We originally replicated DFA with generic capitalization-weighted indexes rather than ETFs because we could go back even further in time, i.e., pre-ETF. This assured a long history of returns to work with and served as a proof of concept. Next we explored the implementation via retail ETFs or institutional funds that offer less return history than the pure indexes themselves but that are directly investable. The return of a DFA fund can be described as the return of a basket of indexes plus an error term, and our characteristic-adjusted replica had a very low error term using data back to the year 2000 (Figure 2).
Our methodology of mapping DFA products to ETFs and creating a tracker structure was as follows:
- Obtain return streams for a sample of DFA funds.
- Select traditional capitalization-weighted indexes that intuitively would be a good starting point for replication. To manufacture DFA Small Cap Value, for example, start with Vanguard Small Cap Value and expect to add Russell Micro Cap or other funds to increase the SmB factor.
- Run a multiple-factor regression to calculate coefficients for DFA using the Carhart-Fama-French four-factor return streams (more on this later).
- Equate the clone’s exposure to the targeted DFA fund by controlling the exposure to the risk factors that drive portfolio return. In other words, compose a blended mix of traditional indexes by matching the Fama-French factors.2
Start by going to the website and downloading the (monthly) world-famous Fama-French factors. Next, subtract the monthly risk-free rate from the targeted DFA fund’s monthly returns (Figure 3).