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ETFs have the momentum. But are they predictive?

When EPFR announced last November that the assets managed by the Exchange Traded Funds (ETFs) it tracks had crossed the $6 trillion mark, it came as a limited surprise to most investors and financial professionals.

Flows into these vehicles, which generally track an index or other benchmark and aim to replicate its performance, have surged since the 2008-09 financial crisis and the subsequent compression of yields as policymakers struggled to contain the damage. Both institutional and retail investors have warmed to the combination of transparency, liquidity and low fees offered by ETFs (see Chart 1).

Chart 1 – Monthly ETF AuM (Mil USD)

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With the money rolling in, ETF providers are scrambling to expand their footprint by tapping into ‘hot’ themes and quantitative innovations. Smart beta, SRI/ESG and minimum volatility ETFs are just some of the ones rolling down the slipway.

Among the questions this raises for quantitative research is the degree to which this flow momentum and focus on cutting edge products translates into predictive signals.

Still climbing the foothills

Although the rise of ETFs is one of the dominant narratives when it comes to mutual fund investing, the raw numbers tell a more nuanced story. For instance, if you use January 1, 2008, as your starting point, the assets managed by all the actively managed mutual funds tracked by EPFR gave grown over 875% versus 213% for all ETFs. Overall, mutual funds still manage much more money than ETFs (see chart below). 

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Also, while ETFs have outperformed mutual funds in recent years, over a longer time horizon those tracked by EPFR still lag mutual funds before fees and expenses. On the equity side, over the past decade Equity ETFs have delivered a collective gain of 72.5% versus just shy of 94% for mutual funds.

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Who to believe?

It is certainly true that flows to Equity ETFs and mutual funds have moved in opposite directions since 2008.

Chart 4 – Monthly Equity ETF Flow (Mil USD) & Cumulative Flow

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Chart 5 – Monthly Equity Mutual Fund Flow (Mil USD) & Cumulative Flow

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If ETF and Mutual Fund flows moving in diametrically opposite directions -- at least over the last decade -- which is more predictive of future market returns?

A basic analysis of flows to ETFs and mutual funds over time, and their correlation with benchmark performance, shows that ETF flows are inversely correlated to market performance. Chart 6, which overlays ETF and mutual fund flows -- in % of AUM terms -- on the benchmark ETF’s performance, illustrates this.

Chart 6 – Monthly Equity ETF & Mutual Fund Flow (% of AuM) vs Benchmark

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Taking a more sophisticated approach, we looked at the results when EPFR’s Global 7 Regional Equity Strategy used ETF flows and when it used mutual fund flow. This strategy is a long only strategy that invests in seven major countries and regions globally (Asia ex-Japan, Europe ex-UK, Japan, Latin America, Pacific ex-Japan, the UK and the USA) and rebalances on a weekly basis.

The factor driving the Global 7 Regional Equity Strategy is calculated using the 4-week moving average for each region or country. Those seven scores are then averaged, and a standard deviation applied to that average to create a Z-score which in turn is converted to a P-score using standard conversions. The distance between the current P value and the distribution average for past scores determines the overweight or underweight assigned by the model to each country or region. Chart 7 below illustrates the progression of this methodology.

Chart 7 – Factor Methodology

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Our final chart shows the hypothetical investment return based on $100 invested at the beginning of 2002. Although the returns driven by ETF flows do outperform the equal weight benchmark, in this particular case they lag the return generated by mutual fund flow data.

Chart 8 – Hypothetical Cumulative Performance

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Proceed with caution

While the rapid growth of ETFs is real, some of the claims made about them should be treated with caution and, where possible, subjected to rigorous quantitative analysis. ETFs may become the dominant investment vehicle and driver of quantitative models. But they are not there yet.

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