The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...

In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span...

The multi-fractal analysis has been applied to investigate various stylized facts of the financial market including market efficiency, financial crisis, risk evaluation and crash prediction. This paper examines the daily return series of stock index of NASDAQ stock exchange. Also, in this study,...

We employ a wavelet approach and conduct a time-frequency analysis of dynamic correlations between pairs of key traded assets (gold, oil, and stocks) covering the period from 1987 to 2012. The analysis is performed on both intra-day and daily data. We show that heterogeneity in correlations...

Purpose of this paper - The current paper aims to analyze the impact of the debt crisis on the FTSE / ASE 20 index volatility. The research also examines the impact of powerful foreign capital markets on the Greek Stock Exchange market, the seasonality returns (Day-of-the-Week effect) and the...

Understanding the pattern of stock market volatility is important to investors as well as for investment policy. Volatility is directly associated with risks and returns, higher the volatility the more financial market is unstable. The volatility of the Zimbabwean stock market is modeled using...

Our study extends the existing literature by exploring the impact of three major risk and uncertainty indices on the Dow Jones Islamic Market (DJIM) World and the ten major sectoral Islamic equity indices. We also look at whether the sectoral indices differ from the global benchmark index...

This paper examines long memory volatility in international stock markets. We show that long memory volatility is widespread in a panel dataset of eighty-two countries and that the degree of memory in the panel can be related to macroeconomic variables such as short- and long-run interest rates...

Forecasting stock market returns is one of the most effective tools for risk management and portfolio diversification. There are several forecasting techniques in the literature for obtaining accurate forecasts for investment decision making. Numerous empirical studies have employed such methods...

This paper uses fractional integration techniques to examine the stochastic behaviour of high and low stock prices in Europe and then to test for the possible existence of long-run linkages between them by looking at the range, i.e., the difference between the two logged series. Specifically,...