Preliminary analysis
In this section, we test for the presence of structural changes in the time series of stock returns and NEF. To this end, we use the iterated cumulative sum of squares (ICSS) algorithm developed by Inclan and Tiao (1994). The ICSS algorithm iteratively searches for multiple change points in the variance at different segments of the series. It is essentially based on the centered version of the cumulative sum of squares presented by Brown et al. (1975). The ICSS algorithm is configured to have a significance level of 5%. For this level, Inclan and Tiao (1994) provide a numerically simulated asymptotic critical value equal to 1.358. The structural changes identified by the ICSS algorithm are displayed in Fig. 2.
The first notable observation is that structural changes distinctively appear around the tumultuous events, particularly the global financial crisis of 2008. In our sample, the period from January 1999 up to November 2001 was the most volatile in the South Korean stock market. This high volatility is most likely caused by the severe recession in the global high-tech industryFootnote 7 in 2001. Moving forward to the period of the global financial crisis in 2008, the volatility of stock returns further decreased in the last stages of this crisis in July 2009. The NEF appear to be highly unstable compared to stock returns and more sensitive to external shocks. Similar to stock returns, the volatility of NEF indicates major changes around the global recession of the high-tech industry in 2001 and the global financial crisis of 2008. Moreover, another structural change of net equity flows in the Korean stock market appears in October 2013. This change is perfectly concurrent with the rumors of the US Federal Bank tapering its fund rate in late 2013. This event, which has become known as “Taper Tantrum” generated worldwide shock waves that severely affected many emerging market economies.
The time-varying stochastic volatility
The stochastic volatility is a critical component of the TVP-VAR-SV model, it allows the time-varying coefficients to adapt to possible variations in the disturbances signaled in the underlying time series. Nakajima et al. (2011) state that time-varying volatility contributes to the VAR estimation, identifying the structural shock with the appropriate variance of the shock size. The posterior estimates of stochastic volatility for stock returns and NEF in South Korea are plotted in Fig. 3. As can be seen, volatility spikes are strikingly obvious around the periods of the global recession of the high-tech industry in 2001 and the global financial crisis of 2008. The volatility spikes around the former are notably higher compared to the period of the latter. In addition, the stochastic volatility of NEF and stock returns in South Korea starts strong at the beginning of the sample period, then follows a downward trend thereafter. Interestingly, there is a significant joint reduction of stochastic volatility starting from 2011 in stock returns and NEF. In general, the dynamics of stochastic volatility are somewhat similar to the incremental shrinkage in the variances given earlier by the results of the ICSS algorithm.
Foreign investors’ impact on stock returns
The time-varying impulse response is one of the main characteristics of the TVP-VAR-SV model. The model offers two methods to present such responses. In the first method, historical impulse response functions can be drawn in a three-dimensional form by computing the recursive innovations of the variables using the time-varying coefficients from the current date to the future period. At each time point, there will therefore be a different set of impulse response functions. In the second method, the responses can be drawn in a time series manner by showing the size of the impulses for specific horizons over time. In the setting of Nakajima’s (2011) estimations of the TVP-VAR-SV model, the response corresponds to a shock size equal to the average of stochastic volatility of each variable in the VAR system. Since the computation of the impulse response functions is based on time-variant parameters, the effects and contributions of shocks may also change over time.
The time-varying response of stock returns to net flow shocks are illustrated in Fig. 4. While the historical impulse responses and contemporaneous relations, shown by graphs a and b, respectively, initially indicate a time-invariant positive contemporaneous impact of NEF on stock returns, graph c shows a time-varying propagation mechanism of the net flow shocks. The propagation mechanism of the net flow shocks is apparently completely dependent on the financial and economic conditions of the stock market. More precisely, the time-varying impact of net flow shocks on stock returns quickly turns to a negative impact during most of the crises, especially the 2001 recession of the high-tech industry and the European sovereign debt crisis in 2010. However, it took a slightly longer horizon to become negative during the 2008 global financial crisis. Note that during the latter, the impact of NEF is not as severe as the other crises. The results also imply that NEF positively predict stock returns, this finding is consistent throughout the sample period and statistically significant, as can be seen in graph b. Moreover, the positive forecast ability of net flows to stock returns is limited to a two-month horizon ahead during the crises, but it can persist to longer horizons at some time points. Notably, during the period from 2003 up to the break-out of the global financial crisis, the impact of net flows remains positive over 8-month horizon ahead. This means that foreign investors enjoyed a longer time window of profitable trades during this period, whereas they have a short time window of positive returns following their trades during crises. Surprisingly, the positive short-horizon forecast ability of net flows becomes more frequent after the “Taper Tantrum” event in May 2013. From this event and forward, the South Korean economy experienced a sharp reduction in foreign capital inflows coupled with a slowdown of economic growth. As shown in Fig. 2, the foreign investors’ net equity trading also began to decline since this event. The weak growth potentials possibly affected the performance of the stock market and led to decreased trading activities by foreign investors. Graph d shows the persistence of net flows, which is a result of net flow response to its own shocks, and provides further insight into the positive contemporaneous relationship between foreign investors and stock returns. It shows that the positive forecast ability is mostly due to the persistence in net flows. This finding is essentially derived from the significant co-movement between time-varying responses of returns and net flows at the horizon of 4-month ahead of the shock. It is also important to note that the co-movements of net flows and returns’ time-varying responses appear at other subsequent horizons. This finding seems to support the hypothesis of “price pressure” rather than “price impact”.
Ülkü (2015) suggests that the evidence of forecast ability may imply a marginal information advantage or a sophisticated response to new information by foreign investors. Based on our findings, the time variations in the positive forecast ability according to the global and local economic conditions, specifically during the last period of slow economic growth, may indicate that foreign investors are strongly informed about the macroeconomic fundamentals of the host market. Foreign investors may still lack local information as suggested by Brennan and Cao (1997) and Griffin et al. (2004). Nonetheless, their equity trading activities are based on superior macroeconomic knowledge. Ülkü and Ikizlerli (2012) and Ülkü (2015) establish this assumption through foreign investors’ positive contemporaneous response to global stock returns. Our findings further support this assumption based on the adjustability of positive forecast ability of net flows according to the macroeconomic conditions.
Feedback trading and the role of economic uncertainty
The time-varying reactions of foreign investors to return shocks are displayed in Fig. 5. Note that these results are derived from estimating TVP-VAR-SV with ordering NEF after stock returns. It is important to note the contemporaneous impact of returns on net flows in graph b while explaining the trading behaviors at the subsequent horizons from graph c. As can be seen in the two graphs, there are some drastic changes in the trading behavior of foreign investors. To make more sense of these changes, we plot the foreign investors’ time-varying responses to return shocks along with the time-varying economic uncertainty as shown in Fig. 6. The time-varying economic uncertainty is a result of its response to its own shocks, which can also be interpreted as persistence of economic uncertainty. The time-varying responses of both variables are presented at different impulse horizons.
Several observations from Fig. 5 are worth highlighting. First, the foreigners in the South Korean stock market are often initially trend chasers, as indicated by the time-varying positive contemporaneous responses of net flows in graphs a and b. Notably, the foreign investors are more aggressively trend chasers during the crises, particularly the 2008 financial crisis and the European sovereign debt crisis in 2010. The aggressive trend-chasing behaviors, during these periods specifically, are undoubtedly a result of the rampant equity sell-off caused by the worldwide collapse of stock markets during the aforementioned crises. Second, the time-varying positive contemporaneous response of net flows frequently reverses to negative response, which amounts to behaviors of negative feedback trading. There is abundant evidence of such trading at the subsequent horizons. Based on the results in graph c, the bulk of the time-varying negative feedback trading is observed in the fourth month after the shock. However, the lagged negative impact of stock returns on net flows can be observed, although seldomly, within one or two months after return shocks; this quick reverse is exclusively found during the year 1999 and the period between February 2001 and September 2002. Third, foreigners’ trading behaviors sometimes appear to be following a specific pattern of feedback trading. In other words, the contemporaneous response of the net flows can be either negative or positive with no reverse of the sign over the entire impulse horizon. For instance, we find evidence that the foreign investors are purely positive feedback traders during several sub-periods: March 2003–February 2004, May–September 2009, and September 2012–August 2014, whereas the response of net flows is entirely negative during the period April–September 2002. Finally, examining the results presented in graphs c and d reveals that the foreign investors tend to be negative feedback traders when the movements of stock returns are weakly persistent.
The latter finding may seem consistent with the analogy provided by Ülkü (2015), who suggests that the positive feedback trading is initially prompted by the response to host market information, then the negative feedback trading appears once the response to this information is completed. However, the results presented in Fig. 6 indicate that the foreigners’ feedback trading is largely dependent on the time-varying perceptions of economic uncertainty. According to these results, the foreigners’ negative feedback trading prevails when the persistence of economic uncertainty becomes weakly sustainable. On the other hand, the behavior of foreigners’ positive feedback trading exceptionally appears during periods of high economic uncertainty. Interestingly, the negative contemporaneous response of net flows observed earlier is associated with extremely low levels of economic uncertainty. Recall that negative feedback trading is equivalent to informedness. This means that foreign investors act as information contributors when economic uncertainty is weak, but they trend-chase while the uncertainty about the economic policy is strong. In fact, their feedback trading mostly appears to be well-timed and often leads the time-varying economic uncertainty during most of the sample period. As expected, the periods of global crises are an exception. This finding sharply contrasts the theories of the informational disadvantage of foreign investors (Brennan and Cao 1997; Griffin et al. 2004; Brennan et al. 2005). The findings can also be considered an extension to the evidence provided by some recent studies on South Korea such as Ülkü (2015) and Ülkü and Weber (2014). the aforementioned studies indeed find strong evidence of lagged negative feedback trading in South Korea. However, their results exclude the possibilities of the negative contemporaneous response of net flows to stock returns and persistent positive feedback trading. Empirical evidence for such patterns of equity trading behaviors are distinctively apparent in our results despite the wide prevalence of the lagged negative feedback trading. Furthermore, we find little evidence that supports the predictions of Hau and Rey’s (2004) portfolio rebalancing model. This model predicts a negative contemporaneous correlation between net flows and stock returns caused by selling appreciated stocks in the host market to mitigate exchange rate risk.Footnote 8 The main implication of Hau and Rey’s (2004) model, that is, the negative contemporaneous impact, is found to be short-lived and is highly driven by extremely low levels of economic uncertainty. The inaccurate predictions of Hau and Rey’s (2004) model are probably due to failure to control for a common driver of the exchange rate, equity returns, and net flows. Alternatively, we suggest that the flow orders in the foreign exchange market that correspond to foreigner’s equity portfolio rebalancing are probably simultaneously driven by the level of economic uncertainty in the host market.
Impact of uncertainty on foreign investors and stock returns
The time-varying impact of economic uncertainty shocks on foreign investors and stock returns are illustrated in Figs. 7 and 8, respectively. We report the results of the two previously explained alternating orders. Although the time-varying impulse responses of net flows to uncertainty shocks are largely similar, the time-varying responses of stock returns to uncertainty shocks differ sharply across the two orders. Under the order of \(\left\{EPU,NEF,R\right\}\), the time-varying response of stock returns is mixed with negative and positive contemporaneous responses throughout the sample period. Meanwhile, stock returns always respond negatively to shocks of uncertainty under the order of \(\left\{EPU,R,NEF\right\}\). However, further results reported in Fig. 10 in Appendix B show that these differences are limited to the contemporaneous responses; the time-varying responses of stock returns at the subsequent horizons are quite similar across the two orders. Note that the time-varying contemporaneous responses of net flows and stock returns under the order of \(\left\{EPU,NEF,R\right\}\) are identical to each other. More importantly, the results in Fig. 8 indicate that a large fraction of uncertainty impact on stock returns quickly diminishes within one month after the shock irrespective of the order. In other words, the past uncertainty news bears a significantly smaller economic impact on stock returns beyond one month.
On the other hand, economic uncertainty sometimes appears to have a long-lasting impact on net flows, particularly during periods of global crises, although the extent of this impact is strongly dependent on the type of uncertainty shock. The longest-lasting positive impact of uncertainty on net flows is notably observed prior to the outbreak of the 2008 global financial crisis. Overall, the negative impact of uncertainty shocks on net flows is found to be contemporaneously stronger, yet less persistent, and relatively less strong than the impact of positive shocks at the subsequent horizons. This finding also points to an asymmetric response of foreign investors to different shocks of economic uncertainty. More specifically, foreign investors may sluggishly respond to positive shocks of economic uncertainty compared to negative shocks at some time points. However, they are eventually more driven by positive shocks of economic uncertainty than the negative ones in longer horizons. It can therefore be concluded that NEF can either co-move or inversely move with EPU. Most of the empirical analyses of static models have so far uniformly reported an adverse impact of economic uncertainty on foreign investments (e.g., see Canh et al. 2020; Choi et al. 2020; Rivoli and Salorio 1996). In contrast, we find that economic uncertainty impact is not limited to creating adverse shocks on foreign equity investments.
Another aspect to consider is the direct connection between net flows’ response to economic uncertainty and foreign investors’ feedback trading. Accordingly, we find that lagged negative (positive) response of net flows to uncertainty is associated with lagged positive (negative) feedback trading. Part of these results is reported in Fig. 11 in Appendix B. Note that the inverse relationship between net flows’ response to uncertainty and foreign investors’ feedback trading becomes regularly apparent starting from the second or third month after the uncertainty shocks. The appearance of this type of relationship distinguishably at the subsequent horizons is due to the asymmetric impact of economic uncertainty on net flows. As previously discussed, foreign investors respond quickly to negative shocks of uncertainty to net flows, which leads to instant positive feedback trading. Contrarily, foreign investors slowly move toward negative feedback trading after a positive contemporaneous response of net flows to uncertainty shocks. This also explains the wide prevalence of time-varying contemporaneous positive feedback trading as documented earlier in the analysis of foreign investor’s feedback trading. The asymmetric response of foreign investors could possibly be explained by the flows of net foreign equity investments into the market despite the increase of economic uncertainty.Footnote 9 In this case, the foreign investors may forcibly be trend chasers as market trends are unpredictable due to uncertainty about fiscal, regulatory, and monetary policies. This explanation is more reliable under the results of estimating TVP-VAR-SV with the order of \(\left\{EPU,NEF,R\right\}\), which reveals that net flows and stock returns have similar contemporaneous responses to economic uncertainty shocks. Foreign investors would move toward negative feedback trading as economic uncertainty begins to decline.