An understanding of volatility in stock markets is important for determining the cost of capital and for assessing investment and leverage decisions as volatility is synonymous with risk. Substantial changes in volatility of financial markets are capable of having significant negative effects on risk averse investors. Using daily returns from 1992 to 2002, we investigate volatility co-movement ...

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...

This paper derives the analytic form of multi-step ahead prediction density a Gaussian GARCH(1,1) process with possibly asymmetric news impact curve in GJR class. These results can be applied when single-period returns are modeled as and interest lies at some future forecast horizon. The has been used applications an approximation to this yet unknown density; derived here shows that density, wh...

This paper aims to estimate the Value-at-Risk (VaR) using GARCH type models with improved return distribution. Value at Risk (VaR) is an essential benchmark for measuring the risk of financial markets quantitatively. The parametric method, historical simulation, and Monte Carlo simulation have been proposed in several financial mathematics and engineering studies to calculate VaR, that each of ...

Infrastructure investment is essential for economic development both developed and developing economies. We analyze the short-term return behavior portfolio characteristics of global, regional, selected Asian countries’ infrastructure indexes during pandemic over sample period 3 July 2018 to 1 2021. According multivariate Glosten, Jagannathan, Runkle (GJR) Generalized Autoregressive Conditional...

We provide a practical methodology for solving the generalized joint replenishment (GJR) problem, based on a mathematical programming approach to approximate dynamic programming. We show how to automatically generate a value function approximation basis built upon piecewise-linear ridge functions, by developing and exploiting a theoretical connection with the problem of finding optimal cyclic s...

In this paper, we examine various characteristics of both base and peak electricity spot prices their returns, investigate dependence structures, extreme co-movements, risk spillovers, integration relationships among the five major European markets, including France, Germany, Netherlands, Spain, UK. To do so, propose a new perspective by applying hybrid ARMA-GARCH, static dynamic copulas, state...