A recent article in Advisor Perspectives offers a number of insights regarding factor investing:
- Data mining, it argues, represents a “huge risk” in factor-based investing. “Many factors have proven to not work in practice and even the most popular factors, like value and momentum, may prove less effective going forward.”
- With investing, the article argues, “true relationships can be hard to see because of randomness and noise in data, and there’s a risk we convince ourselves that certain relationships exist that really do not.” The article provides a detailed example involving value and momentum strategies.
- Past performance does not guarantee future results, it asserts, “especially when back-tested.”
- “Just as markets adapt and evolve, so do business and the economy,” the article states, driving the point that changes in the economy can reduce the effectiveness of some factors. It cites the example of the U.S. economy which, it says, has shifted from a manufacturing-based to being “dependent on intangible knowledge capital in services and technology businesses. This means an increasing amount of the average company’s value is no longer reflected on their financial statements.”
The article concludes: “In this era of big data and cheap computing power, it is easy for anyone to create a winning investment strategy in a back test. But investing is forward-looking, and markets are adept at pricing in known information.”