It wasn’t too long ago that the concept of factors in investing was the exclusive province of professors of finance and a few active “quant” managers. Mainstream portfolio construction was focused primarily on asset allocation. Within equities, that meant achieving the right balance in allocation to various segments such as large cap and small cap, country and sector, and perhaps value and growth styles.
Today, factor allocation has entered the mainstream as a complementary approach to portfolio construction, alongside traditional asset allocation. An important driver of this development has been the creation of a new array of indexes that sharply focus on one factor at a time. This has opened up new possibilities for asset owners and advisors, including investing in index-replicating financial products, both to seek a desired factor exposure at low cost and to benchmark active managers to assess their value added.
One thing that followers of single factor indexes quickly realize is that the payoff for exposure to any one factor is highly variable. Factors typically follow different return patterns: value usually exhibits pro-cyclical performance, while quality is often countercyclical, for example. Market participants who do not employ a factor-timing or factor-rotation strategy are increasingly looking at strategic combinations of factors to gain potential improvements in risk-adjusted outcomes as compared to single-factor outcomes.
A lively debate has emerged regarding what is the best way to combine several factors into a single index. Roughly speaking, there are two camps in the debate: those who advocate a top-down “mixed” composite of individual factors and those who advocate a bottom-up “integrated” approach which results in an index of stocks that have simultaneous factor exposures. Each side argues that their approach produces strong factor exposures with high diversification.
FTSE Russell stands squarely in the bottom-up “integrated” camp. In this paper we will illustrate the FTSE Russell sequential tilting or “tilt-tilt” methodology, which is very much a bottom-up approach. After a brief overview of alternative methodologies, we will walk through a simple three-stock example of how we build a single factor and multi-factor index. We will contrast it with the most common and straightforward of composite “mixed” methods using the same factors. Then we will illustrate the alternative approaches with a large universe of stocks. We will augment the empirical illustration with some recent theoretical results on the trade-off with diversification which are independent of any particular data set. Finally, we will show how our multi-factor methodology can be extended to encompass environmental, social and governance (ESG) considerations.
