An analysis of the sensitivity of Australian superannuation funds to market movements: a Markov regime switching approach

Abstract

This article investigates the sensitivity of Australian superannuation funds in relation to equity and bond markets. In particular, it examines the extent, speed and duration of response of the Australian superannuation funds's returns to movements in the US and Australian equity and bond markets when fund returns are in the up, normal and down regimes, through the application of Markov regime switching analysis. The results reveal that Australian superannuation funds's returns are most affected by movements in the US equity market, followed by the Australian equity market then by the US bond market. Funds's returns are not influenced at all by movements in the Australian bond market. They respond quickly and briefly to market movements irrespective of whether funds returns are in a down, normal or up state. Funds's returns move positively with the US equity market under all states or regimes of funds returns but most especially during the down regime. They are influenced by the Australian equity market only during the normal regime and by the US bond market only during the up regime. In line with those of previous studies, these results imply that Australian superannuation funds are not able to time their exposure to markets and that their performance is indicative of an efficient market.

Acknowledgements

We are grateful to the Editor and the anonymous reviewer of this journal for their constructive comments. We would also like to thank the participants, for the feedback that we have received, of the 11th FINSIA-Melbourne Centre for Financial Studies Banking and Finance Conference held in Melbourne, Australia on 25 and 26 September, 2006 and the Department of Accounting, Finance and Economics, Griffith University Seminar Series on 25 August 2006. The usual disclaimer applies.

Notes

¹ These include funds that are no longer traded, have only monthly data and with missing data for more than two weeks in the Morningstar database.

² The recommended sample size is 311 funds (i.e. calculated at 95% confidence level and 5% confidence limits of the total funds's in multi-sector funds) and there were 313 funds included in this study.

³ The continuous return formula is used as it is well-known to provide more accurate measure of return compared to the discrete formula (Brailsford et al ., 2004, p. 9). Other studies evaluating funds performance have used the same way of measuring returns (Sawicki and Ong, 2000; Benson and Faff, 2003; Bohl et al., 2005).

⁴ This section relies heavily on Krolzig (1997).

⁵ This section borrows heavily from Ehrmann et al . (2003, pp. 10–11).

⁶ This model is able to capture the autoregressive conditional heteroskedasticity effects (Krolzig, 1997, pp. 24–25).