Foreign Fund Flows and Equity Prices During COVID-19: Evidence from India

ABSTRACT

We study the period of the COVID-19 outbreak to assess the impact of foreign institutional investor (FII) flows on asset prices in an emerging market. In a dataset of stock-level foreign fund flows on Indian equities, we show that stocks experiencing abnormally high innovations in foreign fund flows face a permanent price increase (an “information” effect), whereas stocks experiencing abnormally low (negative) innovations in foreign fund flows suffer a partly transient price decline. During the COVID-19 outbreak, the immediate price effects were exaggerated and followed by higher transient volatility. Our methodology shows the efficacy of stabilization policies, initiated notably by the Federal Reserve, in dampening the relation of foreign fund flows and equity prices in the immediate aftermath of the COVID-19 outbreak.

KEYWORDS:

• Foreign Institutional Investors (FII)
• foreign ownership
• portfolio flows
• price impact
• VIX
• volatility

JEL:

• F21
• G11
• G14
• G15

Acknowledgement

The authors thank the National Stock Exchange for providing data on foreign fund flows on Indian equities to study the COVID-19 impact in Jan-June 2020 relative to the period immediately prior.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. See Bohn and Tesar (1996), Brennan and Cao (1997), Froot, O’Connell, and Seasholes (2001), and Hau (2001) for initial studies on this topic.

2. Mutual fund flows within a country can also affect asset prices; however, such domestic fund flow effects are not the focus of our study. Coval and Stafford (2007) show that sudden increases (decreases) in quarterly fund flows cause mutual fund managers in the United States to significantly adjust their holdings, resulting in price pressure effects, which are transient but may take weeks to reverse. Price pressure due to fund flows can cause temporary deviations of stock prices from fundamental values, followed by reversals over time. Frazzini and Lamont (2008) find that mutual fund flows reflect retail investor sentiment and high inflows are associated with lower future returns.

3. Cross-border capital flows can also cause significant real effects. For instance, during the early 1990s, several East Asian countries experienced significant amounts of capital flows into their markets, but subsequently faced a sudden reversal of capital flows in 1997. The currency and stock markets of Indonesia, Thailand, Malaysia, Philippines, and South Korea suffered a major decline due to the flight of capital to safety. Although capital flows reverted to their original levels by 1999, during the interim period (1997–1999), the crisis spread from East Asia to Latin America, leaving many developing countries in a state of recession.

4. We focused on foreign equity flows rather than foreign bond flows data because the bond market in India is highly illiquid and data is sparse. Only the government bond market has sufficient depth that makes it amenable to analysis. However, flight to safety often drives flows in these treasury securities and the overall bond market is less sensitive to fundamental information. On the other hand, equity markets are more liquid and capture the information effect better. The study of bond market flows may be considered for a future study that explicitly accounts for the price effects due to flight-to-safety.

5. Hasbrouck (1988) and Bessembinder and Seguin (1993) point out that the information content of trades can be weeded out by examining the unexpected component of trading rather than the total amount of trading.

6. The price effects associated with the high and low innovation portfolios in our study mirrors the findings in the empirical studies of block transactions in stock markets (e.g., Chan and Lakonishok 1993; Holthausen, Leftwich, and Mayers 1987; Keim and Madhavan 1996; Saar 2001). The prevalent rationalization is that block purchases are motivated by information whereas block sales are motivated by portfolio rebalancing concerns. Our findings are consistent with a similar rationale for FII trading in emerging market stocks.

7. Our study’s findings are closely related to the literature on the determinants of cross-border capital flows in the field of international finance. Researchers have classified cross-border flows into three categories: (i) portfolio flows, (ii) foreign direct investment, and (iii) banking flows. A widely used framework to identify the drivers of cross-border flows is the push/pull framework suggested in Calvo, Leiderman, and Reinhart (1993) and Fernandez-Arias (1996). This framework highlights the relative importance of the local economy’s “pull” factors in comparison to external “push” factors in explaining capital flows (and thereby, asset price formation in the local economy). For a comprehensive review of the literature in this field, see Koepke (2015).

8. An exception was the paycheck protection program lending facility, which showed significant outlays; however, this lending, which was collateralized by loans with federal guarantees was devoid of credit risk.

9. Some studies have used an alternative definition in which net FII trading is normalized by the sum of FII purchases and sales. However, since FII trading can vary significantly with size, normalization by overall trading volume, as used in our measure, better captures the economic significance of FII trading in that stock.

10. In short-run event studies, like the one conducted in our study, a 2-3-day window makes sense. However, in emerging economies, it may be advisable to use a larger 10-day window because the markets are less liquid, and transient effects may contaminate returns over a window of 2–3 days, thus rendering the inference to be questionable. Furthermore, as Dimson (1979) points out, the flow of information could be delayed for smaller less well-known firms that have lower analyst following. Several stocks in our sample are small stocks, and the use of a 10-day window ensures that all permanent and transient price effects are fully captured.

11. We employed an objective Hausman test to find out whether a fixed-effects model or a random-effects model suits the data in our sample. We find that the use of a fixed-effects model is justified. For robustness, we also explored alternative specifications with and without firm fixed effects and time fixed effects. These variations turned out to be qualitatively similar. In additional tests, we conducted a sectoral analysis with three sectors (Banking and Financial Services, Manufacturing, and “Others”). Our findings for the sectoral sub-samples are virtually the same as for the overall sample.

12. Given the time zone difference, it is likely that FIIs take clear views on their portfolio holdings at the close of trading in the U.S. and transmit their orders for execution in Indian stock exchanges in the immediately following trading session. Therefore, we are more inclined toward the hypothesis that abnormal flows drive asset prices.