It's absolutely true that keeping portfolio costs low is important.


However, there is more going on to explain why most actively managed funds can't be relied on to beat the relevant benchmark (and trackers thereof) in the long run.


It's about minimising the chance of introduction of errors.


1. An actively managed portfolio is by definition the practical implementation of a set of forecasts, which are fluid and changing over time.


2. No matter how smart the managers, there is always a small chance that some of those forecasts turn out wrong; we can't accurately predict the future.


3. The more forecasts involved in a portfolio, the more chance that some forecasts turn out wrong and errors are introduced.  Basic probability theory.


4. The longer the period of observation, the more chance that some forecasts turn out wrong and errors are introduced.  Basic probability theory.


5. Yes, actively managed portfolios typically have higher costs than passively managed, however this is unlikely to be the main reason for  the scale of active underperformance versus passive.  It's because:


6. Passively managed portfolios (index trackers) do not require forecasts, being rules-based.  Therefore zero scope for introduction of errors.  As long as you have selected the right index, passively tracking is generally more reliable.


7. Some outperforming actively managed funds are successful because they are internally rules-based to some degree (e.g. strictly-adhered-to criteria for asset inclusion, buy and sell).  This is analagous to creating their own index.  Rules reduce the chance of introduction of errors; they reduce the 'degrees of freedom'.  This helps explain why these funds are successful.


Try this Question:

Homer Simpson wants to drive to Moe's bar.  He has two routes that are identical in distance and traffic level.  Should he choose the route with 5 sets of traffic lights, or the route with only 2 sets of traffic lights?


If you chose the route with only 2 sets of lights, you already understand why reducing degrees of freedom gives best results in the long run.



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