Sources of volatility in stock returns in emerging markets

Abstract

In this study, the short-term fluctuations in the monthly returns on composite indexes of 17 emerging markets affected by the financial crises in the late 1990s and 2000 are decomposed with vector autoregressive estimates. The results are compared to the behaviour of variation in returns in developed markets. Three different models are estimated for each market. Due to first order autocorrelations, lagged returns contribute significantly to return volatility in emerging markets. Decomposition of variances indicates that dividend yield and interest rate are determining factors of volatility, but at varying degrees in different emerging markets. However, the role of dividend yield is not as strong as it is in the developed markets as efficient markets hypothesis would imply. In some cases, exchange rates significantly influence market volatility. Fluctuations in the world portfolio return have a small effect on return volatility in national markets. However, there are significant differences across all emerging markets that point to differences in market structures and particular conditions in each country. Significant contributions of interest rates, exchange rates and inflation imply the role of monetary and fiscal policy as precedents of financial crises.

Acknowledgements

An earlier version of this paper was presented at the 52nd Annual Meeting of the Midwest Finance Conference in St Louis, Missouri. We would like to thank Gulnur Muradoglu, Vivian Fernandez and participants at the conference for their comments and recommendations.

Notes

The derivation of the model is available from the authors upon request. The model used is an extension of the asset pricing model developed for an exchange economy in Lucas (1978) and Caner and Önder (1998).

For example, see, Harvey et al. (2002), Korajczyki (1996) or Harvey (1995), to cite a few.

According to the CCAPM, price of the market portfolio is proportional to consumption and k is the proportionality factor.

In the standard CCAPM model the exogenous process is the consumption growth process. The expanded model used here adds the exchange rate as an exogenous stochastic process in addition to the stochastic consumption process. Exchange rate is a determining factor in emerging markets and foreign currencies are often used as a hedging asset. Both the consumption growth rate and the exchange rate are geometric Brownian motion. Furthermore, the drift term of the consumption process is also stochastic.

In the model, the interest rate is also a stochastic process derived from the relationship r = μ + ρ − σ². See, Caner and Önder (2000) and Long and Plosser (1983).

The reasons for choosing a VAR model over a univariate time series model are explained in Campbell (1991). Since error terms would be correlated, a VAR model to estimate the factor contributions to volatility would be appropriate.

For example, see, Harvey et al. (2002), Korajczyki (1996) or Harvey (1995), to cite a few.

Bekeart and Harvey (1995) provide a summary of the MSCI methodology. MSCI indexes are value-weighted with a target of 60% coverage of total market capitalization of each market. The indices replicate the industrial composition of the local markets and the sample represents large, medium and small capitalization stocks excluding nondomiciled companies and investment funds.

A table of correlations of returns between the markets can be provided upon request.

The change in dividend yield has a higher correlation with consumption growth than the GDP growth rate at lower frequencies. Therefore, dividend yield is a better proxy for consumption growth than the GDP growth rate. Nevertheless, the model is also estimated by using growth rate of GDP and the growth rate in industrial production as proxies for consumption growth. Similar to Chowdhry and Goyal (2000), it is found that the GDP growth rate had a minor impact on returns volatility, about 2.9% on average with the exception of the Russian Federation where it is 22%.

Model estimates are provided in Tables 4–6.

Between January 1998 and August 1998, the Russian equity market lost 80% of its value. However, since then the market experienced significant returns albeit in a very restricted market.

According to IRP, exchange rate fluctuations are determined by the interest rate differential between the home country and the foreign country.