Investors have had an aversion to using models, but that may be changing rapidly. More money is being managed by systematic managers or focused on some form of smart beta or a set of rules to investing. Nevertheless, there has been documented fear from letting go and having a model make decisions.

We have written about the problem of algorithm aversion a few years ago, see our post “Algorithm aversion and managed futures”, but we just saw a nice discussion on this issue from Ewan Kirk, the CIO of the systematic manager Cantab, see LSE Alternatives Investment Conference – Algorithm Aversion. The problem of rules avoidance is still perplexing. Why do investors prefer discretion over a rules-based approach even though the rules-based approach may perform better?

I like rules. Rules and models are good and their value is well-documented, yet many do not want to follow them. Thinking about this issue, the aversion to rules may be related to the price of optionality associated with switching the decision process or dropping an algorithm. Individuals may not have an aversion to a model but aversion to binding behavior or a lack of flexibility.

Rules or using models are binding on choice. There is less choice or optionality with a decision when a specific set of rules is employed. If given a choice between a model and discretion which allows for flexibility, an individual may prefer the path that allows more flexibility or discretion. This is especially the case if the flexibility is available for free. The issue or question should be the cost of the option for flexibility. Since you may not pay directly for the option of flexibility, the reason you would give up flexibility is if the choice of flexibility is more expensive versus constrained behavior.

The reason for choosing an option that binds behavior is that the inflexible algorithm is superior in performance relative to the discretionary flexible choice. The relative difference in performance will determine the price for maintaining flexibility. If flexibility is painful or costly, an investor will more likely bind to a rules-based approach. Now, the research suggests that individuals place more negative weight on model uncertainty even if an algorithm does better overall than discretion. This suggests that the pricing of choice (binding versus flexibility) is not easy to measure. More research should be conducted in this area.

In some sense, the switch to passive index or rules-based investing versus a discretionary active approach is driven by the fact that rules do better and the evidence of this quality is increasing. The cost of the option for flexibility is high (under-performance). If systematic managers under-perform, investors may opt for discretion over switching to another algorithm. The cost of having flexibility (discretion) is low when rules do underperform. When the cost of having flexibility (discretion) is high low performance, the switch will be to algorithms. The cost and uncertainty of flexibility will drive the aversion. Unfortunately, the analysis shows this process to be fairly complex.