Dimensional Fund Advisors Case Analysis Essay

b.What are the amounts and timing of the acquisition investment’s free cash flow from 2013 through 2022?

Dimensional uses the EMH to its advantage in coming up with its strategies. First the focus on stocks over bonds because there is a greater return on stocks. Second, they focus on several different kinds of smaller stocks instead of just one particular larger kind. The is always a risk when investing in anything. Time, relationships, and money. DFA is aware of the risks and do everything they can to make sure the best options are available to their clients. They focus on diversification of the market as a tool to reduce the risks involved. DFA uses research based portfolios that are specific to the task at hand. Its dimensional funds returned at 42% which is way above other firms in the same field.

DFA’s founders believed in two principals (outside of efficient markets): the value of sound academic research, and the ability of skilled traders to contribute to a fund’s profits even when the investment was inherently passive. By working closely with the academic world, DFA is able to exploit opportunities generated from academic research before others are able to; this creates opportunities for short and long-term excess return. Also, working in stocks that other mutual funds do not participate (micro, small-cap) allows DFA to exploit opportunities in otherwise illiquid stocks. By having a large presence in this market, the company is able to take advantage of trading opportunities with counterparts (liquidity discounts from block purchases).

When USAA started in 1922, they were a property and casualty insurance company however, with time they expanded their services to their members and became a financial institution.

Dimensional Fund Advisors, further referred to as DFA, is an investment company that bases its strategy

DFA has had a very consistent strategy since its inception in 1987. They use academic research as the backbone of their decisions. At the heart of their strategy is the efficient market theory, meaning that in liquid markets, prices reflect all available information. This is contrary to most mutual funds that attempt to continually beat the market. Instead DFA looks to academic research to invest in asset classes that historically produced higher expected returns and structure their holdings around those classes. This enables them to stay passive but add alpha over index funds. Other sources of alpha are contributed by block trading and buying in bulk at a discounted price, and finally by constructing products for niche tax advantages. Ultimately DFA is not looking to profit by exposing arbitrage in the market but instead building strategies under the assumption of fair pricing allowing them to focus their attention on investments that compensate investors for taking. Under these assumptions, the market risks come at a premium which may allow for higher expected returns. They put a strong weight on academic research and results from practicing investors that show robust long term strategies. The research behind their beliefs show that small companies have higher expected returns than large companies, high B/M “value” companies have higher expected returns than low B/M “growth” companies, and finally companies with high profitability have higher expected returns than

Working for an investment firm I was recently asked by my boss to help advise two of firm's best clients. The client's names were John and Jane Mooney. Both John and Jane are in their early 40's and have no children. John is a fireman for the local fire department while Jane is a professor at the local community college. The Mooney's annual income is roughly $115,000. The Mooney's own their home and are virtually debt free.

Many extensive studies have been conducted on the behavior of stock prices, which has provided a numerous number of theories that propose how prices will change given certain circumstances. The most fundamental theory on the behavior of the stock market was published in 1970 by Eugene F. Fama in his research, titled Efficient Capital Markets: A Review of Theory and Empirical Work. The theory he proposed is referred to as the Efficient Market Hypothesis (EHM) and is considered to be one of the most classical and resilient economic theories. In his work he proposes the securities markets are extremely efficient in a way that information about individual stock prices is reflected across the market so quickly that an investor cannot beat the market, meaning a portfolio comprised of similar risk stocks will generate comparable profits. Furthermore, this theory suggests that stock prices are entirely unpredictable, such that the only relevant information on what the price of a specific stock will be tomorrow is the news that occurs that given day.

Since Fama-French Three Factor Model seem to explain average returns on stocks and bonds of North American publicly traded companies (Fama et al., 1993). But no test has been performed on the firm-level returns. Therefore, we present the following hypotheses formally here:

246). Samuelson’s dictum asserts that individual-firm stock price variations are dominated by genuine information about future cash flows of the firm, but they are not perfect indicators of these cash flows either. Cohen et al. (2001) used a method similar to that in Vuolteenaho (2002) to derive a decomposition of the cross-portfolio variance of the log ratio of book value to market value into three components: a component that could be justified in terms of information about future cash flow, a component related to the persistence of the value spread, and what we might call an ‘‘inefficiency component’’ that generates predictable future returns.2 They also used a longer sample period, an international data set, and some improvements in method. Their conclusions with U.S. data 1937–97 and 192,661 firmyears were that 80% of the cross-sectional variance in the log ratio of book value to market value can be justified by the first few components, only 20% by the inefficiency component that explains 15-year returns. Their conclusion with international data on 22 countries 1982–98 and 27,913 firm-years was that 82% of the cross-sectional variance of bookto-market values was explained by the first two components, and only 18% by the inefficiency component that explains five-year returns.

This paper examines the Capital Asset Pricing Model(CAPM) and the Fama-French three-factor model(FF) and the Fama-MacBeth model(FM) for the 201211 CRSP database using monthly returns from 25 portfolios for 2 periods ---July 1931 to June 2012 and July 1631 to June 2012. The theory’s prediction is that the intercept should equal to zero the slope should be the excess return on the market portfolio. The findings of this study are not substantiating the theory’s claim for the fact that in some portfolios the alpha is

Efficient Market Hypothesis was firstly brought forward by E. Fama in 1960s. Its main believing is in that security prices fully reflect all available information in an efficient market, which allows investors to earn no above average risk-adjusted return (Fama, 1965). Although some technical studies and opportunistic investors have stretched hard in searching for proofs to challenge the efficient market hypothesis, and to prove above average returns could be gained by predicting the future price using the existing information, their efforts result only in finding of the ¡®anomalies¡¯ in the market which are destined to self-destructing in the long run or being proved worthless taken the transaction cost.

Figure 1 outlines seven commonly discussed factor exposures that are notable both for the extensive literature documenting each, and for the empirical evidence of historical positive risk-adjusted excess returns associated with them. We do not attempt to exhaustively analyze these factors; rather, we briefly emphasize relevant aspects for investors to consider in evaluating the factor-based approach. Two points should be mentioned at the outset: First, investors may knowingly or unwittingly already hold certain factor exposures within their portfolios. For example, a portfolio of stocks with low price/earnings ratios is likely to have exposure to the "value" factor. Second, the investment case for some factors is subject to ongoing debate- namely, whether past observed excess risk-adjusted returns will continue going forward.

Since CAPM was accepted and admitted in fundamental concepts by most people in financial economics, factor model researching becomes a popular topic in finance. In 1992, Eugene Fama and Ken French established the empirical foundations for the Fama & French Three-Factor Model. It is designed to capture the relation between average return and size and the relation between average return and B/M (price ratios).

Note that the institution’s objectives and constraints drive the factor allocation decision, not the indexes themselves, a point that is often lost in the arguments about why one index might be superior to another. Simply focusing on a particular index’s rules and construction process leads to the slippery slope of data-mining. There are thousands of options for generating indexes by varying the weights or criteria for selecting stocks. Any given set of index construction rules can lead to outperformance of the market through statistical sampling alone. Before evaluating any factor indexes, the institution should identify its goals for factor investing and evaluate potential candidate factors based on criteria that follow from their objectives and constraints. Choosing a factor index is an implementation decision that turns the objectives, goals, and factor beliefs into actual allocations. Next, in Section II, we discuss how an institution’s objectives and constraints motivate the appropriate choice and blend of factors and factor indexes. In Section III, we look at investability, which is