It is hard to successfully time any investment. Whether it’s deciding to pull money out of the stock market, overweight foreign stocks or a particular sector, or trim duration risk, adjusting a portfolio based on expectations about the future can easily backfire because the future is hard to predict. Yet, there is an emerging body of research that suggests it is possible to successfully time exposure to factors like value, momentum, size, quality, and low volatility. While each of these factors has a good long-term record, they all go through cycles of underperformance. If timing really works, it could help mitigate this cyclicality, which is one of the biggest drawbacks to factor investing.
A healthy dose of skepticism is in order. Much of the research done thus far has come from practitioners, rather than academia, who work for asset managers with a vested interest in bringing new products to market. As with most financial research, data mining is also a risk because there are many variables researchers could have tested to find a predictive relationship that worked in sample but may not work out of sample. Even if there is a return benefit from factor-timing, implementing it reduces diversification relative to a static multifactor portfolio, which may outweigh the benefit. And it’s important to bear in mind that even if a timing signal works on average, it won’t always get the calls right. There is no pain-free way to beat the market. That said, factor-timing warrants serious review.
Factor-Timing Signals
