![]() Thus, with four quartiles-a highest-expected-return (Quartile 4) and a lowest-expected-return (Quartile 1) quartile in both regions-we have 28 total region-factors. At this point, each of the quartiles is composed of 7 factor portfolios. In June 1996, the factor pool widens with the introduction of Europe, increasing the total number of factors to 28 from 14 each factor is constructed in the two regions. We introduce the other five regions into the portfolio construction process as data availability allows. We rank each portfolio by its expected return, and place the highest four in Quartile 4 and the lowest four in Quartile 1, repeating the exercise for the next month, and so on. Because the United States has the longest history, the first month of our analysis period (June 1969) includes only US data. This process yields 14 separate factor portfolios. We construct a small and a large portfolio for each factor, with the exception of market and size. 2 Appendix A provides the factor definitions and their returns over the four economic stages. We examine the same eight primary factors as Aked (2020) (market, value, investment, size, illiquidity, profitability, low beta, and momentum) across the same six regions of Australia, United States, Europe, United Kingdom, Japan, and the emerging markets. Therefore, whereas keeping track of the economy is an important part of the overall investment process, the most important element in factor investing strategies is maintaining a close link to a factor’s discount and momentum. We find that the first strategy, using a factor’s historical performance as a guide to the future, is nearly worthless. Although a factor’s return changes throughout the business cycle, the ability to predict economic regimes and alter factor allocations accordingly produces less successful results despite being intuitively pleasing. We find that the third strategy, employing a factor’s discount and momentum, is the most effective tool for determining how to vary a factor’s exposure through time. In each case, the strategy is constructed out of sample, using data only available at the time of the specific sample period. ![]() I evaluate three factor-timing strategies using 1) a factor’s historical return, 2) the economic stage, and 3) a factor’s discount and momentum. ![]() 1 Here, I extend the research of Aked (2020) to help investors better understand how they can vary their factor exposures through factor timing to potentially gain more profitable and more dependable investment results.įactor timing is the ability to add value to an investment strategy by altering the exposure to various factors through time. Therefore, the ability to add additional sources of return by adding exposure to more than one factor should be of great interest to investors who seek more consistency in shorter-term results. Readers of “ Factor Returns’ Relationship with the Economy? It’s Complicated” (Aked, 2020) learned that some degree of variability in a factor’s return across the business cycle exists.
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