US INTERNATIONAL EQUITY FLOWS TO ASEAN-4 EMERGING MARKETS

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1 US INTERNATIONAL EQUITY FLOWS TO ASEAN-4 EMERGING MARKETS Norlida Mahussin Faculty of Science and Technology, Universiti Sains Islam Malaysia, Rabihah Md.Sum Faculty of Science and Technology, Universiti Sains Islam Malaysia, Hasri Mustafa Faculty of Economic and Management, Universiti Putra Malaysia ABSTRACT This paper examines the behavior of US international equity flows (gross flows and net flows) to ASEAN-4 emerging markets from January 1992 to August Our findings show that US investors engaged in more purchase of ASEAN-4 equity than sell. The flows series show positive correlation, and gross flows (sales and purchase) are determined by past flows. Foreign countries equity returns and dividend yield play an important roles in determining flows to ASEAN-4 compare to push factors except for US credit spread. Our findings show the existence of local and global return chasing of US investors in ASEAN-4 equity markets. Field of Research: returns equity flows, cross border investment, US equity flows, Asean-4, equity 1. Introduction The liberalization of ASEAN emerging markets in late 1980 provide expanding opportunities for foreign investors to diversify their portfolio across these markets. With the strengthening of ASEAN economy community and expected gross domestic product (GDP) exceeding USD1 trillion by , these markets are able to attract more foreign investors in the near future, including US investors, the world largest international investors. According to US Treasury, as at December 31, 2016, the total holding of ASEAN-4 (Indonesia, Malaysia, the Philippines and Thailand) equity by US investors was approximately USD99, 239 million comparing to only USD75, 534 million in 2010 and USD20,773 million in These figures prove the increasing importance of ASEAN-4 equity in US investors foreign portfolio holdings. Empirical evidences on US international investment document at least two common regularities in US investors transactions in foreign countries. First, the persistence of net inflows. Secondly, the return chasing. For the first, literature shows equity flows display considerable serial correlation, with net flows reversing after one year (Albuquerque, Bauer, and Schneider, 2009), five to six quarters 1 Based on a recent study by HIS Inc. a US-based global information company. 2 US Treasury reports US total holding of equity at the end of 2016 in Indonesia, Malaysia, Philippines and Thailand were approximately USD30,357 million, USD18,870 million, USD15,756 million and USD34,256 million respectively. Organized By Page 506

2 (Albuquerque, Bauer, and Schneider, 2007) or at least in two quarters (Bohn and Tesar, 1996). As such, the net purchase of foreign equity by US investors in some period can predict the future purchase in other period. For the second, literature shows the US net purchase of equities correlates positively with excess returns of foreign markets. As such, US investors invest in foreign markets when market is high and sell when market is low (Albuquerque, Bauer and Schneider, 2009; Bekaert, Harvey, and Lumsdaine, 2002; Brennan and Cao, 1997; French and Li, 2012). The explanation for return chasing is based on information asymmetry between local and foreign investors (Brennan and Cao, 1997; Albuquerque et al., 2009) which is determined by various factors. Literature shows that push and pull factors play an important role for international equity flows which represent the expected risk and return of foreign investment. The push factors refer to global factors such as change in global interest rates and change in global risk, and the pull factors refer to country specific factors such as country s equity returns and dividend yields (Chuhan, Claessens, and Mamingi, 1998; Forbes and Warnock, 2012; Fratzscher, 2011). Some studies also relate equity flows to other factors including contagion and familiarity (Forbes and Warnock, 2012; Portes and Rey, 2005). In this paper, we examine the behavior of US equity flows to ASEAN-4 emerging countries (Indonesia, Malaysia, Philippine and Thailand). We refer flows to sales and purchase of foreign equities by US investors. While most studies on US equity flows focus on net flows (for e.g., Bohn and Tesar, 1996; Brennan and Cao, 1997, Edison and Warnock, 2008; Guo, 2016), we study gross flows (sales and purchase) and net flows of ASEAN-4 equities by US investors and their relation to local equity returns. We find that gross flows and net flows behave differently. Our findings are in line with previous literature on local and global return chasing behavior of US investors in foreign markets. We further investigate the factors effect gross flows and net flows using ordinary least square regression (OLS) and found the importance of pull factors in determining net flows to ASEAN-4 countries. The reminder of this paper is organized as follows. The next section presents a brief review on international cross border flows. Data used in the analysis are discussed in the following section. In empirical results, we present the paper findings. The final section concludes. 2. Literature Review The diversification benefits of international investing attract US investors to emerging markets (Bekaert and Harvey, 2000) and international investing by US investors can be explained by two possible reasons; low correlation between US national equities and foreign equities, and higher return in non- US markets (Conover, Jensen, and Johnson, 2002). However Bohn and Tesar (1996) find that US investors invest in foreign markets not for portfolio rebalancing rather chase past return. They tend to be net buyers when foreign stock prices are rising. The argued explanation is based on information asymmetry between local and foreign investors. Foreign investors are believed to have less information about the local market compare to local investors. Brennan and Cao (1997) develop a model where local and foreign investors possess different information about the local stock market, and demonstrate that the less informed foreign investor react more strongly to public information. They provide a scenario that if the public signal conveys good news about the payoff on the domestic market portfolio, foreign investors will increase their assessment of the expected payoff faster than the better informed domestic investors. As a result, price rises to clear the market, and the less well informed foreign investor purchase more of the domestic market portfolio than the better informed domestic investors (Brennan and Cao, 1997, p.1854). Empirical findings on information asymmetry have also been documented in country specific studies including Brazil (French and Li, 2012), Korea (Choe, Kho, and Stulz, 1999), Indonesia (Dvořák, 2005), Finland (Kalev, Nguyen, and Oh, 2008) and Turkey (Diyarbakirlioglu, 2011). These studies favour informational disadvantage of foreign investors. Organized By Page 507

3 Even though an average foreign investor has less local knowledge than an average local investor, some foreign institutions have better information because of their experience and expertise (Dvořák, 2005; Grinblatt and Keloharju, 2000; Seasholes, 2000). Foreign investors sometimes beat local investors performance which shows that foreign investors may have information advantage (Albuquerque et al., 2009). Albuquerque et al.. (2009) examine US international equity investment by considering global private information that is relevant for trading in many foreign countries simultaneously. In their theoretical model, stock returns are derived from both local and global factors. Since global factors are commonly related to the US, they assume that the fraction of investors who receive global signals is larger in the US than in the rest of the world 3. The findings show the existence of global private information in the portfolio equity trades of US investors. Nevertheless, Curcuru, Thomas, Warnock, and Wongswan (2011) find contradict evidence to previous regularities. Following Bertaut, Griever, and Tryon (2006), they estimate US portfolio data by combining data on TIC US foreign equity monthly transactions and equity positions data. They show that US investors do not chase past returns or rebalancing their portfolios. To a certain extent, US investors increase portfolio weights on a country s equity market just prior to strong performance. This indicates at some points, US investors have information advantage while buying and selling equities in foreign market. Guo (2016) provides evidences that US investors do not blindly chase past return but the action reflects their knowledge on foreign fundamentals. Clark and Berko (1997) argue if foreign demand is expected to ultimately push prices to higher equilibrium level, but foreigners only invest gradually, price should rise ahead of the actual inflows. Furthermore, if investors are unsure of the magnitude of new foreign demand for stocks, the arrival of new information that causes investors to raise their estimate of total foreign inflows should push prices to a higher level. They show that one-seventh of the monthly variation of Mexican stock returns is explained by foreign inflows and an unexpected foreign purchase of 1 percent of market capitalization is associated with contemporaneous price rises of about 13 percent. Froot, O connell, and Seasholes (2001) find a highly significant impact of contemporaneous flows on return. The impact can be in the weeks and months after the shocks. Similarly, Bekaert, Harvey, and Lumsdaine (2002) also discover an unexpected shock to equity flows have a strong positive contemporaneous effect on returns in emerging countries. Richards (2005) identifies a strong positive correlation between the net purchase of the foreigners in a market and the same day return in that market. His analysis using VAR shows that surprise in inflows has ongoing impacts on prices and last for a few days. Lin and Swanson (2004) discover a positive association between equity flows and returns in Korea, Malaysia and Thailand but not for other Asian countries. Jinjarak, Wongswan, and Zheng (2011) find evidences regarding the relation between inflows and returns. In the advanced Pacific and emerging markets, the results show that past net inflows contain information of current net inflows. Furthermore, past local market returns contain information of current net inflows in emerging markets specifically in Europe, Middle East and Latin America. While past net inflows contain information on current local market returns in North America and Pacific markets. The other strand of literature studies the determinants of cross border flows. Large number of studies divide the factors into two categories: push factors and pull factors (eg., Chuhan, Claessens and Mamingi, 1998; Edison and Warnock, 2008; Fernandez-Arias, 1996; Forbes and Warnock, 2012; Fratzscher, 2011; Taylor and Sarno, 1997). Push factors is refer to global factors such as change in global risk and return and change in US macroeconomics variables. As leading economies, US variables 3 Albuquerque, et al. (2009) refers global private information as US specific variables in which US investors have superior knowledge compare to domestic investors. Organized By Page 508

4 documented to have great influences on global economy (Fratzscher, Lo Duca and Straub, 2016; Nikkinen, Omran, Sahlstrom and Aijo, 2006). Forbes and Warnock (2012) refer global risk, global liquidity, global interest rate and global growth as push factors. Rather than using US macroeconomics variables, they use universal global variables. They find a strong association between global factors and wave of capital flows. The importance of global factors appears strong prior to the global financial crisis as well as during the crisis (Fratzscher, 2011), however become less important in driving capital flows after the crisis in some emerging countries. Even though most studies show the prominence of push factors in explaining cross-border capital flows, pull factors are also found to be significant drivers in certain countries. Pull factors or country specific factors refer to domestic opportunity and risk such as country s debt, credit rating, price-earnings ratio and rate of return. Taylor and Sarno (1997) investigate the long and short-term determinants of US portfolio flows to developing countries and discover that country specific factors are important in determining equity flows in short and long term period. Furthermore, domestic factors were more important in explaining net capital flows to emerging countries in Asia during late 1980 and early 1990 (Chuhan, et al., 1998), and after the global financial crisis in Asia and Latin America emerging countries (Fratzscher, 2011). Other studies relate flows to other factors such as familiarity (Lane and Milesi- Ferretti, 2008; Lee, Huh, and Kim, 2011; Portes and Rey, 2005) and contagion (Forbes & Warnock, 2012). 3 Data We study the period from January 1992 to August 2016 (296 monthly observations) for ASEAN-4 emerging markets (Indonesia, Malaysia, Philippines and Thailand). Our sample begins in 1992 following the liberalization of ASEAN Emerging capital market in late We collect data on US equity flows from US Treasury International Capital (TIC) reporting system. 5 The TIC reporting system is the US government s source of data on capital flow into and out of the United States, excluding direct investments. This data is used by the Bureau of Economic Analysis in the computation of US Balance of Payment account and the US International Investment Position. The system provides monthly data on transactions and holdings of long term securities of US investors. This data however has several shortcomings. The information on US transactions with foreigners in long term securities is reported opposite the country in which the immediate foreign transactor is located. Thus the country breakdown does not necessarily representing the country of beneficial owner or issuer. 6 The system does not capture those transactions below $50 million. These data however, has been used widely in many studies (eg; Albuquerque, et al., 2007; Albuquerque, et al., 2009; Brennan & Cao, 1997; Chuhan, et al., 1998; Tesar & Werner, 1995, among others). We study gross sales and purchase of foreign equity by US investors normalized by the beginning of the month market capitalization. gs/gp j,t = sls/pch j,t m j,t (1) 4 We refer to Bekaert and Harvey (2000) official liberation date: September 1989 for Indonesia, December 1988 for Malaysia and September 1987 for Thailand. The official liberalization for Philippines as in Bekaert and Harvey (2000) is June 1991 following the signing of Foreign Investment Act into law, though the IFC official date is October The TIC data are published on the US Department of the Treasury s website at 6 Excessive flows reporting in international financial centres such as UK, Belgium, Luxembourg, Switzerland and the Cayman Islands. For further discussion on TIC data, refer to Bertaut, Griever and Tryon (2006). Organized By Page 509

5 np j,t = gp j,t gs j,t (2) Where, gs/gp is the normalized gross sales or gross purchase of country j equity by US investors for month t, sls/pch j,t is the monthly gross sales or gross purchase of country j equity by US investors at month t and m j,t is the equity market capitalization of country j at the beginning of month t. Net purchase (np) is the difference between normalized gross purchase (gp) and normalized gross sales (gs). We use beginning of the month Datastream total equity return (rt) in US dollars as foreign market return. To examine the factors determine the flows, we collect data on push (global) and pull (country specific) factors. The selection of US variables is also appropriate as we study US foreign equity flows. Thus, we employ US equity returns (usrt), US short-term interest rates (usin) and US credit spread (uscr) as push factors. We use US 3-months rate as US short term interest rate. An increase in US interest rates will increase US investors risk free rate of return, therefore foreign investment is likely becomes less attractive. This will result in a decrease in cross-border equity transactions. Meanwhile, higher US equity returns will result in less equity investment abroad. We include US credit spread, the difference between the AAA and BBB bond yields to account for transaction that motivated by changes in US investors wealth (Albuquerque et al., 2009). We use foreign countries dividend yield (dy) and stock market returns (rt) as pull factors. Fama and French (1988) and Ang and Bekaert (2007) show that dividend yield predict stock returns. Increase in dividend yield is expected to increase equity inflow to a country. All data are from Datastream and data on US credit spread is downloaded from US Federal Reserve website. 4 Empirical Findings 4.1 Descriptive Statistics Table 1 reports the descriptive statistics of US equity flows to ASEAN-4 during January 1992 to August We find that US gross flows are more volatile than net flows in Malaysia and Thailand but the opposite for Indonesia and Philippines. Positive net purchase exhibits US investors engaged in more purchase of foreign equities than sell for all countries except Philippines. During the sample period, Indonesia received the largest net flows by US investors with the average of percent. Generally, the flows series show positive correlations, although the series are appeared stationary. Figure 1 shows US investors gross sales and puchase of ASEAN-4 equities during the sample period. Overall, the figure shows that US investors simultaneously buying and selling foreign equities in a given month. Table 2 presents summary statistics for pull factors: foreign equity returns (rt) and foreign dividend yield (dy) and push factors; US variables which we include US equity returns (usrt), US short term interest rate (usin) and US credit spread (uscr). ASEAN-4 equity returns for the period range between percent to percent, slightly higher than US equity returns (0.885 percent), and more volatile than US returns. Thailand shows the highest dividend yield of 0.704, followed by Malaysia at Organized By Page 510

6 Figure 1 Gross Sales and Purchase of Foreign Equities by US Investors Indonesia Malaysia gross sales/gross purchase gross sales/ gross purchase m1 1995m1 2000m1 2005m1 2010m1 2015m1 month 1990m1 1995m1 2000m1 2005m1 2010m1 2015m1 month gross sales gross purchase gross sales gross purchase Philippines Thailand 0 0 gross sales/ gross purchase gross sales/ gross purchase m1 1995m1 2000m1 2005m1 2010m1 2015m1 month 1990m1 1995m1 2000m1 2005m1 2010m1 2015m1 month gross sales gross purchase gross sales gross purchase Note: Data is for gross sales and gross purchase of foreign equity by US investors for Indonesia, Malaysia, Philippines and Thailand for the period of January 1992 to August 2016 (296 months observations). Gross sales is the sales of foreign equity by US investors to foreign residents and gross purchase is the purchase of foreign equity by US investors from foreign residents. Sales and purchase are normalized by dividing by the beginning of the month total market capitalization of the foreign equity, in US dollar. Dickey-Fuller tests reject the null hypothesis of a unit root in all countries. Organized By Page 511

7 Table 1 Summary Statistics of US Investors Sales and Purchase of Foreign Equities Mean Std. Dev Min Max Autocorrelation L1 L6 L12 Gross Sales Indonesia Malaysia Philippines Thailand Gross Purchase Indonesia Malaysia Philippines Thailand Net Purchase Indonesia Malaysia Philippines Thailand The table reports the summary statistics of gross sales, gross purchase and net purchase of US investors for Indonesia, Malaysian, Philippines and Thailand for the period of January 1992 to August 2016 (296 months observations). Gross sales is the sales of foreign equity by US investors to foreign residents and gross purchase is the purchase of foreign equity by US investors from foreign residents. Sales and purchases are normalized by dividing by the beginning of the month total market capitalization of the foreign equity, in US dollar. Net purchase is the difference between gross sales and gross purchase. Sales and purchase series are expressed in monthly percentage. The estimated autocorrelation for the flows series are for a 1, 6 and 12-month lag respectively. 4.2 Return chasing behavior Our results on return chasing behavior of US investors in ASEAN-4 equity markets are in line with many studies (for e.g., Brennan and Cao 1997; Albuquerque et al., 2009; French and Li, 2012). Table 3 presents the correlation of US investors net purchase of foreign equities and foreign equity returns in ASEAN-4 countries. Net purchase of US investors correlates positively with foreign equity returns, and statistically significance at 10 percent for Indonesia and Philippines, and 1 percent for Malaysia and Thailand. These findings show that US investors buy when ASEAN-4 equity prices rise and sell when equity prices fall. Albuquerque et al. (2009) documented global return chasing of US investors net purchase in developed market. We examine this behaviour and find similar findings on global return chasing in ASEAN-4 countries. 7 US investors net purchase of ASEAN-4 markets correlates positively with other ASEAN-4 equity returns. For example, when equity returns in Philippines increase, US investors not only purchase Philippines equities by also increase equities purchase in Indonesia, Malaysia and Thailand. We find several negative correlations between net purchase of US investors in 7 Albuquerque et al. (2009) empirical findings on developed markets support their model on global private information acquired by US investors that helps them forecast inernational returns. We do not run further test to confirm their findings on ASEAN-4 countries. Organized By Page 512

8 ASEAN-4 countries with equity returns in other ASEAN-4 countries, but the results are not statistically significance. These findings are likely to explain the superior global information possesed by US investors in international investing (Albuquerque et al., 2009) or foreign returns reflect foreign fundamentals that drove US investors to purchase foreign equities (Guo, 2016). Table 2: Summary Statistics of Push and Pull Factors Mean Std. Dev Min Max Equity returns (rt) Indonesia Malaysia Philippines Thailand Dividend yield (dy) Indonesia Malaysia Philippines Thailand US variables Equity returns (usrt) Interest rate (usin) Credit spread (uscr) The table reports the summary statistics of foreign equity returns (rt) and foreign dividend yield (dy) for Indonesia, Malaysia, Philippines and Thailand and US variables: equity returns (usrt), short term interest rate (usin) and credit spread (uscr). Foreign equity return is the beginning of the month Datastream total market equity return (rt) in US dollars and foreign dividend yield (dy) is Datastream total market dividend yield. US equity returns is Datastream total market return, US short-term interest rates (usin) is US 3-month rate and US credit spread (uscr) is the difference between US AAA and BBB corporate bond yields. Sample period is from January, 1992 to August, Determinants of flows We further examine the determinants of gross and net flows using ordinary least square regression (OLS) using the following specification: np/gs/gp j,t = α j,t + β 1 L. np/gs/gp j,t 1 + β 2 Pull j,t + β 3 Push j,t (3) np/gs/gp j,t are net purchase, gross sales and gross purchase of foreign equities by US investors for country j at month t, Pull j,t is foreign countries return and dividend yield for country j at month t, Push j,t is a set of US variables: US equity returns (usrt), US short-term interest rates (usin) and US credit spread (uscr). We include lagged flows, L. np/gs/gp j,t 1 as flows data shows serial autocorrelation. Table 4 reports the regression results of the determinants of gross sales, gross purchase and net purchase of ASEAN-4 equities by US investors. Flows are determined by past flows and highly significant at 5 percent. Foreign equity returns show no effect on gross flows. We expected a positive (negative) relationship between dividend yield and gross purchase (sales) as increase (decrease) in Organized By Page 513

9 prospective returns encourage US investors to buy (sell) foreign equities, however the relationships are mixed. Higher interest rate in the US should results in lower purchase and higher sales but both show positive relationships. We suspect that the regression results for gross flows are more likely to be meaningless as US investors are found to simultaneously buy and sell foreign equities as in Figure 1. Regression result for net purchase is more meaningful as increase in past (rt) and prospective (dy) returns, US investors purchase more foreign equities than sell. The positive relationship between net purchase and returns is in line with return chasing behaviour of US investors documented in the literature. The negative impact of US credit spread shows US investors become net buyers of foreign equities as the spread contracts, indicates the trading of foreign equities to some extent, are driven by changes in US investors wealth, contrary to Bohn and Tesar (1996) s finding on portfolio balancing of US investors. Other factors are not significant in determining US equity flows to ASEAN-4 countries. We run several regressions on lagged flows, lagged flows and pull factors and, lagged flows, pull and push factors to examine the impact of different factors on flows. The findings show large variation of flows (R 2 ) are determined by past flows (we do not show the results of the regression here). Table 3 Correlation of US investors net purchase of foreign equities with foreign equity returns (return chasing) US investors net purchase of foreign equity in Equity return in Indonesia Malaysia Philippines Thailand Indonesia *** (.059)* (.001) (.720) (.100)* Malaysia *** (.485) (.002) (.011)** (.902) Philippines.136**.208***.097*.142** (.019) (.000) (.094) (.015) Thailand ***.151***.153*** (.317) (.001) (.009) (.009) The table presents the correlation coefficient of US investors net purchase of foreign equity and foreign equity returns for Indonesia, Malaysia, Philippines and Thailand for the period of January 1992 to August 2016 (296 monthly observations). Significance level are given in parentheses. ***, **, and * represent significance at 1%, 5%, and 10% level, respectively. 5 Conclusion This paper examines the behavior of US investors sales and purchase of ASEAN-4 equities. Our findings confirmed the stylist fact of return chasing behviour of US equity investors in foreign markets. We also find the existence of global return chasing documented in Albuquerque et al. (2009). Our study however ignores the impact of Asian and global financial crisis. Further research perhaps include these factors and might be able to provide further evidence on US investors behavior in ASEAN emerging markets. Organized By Page 514

10 Table 4 OLS regression of the determinants of gross sales, gross purchase and net purchase of ASEAN-4 equities by US investors. Gross sales (gs) Gross Purchase (gp) Net Purchase (np) L.gs.469*** (.000) L.gp.534*** (.000) L.np.294*** (.000) rt *** (.718) (.286) (.006) dy.017***.021***.006* (.000) (.000) (.090) usin.068***.048*** (.000) (.008) (.341) usrt (.683) (.406) (.471) uscr ** (.572) (.243) (.031) N R This table presents results from OLS regressions of US investors gross sales, gross purchase and net purchase of foreign equities on push and pull factors. Gross sales (gs) is the sales of foreign equity by US investors to foreign residents and gross purchase (gp) is the purchase of foreign equity by US investors from foreign residents. Sales and purchases are normalized by dividing by the beginning of the month total market capitalization of the foreign equity, in US dollar. Net purchase is the difference between gross sales and gross purchase. Sales and purchase series are expressed in monthly percentage. Pull factors: equity returns (rt) and foreign dividend yield (dy) for Indonesia, Malaysia, Philippines and Thailand and US variables (push factors): equity returns (usrt), short term interest rate (usin) and credit spread (uscr). Foreign equity return is the beginning of the month Datastream total market equity return (rt) in US dollars and foreign dividend yield (dy) is Datastream total market dividend yield at the beginning of the month. US equity returns is Datastream total market return, US short-term interest rates (usin) is US 3-month rate and US credit spread (uscr) is the difference between US AAA and BBB corporate bond yields. ***, **, and * represent significance at 1%, 5%, and 10% level, respectively. Organized By Page 515

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