This article examines hedging in South African stock index futures market. The hedge ratios are estimated by six econometric techniques: the standard OLS regression, simple and vector error correction models, the ECM with generalised autoregressive heteroskedasticity (GARCH), as well as...

This paper examines the effect of return dispersion on the dynamics of stock market liquidity, risk and return. Moreover, the importance of return dispersion in forecasting aggregate economic activity is rediscovered in the context of a regime switching model that accounts for stock market...

Autoregressive fractionally integrated moving average (ARFIMA) and heterogeneous autoregressive (HAR) models are estimated and their ability to predict the one-trading-day-ahead CAC40 realized volatility is investigated. In particular, this paper follows three steps: (i) The optimal sampling...

Purpose – The purpose of this paper is to focus on the performance of three alternative value-at-risk (VaR) models to provide suitable estimates for measuring and forecasting market risk. The data sample consists of five international developed and emerging stock market indices over the time...

The paper investigates the time-varying correlation between stock market prices and oil prices for oil-importing and oil-exporting countries. A DCC-GARCH-GJR approach is employed to test the above hypothesis based on data from six countries; Oil-exporting: Canada, Mexico, Brazil and...

The time-varying correlation between oil prices returns and European industrial sector indices returns, considering the origin of the oil price shock, is investigated. A time-varying multivariate heteroskedastic framework is employed to test the above hypothesis based on data from 10 European...

In this article an asymmetric autoregressive conditional heteroskedasticity (ARCH) model is applied to some well-known financial indices (DAX30, FTSE20, FTSE100 and SP500), using a rolling sample of constant size, in order to investigate whether the values of the estimated parameters of the...

This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices...

A number of ARCH models are considered in the framework of evaluating the performance of a method for model selection based on a standardized prediction error criterion (SPEC). According to this method, the ARCH model with the lowest sum of squared standardized forecasting errors is selected for...