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The 3 Factor Model

The following is an extract from our book - Your Guide to Being a Successful CEO of Your Life.

This chapter explores the 3 factor model, an academic model that says that within investment markets not only is the average return a source of returns, 'small' and 'value' companies outperform the average market return.


There are many people for whom the index investing story does not provide a strong enough value proposition to entice them to take action.  Somehow it is not compelling enough.  The application of the 3 factor model to investment portfolios makes a passive approach to investing more compelling, as it allows investments in small and value companies, which provide a higher expected return for portfolios. 


Fama and French, researchers and finance professors from the United States, found that investing in companies with specific attributes could provide an expected return above that of the index.  Indexing was the exciting innovation of the 1970's, and Fama and French's research provides the more recent and exciting innovation.


The previous chapters have outlined the benefit of taking index positions, over time.  This chapter asks:

Ø      Is there potential to tweak this model to produce slightly higher returns?

Ø      Are there market segments that consistently outperform according to their risk, over time?


Some leading academic research, initiated by Fama and French's research, suggests that there are possible positions that can be taken by investors to achieve premiums above the expected index return.


Basic Principles


Before delving into the specific research, let's first review some of the important principles surrounding this issue.  We clearly subscribe to the view that markets are efficient.  This means that we believe that prices of traded assets reflect all known information and in doing so identify the collective beliefs of all investors about future prospects.  In short, this implies that it is impossible to consistently outperform the market once it has been adjusted for risk.  As shown earlier in this book there is significant evidence that backs up this belief.


We also agree with the basic principles outlined in Sharpe's Single Factor Model as outlined in his 1964 Journal of Finance article.   Sharpe suggested that investors are rewarded for the amount of risk they take relative to all other things in which they could have invested. i.e. the entire stock market.  This model is also known as the CAPM, Capital Asset Pricing Model.  Investing in the stock market entitled the investor to the 'market risk premium', additional return for the risk that they have taken on.


However, later research has shown that the CAPM does not tell the full story.  In particular, research carried out by Fama and French, as published in their Journal of Finance article in 1992, determined that there was more than just a simple relationship between stock returns and market returns suggested by the US stockmarket data that existed for the period 1941 to 1990.  The researchers continued on to suggest, supported by the data, that there was instead evidence to suggest that a multi-dimensional approach to explain returns was more appropriate.


Fama & French Research


Fama and French, discovered that 3 factors together do the best job explaining expected returns:


Ø      Market beta - a measure of overall market risk

Ø      Firm size -market capitalisation

Ø      The Value Effect - based on book-to-market measurement


As such, Fama and French concluded that all 3 factors were risk factors that markets reward with higher average returns over time.


Intuitively, the market beta factor makes sense.  Most investors would acknowledge that investing in the stock market pays a premium over fixed interest securities such as government bonds.  Investors are rewarded for the extra risk they take investing in the sharemarket.


Similarly, many would agree that small cap stocks are riskier than large stocks, and therefore have a higher expected return for investors. This relates to Miller's idea that a firm has a 'cost of capital', and the higher the cost of capital the higher the returns that a firm has to offer an investor to invest in that company.  Small companies, being perceived as riskier, have to offer higher returns to compensate for this higher risk when they issue shares.


However the third factor, the value effect, where an investor has a higher expected return from value stocks is a little more difficult to understand at face value.  Fama and French suggested that a measure of book-to-market gave an indication of an underlying source of risk - the level of financial pressure or distress.  High BtM stocks are lower-priced stocks.  The market values the book value of the company at a lower level than other stocks.  Why?  The market judges that the company is in some kind of financial pressure or distress, maybe from poor management, difficult industry conditions or poor historical returns.


Why does this make sense? As investors view a company as distressed they expect a higher level of return for the money that they invest in the company.  This expected return is the cost of capital to the business.  Investors require greater returns from these distressed companies to entice them to invest in them.


Anecdotal Support - Michelle Clayman's - In Search of Excellence or Unexcellence


In 1987 Michelle Clayman published a study in the Journal of Finance (Volume 63 May-June) where she looked at a group of 29 "Excellent" companies as identified in a New York Times best-seller written in 1982 by Tom Peters and Bob Waterman In Search of Excellence.  Using the same criteria, Clayman identified the 29 worst companies and called these the "Unexcellent" companies.  She then compared the investment return of value-weighted portfolios of the Excellent companies versus the Unexcellent companies.  From 1981 to 1985 the Unexcellent companies outperformed the S&P 500 by 12% while the excellent companies outperformed the S&P 500 by only 1%.


To be fair though, Clayman conducted a similar study from 1988 to 1992 and in this study the Excellent companies outperformed the Unexcellent companies.  She published her results in the May-June volume of the Financial Analysts Journal of 1994.  Clayman concluded that combining the two studies, there appears to be a tradeoff between growth and profitability versus valuation ratios.  "Good companies do not necessarily make good investments, the market appears to reward profitable companies selling at reasonable multiples."


Clayman's studies support the idea that portfolios with different characteristics perform differently at different periods of time.  It also contains a small sample of companies that fit the criteria of a higher value company.  To make the optimal position an investor should take a diversified position by investing in most if not all companies that fit the description of a high value company.


Further Support


Another earlier study looking at value stocks was conducted by Paul Miller.  In 1964, Miller compared buying the 10 lowest and 10 highest P/E (price/earnings) stocks of the Dow 30 from July 1936 to June 1964.  The P/E ratio is the price of the company divided by the earnings of the company.  A lower P/E ratio is another definition of a value stock.  He found that the 10 lowest P/E stocks greatly outperformed the 10 highest.  However the lowest 10 P/E stocks also had a greater variation in returns.  This identified that returns for these stocks were more volatile suggesting that there was a greater risk in holding these shares.


It should be noted that the measurement of value could also be undertaken by using the Price to Earnings ratio (P/E) as used by Miller.  This measures how much shareholders are paying for each dollar of earnings of the company.  The smaller the P/E ratio, the cheaper is each dollar of earnings.  A practical problem with using this ratio is that some companies do not have any earnings, they make losses.


A third measure of value is dividend yield.  This ratio measures the amount of dividend paid to shareholders divided by the price of the stock.  Use of this unit of measurement also has problems as some companies may not issue dividends, or reduce the amount of dividend issued during a period of growth, instead using profits for developing new business ventures.  Alternately companies may not be able to issue dividends due to poor performance or distress.


For these reasons Fama and French chose the Book to Market (BtM) ratio as the most consistent financial ratio to identify ?value' companies.  Every company has a book value, the net value of its assets and relatively stable from year to year.


What all 3 studies are saying was that investing in bad companies provides a premium to investors.  This may be due to the fact that these companies are somehow 'out of favour' with the market (the behavioural explanation) or that these companies are under financial pressure and have therefore been 'sold down' by the market.  Good companies, conversely, are expensive relative to their book value.


The cost of capital argument also helps to understand this situation.  Bad companies will have to offer high expected returns to entice investors, whereas the good companies will be able to offer lower expected returns and still entice investors.  Once a company is trading on the stock exchange, the stock exchange acts as the pricing mechanism through which investors bid the prices that they will be prepared to pay for a company.  These prices will be based on the required returns needed, with investors needing higher expected returns to entice them to invest in the poorer companies.


It should be acknowledged that at the time of the research and subsequent publication of findings, Fama and French were criticised for what is referred to as data mining.  Basically this suggested that they had a hypothesis and then went looking for the data to back up their position.  It should also be noted that a significant number of studies have followed that support the work of Fama and French.  These further studies have included studies in many different countries and over many different time periods.  There is a strong body of research that now supports the concept that small and value companies outperform over time.


So well accepted is the Fama and French research that almost all academic studies of share market performance now use the 3 factor model as the benchmark for investment returns.


Practical Implications


By using the findings of Fama and French, long term investment strategies can be developed to harness some of these expected premium returns.  Positions could be taken in small companies and / or value companies with high BtM ratios.


Ø      Can we pick which small and value companies we should invest in?


The answer, as before is no.  Rather a ?passive' position should be created. 


We have previously talked about index funds, where a managed fund holds all the investments in an index in the proportion that they occur in the index.  In this case, there is no formal 'small company' index or 'value company' index.  However, it is possible to form a sub group of companies that have the common characteristic of being small companies or high BtM companies.


That means we take all the small cap companies in the index or all the high BtM companies or all the small companies that are available for investment.  Taking these positions reduce the risk of picking the 'right' or 'wrong' shares.  It also saves the cost of researching exactly which companies should be selected, and saves ongoing trading while providing an extremely well diversified portfolio of companies.  The approach is a 'passive' one, where an investment universe of small companies or value companies is created for investing.


Of course the approach taken must consider the relevant risk aversion of the individual investor.  Investments in small companies and / or value companies will be more volatile reflecting the inherent extra risk.  If this risk does not sit well with an investor they should hold investments in less risky assets such as the market indexes, or hold a portion of their portfolio in cash investments.


Practical Evidence in Australia


Dimensional Fund Advisors have worked with the Fama and French research to build passive managed funds that invest in small and value companies.  Indeed, both Professor French and Professor Fama are key people in Dimensional Fund Advisors.


Dimensional Fund Advisors have now been in Australia long enough that there is 5 year historical data from their Australian small and value companies.  There is also 5 years of data for the international small and value funds set up for Australian investors.  We have compared these returns with the relevant index, the ASX 300 in the case of Australian shares and the MSCI world index (excluding Australia) in the case of international shares.  In each case returns are after fees.


Please click to go to more up to date data found on our website - Dimensional Fund Performance Graphs.

The graph of returns from international shares for Australian investors reminds us that investing must be a long term venture, and that even a 5 year investment period may not produce strong results.  Even the investment returns from the Dimensional small company and value company funds, while stronger than the returns of the underlying index, have been poor over this 5 year period.

Keep in mind that in the graphs presented we have compared an index return to the return of the Dimensional small company and value company strategies.  An actual index fund, which we can invest in, will approximate the return from the index, less the costs of the fund.


How Do We Apply This?


In a nutshell, the three factor model suggests that the only way to outperform or under-perform the investor next to you (and the market) is to invest in companies with more or less size and / or Higher Value (BtM) risk. 


The power of this is that investors can now build a passive portfolio that, through exposure to small companies and value companies can outperform the simple index.  This method does not require investment skill, expensive research or tax ineffective trading.