This is a summary of the paper entitled : “The Mean Squared Prediction Error Paradox”. In that paper, we show that traditional comparisons of Mean Squared Prediction Error (MSPE) between two competing forecasts may be highly controversial. This is so because when some specific conditions of...

The Basel Committee regulations require the estimation of Value-at-Risk at 99% confidence level for a 10-trading-day-ahead forecasting horizon. The paper provides a multivariate modelling framework for multi-period VaR estimates for leptokurtic and asymmetrically distributed real-estate...

The purpose of this work is to identify variables that are relevant to the copper price setting in the international market. Thus statistical hypothesis tests and statistical tools that help to identify historical relevance and to measure the intensity of the impact of each variable on the...

We propose two tests for the equality of covariance matrices between two high-dimensional populations. One test is on the whole variance-covariance matrices, and the other is on offdiagonal sub-matrices which define the covariance between two non-overlapping segments of the high-dimensional...

We propose two tests for the equality of covariance matrices between two high-dimensional populations. One test is on the whole variance-covariance matrices, and the other is on offdiagonal sub-matrices which define the covariance between two non-overlapping segments of the high-dimensional...

In this paper we show that the MSCI ACWI Metals and Mining Index has the ability to predict base metal prices. We use both in-sample and out-of-sample exercises to conduct such examination. The theoretical underpinning of these results relies on the present-value model for stock-price...

This paper studies empirically the emerging Asian stock market vulnerability to pandemics. Taking the Covid-19 virus as a case study, we used the ARDL panel data approach to investigate the impact of the daily Covid-19 confirmed cases along with a behavioral component based on a triggering fear...

This paper studies empirically the emerging Asian stock market vulnerability to pandemics. Taking the Covid-19 virus as a case study, we used the ARDL panel data approach to investigate the impact of the daily Covid-19 confirmed cases along with a behavioral component based on a triggering fear...

This paper studies empirically the emerging Asian stock market vulnerability to pandemics. Taking the Covid-19 virus as a case study, we used the ARDL panel data approach to investigate the impact of the daily Covid-19 confirmed cases along with a behavioral component based on a triggering fear...

Non-Gaussian state-space models arise in several applications, and within this framework the binary time series setting provides a relevant example. However, unlike for Gaussian state-space models — where filtering, predictive and smoothing distributions are available in closed form — binary...