Factor-Based Investing

The CFA Women’s Network hosted a lively and vibrant event featuring Patricia Halper, CFA, partner and co-chief investment officer at Chicago Equity Partners. Halper spoke to a room full of engaged members on the topic of factor-based investing which coincides with the popular topic “Smart Beta” investing. The subject is more relevant than ever as investors question the worth of fundamental active stock-pickers in search of both better performance and lower expenses. As a brief introduction, Halper has been working at Chicago Equity Partners for over twenty years as both a member of the quantitative research team and a portfolio manager.  Prior to CEP, she worked at Paine Webber on the institutional futures sales desk. Halper holds a bachelor’s degree in mathematics from Loyola University Chicago, a master’s degree in financial mathematics from the University of Chicago, and is also a CFA charterholder. Currently at Chicago Equity Partners, Halper utilizes factor-based investing strategies to support the firm’s equity decision making processes.

Simply stated, a “factor” is a characteristic of a security that explains its investment return. Factor investing in its most simplistic form can be described by the traditional CAPM equation: E(r) = rf * B(Rp-rf) where beta represents the single factor. In examining how a factor can be used towards making investment decisions, the question an investor must then ask is twofold: “Is this factor a good predictor of future price movements?” and then secondly “Which side of the factor (high beta or low beta in this case) will outperform the index?” Expanding upon a tradition single-factor model, Fama and French introduced the three-factor model in the 1990s which included beta, size and value.  In the late 1990s, quality factors came into light such as balance sheet quality, earnings quality, and quality of the management team. Today, there are hundreds of factors that investment professionals analyze to explain investment returns. Bottom line: factor investing is a known proven strategy that has been around for many years.  If you get the direction of correlated factors correct, you will likely outperform your benchmark.

Some of the most common factors used today include:

  • Value:  Low price/earnings, low price/sales, low price/book value
  • Quality: Strong management team, high earnings quality with lack of one-time items, low balance sheet leverage
  • Momentum: Both price momentum and earnings momentum generally provide outsized returns.
  • Size:  Smaller companies have outperformed larger companies over a long period of time
  • Volatility: Less volatile stocks provide higher expected return over the long term.

There is a key asterisks to the factors noted above. High value, high quality, positive momentum, small market cap, and low volatility have all shown to be positive factors of price performance…  over a 20 YEAR period. Often times, clients don’t have the investment horizon (or patience) to stick with a strategy that doesn’t work over several years, or even more commonly over several quarters.  In fact, the opposite of what is true in the long term (20 years) can be true in the short term (several quarters to even years). The key to understanding which factor is the most relevant to excess return is to understand what cycle of the market we are in. Halper described three market cycles:

  • Expansion: Most often markets are in expansion mode as markets generally trend higher. Momentum factor outperforms the most in expansionary periods (5%+ excess returns) and tends to work because investors tend to chase winners.
  • Downturn: At the end of the expansion period, you see a shift to Low Volatility and High Quality names with strong balance sheets that provide the best excess returns. This period can be considered recessionary with negative GDP growth.
  • Rebound: Finally, the rebound period doesn’t last long between when the downturn ends and when the expansion cycle begins—typically 2-3 quarters.  During this short time period, Value outperforms best.

Taking our single-factor observations above one step further, there is empirical evidence that If you know how to combine multiple factors into a model, a multi-factor portfolio will outperform a single-factor portfolio with less risk. There is a cyclicality in any one factor  and the cyclicality of factors increased during the global financial crisis.  It is best as an investment manager to pick at least two factors to structure your portfolio. That being said, you have to use two factors that are moderately correlated, otherwise one factor will tell you to buy and another to sell and you will naturally be holding the indexed market.. or cash!  How you combine factors, how you weight them, and how you allocate each factor is the name of the game for outsized returns. It is also critical to highlight that another key to successful factor based investing is having high quality data. High quality data has both a wide breadth and a long time horizon and without high quality data, your model will give false signals into which assets to buy and sell.

The analysis of factor based investing begs the question how is it related to the popular term in the industry right now “Smart Beta” investing.  Smart Beta strategies have shown tremendous AUM growth largely due to a general dissatisfaction with traditional equity asset managers. Asset allocators ask of Smart Beta products, “Can you perform better than a traditional passive index at a rate that is cheaper than active equity managers?” To put figures around the growth, in 2008, there was $100mm invested in Smart Beta strategies. Today, there is over $1 Trillion, a ten-fold increase in the last 10 years.  The largest smart beta funds, largely run by Vanguard and Blackrock, trade based on growth and/or value, what is otherwise a very traditional style-based factor investing that has been around for 20 years. When you take a closer look under the hood, even though these products are called “Smart Beta”, it is really the same principles just repackaged with a sexier word for the times. It’s not quant analysis, and if the product is only focused on a single factor, it’s not multi-factor investing either. If the Smart Beta product is only using a single-factor approach, it is simply “Quant 101” that has been around for over 20 years. Multi-factor Smart Beta products are a very small portion of the market which undoubtedly will grow over time. Investors should note that if they plan on buying a smart beta product, be aware of the sector exposures, as some have very high sector exposures which can overwhelm your factor exposure if you are overinvested in an industry that has sector specific issues.

What does the next 10 years look like? What factors will outperform in this current market environment? The Fed is now raising interest rates and ending its 10-year quantitative easing program.  How will turmoil in foreign markets and currencies impact our domestic equity and bond markets here at home? Only time will tell, but what is clear is that factor-based investing should be in every investment manager’s tool chest as they evaluate market trends and the price movements of its underlying securities.

Smart Beta: Smoke and Mirrors or the Next Generation of Investing?

DSC_2604Smart Beta – is it a bad fad or here to stay?

On February 23, two panels set out to discuss that question at the University Club.

Moderator Ben Johnson, CFA, Director of Morningstar’s global ETF research kicked off the discussion with a brief introduction into Smart Beta.

Ben said that the strategies of smart beta don’t necessarily feel smart over the full cycle. Right now there are 539 Exchange Traded Products (ETPs) doing smart beta, with $424 billion in assets and ETPs represent just one wrapper of the strategy. 21% of all ETPs are in the US, and 20% of all total new asset flows are going into smart beta products. The size of smart beta means that it’s too big of a market to ignore. Similarly, in the increasingly crowded ETP space, over a quarter of new launches involves smart beta funds. “This has been an organic growth story,” Ben said. Ben introduced the first panel and asked them to level set the conversation by defining what smart beta means to them.

DSC_2601Craig Lazzara of S&P Dow Jones said he prefers the term “Factor Indices” over smart beta. He quoted Voltaire and said that the saying “The Holy Roman Empire is neither Holy, nor Roman, nor an Empire” applies to smart beta. He encouraged the audience to read William Sharpe’s The Arithmetic of Active Management, which concluded that the average active manager’s return will be less than the average passively managed dollar, a conclusion that helps support the smart beta premise. Craig’s definition of smart beta is simple: Indices that try to deliver returns (or a pattern of returns such as low beta, high volatility, etc) of a factor, not of a benchmark.

Craig went on to say that smart beta factor indices allow a user to “indicize” returns of an active management strategy. “Twenty or thirty years ago, you’d have to pay an active manager to get these kinds of returns,” Craig said. And now with smart beta products, you don’t.

Eugene Podkaminer of Callan Associates began his remarks by saying that he was skeptical about smart beta and thinks that the name smart beta is “stupid”. He said that there is a lot of confusion around smart beta, how strategies are packaged and sold and what is under the hood. Smart beta has been driven largely by retail investors, who are susceptible to return-chasing behavior and clever marketing, while institutional investors with longer time horizons haven’t been as involved. “When you open the hood of a smart beta investment, it’s a different story,” said Eugene, who said he is interested in smart beta from a risk factor allocation perspective.

One important question that needs to be asked of smart beta, according to Eugene is “are you confident that the returns from these factors will continue?”

Trey Heiskell of Blackrock said that smart beta is both old and new. Like Eugene, he also hates the term smart beta and prefers ‘factor-based investing’, which he believes to be a more accurate name. “There is a shift from alpha to smart beta happening right now,” Trey said. And much of its growth is due to the context of the market we are in, with retail investors dissatisfied with the recent underperformance of active managers and growing adoption of ETFs. These are some of the main factors driving the growth in smart beta.

Craig agreed with Trey about smart beta being both old and new, saying that “these strategies have been around for years, packaged differently”.

Once, Craig was asked “What is it that ETFs allow large institutional investors to do that they can’t already do?”

DSC_2612“Absolutely nothing,” he answered. But as a retail investor, now you can get the benefits of factor exposure you want cheaply and easily without dealing with an active manager.

Eugene gave an update on how Callan’s process has evolved and said that now they are very risk and diversification-focused, and when evaluating a potential investment, more interested in its covariance with other investments than its forecasted returns. You need to have a robust set of tools to determine what your factor exposures are, such as a risk model. Some advantages of smart beta ETFs are that they are liquid, transparent and cheap. He said that the question “Why am I paying so much for hedge funds,” will continue as risk factor-based investing grows in popularity. “Indexing and smart beta have chipped away at what we call alpha,” Eugene said.

Craig said that investors need to think about their investments not as a portfolio of stocks, but as a portfolio of attributes. He thinks investors need to consider how they might use smart beta to avoid or minimize paying active management fees.

Eugene stated that smart beta does have some problems. Just because the portfolio appears to perform well in the past, the returns won’t necessarily continue. “Backtests by definition look good,” Eugene said. Smart beta needs to be forward looking, it has to be ex-ante, he said. Investors are trying to build portfolios that work well in the future, and you need to forward-looking economic rationale for any investment you make, which also must apply to smart beta products. Smart beta puts the onus of complex portfolio management tasks on the individual, who now must answer “Why did I make that tilt” instead of asking that same question to a manager.

Trey responded that while an economic rationale is important, it is dangerous to be hyper-focused on short term performance of smart beta.

Craig noted that it is important to watch out for spurious correlation, giving an example of extensive data mining leading to a researcher to conclude that butter production in Bangladesh is a strong leading indicator of the S&P 500.

Trey said that just because it is smart beta, it doesn’t mean you’re excluded from doing your own due diligence.

Eugene posed a philosophical question and asked “Can all market participants do the same thing at the same time? And can everyone be in smart beta at the same time?” This isn’t possible. There has to be someone on the other end. We can’t all be in low volatility products. Why ought to these risk factors continue to deliver these kinds of returns? And how many factors truly exist? At Callan, they don’t believe that there are hundreds of investible factors, they look at about 10.

DSC_2605Trey said that better product definitions on smart beta from index providers are coming up. “Smart beta is the gateway drug to explicit risk factor investing,” said Trey.

Eugene said that smart beta is interesting like a bicycle is interesting, while risk factor investing is more like a race car. “Everyone hates fixed income benchmarks,” Eugene said, saying that that may lend itself well to a smart beta product.

Michael Hunstad said that Northern Trust has been doing factor based investing for 20 years and smart beta is definitely not new. “The hard part with smart beta is making a lot of decisions that were formerly made by your portfolio manager”, Michael said. Some of these decisions are “what factors do I choose?” There are many smart beta providers also, and there are some big considerations involved that clients need help and guidance with.

“Where does smart beta go in my portfolio,” is a very good question. It’s not exactly active, yet not totally passive either. The old way of deciding a manager allocation was by making a list, and allocating to the manager who performed best. This doesn’t work with smart beta, and the selection of products is tough. According to Michael, smart beta is two things:

1) A source of excess return
2) A risk paradigm

If smart beta risk factors are independent sources of return, then they are also independent sources of risk.

Mehmet Beyraktar counted himself among the many in the panel who dislikes the term smart beta, and said investors need to question how the products complement their existing portfolios, and the challenge of smart beta is how to integrate. He said that a big part of the investment process is obtaining the right tools to get transparency into smart beta investments and a means of calculating exposure to risk factors, such as a factor-based risk model. Not that much research is available into how risk factors and smart beta will perform is available just yet, he said.

Ben offered an exchange he heard between a Middle East-based client and an advisor, where the advisor asked how long the client’s time horizon was, and he responded “We measure in generations.” The client then asked “How often do you look at performance?” and the client said “quarterly”, a huge mismatch between the evaluation period and the investment horizon.

Michael told a story about an investor who thought he could use PMI to make a tactical call on the market. There certainly are leading indicators, but the hard part is determining when they will play out. He said that he doesn’t have much confidence in anyone’s ability to time cycles and market behavior. But multifactor products are the wave of the future in dealing with cyclicality. With smart beta, there is a concentration risk on one end of the allocation spectrum and a dilution risk on the other end. If you simply allocate equally among all the risk factors, you probably will end up with an investment that looks very similar to a cap-weighted benchmark.DSC_2610