013) Harvey (2013). resulting eigenvalue GARCH – labeled ‘?-GARCH’ diff...

This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC estimation procedure is applied to a portfolio of daily returns on currency futures, government bonds and...

Sequential behavior and sequence learning is essential to intelligence. Often the elements of sequences exhibit an internal structure that can elegantly be represented using relational atoms. Applying traditional sequential learning techniques to such relational sequences requires either to ignore the internal structure or to put up with a combinatorial explosion in the model complexity. This c...