Due to the hyper technology associated to Big Data, data availability and computing power, most banks or lending financial institutions are renewing their business models. Credit risk predictions, monitoring, model reliability and effective loan processing are key to decision making and...

We propose a simultaneous equation system with GARCH errors to model the contemporaneous relations among Asian and American stock markets. On the estimated residuals, we evaluate the correlation matrix over rolling windows and introduce a correlation matrix distance, which allows both a...

This paper aims at the production of a chronology for the EU15 business cycle by comparing parametric and non-parametric procedures on monthly and quarterly data as well in a combined approach. The main innovation is the joint use of the monthly series for the EU15 Gross Domestic Product (GDP)...

We study the effect of financial crises on hedge fund risk. Using a regime-switching beta model, we separate systematic and idiosyncratic components of hedge fund exposure. The systematic exposure to various risk factors is conditional on market volatility conditions. We find that in the...

We propose a new Bayesian Markov switching regression model for multi-dimensional arrays (tensors) of binary time series. We assume a zero-inflated logit dynamics with time-varying parameters and apply it to multi-layer temporal networks. The original contribution is threefold. First, in order...

We propose a spatial approach for modeling risk spillovers using financial time-varying proximity matrices based on observable networks. We show how these methods could be useful in (i) isolating risk channels, risk spreaders and risk receivers, (ii) investigating the role of portfolio...

A new Bayesian multi-chain Markov Switching GARCH model for dynamic hedging in energy futures markets is developed by constructing a system of simultaneous equations for the return dynamics on the hedged portfolio and futures. More specifically, both the mean and variance of the hedged portfolio...

We adopt the Dynamical Influence model from computer science and transform it to study the interaction between business and financial cycles. For this purpose, we merge it with Markov-Switching Dynamic Factor Model (MS-DFM) which is frequently used in economic cycle analysis. The model suggested...

The purpose of this paper is the construction of an early warning indicator for systemic risk using entropy measures. The analysis is based on the cross-sectional distribution of marginal systemic risk measures such as Marginal Expected Shortfall, Delta CoVaR and network connectedness. These...

This paper develops several risk measures that captures the tail risk of single hedge fund strategies and the tail risk contribution of these hedge fund strategies to the overall portfolio tail risk, conditional on the level of market distress. We show that, during the recent global financial...