This article compares the performance of bivariate error correction GARCH and FIGARCH models when estimating long term dynamic minimum variance hedge ratios (MVHRs) on the Australian All Ordinaries Index. The paper therefore introduces the bivariate error correction FIGARCH model into the hedging literature, which to date has only employed the GARCH class of processes. This is important for tho...

in this paper we investigate the long memory of tehran securities price index and fit arfima model using 970 daily data since 1382/1/6 until 1386/4/17. furthermore, we compare the forecasting performance of arfima and arima models. the results show that the series is a long memory one and therefore it can become stationary by fractional differencing. we obtaine the fractional differencing param...

We consider the modelling of volatility on closely related markets. Univariate fractional Ž . volatility FIGARCH models are now standard, as are multivariate GARCH models. In this paper, we adopt a combination of the two methodologies. There is as yet little consensus on the methodology for testing for fractional cointegration. The contribution of this paper is to demonstrate the feasibility of...

The present study aims to model systematic risk using financial and accounting variables. Accordingly, the data for 174 companies in Tehran Stock Exchange are extracted for the period of 2006 to 2016. First, the systematic risk index is estimated using the ARFIMA-FIGARCH model. Then, based on the research background, 35 affective financial and accounting variables are simultaneously used with t...

Financial time series such as stock prices, inflation rates, interest and exchange rates are known to exhibit upward downward trend often possesses long memory volatility behavior. These behaviors crucial in the analysis, modeling forecasting of data. Unfortunately, many analysts don’t take into consideration consequences while financial Therefore, this paper intends examine effect Exchange Rat...

Autoregressive fractional integrated moving average modeling strategy was used to model the daily average temperature (DAT) series of Sokoto metropolis for the period of 01/01/2003 to 03/04/2007. The time plot suggests that there is persistence dependence in the series. The order of fractional integration was found to be 0.6238841. The correct model for the daily average temperature data (DAT) ...

risk prediction plays an increasing role in financial risk management. this study aims to investigate existence of asymmetry and long memory volatility in tehran stock exchange index daily data over period of 1998-2006. 1467 daily index returns are used for volatility modeling via garch (long & short memory) processes for both normal and t-student innovations. the specification and forecasting ...