In 2004 Alan Greenspan offered the following: "When confronted with uncertainty, especially Knightian uncertainty, human beings invariably attempt to disengage from medium to long-term commitments in favor of safety and liquidity." I stumbled upon this quote in an article by Ricardo J. Caballero and Arvind Krishnamurthy in the October 2008 issue of The Journal of Finance. Their article deals with the common flight to quality events that occurs during severe market jolts and the role that the lenders of last resort (LLR) typically have. My intent at bringing this up isn't to address their subject, although it's quite an interesting one and one that we will be addressing more formally at a later date, but rather to touch on this term "Knightian uncertainty."
If you're like me, it's one that you're not familiar with. It is derived from a book by Frank H. Knight (Risk, Uncertainty, and Profit) that was written in 1921. I was able to find a 1965 edition and haven't yet read it, though I intend to at least skim through to see what gems lie between its covers.
The term "Knightian uncertainty" wasn't coined by Knight (just as "Sharpe ratio" wasn't coined by Sharpe), but probably not by Greenspan, either. A "google search" brought me to the often times reliable Wikipedia site which informs us that Knight distinguished risk and uncertainty. It involves the presence of immeasurable risk. To further quote Wikipedia, "Knightian uncertainty is risk that is immeasurable, not possible to calculate."
The site specifically references the book and provides the following: “Uncertainty must be taken in a sense radically distinct from the familiar notion of Risk, from which it has never been properly separated.... The essential fact is that ‘risk’ means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far-reaching and crucial differences in the bearings of the phenomena depending on which of the two is really present and operating.... It will appear that a measurable uncertainty, or ‘risk’ proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all.”
When it comes to measuring risk, many will recognize that most of our common risk measures (e.g., standard deviation, beta, tracking error) are measures of volatility or, if you prefer, variability, which many argue isn't risk. This causes one to ask, "well what IS risk?" The most commonly cited definition deals with the inability to meet an objective, while the potential for loss is also often used. I've seen uncertainty referenced in the past, though on my own wondered how one would measure it. Well, Knight pointed out almost 100 years ago that you can't measure it! I wish someone had told me.
Moving further along I came across http://www.rgemonitor.com/blog/roubini/210688, which offered the following: “Economists distinguish between ‘Risk’ and ‘Uncertainty’: the former can be priced by financial markets while the latter cannot. The distinction between the two was made by the famous economist Frank H. Knight in his seminal book, Risk, Uncertainty, and Profit (1921). In brief, ‘Risk is present when future events occur with measurable probability’ while ‘Uncertainty is present when the likelihood of future events is indefinite or incalculable.’”
Why the need to qualify the term "uncertainty" isn't clear to me, though it's worth understanding a bit more about the term, in general. It is interesting, isn't it, that the basis for much of what we do was addressed years, decades, or perhaps even a century ago, but unfortunately isn't always known to us, for a variety of reasons.
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While there may be nothing more than semantics that separate "risk" and "uncertainty" we can be sure that we face greater peril from failing to recognize the types of risk we face, as opposed to failing to measure the risks we do recognize with enough precision. For example, we argue about the limitations of standard deviation as a risk measure while we ignore other aspects of risk that could be deadly (defined as causing the total failure of a financial plan.) Consider that in 2008 the risk of having inadequate liquidity was perhaps the greatest risk faced by investors. They were not surprised that their diversified portfolios lost money, although they were probably surprised at the severity of their losses. They were more surprised that their so-called "liquid" investments like bonds were actually the least liquid part of the overall market, as corporate bonds were completely untradable for a good part of the crisis. We found that liquidity risk was not part of anyone's "risk model." So, we might conclude that these elegant and mathematically oriented risk models were failures because they did not incorporate all of the significant risks faced by investors.
ReplyDeleteAnd so we see another risk that brings the potential for great peril: the risk that our assumptions are wrong. We assume that the world is normally distributed, with the result that market downturns that have been observed every 25 years are treated as statistical events with a likelihood of occurring only once in 400 years! We assume that we can liquidate any part of the portfolio to meet our financial obligations, only to find that the most "sophisticated" investment managers (think Yale and Harvard) are now borrowing money to pay their bills. Meanwhile, our quantitative approach to investing gives us false comfort about our ability to control risk. Unfortunately, you can't control what you fail to consider. We should first consider that we are probably missing some risks, and that we have a great potential to be wrong while being confident that we are right. Overconfidence is probably the greatest risk we face. Maybe you can't measure it, but you are better off if you consider it.