This paper assesses the effect of extreme weather variability in predicting the impact on two agricultural crop-related variables: yield and production. We use a Markov-Switching time-varying copula to describe the joint dependence structure between extreme weather variability and crops in East...

This study contributes a rich set of quantitative methodologies including a non-parametric approach (Chi-plots and K-plots) as well as copulas (traditional and time-varying with Student's t-copulas) to the existing literature in terms of determining the dependence structure in ASEAN stock...

This study contributes a rich set of quantitative methodologies including a non-parametric approach (Chi-plots and K-plots) as well as copulas (traditional and time-varying with Student’s t-copulas) to the existing literature in terms of determining the dependence structure in ASEAN stock...

We apply Bayesian Model Averaging and a frequentistic model space analysis to assess the pricing-determinants of credit default swaps (CDS). Our study focuses on the complete model space of plausible models covering most of the variables and specifications used elsewhere in the literature,...

We apply Bayesian Model Averaging and a frequentistic model space analysis to assess the pricing-determinants of credit default swaps (CDS). Our study focuses on the complete model space of plausible models covering most of the variables and specifications used elsewhere in the literature,...

Oil is perceived as a good diversification tool for stock markets. To fully understand this potential, we propose a new empirical methodology that combines generalized autoregressive score copula functions with high frequency data and allows us to capture and forecast the conditional...