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DFA’s investment strategy is based on their belief in the principle that stock market is efficient. They attempt to match a broad-based, value-weighted small-stock index and position themselves in the market as a passive fund manager that still claimed to add value by capturing specific dimensions of risks identified by financial science. DFA’s investment strategy incorporates elements of both passive and active management. It is passive in the sense that like many other index managers, it focuses on the importance of diversification, lower turnover and lower fees than actively managed portfolios.
It is active in the sense that it develops its small-value stock focus based on academic research and uses certain techniques (such as its unique trading method in obtaining discounts and lower transaction cost) to contribute to a fund’s profits eve when the investment is inherently passive.
DFA’s clients are mainly major institutions (including corporate, government, union pension funds, college endowments and charities) and high-net-worth individuals.
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The main concern of their existing clients is potential high costs due to illiquid nature of many DFA holdings. DFA’s new product is a family of funds managed to reduce tax payments and the new clients it tries to serve are investors who are eventual taxpayers on any taxable flower received by a DFA fund they hold. To serve this new client base, DFA needs to continue its strength in keeping trading costs low and focus on reducing the taxes paid by clients. Some new issues that DFA will face include the complication of tax-optimization (such as handling the trade-off between putting more weight on non dividend-paying stocks and assuming more portfolio tracking error and volatility) as well as the possibility that tax management may lead to higher transactions costs.
Based on information given in the case, DFA accepts semi-form efficiency which indicates that stock prices fully reflect all past prices and all publicly available information.
DFA’s trading strategies reflects that it felt that on average the market price correctly incorporated all public information, so it is only concerned about whether there is negative private information known to the seller of the block of stocks but not to the market.
DFA’s trading strategy such as avoiding stocks if news announcements are coming in the near future or if stock has recently reported sales by insiders reflect a belief that stock prices can potentially not reflect all private information. DFA also does not accept the weak-form efficient because if stock prices only reflect all information in past prices, they would see the value of performance fundamental analysis of the firm they are looking at (but the case indicates that DFA does not performance fundamental analysis).
Fama and French’s three factor model attempts to explain the variation of stock prices through a multifactor model that includes a size factor and BE/ME factor in addition to the beta risk factor. Fama-French model essentially extended the CAPM (which breaks up cause of variation of stock price into systematic risk which is non-diversifiable and idiosyncratic risk which is diversifiable) by introducing these two additional factors. Fama and French find that stocks with high beta didn’t have consistently higher returns than stocks with low beta and this indicates that beta was not a useful measure under their model. Their model is based on research findings that sensitivity of movements of the size and BE/ME factor constituted risk, and therefore risks associated with small companies and risks associated with high BE/ME companies in addition to beta risk explain a great deal of the variation of stock prices.
The two factors in Fama-French model(company size and company BE/ME)are both firm specific risk and not market related risk, and it would appear that DFA (which base a lot of their strategies on this type of academic research) is not utilizing macroeconomic variables. However, as Fama and French argued, these factors explained so much of the common variation in stocks that they essentially capture sensitivity to risk factors related to macroeconomic variables. Therefore, not directly using macroeconomic variables (which is inherently hard to find or predict), but using the size and BE/ME factor may be a better way to represent certain types of market risk. In addition, because DFA is positioned as a passive manager that adds value, its goal then would not be to beat the market, but to follow it with the belief that in the long run indices will perform better than active strategies (which may focus on designing products that addresses macroeconomic variables such as market timing, etc).
The efficient market enthusiasts believe that small stocks will outperform large ones, and stocks with high BE/ME will generate higher returns than stocks with low BE/ME. On the other hand, behaviorists believe that the size and value premia is not always true, and there are several variable factors need to be considered.
For example, in the early 1980s, when the US went into a recession, the small companies were particularly performed poorly, even when the economy and stock market rebounded after a decade, those small stocks still continued to lag.Also, by late 1990s, value stocks’ return was surpassed by the spectacular performance of growth stocks due to the high-tech stocks with very high market capitalization and relatively low assets. However, DFA believes in the efficient market theory, they prefer small stocks over large ones and value stocks over growth stocks.
DFA should justify its belief by stating that although the systematic risk would cause certain efficient market theories to bereversed during such times (large stocks outperform small stocks; growth stocks outperform value stocks), the market efficient theory will eventually prevailin the long-run based on the historical data done by Fama and French. Other than the market efficient theory, DFA also believes in two other principles: the value of sound academic research and the ability of skilled traders. Those two factors can contribute to fund’s profits. Because of DFA’s ability to excel in those two areas, they believe that they can provide more value even in efficient market environment.
Trading costs associated with small and value stocks include illiquidity and adverse selection problems. To be more specific, the illiquidity of small stocks may cause the stock price move substantially when a purchased is made. Also, the information asymmetry may also result in the adverse selection problem. DFA manages the small stocks illiquidity problems by using block trade to extract a discount on a stock purchase, thus creating value for the clients.
In addition, to avoid the adverse selection problems, DFA’s traders follow several steps:
It’s not an embarrassment for DFA when small stocks underperformed large stocks in the mid of 1980s. Because systematic events can’t be possibly avoided. In fact, DFA’s small stocks portfolio outperformed other small stocks investing competitors during the recession. This suggests that DFA’s focused principles in academic research and traders’ ability are adding value to its investors. Besides, this event alone doesn’t prove either rational or behavioral explanation is more likely since the recession is a one-off event.
Therefore, DFA should not abandon its small stocks strategy because in the long run the trend is more likely to reverse itself. Even if small stocks were to continue to outperform large stocks for another decade, DFA could still provide value then other small stock investment fund. And as more fund are trading on large stock, the benefit of return on large stock may eventually goes away, making small stock.
Dimensional Fund Advisors Case in Marketing Analysis. (2016, Oct 07). Retrieved from https://studymoose.com/dimensional-fund-advisors-case-in-marketing-analysis-essay
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