نوسانات و جریان اطلاعات در بازار سهام در حال ظهور : مورد بورس اوراق بهادار کره ای

Applying the generalized autoregressive conditional heteroskedasticity (GARCH) model to the Korean Stock Exchange, this study examines: (1) the statistical property of time-varying volatility in returns and trading volume data found in an emerging capital market, and (2) the property of the conditional variances of returns in predicting the flow patterns of information across the firms of different sizes. The results find that current trading volume as a proxy of information arrival dramatically reduces the persistence of the conditional variance, meaning that the arrival of information is a source of the ARCH effect in the emerging market just as it is in the U.S. The results also show that just as the volatility of larger firms can be predicted by shocks to smaller firms, the volatility of smaller firms can be predicted by shocks to larger firms. However, the volatility spillover effect from larger to smaller firms is more significant than that from smaller to larger firms.

This study examines the relationship between information flows and return volatility in the Korean stock market. An analysis of stock return volatility and trading volume as a source of the ARCH effect in the Korean market is performed. With a release of the i.i.d. assumption on the mixing variable, the relevancy of MDH in explaining the conditional heteroskedasticity of returns is tested with a GARCH (1,1) model specification. The result shows that adding current trading volume in the conditional variance equation (that is, adding the current trading volume as a proxy for the rate of information arrival to the market) dramatically reduces the volatility persistence of returns. This implies that volume data denoting the arrival of information is a source of the ARCH effect, and that the MDH is relevant in the Korean stock market. This study also evaluates the volatility spillover effect across large and small firms with two sample portfolios from the Korean Stock Exchange, examining the predictability of volatility variance in one portfolio that may affect the conditional volatility in another portfolio. The results show that, in general, the volatility of larger firms can be predicted by shocks to smaller firms, and vice versa. However, the most interesting aspect of the evidence is the distinct asymmetry in the volatility spillover effects across securities: The estimated effect of shocks of larger firms on the volatility of smaller firms is almost five times larger than the effect of shocks of smaller firms on the volatility of larger firms. Since the volatility of returns is directly related to the rate of flow of information, the possible explanation for asymmetry in the predictability of the volatility is that aggregate information that first affects large firms is impounded to a large degree by a lag in the prices of small capitalization companies, while aggregate information that first affects small firms is impounded to a small degree by a lag in the prices of large capitalization companies.