The industrial relationships in time-varying beta coefficients between Korea and United States

Abstract

This article examines financial linkage of systematic risks for 20 industry portfolio returns between Korean and US stock markets. Time-varying beta coefficients of Capital Asset Pricing Model are estimated and Granger-causality tests are carried out for identifying the significance of the industrial relations between the two stock markets. The empirical findings show that the strength and the causality of international financial linkage vary depending on the types of industry and the shocks in the systematic risk. Some Korean industries, including financing industries, iron and metal industries, service, and textile and wearing industries are relatively vulnerable to systematic risk associate with US industries.

Acknowledgements

The authors are grateful for the valuable comments and suggestions from the anonymous referees and editor. All errors remain the responsibility of the authors.

Notes

¹ The capital asset pricing model (CAPM), first introduced by Sharpe (1964) and Lintner (1966), has made a profound impact on the way investors understand the relationship between price and risk of capital assets.

² Black (1993) argues that previous findings of a flat relationship between beta and return (e.g. Fama and French, 1992) may be attributed to data mining bias.

³ We often need to know the direction of influence between variables in empirical work, that is, does A affect B, or does B affect A, or is the influence bi-directional. When theory is silent about causation or an empirical analysis is necessary to verify the theory, Granger causality tests can be used to determine when one random variable precedes another (Granger, 1969; Sims, 1972). Note that this is not causality in the standard sense of the word since precedence does not imply causation. Causation is a purely theoretical issue. Therefore, tests of Granger causality should be interpreted strictly as precedence rather than as true causality.

⁴ Given the low return-high risk measured by the ratio between mean return and SD, the Korean market seem unattractive to foreign investors.

⁵ Both ADF and Phillips–Perron test showed that the Kalman betas of all the portfolios are I(0) integrated.

⁶ The results show that the means of the Kalman beta processes are roughly similar to the means of the systematic risk under the assumption of constant risk. For example, the mean of constant betas for Korean 20 industries is 0.941 and the mean of time varying Kalman betas over portfolios is 0.861. For United States, the mean of constant betas is 0.979 and the mean of Kalman betas is 1.027. The correlation between Kalman beta and constant beta is more than 0.89.

⁷ The numbers of lags used while conduction Granger-causality tests are between 2 and 12.