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Distress Testing The Efficient Frontier

Click to enlarge Many historically inclined residents of White Plains, New York can recount the legend of Sleepy Hollow and what inspired it. The day was October 31, 1776, and our young Revolution was in the throes of a heated battle. One this bloody All Hallows Eve, so stirred by his witnessing of a horrific incident on the Merrit Hill battlefield was American General William Heath that he dramatically recorded the horror of it in his journal as such: “A shot from the American cannon at this place took off the head of a Hessian artillery-man. They also left one of the artillery horses dead on the field. What other loss they sustained was not known.” It was the general’s vivid recollection of this scene that was to be the inspiration for author Washington Irving’s penning of his classic ghostly retelling of Heath’s journal entry, America’s version of a common folk tale dating back to Celtic times when for the first time the Headless Horseman set out on his eerie ride. Today, investors may find themselves wondering just what financial spirits have already been unleashed to darken the legacy of the Federal Reserve’s current head. They know what lingers to ominously shadow two of her notable predecessors. Alan Greenspan will forever be disturbed by the ghost of irrational exuberance, and his successor Ben Bernanke by the vestiges of subprime being “contained.” Given the state of the financial markets today, odds are Janet Yellen will be perennially preoccupied with the death of the efficient frontier. In a perfect world, as we were schooled in Portfolio Management 101, investors maximize their return while minimizing their risk. To accomplish this, we’ve long relied on the work of Harry Markowitz who, in 1952, developed a system to identify the most efficient portfolio allocation. Using the expected returns and risks of individual asset classes, and the covariance of each class with its portfolio brethren, a frontier of possibilities is conceived. Where to settle on this frontier is wholly contingent on a given investor’s unique risk appetite. And so it went – in yesteryear’s perfect world. Unfortunately, the Fed’s fabricating of a different kind of perfect world has all but rendered impotent the efficacy of the efficient frontier. There are countless ways to illustrate this regrettable development, one of which can be viewed through the prism of volatility. Investors are now so enamored of the good old days, when assets traded in volatile fashion based on their individual risk characteristics that the “VIX” has become a household name. In actuality, it is as it appears in its all-cap glory – a ticker symbol for the Chicago Board of Options Exchange Volatility Index. What the VIX reflects is the market’s forecast for how bumpy things might, or might not, get over the next 30 days. As is stands, at about 13, the VIX is sitting on its 2016 lows which are on par with where it was in August following the Chinese devaluation scare. But it has not been uncommon in market history for the VIX to dip below 10 into the single digits, as it did in late 1993. It again broke below 10, but with much more fanfare, in 2007 ahead of a vicious bear market that ravaged investors in all asset classes. Writing up to 16 markets briefs per year for nearly a decade inside the Fed required no small amount of title-writing technique. One of the most memorable of these immortalized in early 2013 was “Fifty Shades of Glaze,” which touched on the very subject of investor complacency using the VIX as evidence. The Wall Street Journal reported on March 11 of that year that investors were “worry free” in light of the VIX falling below 12, a number not seen since 2007. The hissy fit that markets pitched a few months later following the Fed’s threats to taper open market purchases served to send the VIX upwards. But things have since settled down, convinced as markets are that lower for longer is the newest ‘new normal.’ In a seemingly comatose state, the VIX has breached 15 on the downside twice as often since 2013 as it has on average since 2005. “I’ve been making the argument since 2010 that heavy-handed central bank policy is destroying traditional relationships,” said Arbor Research President Jim Bianco, who went on to add “stock picking is a dead art form.” By all accounts, Bianco’s assertion is spot on – the death of stock picking has not been exaggerated. It’s no secret that indexing is all the rage; index-tracking funds now account for a third of all stock and bond mutual fund and exchange-trades fund assets under management. The problem is that the most popular index funds have distorted valuations precisely because passive investing has become so popular. Consider the biggest index on the block, the S&P 500. Now break it down into its 500 corporate components. Some are presumably winners and some not so much. But every time an investor plows more money into an S&P 500 index fund, winners and losers are purchased as if their merits are interchangeable. The proverbial rising tide lifts all boats – yachts and dinghies alike. If that sounds like a risky proposition, that’s because it is. Not only are stocks at their most overvalued levels of the current cycle, index funds are even more overvalued, and increasingly so, the farther the rally runs. As Bianco explained, “In today’s highly correlated world, company specifics take a back seat to macro considerations. All that matters is risk-on and/or risk-off. Unfortunately, this makes the capital allocation process inefficient.” The question is, what’s a rational, and dare say, prudent investor to do? In one word – suffer. Pension funds continue to fall all over one another as they jettison their hedge fund exposure; that of New York City was the latest. It’s not that hedge fund performance has been acceptable; quite the opposite. But ponder for a moment the notion that pensions no longer need to hedge their portfolios. Is the world truly foolproof? Of course, hedge funds are not alone in being herded to the Gulag as they are handed down their Siberian sentences. All manner of active managers have underperformed their benchmarks and suffered backlashing outflows. They’ve just come through their worst quarterly performance in the nearly 20 years records have been tracked. And so the exodus from active managers continues while investors maintain their dysfunctional love affairs with passive, albeit, aggressive investing. When will this all end? It’s hard to say. Bianco contends that it’s not as simple as what central banks are doing – they’ve abetted economic stimulus efforts before. Remember the New Deal? What’s new today is the size and scope of the intervention. How will it end? We actually have an idea. Passive bond funds “enabled the borrowing binge by U.S. oil and gas companies,” as reported by Bloomberg’s Lisa Abramowitz. It was something of a vicious process that started with – surprise, surprise – zero interest rates compelling investors to reach for yield. Enter risky oil and gas companies whose bonds sported multiples of, well, zero. It all started out innocently enough in 2008, with these issuers having some $70 billion in outstanding bonds. But every time they floated a new issue to hungry managers, their weight in the index grew proportionately. In the end, outstanding bonds for this cohort rose to $234 billion. “Their debt became a bigger proportion of benchmark indexes that passive strategies used as road maps for what to buy,” Abramowitz wrote. “Leverage begot leverage begot leverage.” Since June 2014, some $65 billion of this junk-rated debt has been vaporized into a default vacuum. Yes, passive investing involves lower fees. But it can also suffer as indiscriminate buying can just as swiftly become equally indiscriminate selling. Such is the effective blind trust index investors have put in central bankers to never allow the rally to die. “The actions of people like Janet Yellen or Mario Draghi matter far more than any specific fundamental of a company,” Bianco warned. “It’s as if every S&P 500 company has the same Chairman of the Board that only knows one strategy, resulting in a high degree of correlation between seemingly unrelated companies.” Nodding to this dilemma, several years ago, the CFA Society raised a white flag on the efficient frontier in a Financial Times article. Any and all applicants were welcome to suggest a new order, a new way for investors to safely design portfolios to comply with their individual risk tolerance. Just think of the inherent quandary facing the poor folks who run insurance companies. These firms have a fiduciary duty to own at least some risk-free assets. That’s kind of hard to do when yields on these assets are scraping the zero bound, or worse, are negative as is the case with some $7 trillion in bonds around the globe. “Investors have traditionally been able to build balanced portfolios with the inputs of risky and risk-free assets,” said one veteran pension and endowment advisor. “Now that risk-free assets sport negative yields in many countries, to earn any return at all, you have to take undue risk. This breaks the back of the whole equation that feeds the efficient frontier.” A while back, Yellen warned investors of the potential pitfalls of owning high yield bonds. She was no doubt studying data that showed mom & pop ownership of these high octane assets was at a record high. Many onlookers balked at the head of a central bank wading into the wide world of investment advice. But perhaps it’s simply a case of recognizing one’s legacy well in advance. Small investors today have record exposure to passive investing. If Yellen fully grasps what’s to come, she’s no doubt preemptively struck and tormented by the future ghost of rabid animal spirits. “It’s like giving a teenage daughter a Ferrari and hoping she won’t speed,” the advisor added. “If central banks keep price discovery in shackles indefinitely, Markowitz will have to return his Nobel prize.” Let’s hope not. If that’s the case, and the efficient frontier never regains its rightful place in the investing arena, we will find ourselves looking back with less than wonderment as the hedgeless horseman gallops away with our hard earned savings.

The Confounding Bias For Investment Complexity

“Simplicity is a great virtue but it requires hard work to achieve it and education to appreciate it. And to make matters worse: complexity sells better.” – Edsger W. Dijkstra 1 Our tenure in the investment business has made us keenly aware of a profound investor bias toward complexity. In this article, we examine the reasons for the bias, which we believe are behavioral in nature. One reason is the rationalization by asset managers that to charge higher fees requires offering more complex strategies. A similar line of reasoning may also influence those who recommend managers: consultants and advisors. A second reason for the bias is the rationalization by investors that a complicated strategy is necessary to beat the market. Each explanation has implications-biased toward the negative-for an investor’s long-term performance. Complexity Can Confound Performance In contrast to the overwhelming pressure from all sides in advancing complexity, our experience, as well as our research and that of others, supports the virtues of a simple approach. For example, in 2009, DeMiguel, Garlappi, and Uppal demonstrated that numerically optimized portfolios using various expected return models generally perform no better than a simple equal-weighted approach. An example of our research in this area, the article “A Survey of Alternative Equity Index Strategies” by Chow et al. (2011), is an analysis of the most popular smart beta strategies. We found that simple, low-turnover and complex, high-turnover strategies all work roughly the same on a gross-of-fee basis, suggesting on a net-of-fee basis the simple, low-turnover strategies might have an advantage. Looking beyond the story telling that characterizes various investment philosophies, the long-term return drivers of many complex smart beta strategies are tilts toward well-known factor/style exposures, such as value, size, and low volatility. Each exposure is a natural outcome of breaking the link between portfolio weighting and price, and of the requisite rebalancing. Indeed, little data or research supports one “best” way to construct an exposure (e.g., value or low volatility) that maximizes the factor premium capture. Complex constructions in the historical backtest appear to mostly guarantee higher turnover, higher management fees, and potentially worse out-of-sample returns. So, if complexity doesn’t naturally lead to outperformance, why do asset managers persist in offering increasingly complicated strategies to investors, and why do investors persist on investing in them? Allow John to tell an illustrative parable. John’s Fish Tale The oceans in which fish hide from fisherman are amazingly complex ecosystems. The circumstances leading to a successful day (or not) on the water are almost innumerable. The fish obviously have to be at the fishing spot. But that’s probably less than half the battle. A veritable mosaic of tides, currents, sunlight, moonlight the night before, available prey, time of day, tackle, and so on, influence the catch. With such a myriad of factors, it’s no small wonder that tens of thousands of fishing products jam their way into even the smallest of tackle shops. But, as an avid deep sea angler, I can attest to catching twice as many tuna with the simplest of lures than all of the rest combined. The lure? The innocuous-looking cedar plug pictured in Exhibit A . Simple? Yes! For crying out loud, it’s a piece of lead attached to an unpainted piece of wood with one lousy hook! It looks like an industrial part. Sexy and complex? Most certainly not. Imagine you get the itch to catch some tuna. Perhaps it’s your first foray into tuna fishing so you decide to delegate the task to an expert charter boat captain. But which one? You stroll along the dock and ask each captain how they catch tuna. The first presents a cedar plug, just like the one in Exhibit A, and tells you, “I go out to where I see signs of fish and then I drag four of these lures behind the boat at a steady speed until I catch some. Then I keep doing it until it’s time to head in.” The second captain displays a dozen tackle drawers filled with lures resembling those shown in Exhibit B and proclaims, “Tuna are very elusive. I have perfected a system over many years that optimizes my lure selection among 60 lures, five sunlight conditions, seven moon phases, and six different tidal stages. I troll, adjusting my speed in five-minute intervals, based again on very extensive testing.” You hate long boat rides, but are starving for fresh sashimi. Which captain would you choose? Most sashimi lovers would pick the second captain. The ocean is big, and multiple factors influence the tuna catch. It seems like the higher-calibrated approach would be the way to go. But I can tell you (admittedly anecdotally, as I’m still waiting for Research Affiliates to approve my request for a more exhaustive scientific survey!) that it would probably yield a lower catch. Investors’ Preference for Complexity Complexity likewise appeals to investors because the markets that drive securities prices, like the teeming and mysterious ocean, are deep and complex. It only stands to reason (right?) that a sophisticated strategy is a requirement for mastering and benefiting from the intricate web of financial markets and asset classes. The globally integrated investment markets and economies are anything but simple, so it would not at first appear that a simple strategy could carry the day. The belief that simple relationships exist is absolutely counterintuitive to most casual-and sometimes, not so casual-market observers. Persuading an investor that a complicated strategy-often derived through data mining (i.e., back testing historical data until it produces what can be viewed as a signal)-is unlikely to perform as expected, can be a real challenge. The air of scientific authority exuded by PhDs who scribble differential calculus equations as fast as Charles Schultz drew Peanuts comic strips gives just that much more “credibility” to black box approaches. And agents compound the issue. Advisors or consultants hired to help investors make sense of the noise in the market and to find the skilled managers are also incented by the complex. Charging a respectable fee for a manager selection process that puts the client into a simple, straightforward strategy is not so easily justified to the client. The very natural, economic, and rational response to this conundrum is to recommend (in the case of advisors) or to offer (in the case of managers) the more complex strategies. Asset managers certainly find it easier to charge a higher fee for a complex strategy (i.e., flashier lures with molded plastic and psychedelic paints) than for a simple strategy (i.e., unpainted cedar plugs). Simplicity vs. Complexity: Why Does It Matter? The point we wish to make is not that simple strategies always perform on par or better than the complex ones. Our point is that complexity creates a problem for investors, which is unfortunately largely self-induced: complexity encourages performance chasing. We can better understand why this is true if we apply Daniel Kahneman’s construct of System 1 and System 2 thinking, as described in his book Thinking, Fast and Slow (2011). System 1 thinking is described as automatic, emotional, and passive, whereas System 2 thinking is effortful, deliberate, and active. When presented with a complicated investment strategy, an investor engages first in System 1 thinking, which triggers an immediate response such as “I don’t understand the strategy. Clearly I’m not as smart as this asset manager.” System 2 thinking then takes over, and the investor’s response transitions to “Because this asset manager is so smart, her strategy must outperform. I think I’d like to invest with this asset manager.” The investor then feels safe and comfortable in making a rational delegation decision. At the end of the day, the acceptance of complexity is related to calming the investor’s ego-at least, temporarily. This thinking works in reverse, however, if the asset manager fails to perform as expected. Neuroscientists, such as Knutson and Peterson (2004), have demonstrated that the anticipation of receiving money triggers a dopamine reward in the brain. Conversely, the anticipation of losing money removes that pleasurable experience. When this happens, the System 1 response is “Yikes! I need to fire this manager so I can stop feeling so bad.” Then the System 2 response kicks in with the rationalization, “I didn’t make the decisions that created the underperformance, so I’m not to blame.” Because the investor doesn’t “own” making the “bad” decisions, it is easier to end the relationship. Following this line of thinking, investors are liable to sell a complicated, poorly understood strategy with little provocation as soon as performance takes a nose dive. The long-term result is apt to be especially disappointing performance if the investor becomes ensnared in a whipsaw pattern of buying and selling at all the wrong times. Our research (Hsu, Myers, and Whitby [2015]) shows that the frequent hiring and firing of managers based on short-term performance is the primary cause of investor underperformance. Our findings are valid even when investors hire skilled managers. Although never a good idea for investors to make buy and sell decisions based on short-term performance, a poorly understood strategy can compound the harm. An example of how Kahneman’s System 1 and 2 thinking supports an investor’s choice of a simple behavioral factor strategy, let’s consider the following scenario. Upon first encountering the strategy, the investor’s System 1 thinking blurts, “This strategy is intuitive to me. I am a smart investment professional. This will work.” But soon his System 2 thinking chimes in, “I don’t need to pay a high fee for this. I just need a low-cost implementer of systematic strategies to execute on my chosen factor.” When the strategy fails to perform as expected, the investor’s System 1 reaction is, “I am not wrong. The market is wrong.” Then his System 2 thinking kicks in, reasoning, “I vetted the research behind this factor carefully. Short-term performance is noisy. This exposure will work well in the long run.” The investor chooses to hold his strategy. Investors in simple strategies generally trade in and out of their managers infrequently. Our research finds that these investors tend to achieve meaningfully better results versus their counterparts who actively turn over managers due to recent performance. Simplicity leads to better investor outcomes not because simplicity in and of itself produces better investment returns, but because a simple strategy forces investors to own their decisions and to be less likely to overreact to short-term noise. A Simple Choice We believe that making investors aware of the benefits of selecting a simple approach, strategy, or model is important. Unnecessary complexity is costly, not only directly (i.e., fees), but indirectly. Complexity can dampen investor understanding, which can lead to poor investment decision making so that an investor’s long-term financial goals are not achieved. As Steve Jobs said, “Some people think design means how it looks. But of course, if you dig deeper, it’s really how it works” (Wolf, 1996). If a simple design works, ample evidence suggests that the investor benefits by choosing simplicity. Endnote 1. Edsger W. Dijkstra was a Dutch computer scientist and winner of the Turing Prize in 1972 for fundamental contributions to developing programming languages. References Chow, Tzee Mann, Jason Hsu, Vitali Kalesnik, and Bryce Little. 2011. ” A Survey of Alternative Equity Index Strategies .” Financial Analysts Journal , vol. 67, no. 5 (September/October):37-57. DeMiguel, Victor, Lorenzo Garlappi, and Raman Uppal. 2009. “Optimal Versus Naïve Diversification: How Inefficient Is the 1/N Portfolio Strategy?” Review of Financial Studies , vol. 22, no. 5 (May):1915-1953. Hsu, Jason, Brett Myers, and Brian Whitby. Forthcoming 2016. ” Timing Poorly: A Guide to Generating Poor Returns While Investing in Successful Strategies .” Journal of Portfolio Management , vol. 42, no. 2 (Winter). Kahneman, Daniel. 2011. Thinking, Fast and Slow . New York: Farrar, Straus and Giroux. Knutson, Brian, and Richard Peterson. 2005. “Neurally Reconstructing Expected Utility.” Games and Economic Behavior , vol. 52, no. 2 (August):305-315. Wolf, Gary. 1996. ” Steve Jobs: The Next Insanely Great Thing .” Wired Magazine (February)