abstract: with regard to the basel committee’s emphasis on the necessity of using 10-day value-at-risk (var) internal models in order to determine minimum market risk capital requirements, and downsides of the square-root-of-time rule, our purpose is to produce more accurate forecasts of the multi-period var using sixteen models for three stock indices, the tepix, nasdaq, and ftse. the results,...

Purpose of the paper 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 portfolio returns. The purpose of the paper is to estimate accurate 10-day-ahead 99% VaR...

We analyzed the volatility dynamics of three developed markets (U.K., U.S. and Japan), during the period 2003-2011, by comparing the performance of several multivariate volatility models, namely Constant Conditional Correlation (CCC), Dynamic Conditional Correlation (DCC) and consistent DCC (cDCC) models. To evaluate the performance of models we used four statistical loss functions on the daily...

return and volatility spillovers are important for portfolio selection, asset valuation and market efficiency investigation. using a var-bekk framework model, this paper investigates return and volatility spillover effects between three size-sorted equity indices in tehran stock exchange (tse). although daily return of large stocks leads small stocks (lead-lag effect), there wasn’t any spillove...

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 ...

To assess the time-varying dynamics in value-at-risk (VaR) estimation, this study has employed an integrated approach of dynamic conditional correlation (DCC) and generalized autoregressive heteroscedasticity (GARCH) models on daily stock return emerging markets. A log-returns three leading indices such as KSE100, KSE30, KSE-ALL from Pakistan Stock Exchange SSE180, SSE50 SSE-Composite Shanghai ...