What is Factor Investing and How Does it Improve Your Returns
Have you ever wondered if there are any common traits to stocks that are about to perform better than the market - before it has already happened? Decades of research into this have resulted in what is now called factor investing. This means investing in stocks with certain characteristics (factors) that tend to outperform the market in the long run. This post explains how it works.
Theoretical background behind stock factors
You may have heard about the Efficient Market Hypothesis (EMH), which states that all publicly available information is always immediately priced into a stock, and therefore it is not possible to consistently outperform the market. This view has received a lot of critique as it also leads to the death of stock picking and basically to stock market analysts being useless.
The Fama & French studies
EMH and related models and theories such as CAPM led to a lot of research into identifying market anomalies or behavior that deviated from EMH. For instance, how could people like Warren Buffett consistently beat the market for decades, if the efficient market hypothesis was true? In a famous study from 1992 Eugene Fama and Kenneth French proposed a model consisting of three factors to explain stock market returns:
- The market beta factor: The returns given by simply being in the market
- The value factor: The excess returns found in value stocks compared to expensive stocks
- The size factor: The excess returns found in smaller stocks compared to large stocks
While the market beta factor can be considered the expected result of EMH, the value and size factors were the first two anomalies found that were widely accepted. Fama & French basically showed that small (size factor) and cheap (value factor) stocks had more or less consistently outperformed the market during their investigation period starting in 1963. I have written another post specifically about using size together with value.
So, what exactly is a factor?
Factors can be explained as sets of characteristics surrounding a group of stocks, that can be measured in a quantitative way. The goal of factors is to identify characteristics that tend to lead to above-market returns (also known as alpha).
For instance, researchers have found that in the long run companies with a low price/earnings value gave higher stock returns than companies with a relatively high price/earnings value. This metric, along with a handful of other similar metrics, goes into the definition of the value factor. The more a company fits the value metrics, the more it can be said to have "exposure" to the value factor.
For other factors, there are other metrics to look into, but it must always be completely quantifiable and clean from subjective input. This also means it's easy to automate ETFs that hold all the stocks with the most exposure to a certain factor and continuously adapt the list to changing values. I'll get back to that.
Before diving into the actual factors, I want to mention a brilliant book on this topic by Andrew Berkin and Larry Swedroe titled Your Complete Guide To Factor-Based Investing, if you're interested in further reading.
Factors you should know
Following the findings of Fama and French, hundreds of new factors were proposed in financial academic research. The vast majority, however, were either not consistent anomalies or already explained by other factors. Today there are four proven factors you need to know about. I will explain each of them briefly in the sections below.
The size factor is the easiest one to understand. This is simply a matter of stocks with low market capitalization generally performing better than the larger ones. Berkin and Swedroe found that from 1927 to 2015 the smallest 50% of all US stocks outperformed the largest half by 3.3% annually on average.
Of course, there are good a bad years for small-cap stocks, and there are even bad decades. Over the past 15 years, they have generally underperformed large-cap stocks, but this may change at any time. Utilizing the size factor for investing is super easy, as it's just a matter of buying a small-cap fund or ETF.
I also touched upon the value factor above. There are many definitions for this, but generally, it's a matter of isolating cheap stocks - either measured via price to earnings, price to book value or something else. The definition might as well be a combination of metrics, but it usually doesn't make a huge difference.
Berkin and Swedroe compared the 30% cheapest stocks with the 30% most expensive stocks and found an average annual difference in returns of 4.8% from 1927 to 2015. This means cheap stocks (known as value stocks) have historically performed way better than their expensive counterparts, known as growth stocks.
The momentum factor works in a very different way, as it doesn't care about any fundamental values of a business. Instead, it focuses entirely on the recent performance of the stock, called the momentum. More specifically it ranks all stocks by their performance over the last 12 months (their gain or loss measured in percent).
Comparing the 30% of all stocks with the highest momentum (best returns over 12 months) with the 30% with the lowest momentum, Berkin and Swedroe found a remarkable difference of 9.6% in annual average performance over the same 88 years as the other factors were investigated.
This is an important reminder to us all, that stocks that go up tend to continue going up, and the same goes for the opposite.
Quality (or Profitability)
The quality factor combines a number of financial key metrics regarding the health of the business, such as revenue, return on equity, and EPS consistency. Depending on the metrics used for the definition, this factor is also called the Profitability Factor.
Again I reference Berkin and Swedroe, who found that the 30% of companies with the most quality factor returned on average 3.8% higher annually than the worst 30% of stocks from 1927 to 2015. Once again we have a systematic outperformance over a large timeframe just by looking at quantitative values with no further analysis involved.
Factor premiums and success rate
Now you might want to jump straight into buying factor stocks, but which factor should you choose? The table below summarizes numbers from Berkin and Swedroes book mentioned above (this book is truly a bible on factor investing!).
|Factor||Annual premium||10-year success rate|
The premiums show the difference between high and low exposure to each factor - not the excess returns above market level. This can be expected to be somewhere around half of these values or slightly lower since much of the premiums come from "avoiding" the stocks with very low exposure to each factor.
The 10-year success rate shows the probability of outperforming the market in any given 10-year period. These numbers are based on historical data from 1927 to 2015.
How to invest using factors
So, momentum stocks look pretty interesting, right? Be aware that for all the factors there are long periods of underperformance and bad drawdowns compared to the overall market. Read my post about momentum investing for more details on this. Factor investing requires a long time horizon and the ability to stick to the strategy in bad times.
That being said, it's not difficult to invest using factors. There are a few ways to go about it, which I will explain here:
The easiest way to get started is using single-factor ETFs. These are just like the common index ETFs, except they are filtered to only hold the companies that have a high exposure to a certain factor. There are plenty of these ETFs out there, but I can recommend the ones from iShares with names like these:
- iShares MSCI World Value Factor ETF
- iShares MSCI USA Momentum Factor ETF
- iShares MSCI Europe Quality Factor ETF
The problem with single factor ETFs is that long periods of underperformance will be involved with each of them. If you want to smoothen out and spread your eggs across multiple factors, you may of course just buy an equal amount of each single-factor ETF.
Another option would be to buy a multi-factor ETF. These are a bit more complex, but their goal is to calculate a total factor score for each stock in the market and only include the best ones. That is, the stocks that have the most total exposure to all the factors they target. This is interesting, as it provides a portfolio of stocks that are typically high on more than one factor. Again iShares provides a multi-factor ETF for each region, but there are also other players out there.
Finally, you may decide to incorporate factors into a stock-picking strategy. If you practice stock picking anyway, you may want to start paying attention to the factor exposure when analyzing a potential buy. After all, a high factor exposure seems to be one of the best indicators of future outperformance.
It takes a bit of work though to find the numbers you need to be able to judge the factor exposure of a stock. A shortcut to this may be to simply look up the holdings of factor ETFs, which are always publicly available. There you will find a list of all the stocks that were selected for a given factor by an algorithm designed by professionals.