A parametric approach to estimating and forecasting Value-at-Risk (VaR) and expected shortfall (ES) for a heteroscedastic financial return series is proposed. The well-known GJR–GARCH form models the volatility process, capturing the leverage effect. To capture potential skewness and heavy tails, the model assumes an asymmetric Laplace form as the conditional distribution of the series. Further...

This paper evaluates the out-of-sample forecasting accuracy of eleven models for monthly volatility in fifteen stock markets. Volatility is defined as within-month standard deviation of continuously compounded daily returns on the stock market index of each country for the ten-year period 1988 to 1997. The first half of the sample is retained for the estimation of parameters while the second ha...

Purpose This paper tests the accuracies of models that predict Value-at-Risk (VaR) for Market Integrated Latin America (MILA) and Association Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods. Design/methodology/approach Many VaR estimation have been presented in literature. In this paper, is estimated using Generalized Autoregressive Conditional Heteroskedasticity, E...

This paper investigates the dynamic tail dependence risk between BRICS economies and world energy market, in context of COVID-19 financial crisis 2020, order to determine optimal investment decisions based on metrics. For this purpose, we employ a combination novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, vine copula methods. Using data set cons...

Abstract This study investigated the reaction of German stock market volatility (Dax index) to European Central Bank (ECB)’s unconventional monetary policy (UMP) announcements. The financial crisis 2008 proved that traditional policy’s tool (the short -term interest rate) has lost its effectiveness meet new challenges. So, key central banks, ECB included, had implement new, untested and nonstan...

Despite increased demand for cleaner fuel alternatives such as ethanol in recent decades, portfolio weight allocation has become challenging due to the complex interlinkage amongst crude, and soft agricultural commodities that form part of value chain. As a result, returns face three trade-offs terms risk: dispersion across mean, risk arising market interconnectedness, global shocks assets shar...

The purpose of this research is to model the volatility Stock Indices in Indonesian capital market. This focuses on two stock indices namely SRI-KEHATI and LQ45. SRI_KEHATI a index that consists companies whose operations are sustainable environmentally friendly. also known as “green index” due its environment sustainability concern. novelty fills gap literature which not much regarding gre...

The autoregressive conditional heteroskedasticity (ARCH) and generalized autoregressive conditional heteroskedasticity (GARCH) models take the dependency of the conditional second moments. The idea behind ARCH/GARCH model is quite intuitive. For ARCH models, past squared innovations describes the present squared volatility. For GARCH models, both squared innovations and the past squared volatil...