Multiday expected shortfall under generalized t distributions : evidence from global stock market

We apply seven alternative t-distributions to estimate the market risk measures Value at Risk (VaR) and its extension Expected Shortfall (ES). Of these seven, the twin t-distribution (TT) of Baker and Jackson (2014) and generalized asymmetric distribution (GAT) of Baker (2016) are applied for the first time to estimate market risk. We analytically estimate VaR and ES over one-day horizon and extend this to multi-day horizon using Monte Carlo simulation. We find that taken together TT and GAT distributions provide the best back-testing results across individual confidence levels and horizons for majority of scenarios. Moreover, we find that with the lengthening of time horizon, TT and GAT models performs well, such that at the ten-day horizon, GAT provides the best back-testing results for all of the five indices and the TT model provides the second best results, irrespective period of study and confidence level

Australia’s equity home bias and real exchange rate volatility

Coordinated portfolio investment survey, Float home bias, Real exchange rate volatility, Generalized method of moments, G11, G15, G18,