By: Rayhaan Joosub, Co-founder and Portfolio Manager, Sentio Capital and Yashin Gopi Head of Quantitative Analysis, Sentio Capital
Smart Beta or factor investing is a popular approach that systematically captures factor premiums, which are believed to be a reward for some form of systematic risk or behavioural biases of investors. However, one of the major issues with factor investing over time has been that these strategies have worked well in-sample but below expectation out-of-sample. Most factor premiums can certainly be positive in the long term; however, in the short term, the performance of these factors can be quite cyclical.
There are several reasons that can lead to underperformance, such as:
- The economic exposure of a factor being out of sync with the current economic cycle
- The valuation of a factor itself being expensive
- Market sentiment shifting away from a factor
- Structural constraints impeding the ability of investors to capitalise on a factor premium.
The table depicts the annual performance of six popular investment factors. Blue highlights the good performance (ranked in the top 2) and red highlights the poor performance (ranked in the bottom 2) among the styles.
One can see that many investment factors can experience consecutive periods of poor performance, such as Value from 2011 to 2015 or Small Caps from 2009 to 2013. Managers who tether their investment philosophy to any of these factors may face pressure from clients to adapt their approach to match the currently favoured factor. Since 2016, there has been consistent cycling in the performance of these factors, with no one factor dominating for a sustained period.
At Sentio, we believe that using alternative data sources, enhancing existing factors, and applying more computationally demanding machine learning techniques can lead to superior returns from a smart beta strategy. Machine learning techniques can also help to quantify the risk of a shift in the economic or market cycle and identify which investment factor should outperform in that phase. We call this ‘Hybrid Intelligence’. The future of investing is still human, only smarter and faster!
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