Investment factors are a set of quantitative criteria used to explain investment returns.

The idea is that some baskets of securities that have similar criteria might deliver superior risk-adjusted returns. 

At its simplest, an investment factor is a characteristic of a security that is associated with superior risk-adjusted returns. That could be a low valuation, price momentum, earnings growth, insider buying, etc.

While there’s hundreds of different investment factors published in academic literature, the factors that get the most attention, have the most institutional support, and the most scalability, are value, momentum, size, low-volatility, and quality. 

Why Factor Investing?

Factor investing in many ways is a solution for investors that can’t stomach a purely passive indexing approach.

They don’t like that they’re blindly investing in hundreds of companies based on the notion that the market always goes up over time, but they’re also aware of the flaws of picking individual stocks or timing the market.

Investing in factors that make sense to the investor can be a good compromise here.

For example, you might have a strong belief in the value investing philosophy, that you should always strive to buy a business at the right price.

You could opt to invest a large portion of your equity allocation in value factor ETFs or mutual funds with the peace of mind that, even though you don’t know what you own specifically, at least you know that you own lower valuation companies. 

Essentially, a factor investment portfolio is built using simple quantitative criteria.

For value stocks it’d be ranking a universe of stocks based on a valuation metric.

For momentum, it might be a 12-month lookback at returns. Of course, factor investors optimize and have more sophisticated models, but the big ideas are simple and laid out in this article. 

The Value Factor

The value factor represents the historical tendency for stocks with low valuation to earn excess returns compared to both the overall market, and their high valuation counterparts.

How do you define a low valuation, though? A few decades ago, a 20 PE was very high, while today it’s the market average. 

This is why factor-based strategies employ a relative valuation approach.

They buy what’s cheap compared to the rest of the market, rather than setting an arbitrary hurdle rate for their investments. This prevents factor-based strategies from taking a specific macro view on what risk premiums should be or will be.

The typical value factor strategy will have a universe of stocks, let’s say the S&P 500. Then it ranks all of them based on a given valuation metric. A few popular metrics are:

• Book-to-market ratio (or price/book)
• EV/EBITDA
• Price/FCF (free cash flow)
• EV/FCF 

So let’s keep it simple and use the price/book ratio. The universe is ranked based on the price/book ratio. Then the model buys the cheapest 20% or so of the universe. 

The Momentum Factor

The momentum factor refers to the tendency for recent outperforming stocks to continue their outperformance in the short-to-medium term.

You can sum this up as “buy what’s going up, sell what’s going down.” And the interesting thing is that most equity momentum models that hedge funds charge fees for are no more complex than that. 

Momentum has always been the red-headed step child when it comes to sources of returns.

Sophisticated investors look down on it and deride them as gamblers or market tourists without skill. I’d say this is more Wall Street culture than anything. Simple solutions are hard to sell because clients can implement them on their own. And most Wall Street executives are Harvard or Wharton educated, and can’t imagine a naive strategy of buying the stocks that go up would ever work. 

But, there’s substantial evidence in favor of the momentum factor providing excess returns. It’s well accepted by both academia and institutional investors alike.

The basic way that a factor-based equity momentum portfolio works is, you rank the universe based on trailing six or twelve month performance, and buy the top performers. There’s some extra algebra involved, but that’s the core essence of it.

There’s some good books like Stocks On The Move and Quantitative Momentum that go into detail about building these models. 

The Quality Factor

The quality factor refers to the tendency for firms with high levels of profits to outperform unprofitable firms. Like the other factors, there’s multiple ways that factor investors might express quality, and there’s not really an agreed upon definition for “quality.”

Between ETF managers, academics, and hedge funds like AQR, everyone has their own definition of the quality factor. But there’s tons of overlap. Here are some metrics you’ll see in a lot of quality models: 

• Return on invested capital (ROIC)
• Return on assets (ROA)
• Gross profits
• Inventory turnover
• Return on equity (ROE) 

As you could probably make out, these metrics are all screening for companies that take money and turn it into more money in an efficient and fast way, with few surprises.

One example of a quality factor model might be to use a weighted average of a few of the above metrics to prevent the risk of an anomaly in a company’s financial statements from ending up in the portfolio.

So you’d rank them, and buy the quartile with the highest quality, and short the lowest. This is similar to AQR’s “Quality Minus Junk” strategy. 

The Low-Volatility Factor

The low volatility factor refers to the tendency for boring stocks to outperform their high-flying, exciting peers in the long-term, on a risk-adjusted basis. Of all five of the major factors, low-volatility is the least explainable.

The rest makes sense and could be explained to a five-year old, “buy what goes up,” “buy the bargain bin,” “buy the top-shelf goods,” “buy the underdogs.” 

Because of the lack of explainability, there’s a higher potential that the outperformance is an anomaly or the result of data mining. The low-volatility factor flies in the face of the Capital Asset Pricing Model, which posits that investors should be compensated for taking on more risk. But, this factor says that the returns are actually higher in the lower risk assets.

Building a low-volatility portfolio would be relatively easy. You can use the stock’s N-day standard deviation, its average true range, or even it’s Beta. Then simply rank and buy the lowest volatility stocks.

Building a long/short portfolio for this factor seems like a disaster waiting to happen, though. 

The Size Factor

The size factor refers to the tendency for smaller stocks to outperform large stocks.

This is probably because with small and micro cap stocks being generally illiquid, an investor deserves a risk premium for taking on the liquidity risk.

Further, it’s much easier to double $100 million of revenue than to double $10 billion of revenue, making the potential for home runs with small stocks much higher. Also, small stocks receive very little Wall Street coverage, and most institutional investors are too big to pay attention to them, leaving alpha on the table. 

According to Your Complete Guide to Factor-Based Investing, the average size premium (the excess returns for investing in smaller stocks) in US markets was 3.3% between 1927 and 2015. The size effect works in almost every global market too,

Combining Factors

Most active factor investors utilize factor timing, combine factors, or otherwise add some sort of secret sauce. Combining factors is an obvious idea that any individual investor can apply themselves. 

One popular example of combining factors is Joel Greenblatt’s “Magic Formula” from The Little Book That Beats The Market. The strategy simply ranks stocks based on value (EVIT/EV) and quality (ROC) and buys 20 or so of the highest ranked stocks.

You can take Greenblatt’s formula a step further and remove large companies from your investment universe, potentially benefiting from the size premium, too.

Tracking Factor Performance

Whether or not you apply factor investing strategies, knowing the dominant factors in the market can tell you a lot about what investors are thinking. For example, in 2021, we saw a rapid shift from growth to value after two decades of severe underperformance for value. This highlighted investors’ fear of inflation. 

A great source for tracking factor performance is Koyfin. It’s a free markets dashboard and they have a great factor analysis page. Here’s what that looks like:

 

If you’d rather remain within your own charting platform, use factor ETFs to track them. Here’s a list of tickers:

• Value: IWD or IVE
• Small Caps: IJR
• Growth: IWF or IVW
• Momentum: MTUM
• Quality: QUAL or SPHQ 

The History of Factor Investing

The idea of factor investing stems from academia.

If you took finance courses in college, you’re of course familiar with Eugene Fama for his work on the efficient market hypothesis. In the 1990s, Fama teamed up with Kenneth French and they improved on the model that formalized the academic understanding of risk and reward in markets: the Capital Asset Pricing Model (CAPM).

Fama and French’s updated understanding reflected evidence that value and small-caps outperform their growth and large-cap counterparts, and that value stocks outperform growth stocks.

This was the beginning of the formal understanding of the different factors that influence a portfolio’s returns. 

Before factor investing, there was just market risk.

Academics understood that different stocks had a different level of risk based on their volatility compared to the broad market. So the risk profile of an equity portfolio of volatile stocks like Tesla (TSLA) and DoorDash (DASH) was viewed differently than a portfolio of boring stable stocks like American Electric Power Company (AEP) and Procter & Gamble (PG).

However, there was a missing piece.

It wasn’t just the market driving the returns. There were hidden variables contributing to returns. They found that stocks with high earnings growth like Texas Instruments (TXN) back in the 1960s had different return profiles from a stable utility company. 

Factor investing is in a way an evolution of passively investing in index funds.

Many take the view that passive investing is the only way. Not only does it take little time, but stock picking and amatuer portfolio construction is a questionable use of time because of the lack of evidence for long-term outperformance, even by professionals. 

However, vanilla index investing is pretty naive. You put money into every company in the index, without regard for its valuation, scandal, fraud, ethics, or the future of its industry. 

So factor investing, as we’ve mentioned, bridges that gap a bit. 

Bottom Line

Factor investing is a welcome extension to passive investing.

It at least takes a stand on something (factor choice), as opposed to the “markets are completely random and unpredictable, except for 8% long-term compounded returns in US equities” philosophy espoused by proponents of index investing. 

Active investors can also benefit from utilizing factors in their screening process, to help them stack more edges on top of each other.