If you asked a traditional active fund manager whether they could effectively replicate their investment approach in a systematic fashion they would almost certainly say no. They would likely cite the advantages of human judgement and the nuances of their process that cannot be captured in a purely quantitative system. And, of course, they have to say this. To suggest otherwise is to infer that the activity they are richly rewarded for can be efficiently and cheaply emulated. Yet incentives and self-interest aside, developing a systematic replica of their fund or portfolio is exactly what every active fund manager should be doing. There is no better way of isolating the noise that impacts their own judgements or better understanding the often-ambiguous advantages that come from qualitative input.
It should not be difficult for a fund manager to create a version of their fund that is run on a systematic basis. All that is required is an algorithm built on a defined set of decision rules. It can be more sophisticated than this – you might use some form of machine learning – but this is not essential. The only question the fund manager needs to answer is: if you had to run your fund in a purely quantitative fashion, how would you do it?
In its most basic form all that is required is a set of portfolio construction rules (number of positions, position sizes, concentration) and criteria about when to buy or sell securities. This can be as simple or complex as is desired, provided it can be managed and maintained by a computer with minimal human involvement.
There are three key reasons why such an approach should be valuable to active fund managers:
Idea Generation: Although not its primary purpose, it can function as a buy and sell idea generation tool that is more sophisticated than a screen or filter. If you continue to hold a stock that the systematic version of our strategy has sold, you should be able to justify why.
Noise Cancelling: The most impactful feature of the approach is the ability to observe investment decisions being made absent much of the noise that influences human judgement. There are a multitude of factors that lead us to make inconsistent and erratic choices. Running a systematic version of a fund removes this issue by focusing solely on the rules prescribed. How much of the potential loss in rigour and detail is compensated for by the removal of noise?
Identifying Value-Add: Active fund managers often struggle to convey what their true value-add or edge is. Too often it is overly generic (‘growth at reasonable price’) or suitably vague (some kind of ‘secret sauce’ or ‘art’). This is a problem. If fund managers are attempting to sell a skill at a high price, it would be helpful to know what it is. Running a systematic version of a fund can be incredibly beneficial in this regard.
By comparing the behaviour of the standard (qualitative) fund to the systematic replica it is possible to contrast the divergences in decision making. Through time a history of disparity can be built. By understanding when and why these occur a fund manager can identify exactly what the specific tasks or behaviours are that add value relative to a systematic approach.
Not only is creating a systematic replica useful in conveying to potential investors what the skill of the manager or team might be, it should also greatly assist the manager in refining their process. It should allow them to focus on circumstances and situations where they are most likely to prosper, and abandon those where they consistently fare worse than an algorithm.
There is a glaring problem with this whole idea. What if it tells a fund manager what they don’t want to hear? What if a simple systematic approach consistently makes better decisions? But this shouldn’t really be the case because most fund managers must believe that what they are doing is superior, otherwise it would be a fairly unfulfilling (if lucrative) endeavour. Fund managers should also always be willing to better understand their own decision making and seek to improve it.
Before worrying about beating a benchmark, active fund managers should first try and beat a systematic version of themselves.
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