Price discovery in emerging market ETFs

ABSTRACT

This study investigates the price discovery role of exchange-traded funds (ETFs) by examining the predictive relation between the returns of emerging market ETFs traded in the US and the returns to the aggregate equity indices that they track. In a sample that covers 18 countries, we find that ETF returns can predict one-day-ahead returns of their underlying indices. This relation is robust after controlling for the non-synchronicity between markets, serial correlation in index returns, and various determinants of aggregate returns. Moreover, the predictive relation is more pronounced during periods of higher volatility and evidence for bidirectional spillover effects is weak. We also find that an out-of-sample rolling window strategy outperforms investing in the market index several-fold in the majority of the markets, especially in the high-volatility subsample.

KEYWORDS:

• Exchange traded funds
• equity markets
• price discovery
• information efficiency
• international finance

JEL CLASSIFICATION:

• G10
• G11
• G12
• G14

Disclosure statement

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

Notes

1 Another contentious area in ETF research is related to the impact of ETFs on the liquidity of their underlying securities. Although studies such as Agarwal et al. (2018) and Marshall et al. (2020) argue that ownership in ETFs enhances liquidity, Petajitso (2017), Dannhauser (2017), Piccoti (2018) and Evans et al. (2019) present evidence that ETF ownership increases transaction costs in the underlying securities due to crowding out effects. Moreover, Ben-David, Franzoni, and Moussawi (2018) find that ETFs increase the volatility of their underlying assets through non-fundamental demand.

2 For some countries, the NYSE lists multiple ETFs that track the country’s equity market’s performance. One example is Colombia for which both Global X MSCI Colombia ETF (GXG) and iShares MSCI Colombia ETF (ICOL) exist. In such cases, we choose the ETF with the largest asset size as of April 2019.

3 We also add the lagged return on the S&P 500 index to the full specification as an additional control variable. The results indicate that 11 slope coefficients retain their significantly positive coefficients. Moreover, we estimate these regressions by excluding Indexret from the set of independent variables. We find that 14 out 18 equity ETFs exhibit predictive power for future index returns.

4 We also estimate panel regressions using data from all markets rather than estimating a single time-series regression for each market. For the univariate specification, ETFret has a coefficient of 0.0658 with a t-statistic of 2.86. For the full specification, ETFret has a coefficient of 0.0926 with a t-statistic of 2.24.

5 We also calculate out-of-sample R² statistics following Campbell and Thompson (2008). Specifically, we use initial windows of varying lengths to estimate univariate or multivariate predictive regressions of one-day-ahead open-to-close index returns to produce the first out-of-sample forecast in each market. Next, we expand the estimation window by one day at a time and repeat this procedure to produce out-of-sample forecasts for the next period until the end of the sample. Out-of-sample R² statistics are calculated as one minus the ratio of the sum of squared deviations of actual excess market returns from forecasted excess market returns to the sum of squared deviations of actual excess market returns from their historical average benchmark. We find negative values for the R² statistics to be rare indicating that the predictive regressions do not underperform the historical averages in terms of mean squared forecasting errors.

6 South Korea presents an anomaly in the sense that Table 4 indicated a negative intertemporal relation between ETF returns and future index returns in this market. Although this finding is not consistent with the hypothesis of price discovery in ETFs, the rolling window strategy still generates considerable returns due to its long-short nature.

7 We also check the economic significance of our findings by comparing the Sharpe ratios of the rolling window strategy and the aggregate market index for each country. The rolling window strategy again has a superior performance in 14 markets with the exceptions of Argentina, Brazil, China and Poland.

Additional information

Funding

This work was supported by the BAGEP Award of the Science Academy and GEBİP Award of TÜBA.