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Fund flows has generally been used to run cross-sectional analysis between different asset classes/ countries or sectors. For example, comparing flows between emerging markets and developed market equities shows the shift in consensus between investors towards one of the asset classes. Or comparing flows between different sectors likewise could uncover an increased appetite towards a sector. A diversified investor can use this information to increase allocation on selected stock/sector or country to generate additional returns.

When, how and to what extent fund flows effect prices directly? How can we exploit time-series information in fund flows on top of cross-sectional information? And how does fund flow information interact with other market variables?

Finding a pattern from a time-series is a hard task. Prices tend to follow patterns that are close to random walks and can be very difficult to predict. A very simple regression between US Equity fund flows at (t-2) as a percentage of the total AuM invested and S&P500 returns yields the following chart.

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This chart simply tells us that there is no significant predictive relationship between single-day fund flows to US Equities and S&P Index in the long-term. To make things simpler let’s look at different quintiles of flows through time and returns of SP500 in the following chart. This charts actually links relatively lower flows(%)with higher returns at t+2. A sign of reversal between flows and returns.

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US Equity Flows - Quintiles through time vs Returns

What happens if we condition flow information on market volume through time? For example, if we look at volume of S&P500 index through time, we can find a clear relationship between volume and SP500 returns in the following chart. When the Volume of SP500 increases, there is an increased probability of a negative return. 

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SP500 Volume Quintiles through time vs Returns

If we focus on Quantile 1 of the above chart– the days with relatively low Volumes, then we can see the power of using fund flows as a time series.

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Effect of Fund Flows on S&P500 Returns on Low-Volume Days

On days with relatively low-volumes – higher fund flows start generating price pressures on S&P500 index. This somehow a surprising result. We would expect fund managers to be price sensitive and avoid stocks that have gone overvalued – due to non-fundamental reasons like price pressures/ low liquidity or low market volume.

To investigate further – we use granularity in EPFR data and run the same analysis this time separating active and passive manager fund flows.

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Effect of Active Fund Flows on S&P500 Returns on Low-Volume Days

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Effect of Passive Fund Flows on S&P500 Returns on Low-Volume Days

This overall effect on low volume days tend to be related to passive investors. So in practice, if we are experiencing a relatively low volume day than one should look at passive fund flows – because they can generate price pressures that can lead to alpha opportunities.

In theory, we don’t expect non-fundamental variables to predict such price pressures. But in practice, Fund flows can explain meaningful price movements – even in the time series dimension.

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