Multifactor is now the de facto standard in systematic investing.
But there are roughly as many ways to be multifactor as stars in the night sky.
Which factors should you pursue? How should you best combine them? And how do you assess whether your multifactor solution is performing as advertised?
Multifactor investing has its roots in the Fama-French three-factor model, published in 1993 by Nobel laureate Eugene Fama and his collaborator Ken French. According to their model, not only are stocks expected to outperform bonds, but small and value stocks have higher expected returns than large and growth.
The model’s 30-year anniversary in 2023 will likely pass without fanfare, but its significance for understanding what drives investment performance cannot be overstated.
There were, of course, value investors and people with an affinity for smaller companies before 1993. But the Fama-French model provided a framework for why certain stocks and fund managers tended to outperform others.
And at a time when most investors faced the binary choice between stock picking and index tracking, the research implied a third option that systematically targets premiums.
Systematic strategies tend to offer lower cost and broader diversification than stock picking. They also need not be constrained by the goal of minimising tracking error or the inflexibility of infrequent rebalancing that characterise index funds.
The oldest funds that take inspiration from Fama and French’s research are close to a 30-year track record, testament to the appeal of the approach.
Since 1993, we have seen an explosion in the number of papers by academics and practitioners that claim to have found new or improved factors that add to Fama and French’s original three.
But when revisiting their research in 2015, Fama and French chose to add just profitability and asset growth to their model.
The framework they apply for choosing factors can help investors decide which ones are worth pursuing in the real world.
The starting point should be a rigorous theoretical foundation. Without that, you cannot credibly expect the historical performance you initially find in your data to continue 'out of sample' (using different data).
Fama and French base their choice of factors on asset pricing theory – the idea that stock prices equal expected discounted cash flows to shareholders. In other words, the price of a stock today is the present value of its future cash flows.
This means if you imagine two stocks with the same expected future cash flows and one has a lower price, investors must be applying a higher discount rate to the cheaper stock and therefore expect a higher return.
As such, we should expect smaller and deeper-value stocks (those with the higher discount rates as described above) to outperform, all else being equal.
The same theory implies that when comparing two stocks with the same relative price; the one with the higher expected cash flows for that same price has a higher expected return.