I have cheekily (some may say unoriginally) adapted the title of a new book by Kenan Malik for the title of this post. Unlike Malik's book, this is by no means a treatise on an ethical approach to investing, but rather a collection of thoughts that will continue to be refined through experience and discourse. As Malik says in his introduction, "In the modern world, morality is inseparable from choice." Earlier this week, I finished Kurt Eichenwald's excellent Conspiracy of Fools, which narrates the rise and fall of Enron. Mercifully, scandals on the scale of Enron happen infrequently, but I was struck by how many people were complicit in its collapse through indifference to detail, fears for job security and subservience to presumed expertise (as opposed to those driven by outright greed & intent to defraud).
The world of investing, as we know from the likes of Bernie Madoff, is equally fraught with such moral decisions. More subtly, investors make implicit ethical choices by investing in companies or asset classes, or even by settling on different investing strategies. (If this sounds impossibly sanctimonious, I wish I had some folksy, homespun Buffet-isms to help, but they would probably sound pretty ridiculous coming from someone from Singapore). Bodies like the CFA Institute attempt to sketch out guidelines for financial professionals' "fiduciary duties", but these can never cover the complex interaction of real-world investors and clients. Fiduciary duty can only be described vaguely as "doing what's right for one's client". I list some examples below of possible areas of ethical conflict for those engaged in the purchase of securities or allocation to managers and strategies:
1) Is it ethical to invest a new dollar for a client if you believe a market is overvalued? Inflows from clients (particularly retail) are notoriously pro-cyclical, which suggests that you are very likely to be receiving new capital late in the game when valuations are stretched. Some PMs seem to take the view that investors have given them a mandate, and that they should then meet that mandate by investing in ideas that can outperform a benchmark, thereby achieving relative, if not absolute outperformance. Their clients, they argue, are not paying them to hold cash. I, on the other hand, think there are plenty of times when it's more appropriate to hold cash, and consider it another asset class. I understand well that the pressures of running a business often compel investors (particularly long-only funds) to be fully invested at all times, but this strategy seems doomed to the occasional (and possibly fatal) blow-up.
2) The recent decision by Stanford University's endowment to divest from coal-related investments has renewed (no pun intended) the debate on socially responsible investing. The investor's role is obviously to make the highest return possible for his client within a socially acceptable framework of risks and care for society and other stakeholders, but delineating that framework is tricky. Stanford has reportedly kept its stakes in oil & gas companies because of a lack of alternatives for those fuels. A cynic might plausibly suggest that given the growing prospects of natural gas and renewables, the likelihood of explicit or implicit carbon taxes in the future and the poor returns on coal-related equities, Stanford has simply decided to take its lumps on its coal holdings (ok, I meant that one). Arguably, a socially motivated owner could do more good by pushing his company to engage with regulators more keenly, rather than merely selling his stake.
3) This one might be the most controversial of the three. I've been listening to a lot of Michael Covel's podcasts lately on trend-following strategies (the longer interviews often feature interesting guests; the shorter ones seem less worthwhile). I recognize the potential for profitable trend-following/momentum strategies (right on cue, AQR has contributed its intellectual heft in defense of momentum investing), not to mention other technical strategies as laid out for popular consumption here by Andrew Lo and Jasmina Hasanhodzic. Mind you, an investor doesn't have to have an exclusively technical framework to be a momentum investor - as George Soros famously said, "When I see a bubble forming I rush in to buy, adding fuel to the fire." Yet one of the supposed benefits of a market is that it generates prices, which in turn provide information about the allocation of resources. I've seen it said that Soros used to say of his speculating, "I shouldn't be allowed to do what I do, but I'll do it as long as I'm allowed." That seems an amoral escape route, and one I suspect Soros himself has largely abjured in his later incarnation as global statesman. One can often make a good deal of money pushing up the price of an asset from fair value to overvalued levels before offloading to an unsuspecting patsy, but that hardly seems like a socially defensible form of investing, philosophically indistinct to me from other forms of legal but unethical business practices. But before I sound like I'm on my high horse and ready to break into canter, let me say that this somewhat ideological notion of contributing information to the market can be taken to extremes. Those dogmatically opposed to market exuberance would have been shorting Internet stocks in early 1999 and eventually cast in the sea of bankrupt investors in a shroud of ideological purity. Logotherapy is best saved for the therapist's couch, and shouldn't be bankrolled by one's clients. I'm sure there are some Herbalife investors out there who agree on that count. All told, it can be difficult discern whether and to what extent an investor owes a duty to society as a whole.
As I said, this is by no means an exhaustive survey of possible ground for ethical dilemmas in investing, but a recognition that these quandaries exist. I look forward to comments.
Sunday, May 18, 2014
Tuesday, May 6, 2014
Risk: Its Wildness Lies In Wait
G.K. Chesterton wrote that "[life] is a trap for logicians. It looks just a little more mathematical and regular than it is; its exactitude is obvious, but its inexactitude is hidden; its wildness lies in wait." I'm often reminded of this when I hear sophisticated investors describe their risk management processes. For many investors, particularly if they are institutions or cater to institutions, it seems to be a prerequisite that a rigorous risk management system is by definition highly quantitative. There are three possibilities where the use of these models is concerned:
(1) Their risk models actually drive portfolio construction.
(2) Their risk models are presented to investors to give the veneer of rigour, but are basically ignored.
(3) Risk models are used to augment commonsense approaches, but are not the final arbiter of portfolio construction.
I suspect (2) and (3) are significantly more common than (1). While (2) is unethical, it may have the benefit of shielding investors from blind submission to a model. The version of risk (i.e. volatility) taught in introductory investments textbooks can be a dangerous tool. It's particularly problematic when investors don't understand the math and statistics that underlie these quantitative risk models, and are therefore unable to fully grasp their limitations. For example, it seems like a lot of people are willing to say, "Yes, we understand that asset prices don't follow a normal distribution, but let's use it as a tool anyway." Obviously, one doesn't need to be an automotive engineer in order to drive a car, but I think being unclear about the limitations of one's vehicle creates the need for humility, and caution.
The quintessential definition of risk comes from Frank Knight in Uncertainty and Profit. "The practical difference between the two categories, risk and uncertainty, is that in the former the distribution of the outcome in a group of instances is known (either through calculation a priori or from statistics), while in the case of uncertainty this is not true, the reason being in general that it is impossible to form a group of instances, because the situation dealt with is in a high degree unique."
Critics like Taleb waste no time in attacking Knight's classification. Taleb writes, "Had [Knight] taken economic or financial risks he would have realized that these "computable" risks are largely absent from real life! They are laboratory contraptions!" Indeed, those who take Knightian risk to excessive lengths (and I don't think Knight himself intended this) are guilty of reifying risk. Berger & Luckmann, in their classic The Social Construction of Reality describe reification as "the apprehension of the products of human acitvity as if they were something else than human products - such as facts as nature, results of cosmic laws, or manifestations of divine will. Reification implies that man is capable of forgetting his own authorship of the human world... The reified world is, by definition, a dehumanized world." This is how simplistic models treat risk - as historical volatility which is indicative of future volatility because of some inherent feature, rather than as the product of economic fundamentals and economic agent action.
One reason this thinking is dangerous is because of what economists have termed endogenous risk. This is just a fancy phrase for something that other social scientists are well aware of. For example, the sociologist Kathleen Tierney notes that, "Risks associated with social and physical systems are not inherent in those systems, nor are they fixed; rather they are the outcome of interactions among those social and physical units, social structure, and human (usually organizational) decisions." Translating this into economics jargon, Danielsson and Shin define endogenous risk as "the risk from shocks that are generated and amplified within the system." Woody Brock cautions that, "In episodes of market turmoil, the relevant endogenous risks have probability distributions that cannot be known. This, in turn, means that those "market risks" we prattle on about cannot be properly assessed and thus cannot be correctly priced and thus cannot be optimally "managed" by individuals or institutions - despite widespread beliefs by today's risk managers that they can. Ironically, just when optimal risk assessment and risk management tend to be most needed - in periods of crisis - we learn that they cannot exist." No doubt there are very clever folks out there with complicated models that can simulate the effects of the economy and financial markets as complex adaptive systems (the Danielsson and Shin paper suggests competitive equilibrium and game theoretic models), but since I don't understand their workings, I have no way of commenting whether these models will actually work for investors.
The backward-looking nature of many of these models is also widely recognized, but considered by many to be a necessary evil. But it is worth considering, for example, whether low historical correlation between certain assets will hold as large institutional investors become ever more creative in allocating funds.
I'm not suggesting that we should give up on thinking about risk, merely that quantifying it may not be helpful for everyone. But I also reject the notion of risk as the "permanent loss of capital". In a terrific article on his Top 10 Peeves, AQR's Cliff Asness very effectively defends the use of volatility in an investing framework. He clarifies first, "Volatility isn't how much the security is likely to move; it's how much it's likely to move versus the forecast of expected return." More importantly, he explains, "Risk is the chance you are wrong. Saying that your risk control is to buy cheap stocks and hold them... is another way of saying that your risk control is not being wrong. That's nice work if you can get it. Trying not to be wrong is great and something we all strive for, but it's not risk control. Risk control is limiting how bad it could be if you are wrong."
That's a great description of risk management, and I appreciate the fact that Asness is able to convey it in straightforward language. Highly quantitative risk models are not appropriate for many investors, but that doesn't mean they need to eschew risk management altogether, or feel insecure about the lack of precision in their attempts. As Danielsson and Shin note, "an effective risk manager should be able to make an intelligent distinction between those cases where those cases where the standard "roulette wheel" approach view of uncertainty is sufficient, and to distinguish those cases from instances where endogeneity of risk is important. Common sense and a feel for the underlying pressures dormant in a market are essential complements to any quantitative risk management tool that merely looks back at the recent past." In a future post, I'll attempt to lay out a commonsense approach to thinking about risk and its management.
(1) Their risk models actually drive portfolio construction.
(2) Their risk models are presented to investors to give the veneer of rigour, but are basically ignored.
(3) Risk models are used to augment commonsense approaches, but are not the final arbiter of portfolio construction.
I suspect (2) and (3) are significantly more common than (1). While (2) is unethical, it may have the benefit of shielding investors from blind submission to a model. The version of risk (i.e. volatility) taught in introductory investments textbooks can be a dangerous tool. It's particularly problematic when investors don't understand the math and statistics that underlie these quantitative risk models, and are therefore unable to fully grasp their limitations. For example, it seems like a lot of people are willing to say, "Yes, we understand that asset prices don't follow a normal distribution, but let's use it as a tool anyway." Obviously, one doesn't need to be an automotive engineer in order to drive a car, but I think being unclear about the limitations of one's vehicle creates the need for humility, and caution.
The quintessential definition of risk comes from Frank Knight in Uncertainty and Profit. "The practical difference between the two categories, risk and uncertainty, is that in the former the distribution of the outcome in a group of instances is known (either through calculation a priori or from statistics), while in the case of uncertainty this is not true, the reason being in general that it is impossible to form a group of instances, because the situation dealt with is in a high degree unique."
Critics like Taleb waste no time in attacking Knight's classification. Taleb writes, "Had [Knight] taken economic or financial risks he would have realized that these "computable" risks are largely absent from real life! They are laboratory contraptions!" Indeed, those who take Knightian risk to excessive lengths (and I don't think Knight himself intended this) are guilty of reifying risk. Berger & Luckmann, in their classic The Social Construction of Reality describe reification as "the apprehension of the products of human acitvity as if they were something else than human products - such as facts as nature, results of cosmic laws, or manifestations of divine will. Reification implies that man is capable of forgetting his own authorship of the human world... The reified world is, by definition, a dehumanized world." This is how simplistic models treat risk - as historical volatility which is indicative of future volatility because of some inherent feature, rather than as the product of economic fundamentals and economic agent action.
One reason this thinking is dangerous is because of what economists have termed endogenous risk. This is just a fancy phrase for something that other social scientists are well aware of. For example, the sociologist Kathleen Tierney notes that, "Risks associated with social and physical systems are not inherent in those systems, nor are they fixed; rather they are the outcome of interactions among those social and physical units, social structure, and human (usually organizational) decisions." Translating this into economics jargon, Danielsson and Shin define endogenous risk as "the risk from shocks that are generated and amplified within the system." Woody Brock cautions that, "In episodes of market turmoil, the relevant endogenous risks have probability distributions that cannot be known. This, in turn, means that those "market risks" we prattle on about cannot be properly assessed and thus cannot be correctly priced and thus cannot be optimally "managed" by individuals or institutions - despite widespread beliefs by today's risk managers that they can. Ironically, just when optimal risk assessment and risk management tend to be most needed - in periods of crisis - we learn that they cannot exist." No doubt there are very clever folks out there with complicated models that can simulate the effects of the economy and financial markets as complex adaptive systems (the Danielsson and Shin paper suggests competitive equilibrium and game theoretic models), but since I don't understand their workings, I have no way of commenting whether these models will actually work for investors.
The backward-looking nature of many of these models is also widely recognized, but considered by many to be a necessary evil. But it is worth considering, for example, whether low historical correlation between certain assets will hold as large institutional investors become ever more creative in allocating funds.
I'm not suggesting that we should give up on thinking about risk, merely that quantifying it may not be helpful for everyone. But I also reject the notion of risk as the "permanent loss of capital". In a terrific article on his Top 10 Peeves, AQR's Cliff Asness very effectively defends the use of volatility in an investing framework. He clarifies first, "Volatility isn't how much the security is likely to move; it's how much it's likely to move versus the forecast of expected return." More importantly, he explains, "Risk is the chance you are wrong. Saying that your risk control is to buy cheap stocks and hold them... is another way of saying that your risk control is not being wrong. That's nice work if you can get it. Trying not to be wrong is great and something we all strive for, but it's not risk control. Risk control is limiting how bad it could be if you are wrong."
That's a great description of risk management, and I appreciate the fact that Asness is able to convey it in straightforward language. Highly quantitative risk models are not appropriate for many investors, but that doesn't mean they need to eschew risk management altogether, or feel insecure about the lack of precision in their attempts. As Danielsson and Shin note, "an effective risk manager should be able to make an intelligent distinction between those cases where those cases where the standard "roulette wheel" approach view of uncertainty is sufficient, and to distinguish those cases from instances where endogeneity of risk is important. Common sense and a feel for the underlying pressures dormant in a market are essential complements to any quantitative risk management tool that merely looks back at the recent past." In a future post, I'll attempt to lay out a commonsense approach to thinking about risk and its management.
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