We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set 248 multivariate models that differ in their specification of the conditional variance, conditional correlation, and innovation distribution. All models b...

Conditional imitation learning (CIL) trains deep neural networks, in an end-to-end manner, to mimic human driving. This approach has demonstrated suitable vehicle control when following roads, avoiding obstacles, or taking specific turns at intersections reach a destination. Unfortunately, performance dramatically decreases deployed unseen environments and is inconsistent against varying weathe...

This paper investigates the dynamic conditional correlations (DCC) of stock returns between China and international markets. Statistics suggest that stock-return correlations across markets are time-varying, displaying a structural change triggered by an upward shift in China’s adoption of financial liberalization and the occurrence of the worldwide financial crisis. The dynamic correlations ar...

The proper description of dynamic information correlation among individual stages is very important for the construction of multi-period risk measure and the selection of optimal investment strategy. To overcome the limitations of existing random frameworks, we initially introduce a ”two-level” structure to describe the dynamic information evolution: the outer-level describes endogenous marcoma...

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...

We study the correlation of monthly excess returns for seven major countries over the period 1960-90. We find that the international covariance and correlation matrices are unstable over time. A multivariate GARCH(1,1) model with constant conditional correlation helps to capture some of the evolution in the conditional covariance structure. However tests of specific deviations lead to a rejecti...

Motivated by the security of the nonlinear filter generator, the concept of correlation was previously extended to the conditional correlation, that studied the linear correlation of the inputs conditioned on a given (short) output pattern of some specific nonlinear function. Based on the conditional correlations, conditional correlation attacks were shown to be successful and efficient against...