We propose a model that can capture the typical features of multivariate extreme events observed in financial time series, namely, clustering behaviors in magnitudes and arrival times of multivariate extreme events, and time-varying dependence. The model is developed within the framework of the...

This paper investigates asymmetric increasing trends in dependence in major international equity markets. To this end, we develop a multiple-regime smooth-transition copula GARCH model and address several important questions, including the number of regimes and the existence of increasing...

This paper develops a dependence-switching copula model to examine dependence and tail dependence for four different market statuses, namely, rising-stocks/appreciating-currency, falling-stocks/depreciating-currency, rising-stocks/depreciating-currency, and falling-stocks/appreciating-currency....

This study investigates the dynamic linkages between oil prices and stock markets, also known as the oil price–stock price nexus. Within the framework of a VAR (vector autoregression) we examine dynamic interactions between daily Brent spot prices and several Lebanese stock prices. As...

Using an innovative GMGARCH-MSKST model that allows for asymmetric generalized dynamic conditional correlation, this paper analyzes return and volatility interactions among spot, non-deliverable forward (NDF) and deliverable forward (DF) exchange rate markets for Korea and Taiwan. With the...

We introduce a flexible copula-based semi-parametric test of financial contagion that is capable of capturing structural shifts in the transmission channel of shocks across a network of financial markets beyond the increase in the intensity of time-varying dependence. We illustrate the...

This paper investigates the dependence structure between the real Canadian stock returns and the real USD/CAD exchange rate returns, using the Symmetrized Joe-Clayton (SJC) copula function. We estimate the SJC copula with monthly data over the period 1995:1 to 2006:12. Our results show...

This paper extends the canonical model of epidemiology, SIRD model, to allow for time varying parameters for real-time measurement of the stance of the COVID-19 pandemic. Time variation in model parameters is captured using the generalized autoregressive score modelling structure designed for...

The common approach to evaluating a model in the structural VAR literature is to compare the impulse responses from structural VARs run on the data to the theoretical impulse responses from the model. The Sims-Cogley-Nason approach instead compares the structural VARs run on the data to...

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new parametric methodology for estimating factors from large datasets based on state space models and...