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Using monthly returns to model conditional heteroscedasticity

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  • Nathan Lael Joseph

Abstract

This empirical study examines the extent of non-linearity in a multivariate model of monthly financial series. To capture the conditional heteroscedasticity in the series, both the GARCH(1,1) and GARCH(1,1)-in-mean models are employed. The conditional errors are assumed to follow the normal and Student- t distributions. The non-linearity in the residuals of a standard OLS regression are also assessed. It is found that the OLS residuals as well as conditional errors of the GARCH models exhibit strong non-linearity. Under the Student density, the extent of non-linearity in the GARCH conditional errors was generally similar to those of the standard OLS. The GARCH-in-mean regression generated the worse out-of-sample forecasts.

Suggested Citation

  • Nathan Lael Joseph, 2003. "Using monthly returns to model conditional heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 35(7), pages 791-801.
    • Handle: RePEc:taf:applec:v:35:y:2003:i:7:p:791-801
    DOI: 10.1080/0003684021000088536
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    References listed on IDEAS

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    Cited by:

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    3. Chung-Hua Shen & Shyh-Wei Chen & Chien-Fu Chen, 2010. "The dual characteristics of closed-end country funds: the role of risk," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 1003-1013.
    4. Mazouz, Khelifa & Bowe, Michael, 2006. "The volatility effect of futures trading: Evidence from LSE traded stocks listed as individual equity futures contracts on LIFFE," International Review of Financial Analysis, Elsevier, vol. 15(1), pages 1-20.
    5. Mojisola Olugbode & Ahmed El-Masry & John Pointon, 2014. "Exchange Rate and Interest Rate Exposure of UK Industries Using First-order Autoregressive Exponential GARCH-in-mean (EGARCH-M) Approach," Manchester School, University of Manchester, vol. 82(4), pages 409-464, July.
    6. Bangassa, Kenbata & Su, Chen & Joseph, Nathan L., 2012. "Selectivity and timing performance of UK investment trusts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1149-1175.

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