Now that the Federal Reserve has begun the process of raising interest rates, and has announced their intention to begin to unwind their policy of quantitative easing (reducing the amount of bonds in their portfolio, either by selling holdings or allowing holdings to mature), investors may be concerned about the impact of rising interest rates on factor premiums.
Wei Dai, senior researcher at Dimensional Fund Advisors, studied the relationship between interest rates and the dimension of expected stock returns in a July 2017 paper. Dai examined the relationship of the realized size, value and profitability premiums over the period from July 1963 through December 2016.
Dai found that while the realized size, value and profitability premiums have been positive on average, there has been substantial dispersion of their realized returns over time. However, there has been no discernable pattern in the historical data suggesting that the size, value and profitability premiums behaved differently in months when the effective federal funds rate went up versus when it went down. And Dai found that the lack of clear patterns held when the federal funds rate was replaced with one-, five- and 10-year Treasuries.You can see the lack of patterns in the exhibit below.
One can see the lack of patterns in the exhibit below:
Dai also found that the R² values (a measure of explanatory power), regardless of which bond yield was used, were close to zero. Thus, bond yields have explained almost none of the variation in the size, value, and profitability premiums.
There is no compelling evidence supporting a robust relation between interest rate changes and the size, value, and profitability premiums.
The conclusion you should draw is that even if you had perfect foresight of interest rate changes (and no such person exists), it would not provide you with information as to future factor premiums. The one exception is that some research, such as the 2016 study by Joost Driessen, Ivo Kuiper and Robbert Beilo, “Does Interest Rate Exposure Explain the Low Volatility Anomaly?”, has found that low-volatility strategies have exposure to term risk (the duration factor). This should not be a surprise because, generally speaking, low-volatility (or low-beta) stocks are more “bond like.” They are typically large stocks, the stocks of profitable and dividend-paying firms, and the stocks of firms with mediocre growth opportunities. In other words, they are stocks with the characteristics of safety as opposed to risk and opportunity. Thus, they show higher correlations with long-term bond returns.
In summary, Dai’s findings on trying to time factor premiums based on interest rates is consistent with other research into whether investors can accurately time premiums using variables besides interest rates, such as valuation ratios and mean reversion. Dai noted that various metrics have been tested and so far the evidence suggests that “rather than making investment changes based on these predictions or views and risking the potentially huge opportunity costs of mistiming the premiums, a more reliable way to pursue higher expected returns is to remain focused on the premiums.”
Further Evidence on Timing Factors
Clifford Asness, Swati Chandra, Antti Ilmanen and Ronen Israel contribute to the literature on timing factor investing with their study “Contrarian Factor Timing is Deceptively Difficult,” which appears in the 2017 special issue of The Journal of Portfolio Management. Among their findings was that, when comparing the impact of value timing (in other words, can dynamic allocations improve the performance of a diversified multi-style portfolio?), they uncovered “lackluster results—strategic diversification turns out to be a tough benchmark to beat.”
Asness, Chandra, Ilmanen and Israel noted that value timing of factors, because it is buying what is relatively cheap, is correlated to the standard value factor as it adds further value exposure to a portfolio. They explain:
If a multi-style portfolio already includes value at optimally diversified levels, value timing the styles may increase value exposure to levels that undermine diversification, leading to weaker performance, particularly in a risk-adjusted sense. For many investors, the original intention of a multi-style allocation is to balance risk across multiple sources of return and capitalize on the power of diversification. Value timing a multi-style allocation may work against that very purpose by effectively increasing the allocation to value.
Portfolio math tells us that returns add linearly while risk adds quadratically. Hence, at larger tilts, the increase in risk from timing may be proportionately larger than any increase in return, resulting in lower risk-adjusted returns.
The authors also examined whether timing would add value if it were done only at extreme levels—when spreads passed a certain threshold. They write:
The timed strategy Sharpe ratio improves as we increase the threshold, but it is a very modest improvement. The timed strategy Sharpe ratio barely exceeds the Sharpe ratio of the non-timed. In fact, increasing the threshold further leads to a slight drop in the Sharpe ratio.
Dai herself also looked at the issue of timing premiums in her March 2016 paper, “Premium Timing with Valuation Ratios.” She studied the performance of the market, size and value premiums over the period from July 1926 through June 2015, as well as the performance