Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution that can be conveniently parameterised by the first two...

In this study, we develop a two-step asset allocation strategy that identifies the tail risk of a benchmark asset and uses multi-moment dynamic portfolio selection to account for possible conditional non-normality of portfolio returns. The TEDAS - Tail Event Asset Allocation strategy is based on...

This paper presents an early warning system as a set of multi-period forecasts of indicators of tail real and financial risks obtained using a large database of monthly U.S. data for the period 1972:1-2014:12 Pseudo-real time forecasts are generated from: (a) sets of autoregressive and...

Reliable early warning signals are essential for timely implementation of macroeconomic and macro-prudential policies. This paper presents an early warning system as a set of multi-period forecasts of indicators of tail real and financial (systemic) risks. Forecasts are obtained from: (a)...

Systemic risk quantification in the current literature is concentrated on market-based methods such as CoVaR(Adrian and Brunnermeier (2016)). Although it is easily implemented, the interactions among the variables of interest and their joint distribution are less addressed. To quantify systemic...