How Studying Mutual Funds And ETFs Can Improve Investment Strategies

How can studying flows in mutual funds and ETFs improve my investment strategy? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.

Answer by Jiacui Li, Assistant Professor of Finance at University of Utah, David Eccles School of Business, on Quora:

This is an important question because mutual funds and ETFs currently hold around 40% of all U.S. stocks.

Before I provide a few approaches, let’s set up the context. When people invest money into these funds (inflows), the funds need to use this money to buy more stocks. Conversely, when people withdraw their money (outflows), the funds have to sell stocks to give the money back. This pattern of buying and selling is largely predictable; you can expect funds to buy more when they get more money from investors and sell more when investors are taking their money out. When a lot of funds are either buying or selling in the same way at the same time because they are experiencing similar inflows or outflows, it can push stock prices up or down significantly. However, these price changes tend to go back to where they were over time. This means that the price increase due to many funds buying will eventually decrease, and the price decrease due to many funds selling will eventually rise again.

Now, how can quantitative investors take advantage of these flows to improve investment performance? There are three approaches.

1) Trade on long-term reversion.

After large flows have happened, trade against those flows and bet on price reversion. This applies to slow-moving strategies as reversions can take years.

As an example, this study finds that fund flows often fluctuate wildly between different size and value/growth styles, creating large style-level price pressures that revert subsequently. I would recommend taking into account such flow-based signals in your asset allocation strategies. For instance, during the 2000s dotcom bubble, investors poured hundreds of billions into large-cap growth funds, and this made large-cap growth stocks more overvalued. On average, such overvaluation leads to substantially lower returns in the subsequent 1-2 years.

2) Front-run near-term flows. You can also predict fund flows and front-run them. This applies to shorter-horizon strategies, ranging from one week to one quarter.

This is slightly more complicated as it requires a deeper understanding of what drives fund flows. As an example, we find that fund flows are heavily determined by Morningstar ratings: funds with high (low) ratings receive large inflows (outflows). Further, Morningstar ratings are computed using mechanical formulas and are somewhat predictable. In follow-up research, we find that a Morningstar methodology change in rating calculation caused large, predictable style-level price fluctuations in June 2002 and also made momentum-type strategies less profitable afterward. Because the methodology change was announced ahead of time, if you understood fund flows and Morningstar ratings, you would have been able to take advantage of it back then.

3) Improve diversification.

If you conduct mean-variance portfolio optimization, you can use fund flows to better estimate return covariance and improve diversification.

Traditionally, quant funds use either factor-based approaches (e.g. BARRA) or Ledoit-Wolf type shrinkage to construct their covariance matrices. For reasons I cannot fathom, most of them do not use information beyond historical returns to estimate covariance matrices. However, fund flows can improve covariance matrix estimates, such as shown in this paper. The idea is very simple: if two stocks tend to be co-held by an overlapping set of funds, they tend to be traded together, and this leads to higher covariance between them.

In ongoing work, I find that incorporating flow- and trading-related data can improve covariance matrices estimation and lead to better diversification and higher Sharpe ratios. This work is still at an early stage and not ready for public consumption. If you are interested, and if you work in quantitative finance as a professional (this is not a topic for retail investors), feel free to email me.

This question originally appeared on Quora – the place to gain and share knowledge, empowering people to learn from others and better understand the world.

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