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Summary

  • When a manager outperforms, it implies that other investors have underperformed.
  • In understanding an investment process, we believe it is critical to understand the source of this outperformance to determine whether it is sustainable or not.
  • We believe there are two key sources of outperformance: exploiting investor behavior and being compensated for bearing risk.
  • By understanding which source a strategy hopes to exploit, we can gain key insights into how we should expect the strategy to perform in the future.

Over the years, we’ve seen countless investment product decks.  The consistent theme across them?  Whatever gets put in front of us always seems to have done superbly well, particularly in recent periods.

While we’d argue that recent outperformance is a great reason to not allocate, the decks always seem to be missing one thing: a rational discussion about where that outperformance came from and why we should expect it to continue.

And we don’t mean those upside-down pyramids that tell us how the manager “culls” their universe into a portfolio.

What we mean is a thoughtful discussion about the true source of the premium.  Consider that for one investor to outperform, another must underperform.

So what is often missing in the product dialogue is exactly where the outperformance is coming from.  Who are we taking it from?  Why do we think we can consistently take it from them?  For the strategy to work, what do we need other investors to keep doing or not doing?

By understanding the source of the outperformance, we can set better expectations for the consistency of the outperformance, when it will work, and, perhaps most importantly, when it won’t.

At Newfound, we put sources of outperformance in two categories.

 

Exploiting Inefficient Behavior

Conventional financial theory tells us that market participants are rational actors.

Behavioral finance tells us otherwise, that investors fall prey to a variety of biases that make them act irrationally.

For example, the low-beta anomaly appears to stem from several behavioral sources including an aversion to leverage and a preference for lotteries.  What do these mean?  Aversion to leverage means that investors typically shy away from borrowing money to invest, instead preferring to access implicit leverage through positions in more volatile securities.  The preference for lotteries means that investors tend to buy low priced, highly volatile stocks with the potential for huge returns, like lottery tickets.

Ultimately, this translates into more volatile stocks being overpriced relative to stocks with lower volatility, meaning that low volatility stocks often outperform on a risk-adjusted, and when levered on an absolute, basis.

We believe the behavioral source for this premium is one of the best arguments, especially considering that this same effect has been found in other asset classes (e.g. lower volatility bonds outperforming higher volatility bonds on a risk-adjusted basis) as well as across asset classes.

Investors seem to suffer from a number of behavioral biases that create other exploitable market anomalies.  For example, anchoring appears to cause investors to underreact herding causes them to overreact to new information.  Together, these biases create trends which can be exploited by momentum traders.

We believe that understanding what behaviors we are attempting to exploit is critical to gaining an understanding of how outperformance may ebb and flow – or outright disappear.

For example, on a recent panel, I was asked what I thought the greatest potential disruptor to active asset allocation was.  My answer was passive investing.  My reason was that if I am looking to create outperformance by exploiting the behavioral biases of other investors, if those investors throw in the towel and go passive, those behavioral biases would disappear.

On the other hand, why do we think these strategies are largely sustainable?  Call it human nature.  Going passive is hard because it means having the discipline to stay invested even in the face of gut-wrenching drawdowns.

However, it is worth pointing out that exploitable behavior is not necessarily irrational behavior.

For example, insurance companies and pension funds often buy debt at the far end of the yield curve, trying to match the duration of their liabilities.  As liability-driven investors, they create a persistent bid in this region of the curve that can create an exploitable mispricing relative to the short end.

Another example comes from institutions that are limited to buying only investment grade bonds by mandate.  When a bond falls from investment grade to below investment grade, they are forced to liquidate, regardless of value or outlook.  This forced liquidation can create a fire sale effect, driving the bond well below fair value.  Unconstrained investors can exploit this behavior by buying companies that have moved from investment grade to junk.  In fact, there has been a whole ETF strategy created around this concept: Market Vectors Fallen Angel High Yield Bond ETF (ANGL).

What all these examples have in common, however, is that investors must continue behaving in a certain manner for the outperformance to be sustainable.  Understanding when or why that behavior may not persist in the future can provide critical insights into performance expectations.

 

Being Compensated for Risk

It is likely that you pay for some sort of insurance in your life.  Maybe it is health insurance, or auto insurance, or some sort of catastrophic insurance like fire, flood, or tornado.

You’re overpaying for that insurance.

How do we know?  Simple: insurance companies aren’t running a charity.

Our second source of outperformance is being paid to bear risk, like an insurance company.

Consider a merger arbitrage strategy.  In a simple merger arbitrage approach, a portfolio manager systematically buys companies that have been announced as acquisition targets and shorts the companies that are intending to acquire them (at least in the case of stock-for-stock deals, exact mechanics will vary depending on deal structure).  Historically, this strategy has generated a return premium.

Why?  When a merger is announced, typically the price of the target’s stock jumps to a point below the acquisition price.  In an efficient market, this discounted price is closely related to the probability of the deal being completed.

Historically, prices for target stocks have jumped to a point below this fair value as those investors who held the acquired company pre-announcement sell in order to lock in their gains.

Why would an individual sell at a price below fair value?  From the investor’s perspective, they are likely sitting on a substantial gain and the marginal return benefit of holding out for the deal to be closed may not outweigh the risk of loss if the deal doesn’t close.

The investor is sitting on a highly idiosyncratic risk.

A manager running a merger arbitrage strategy can exploit this by offering to buy the stock at a slightly discounted price to the fair value.  Why would they take on the idiosyncratic risk?  A manager running this strategy is able to diversify away this idiosyncratic risk by doing a number of these deals over time.

In essence, the individual offloads their downside risk to the to the manager running the merger arbitrage strategy.  For this service, the manager collects a small premium (having acquired the stock below fair value) if the merger is completed.  If the merger falls though?  The manager is on the hook for the loss.

This is not unlike a homeowner paying to insure their house.  The homeowner has a highly idiosyncratic risk.  To offload this risk, they are willing to pay a premium.  The insurance company is willing to bear this risk, and collect the premium, because they can diversify the risk across a large number of policies.

One of the most popular investment approaches in this category is value investing.

The very definition of value investing is acquiring an asset at a price below its intrinsic value.  Typically, these are assets that are perceived as distressed by the broad market.  The asset trades at a discount to fair value because investors are eager to offload the risk of the asset price going to $0.

By buying this asset, a value investor acts like an insurance company.  If the risk materializes – whatever the risk is – and the asset becomes worthless, they are on the hook for the loss.  If it doesn’t, they collect the premium as the asset reverts back to fair value.

While there are ways to implement such a strategy that makes an investor look exactly like an insurance company (e.g. selling put options), a common theme for this type of strategy is that an asset is being acquired below fair value.  It is this discrepancy between asset price and fair value that is the premium the asset owner is paying to offload the risk to the insurer.

We believe that conceptualizing these approaches as being similar to running an insurance company provides a re-framing that can be insightful.  For example, if a manager is pitching a highly concentrated value stock portfolio, we can conceptualize it as a home insurance company with only a few policies.  If we were running such an insurance portfolio, we want to make sure that all the homes weren’t located in the same neighborhood or a single tornado, flood, or fire could wipe out our portfolio.  To justify taking that sort of concentration risk, we’d need to collect a huge premium (i.e. the assets are trading at a massive discount).

Strategies based on being paid for risk can be highly sustainable because investors are, historically, eager to pay to offload risk (arguably they often overpay, an exploitable behavioral bias).  However, these strategies can be difficult to stick with.

First, there is competition among insurers, which means that margins for bearing risk can be razor thin.  Once an asset starts trading at a discount, bids among insurers can drive it back closer to fair value.  For a strategy with this approach to be successful, a manager needs to recognize when the discount to fair value adequately compensates him for bearing the probability and magnitude of potential downside risk.

Furthermore, if a manager misprices the probability or magnitude of risk, they can be quickly put out of business.  As investors in risk-based strategies, we should make sure we have a deep understanding of the process the manager takes on to both price and manage the risks they bear.  At the end of the day, however, we should also consider the catastrophic risks; after all, insurance companies are not immune from going out of business themselves.

 

Conclusion

In evaluating active strategies, we believe it is critical that investors ask themselves what the source of potential outperformance is coming from.  Without identifying the source of outperformance, there is no way to thoughtfully determine whether or not the outperformance will continue going forward.  We believe there are two truly sustainable sources of outperformance: exploiting behavioral inefficiencies and being compensated to hold risk.

Nevertheless, we also believe that even the best strategies must underperform from time-to-time.  Similarly, even the worst strategies will occasionally outperform.  Understanding what behaviors we are exploiting or what risks we are being paid to hold is an important step to understanding when, how, or why outperformance may temporarily or permanently fail to materialize.

Corey is co-founder and Chief Investment Officer of Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Corey is responsible for portfolio management, investment research, strategy development, and communication of the firm's views to clients.

Prior to offering asset management services, Newfound licensed research from the quantitative investment models developed by Corey. At peak, this research helped steer the tactical allocation decisions for upwards of $10bn.

Corey is a frequent speaker on industry panels and contributes to ETF.com, ETF Trends, and Forbes.com’s Great Speculations blog. He was named a 2014 ETF All Star by ETF.com.

Corey holds a Master of Science in Computational Finance from Carnegie Mellon University and a Bachelor of Science in Computer Science, cum laude, from Cornell University.

You can connect with Corey on LinkedIn or Twitter.

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