Factor investing offers patient investors the opportunity for substantial improvement over vanilla total market equity indexes. But, it requires the investor to play the long game. While it’s a big advancement over a vanilla total market investing strategy, it’s not going to track the more familiar indexes.
Failure to understand what causes the tracking deviation causes behavior problems for many investors. If investors don’t understand what drives performance, or can’t stand to ever underperform widely published indexes (S&P 500, EAFE, Total US Market, or Total Foreign Market) they are likely to abandon a superior portfolio strategy at the first sign of perceived underperformance.
The Single Factor Model
Factor investing is a refinement of Bill Sharpe’s early theory (Capital Asset Pricing Model or CAP-M). Investors don’t like risk, so they demand an extra return above what they could get for a no-risk investment in return for enduring an irregular or uncertain result. He called the extra return for enduring market risk Beta. Beta would be proportional to risk as measured by the portfolio’s standard deviation. Thus higher risk portfolios were expected to have higher returns. So, total return was assumed to be the zero risk return plus Beta.
It turns out that Beta is huge, about 6% over the zero risk return. But it comes and goes in random spurts. It can be negative for quite some time. We can point to three periods of at least 13 years where it was cumulatively negative. That means during those long time periods, T-Bills would have performed better.
Investors are pretty used to markets being random. You don’t win every year, but cumulatively you have always won big if you stuck around. So, the single factor model works for investors that play the long game. It is certainly a valid strategy. And it has the huge advantage of being simple for investors to understand and measure.
Sharp’s single factor model assumed that investors only cared about a single factor, volatility (risk). It was a very nice theory and won him a Nobel Prize, but it wasn’t based on any empirical evidence and didn’t work as well as it should have. Clearly something else was going on.
A Four Factor Model
Factor investing refines and improves the single model strategy. But, it adds a little complexity. Because factor performance information is not widely published, it’s more difficult for investors to tease out the impact of factors from total portfolio performance.
The basic concept is very simple: within the broad market are sub sections which have historically outperformed. There is strong economic theory supporting outperformance going forward. These areas can be identified and portfolios then designed to capture the excess performance. Overweighting an existing diversified portfolio to capture this factor would be expected to add significant additional return over time.
Compelling research indicates that there are at least three additional factors that can explain market performance when combined with Beta. They offer the chance of better returns over time than the single factor model.
Size, value, and profitability enhance the explanatory power of market models and lead to potentially better returns over time. Simply put, over the long haul, small companies will outperform large, cheap stocks outperform expensive ones, and highly profitable companies outperform less profitable ones. Overweighting your portfolio in those area would have a positive impact on expected return. But, like Beta, they have their own risks.
In the short run any factor may either boost or drag performance. Performance will vary around the total market. We expect that this variance will be positive more often than not. Based on past history on an annual basis the factors would have added value roughly two thirds of the time. That probability goes up over longer periods. It’s a very good bet. But even loaded dice don’t win every toss, so be prepared for the certain periods of underperformance.
For all practical purposes each of the additional three factors are totally random and not correlated to the others. In real life that means that you may or may not “beat the market” in any particular time period by attempting to capture the performance enhancement. So, for instance, a small company portfolio may seriously lag the total market portfolio for years. Or, sometimes large growth companies will outperform small value companies. That uncertainty is just baked into the system.
Just as stocks often underperform the zero risk investment, any single factor may underperform the broad stock market. And while there is a diversification benefit, even tilting a portfolio to capture all three factors provides no assurance of outperforming the broad market in any particular time period. We simply cannot predict what days or years any or all factors might add value. Yet each factor has been gratifyingly positive over time.
Both the theory and empirical evidence (past history) in support for factor investing are compelling. Tilting a portfolio to capture these factors should have a positive impact over time.
Sorting the Wheat from the Chaff
There are a bewildering number of newly discovered factors, some of dubious validity, and some impossible to capture economically. Funds that capture a single factor or multi factor funds are sprouting like weeds. The trick is to separate valid factors from random noise in the data. There is no good reason to believe that stocks should follow women’s hem lines or which team wins the Super Bowl. Even if the data supports it when back tested, it’s still just random noise.
No Free Lunch
Factor investing is not a free lunch Neither is factor investing a quick fix.. It comes with its own set of risks. It’s a meaningful incremental improvement over previous investment theory that increases the odds of a successful investment experience.
You, our your advisor will need to sort your strategy out very carefully. But, the effort should be profitable.
To realize the benefits the investor must both understand and endure periods of underperformance. Patience pays. Be prepared to play the long game.