Friends or enemies? Foreign investors in Taiwan

Abstract

This study investigates how foreign investors impact the Taiwanese stock market using the AutoRegressive Jump Intensity (ARJI) model proposed by Chan and Maheu (2002), in which stock volatility in Taiwan is classified as either normal or abnormal and the net purchases of foreign investors, together with the classified volatilities, are included in the bivariate Vector Autoregression (VAR) model for further analyses. The sample period comprises of two parts, namely before and after relaxation of the restrictions on Qualified Foreign Institutional Investor (QFII) investors on 2 October 2003 (pre- and post-QFII). The forecast error variance decompositions and impulse–response functions are obtained via simulating the VAR model. Our results indicate why previous studies, in which abnormal volatilities were not taken into account, confronted biased and inconsistent results. Biased results from previous studies tend to be caused by not differentiating between normal and abnormal volatilities, and the results of this study provide a valuable reference for efforts to end conflicting arguments for whether destabilizing or stabilizing stock markets of foreign investor transactions. Furthermore, the study results also indicate why Taiwan was less affected during the Asian financial crisis.

Notes

¹Alternatively, Chiu et al. (2005) investigated the impact of foreign investors' trading behaviour on the trading volume of derivative markets during the presidential election periods and the parliamentary election periods using a bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. Another work by Wang and Lin (2008) also investigated the effect of political activity on the Taiwan Stock Exchange (TAIEX) stock market returns after financial reform using asymmetric GARCH.

²Most previous studies measure stock return volatility using either SD of stock returns or GARCH models or both, such as Li (2007) and Wang and Lin (2008).

³The jump size, , is assumed to be independently drawn from a normal distribution. and the jump component influencing returns from to is . The jump innovation associated with period is expressed as and is contemporaneously independent of .

⁴As foreign investors frequently have superior investment information and more rational investment strategies compared to domestic investors, their actions are frequently used as a guide by individual domestic investors in Taiwan, and this study thus takes the net purchases of foreign investors (transaction volume in logarithm) as substitute variables to study the foreign investment effects on Taiwan's stock market. Furthermore, the diffusion and jump variances were taken as normal and abnormal volatilities from the estimated ARJI model during the pre- and post-event periods following performing tests for testing residuals and related parameters.

⁵The sample period runs from 1 August 1995 to 30 June 2005. Daily TAIEX transaction data were collected and transformed into daily returns, yielding 2610 observations. The day (2 October 2003) on which foreign investment limits in Taiwan were released was taken as the division between the pre- and post-event periods to determine the influence of foreign investment on stock volatility in Taiwan. Both the daily TAIEX index and the net purchases of foreign investors are obtained from the Taiwan Economic Journal (TEJ). The JB test of the daily returns of TAIEX and the transaction of foreign investors are 309.7414 and 5672.871 with p-value 0.000000, respectively. Fundamental descriptive statistics demonstrate that the distributions of the daily returns of TAIEX and the transaction of foreign investors are not a normal distribution, in which average daily returns are 0.007801 and average net purchases of foreign investors are 774.7705.

⁶ Table 1 shows that the estimates of the ARJI model before and after the release of the QFII limit display that the Q and Q² tests of residuals are all insignificant, implying that no serial correlation exists. Thus, the ARJI(1,1) model is feasible for this study.

⁷The conditional variance of returns is decomposed into two components: a smoothly developing conditional variance component related to the diffusion of past news impacts and the conditional variance component associated with the heterogeneous information arrival process which generates jumps. The total conditional variance of returns is .

⁸Ratio of jump variance to total variance, that is, .

⁹The scales of Y-axis become smaller from 14 (pre-event) to 12 (post-event) in abnormal volatility, and lower more from 7 (pre-event) to 2.8 (post-event) in normal volatility.

¹⁰Forecast error variance decompositions reveal that an innovation to unexpected net purchases of foreign investors initially has limited explanatory power on the movements in the abnormal variance. In the long run, the explanatory power increases over time, from 1% to 8% during the pre-QFII period and 0% to 29% during the post-QFII period. In contrast to the clear effect of foreign investors on abnormal volatility variance, foreign investors lead little explanatory power on normal volatility variance, ranging from 0.06% to 0.82% for the pre-QFII period and 0% to 11% for the post-QFII period. This result demonstrates why previous studies faced biased and inconsistent results when they failed to consider abnormal volatilities. Full results can be obtained from the authors.

¹¹Foreign investors were not significant sellers in the Taiwanese stock market during the Asian financial storm. During the periods from 1995 till 2005, foreign investors were net sellers in only 3 years, namely 1995, 1998 and 2002. In summary, foreign investors in years 1997 and 1998 were still net buyers. The results presented here (negative effect) also supports that Taiwan's stock market is not influenced by the financial storm.