Abstract

In the financial services sector, emerging technologies are becoming a decisive frame of reference. Automation of the industry process has become a key priority for many companies who want to stand out by minimizing costs. In light of this trend, we choose to explore two current topical topics relevant in the robo-advisor investment atmosphere: The Black Litterman model in the portfolio management and investment strategies based on machine learning, and reinforcement learning in particular. The purpose of this article is to compare three investment strategies which Ally’s robo-advisor adopted. The first strategy is the classical model, in this case the Black–Litterman framework developed by Fischer Black and Robert Litterman in 1990 – used at Goldman Sachs.

Second strategy would aim be to automate portfolio management step further by the machine and letting the machine decide the task of portfolio weight allocation through machine reinforcement learning, namely that of Ensemble of Identical Independent Evaluators (EIIE). The third is an equal weight portfolio, in other words we’re not doing any work at all in this situation, we will just let uncertainty dictate our choice of weight.

The key difference between the models is in the decrease of administrative cost. Active management in these three models is constrained. While the exchange-traded fund (ETF) allocation is broad based, and across five funds, the portfolio is less amenable to performance distinction through weight allocation as we have only a few funds. Hence, the use of classical methodologies, e.g. Black–Litterman framework, in portfolio management seems to be of little importance, since its implementation effort and cost would have been sufficient. In addition, monitoring the full set of ETFs (from all constituents) cannot be easily achieved, limiting the analysis to the top ten holdings of each ETF in order to achieve the estimation of portfolio weights may induce the selection bias. While being simple, however, the buy-and-hold scheme as a strategy meets the expectations as it is keeping up with the other two strategies in the market place.

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