Should You Be Factor Investing? - YouTube

Factor investing is currently one of the hottest  terms used to sell financial products. You may  

have also heard the term smart beta, which is  referring to the same concept. A simple way to  

think about factors is that they are quantitative  characteristics shared across a set of securities.

The reason that we care about factors is  that those characteristics can be used  

to structure an investment portfolio to outperform  

the market without the need to rely  on stock picking or market timing.

Factors are on the cutting edge of  financial market research, but they  

are also being used to market products that may  be detrimental to investors. Don’t get me wrong,  

factors are more than a sales pitch. They  are the mechanisms that drive asset returns.

I’m Ben Felix, Associate Portfolio  Manager at PWL Capital. In this episode  

of Common Sense Investing, I’m going  to tell you about factor investing.

Before we understood factors, researchers  were noticing that diversified portfolios  

of small stocks were outperforming  diversified portfolios of larger  

stocks. At the time there was no  explanation for this difference,  

and the performance difference may have been  attributed to the skill of the portfolio manager.

As factor research emerged, it became clear  that stocks with certain characteristics could  

explain a lot of the differences in returns  of diversified portfolios. The reason that  

we care about factors is that those performance  differences have been positive. Capturing positive  

return differences exhibited by certain types  of stocks has an obvious benefit to investors.

Currently, factor models explain over 95% of  the return differences between diversified  

portfolios. This is problematic for active fund  managers because their ability to beat the market,  

which was previously assumed to be due to their  skill, can in many cases be explained by factor  

exposure. This is a big deal for investors  because if you can get market beating returns  

with a factor index fund as opposed to an  active manager you will save a lot on fees.

Here is a concrete example to explain  what I mean. In a classic 2015 blog post,  

my PWL colleague Justin bender took a handful  of actively managed market-beating mutual  

funds suggested by Globe and Mail columnist Rob  Carrick and performed a three-factor regression.  

In other words, he used some analysis to  show how much of their performance could  

be attributed to factor exposure as opposed to  manager skill. In most cases the outperformance  

was fully explained by factor exposure,  and in one case it was mostly explained.

This means that while these active funds did  beat the market, they did so by holding more  

small cap and value stocks than the market, not  by skillfully picking the right stocks at the  

right time. Holding more small cap and value  stocks than the market is something that an  

index investor can replicate at a fraction  of the cost of an actively managed fund.

Research on factors emerged in the 1992  paper by Eugene Fama and Ken French titled  

The Cross-Section of Expected Stock Returns.  In the paper, they observe that small stocks  

outperformed large stocks over time, and value  stocks outperformed growth stocks over time.  

The explanation for the return differences is  that stocks with these characteristics, small  

stocks and value stocks, are riskier. Investors  must expect higher returns to own riskier assets,

In 1997, Mark Carhartt added the momentum  factor to the body of research, and later,  

in 2012 Robert Novy-Marx added the profitability  factor. This gave us five factors which together  

explain over 95% of the return differences  between diversified portfolios. Fama and  

French came out with their five-factor model in  2014, combining market, size, relative price,  

profitability, and investment, while ignoring  momentum. The ultimate factor model is unknown,  

but researchers continue to test new factor models  to increase the explanatory power of the model.

Factor research has become not only important  to our understanding of finance and investing,  

but a way for academic researchers to  make a name for themselves. After all,  

Fama was awarded the Nobel Memorial Prize  in Economic Sciences in 2013 for his work  

on asset pricing. This academic competition for  discovery of the next factor has resulted in many,  

many research papers being published  claiming to have identified new factors.

Duke University’s Campbell Harvey, Texas  A&M’s Yan Liu, and University of Oklahoma’s  

Heqing Zhu have identified over 300 factors in  academic literature. This is problematic for  

investors. Targeting five factors in a portfolio  is hard enough. What do you do if there are 300  

of them? Unfortunately for the researchers, and  fortunately for investors, many of these factors  

do not pan out. In many cases they turn out  to be a re-packaging of the original factors.

There is a sniff-test for investors to  know when a factor is worth pursuing,  

and when it should be ignored.

To be taken seriously a factor  should be persistent, pervasive,  

robust to alternative specifications,  investable, and sensible.

It is worth digging into each of these  characteristics. For a factor to be  

persistent it must show up through time  and not be limited to a specific time  

period. To be pervasive a factor must hold  true across various countries, regions,  

and sectors. Robust to alternative  specifications means that the factor  

should not be affected if you slightly  change how the characteristic is defined.

Investable is extremely important -  it means that if the factor cannot  

be cost-effectively captured in portfolios  it is not helpful to investors. Momentum  

is an example of this. The momentum factor  meets many of the previous characteristics,  

but it is a high-turnover strategy. This makes  it expensive to implement in a portfolio.

If there is no sensible explanation for a factor,  then it may not be expected to persist. Again,  

momentum is an example. Unlike the risk  explanation for small and value stocks,  

momentum does not have a sensible explanation.

While many factor products have emerged, there  are very few companies creating factor products  

that get me excited. One company that has  done and continues to do an excellent job  

in this space is Dimensional Fund Advisors. The  research on factors is a commodity - anyone can  

access it. The difference between implementing  factors well and poorly comes down to how the  

company vets the factor research, who does  the vetting, how they interpret the data,  

and their ability to understand of  the limitation of factor models.

The founder of Dimensional Fund Advisors,  David Booth, has said “The research is out  

there for anybody to access. What distinguishes  Dimensional is the way we implement the ideas.”

While I do believe that a factor portfolio is  optimal, Dimensional Fund Advisors’ products  

can only be accessed through specific  firms, like PWL Capital. Based on this,  

and with a lack of ETFs, especially in  Canada, that are effectively capturing  

well-researched factors at a reasonable  cost, I think that DIY investors are probably  

better off, at least for now, focusing on  simplicity rather than pursuing factors.

The Canadian Couch Potato model portfolios  used to pursue the size and value factors,  

but Dan changed the models in 2015 to ignore  factors entirely. Part of his explanation  

was that “many DIYers make costly mistakes when  they try to juggle too many funds. Meanwhile,  

there are exactly zero investors in the universe  who failed to meet their financial goals because  

they did not hold global REITs or small-cap  value stocks.” I agree with Dan in full.

Have you tried to implement a factor  portfolio? Tell me how it went in the comments.

Thanks for watching. My name is Ben Felix  of PWL Capital and this is Common Sense  

Investing. I will be talking about a new  common sense investing topic every two weeks,  

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