mutual information is estimated using the correlation integral from chaos theory. The signi[tanceof the test statistics is … determined with a permutation procedure and a parametric bootstrap in the testsfor serial independence and linearity …

actual sizes. The Monte Carlo implementation allows the use of test statistics which are considerably simpler than for the …

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to … time-varying covariance matrix of the multivariate Student's t distribution. The key novelty of our proposed model concerns … the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we account …

estimatedcorrelations (R2s), regression coefficients (durations)and their significance (t-statistics). Our theoretical findings areconfirmed …

This paper documents the existence of large structural breaks in the unconditional correlations among the British pound … the framework of dynamic conditional correlation (DCC) models, we find that such breaks occurred both at the time the … January 1999. In particular, we document that most correlations were substantially lower during the intermittent period. We …

of determining the optimal sampling frequency, which strikes a balance between variance and bias in covariance matrix …

standardization of the conditional covariance model to obtain the conditional correlation model; and (iii) shows that the appropriate …One of the most widely-used multivariate conditional volatility models is the dynamic conditional correlation (or DCC … three important issues: (i) demonstrates that DCC is, in fact, a dynamic conditional covariance model of the returns shocks …

We develop a new model for the multivariate covariance matrix dynamics based on daily return observations and daily … realized covariance matrix kernels based on intraday data. Both types of data may be fat-tailed. We account for this by … generalized autoregressive score dynamics for the unobserved true covariance matrix, our approach automatically corrects for the …