Conditional risk and return in Asian emerging markets: evidence from the banking sector

Abstract

Previous studies reach no consensus on the relationship between risk and return using data from one market. This study argues that the market factor should be noticed in assessing the risk-return relationship in a partially integrated emerging market. The analysis aims to provide new insight into the nature of the risk-return relationship by a conditional factor GARCH-M framework that controls for time-series effects, to investigate the banking sector in five Asian emerging markets of China, Hong Kong, Indonesia, Malaysia and Taiwan during the period 1995 to 2004. Finally, the study provides evidence on these relations before and after the Asian financial crisis of 1997. The results are generally consistent across the markets and with expectations, and have implications for empirical assessments of the risk-return relationship and diversification.

Acknowledgments

The author acknowledges the financial support from the National Science Council in Taiwan (NSC93-2416-H030-010), and expresses the gratitude to the valuable suggestions of T. J. Brailsford and Jack H. W. Penm.

Notes

¹ Bansal and Lundblad (1999), Campbell and Hentschel (1993), Chou (1988) and French et al. (1987) find a positive relationship between the expected excess market return and conditional variance, whereas Baillie and DeGennaro (1990), Glosten et al . (1993) and Nelson (1991) find the opposite. Alternatively, Noh and Kim (2006) find that for the FTSE 100 futures, the historical volatility using high frequency returns outperforms implied volatility in forecasting future volatility. However, the implied volatility outperforms historical volatility in forecasting future volatility for the S&P 500 futures. The results also indicate that historical volatility using high frequency returns could be an unbiased forecast for the FTSE 100 futures.

² For example, Aquino (2006) examines whether Fama's discrete version of Merton's intertemporal CAPM (ICAPM) can explain the negative market risk premium and the cross-sectional variability of Philippine stock returns after the onset of the Asian financial crisis in July 1997. The results provide a plausible explanation both for the cross-sectional variability of stock returns and the negative market risk premium within the framework of mean-variance optimizing investors.

³ Choi et al . (1992); Madura and Zarruk (1995); Neuberger (1994) and Saunders and Yourougou (1990) argue that the nature of the banking business results in high leverage balance sheet positions. Interest rates are a critical element in bank operations and their profit margins are highly related to borrowing and lending margins. Thus, interest rates have been consistently examined in a pricing context for bank stocks. The results from the approach have generally yielded inconsistent findings, with mixed evidence of a positive and negative systematic influence of interest rates on banking stock returns. Isolating the impact of interest rates is difficult as different studies have looked at different aspects of the pricing relationship including term spreads, credit spreads, innovations in rate movements, real compared to nominal effects and shocks to rate levels.

⁴ Note that returns are first mean-adjusted before entering the ARCH process and hence the intercept is restricted to zero.

⁵ For example, the market indices used are the Shanghai B Stock Index, the Hang Seng Index, the Indonesia JXS Index, Taiwan Weighted Stock Index, etc.

⁶ The Q-statistic is calculated as where N is sample size and r_k is the sample autocorrelation at lag k.