Hemant Kumar Badaye and Jason Narsoo
This study aims to use a novel methodology to investigate the performance of several multivariate value at risk (VaR) and expected shortfall (ES) models implemented to assess the…
Abstract
Purpose
This study aims to use a novel methodology to investigate the performance of several multivariate value at risk (VaR) and expected shortfall (ES) models implemented to assess the risk of an equally weighted portfolio consisting of high-frequency (1-min) observations for five foreign currencies, namely, EUR/USD, GBP/USD, EUR/JPY, USD/JPY and GBP/JPY.
Design/methodology/approach
By applying the multiplicative component generalised autoregressive conditional heteroskedasticity (MC-GARCH) model on each return series and by modelling the dependence structure using copulas, the 95 per cent intraday portfolio VaR and ES are forecasted for an out-of-sample set using Monte Carlo simulation.
Findings
In terms of VaR forecasting performance, the backtesting results indicated that four out of the five models implemented could not be rejected at 5 per cent level of significance. However, when the models were further evaluated for their ES forecasting power, only the Student’s t and Clayton models could not be rejected. The fact that some ES models were rejected at 5 per cent significance level highlights the importance of selecting an appropriate copula model for the dependence structure.
Originality/value
To the best of the authors’ knowledge, this is the first study to use the MC-GARCH and copula models to forecast, for the next 1 min, the VaR and ES of an equally weighted portfolio of foreign currencies. It is also the first study to analyse the performance of the MC-GARCH model under seven distributional assumptions for the innovation term.
Details
Keywords
Verena Tandrayen Ragoobur and Jason Narsoo
The paper investigates into the human capital–economic growth nexus by arguing that investment in early education and health helps in achieving higher economic growth. Early…
Abstract
Purpose
The paper investigates into the human capital–economic growth nexus by arguing that investment in early education and health helps in achieving higher economic growth. Early investment in human capital matters most for economic growth than the increase in human capital over the years.
Design/methodology/approach
A dynamic vector error correction model (VECM) together with the impulse response function and variance decomposition are used on data for Mauritius from 1983 to 2019. The paper distinguishes between the short-run and the long-run effects of human capital measured by the pupil–teacher ratio in pre-primary education and life expectancy at birth.
Findings
This study’s findings reveal that investment in early education and health has contributed positively to growth performance. There is evidence for long-run growth effects arising from a positive shock in the education and health indicators.
Originality/value
This paper contributes to both the theoretical and empirical literature on the human capital–growth nexus. Mauritius as a natural resource poor small economy is an important case study as it has started early in investing in its people to promote economic growth.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0674.