The Volatility Forecasting of Tehran & International Stock Exchanges

Iranian Accounting Studies

29 Pages Posted: 21 Sep 2010 Last revised: 25 Sep 2010

See all articles by Hamid Khaleghi Moghaddam

Hamid Khaleghi Moghaddam

affiliation not provided to SSRN

Saeed Moshiri

Saint Thomas More College University of Saskatcehwan

Kamran Pakizeh

Department of Financial Engineering, University of Economc Sciences

Date Written: September 20, 2010

Abstract

Stock prices are one of the most volatile economic variables and forecasting stock prices and their returns has proved very challenging, if not impossible. In this paper, we apply a battery of linear and nonlinear models to forecast the returns in nine international stock exchanges for the period 1998-2008. The models are random walk, historical mean, moving average, exponentially something, AR, and GARCH class models including ARCH, GARCH, GJR- GARCH, and EGARCH. Volatility is defined as within- month standard deviation of continuously compounded daily returns (log- returns) on the indices of main stock exchanges. We compare the forecasting results of the eight major international stock exchanges with the Tehran stock exchanges (TSE), where the market is highly regulated and therefore less subject to volatility. To evaluate the forecasting results, we use three symmetric loss functions including the mean absolute error, root mean squared error, and the mean absolute percentage error.

Results suggest that the GJR-GARCH model provides the superior forecasting performance in comparison with other volatility forecasting models in international exchanges. However, the simple smoothing model provides superior performance in TSE. While random walk model provides the worst performance for international exchanges, it is a good performing model, second in order, in TSE. Historical average model provides the worst performance and ARCH class models do not rank high in forecasting competition for TSE.

Note: Downloadable document is in Persian.

Keywords: Volatility, Naïve Models, GARCH Class Models, Out-of-Sample forecasting

JEL Classification: C22, G12, G14, G15

Suggested Citation

Khaleghi Moghaddam, Hamid and Moshiri, Saeed and Pakizeh, Kamran, The Volatility Forecasting of Tehran & International Stock Exchanges (September 20, 2010). Iranian Accounting Studies. Available at SSRN: https://ssrn.com/abstract=1679679 or http://dx.doi.org/10.2139/ssrn.1679679

Hamid Khaleghi Moghaddam

affiliation not provided to SSRN ( email )

Saeed Moshiri

Saint Thomas More College University of Saskatcehwan ( email )

1437 College Dr
Saskatoon, Saskatchewan S7N 0W6
Canada

Kamran Pakizeh (Contact Author)

Department of Financial Engineering, University of Economc Sciences ( email )

Roudsar St, Hafez Ave
Tehran, 0098
Iran

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