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Behavioral Finance and Closed-End Fund Investing

Remember to watch out for these common biases.

Steven Pikelny, 07/26/2013

If Morningstar's special report on behavioral finance earlier this week highlighted anything, it's that there is more to investing than simply crunching numbers. Emotions and cognitive biases persistently cloud judgment, and successful investors are ones who supplement their analysis with a psychologically disciplined approach. Academia looks to help in this endeavor by observing the many ways in which investors deviate from "rational decision-making." Unfortunately, this does not always translate to practical advice. The literature on closed-end funds, in particular, is often lacking. Researchers occasionally offer sweeping theories on the persistence of discounts (typically relating to accrued tax liabilities and investor sentiment) and conclude that investors are simply irrational, but researchers tend to stay away from how individual decision-making pertains to CEF investing.

Given the sheer number of catalogued biases, however, finding applications for CEF investors is not particularly difficult. Keep in mind that each investor will find his or her own psychological strengths and weaknesses, many of which can be difficult to overcome completely. But still, awareness is often the first step toward improvement.

Anchoring
As the name suggests, anchoring refers to the tendency to adjust upward or downward from a given reference point (the anchor) rather than make an independent judgment. As our primer on behavioral biases explains--when asked to estimate the population of Chicago, a New Yorker might have a different estimate than a resident of Milwaukee if they both use their home cities as starting reference points.

Bringing things to CEFs, the valuation process can easily be muddled by the status quo, especially as it relates to premium and discount analysis. Investors should avoid latching on to the first number that they see as a basis of comparison against all future premiums and discounts. We always urge investors to view valuation in a historical context, but it is still important to make sure the valuation also makes sense on an absolute basis. Just because a premium or discount makes a sharp movement away from its initial reference point does not necessarily mean that it is overvalued or undervalued. Factors such as special distributions, manager changes, leverage announcements, and corporate actions can have lasting impacts on the fund's value. Because this is more dangerous on the premium side than it is on the discount side (the surprise collapse of a premium can lead to unexpected losses, while the surprise narrowing of a discount can lead to unexpected gains), it is important to be more conservative when analyzing premiums. Large premiums can often collapse quickly and without notice for both specific funds and entire sectors. For this reason, we recommend that investors typically avoid funds trading at double-digit premiums, regardless of their historical valuation.

Availability Bias
Recent memories and anecdotal evidence tend to cloud our vision, and they are more easily recalled than data points. Most recently, Federal Reserve chairman Ben Bernanke ambiguously hinted that the end of the Fed's bond-buying program was in sight, which led to a bond market sell-off in May and June. As expected, CEF fixed-income portfolios fell sharply. Although the amount of evidence supporting behavioral finance biases might outweigh that which favors the efficient-market hypothesis, it may not be entirely unreasonable to assume that the bond market has done a decent job of pricing in a rising rate environment. However, share prices of many CEFs fell much faster than the net asset values. This means that, on top of the decrease in share prices attributable to the decrease in NAVs, investor sentiment saw a negative shift. Moreover, discounts continue to persist for many long-duration funds, some of which were trading at premiums a few months ago.

To be sure, these fears might not necessarily be displaced. It is certainly possible that CEF investors have a better sense of where interest rates are headed than bond investors. But if these new discounts are merely indicative of a sentiment shift, then availability bias is a likely culprit: Quickly falling NAVs make for a scary image.

Similarly, many investors were weary of investing in CEFs after the financial crisis for several reasons. First, the word "leverage" conjured up the picture of Lehman Brothers and Bear Stearns. Second, the large losses suffered by many CEFs in late 2008 and early 2009 left them with a reputation as extremely risky vehicles, even after many funds deleveraged. Third, the ARPS fiasco left the CEF industry with a black eye, even though most fund families have now refinanced into different forms of leverage. 

Survivorship Bias
Performance is often one of the best ways to evaluate managers and their investment processes. After all, one would expect bad managers to perform poorly over a market cycle and good managers to perform well, but not vice-versa. But be careful not to lean too heavily on this line of logic. Because of the laws of statistics, some managers will outperform and some will underperform from blind chance alone. Taking this one step further, the number of lucky managers who continually outperform will diminish, but may never fall to zero. Alternatively, many skilled and unlucky managers who continuously underperform eventually will get fired and will fall out of the sample. This leaves the remaining population of managers (the survivors) with "above-average" track records. To complicate matters, many managers make longer-term bets that they expect to play out over the course of a market cycle. If a market cycle consists of three years, this means that a manager with a 24-year track record only has eight "observations" behind him/her. While it is unlikely that a manager would be correct eight times in a row, it is also unlikely that no manager would beat these odds.

Steven Pikelny is a closed-end fund analyst at Morningstar.
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