Was 2008 really that shocking? The survey makes it clear that the industry was shocked by 2008. I, personally, am shocked that the industry found 2008 so shocking. Based on historical returns since 1926, large cap stocks fell about two and a half standard deviations below their long-term average return. If annual returns were normally distributed (mind you, I did not say they are, just if they were normally distributed) then a downward move of two standard deviations or more would happen roughly 2.5% of the time. That is, one year in 40. Since I have been in this business for over 60 years, I was overdue for a one-year-in-40 event. The following specific morals can be drawn from the fact that once-in-40-years events happen from time to time: the survey reports an increased interest in a portfolio’s Value at Risk (VaR). I have no objection to using VaR as one way to characterise a mean- variance efficient portfolio’s risk exposure; but I hope top management understands that VaR (at the 5% level) is not the most a portfolio can lose, but the least it will lose 5% of the time. Since 5% is one period in 20, losses somewhat in excess of the 5% VaR point (say, between the 1% and 5% probability levels) should be considered routine events in portfolio management.
In late 2007 through early 2009 in particular, pension funds that stayed with an old-fashioned 60/40, or 70/30 or 50/50, or such, mix of stocks and bonds (including an efficient mixture of asset classes such as large cap, small cap, developed markets, emerging markets, and long-term, short-term and high-yield bonds, for example) rebalanced near the market’s nadir while those who were too clever by half suffered tragically.
The danger of using alternatives for diversification The 2013 survey reports an increased use of alternative investments with diversification rather than enhanced expected return as the principal motivation. The goal of diversifying a portfolio by adding exotic asset classes has sometimes proved quite disappointing, and predictably so. The formula for the volatility of a portfolio is rather complicated. Depending on lots of different correlations between the returns of a proposed security or asset class with those of others in a portfolio, the adding of a more volatile security or asset class may or may not reduce the portfolio’s volatility. Estimating volatility of illiquid investments can complicate risk calculations, and some alternative investments intend to reduce beta rather than increase beta.
However, if an investor is exposed to exotic high- beta alternative investments, the result may be that the exotic security or asset class goes down in flames at the same time traditional asset classes are struggling. The institution then says that portfolio
theory with its touted diversification benefits (as represented by some sell-side quant) has failed.
The solution here is simple. The institution should have a trusted quant team make forward-looking estimates of means, variances and covariances involving this security or asset class, perhaps with the help of the factor model of their choice. These estimates, along with such estimates for traditional securities or asset classes, should be presented to the MPT optimiser along with the institution’s legal, institutional, turnover, liquidity, multiple objectives, client preferences and other constraints. The efficient frontier generated by the optimiser from these inputs may or may not have portfolios that use the proposed security or asset class. So be it.
The trusted quant team in the previous paragraph is presumably either that of the institution or a consultant, depending on who regularly produces the institution’s efficient frontier. As the survey notes, sometimes such matters are done in-house and sometimes they are farmed out. If the trusted team errs too badly too often, the institution should hire or develop a different trusted team.
Using the appropriate measure of risk The survey notes that many pension funds, especially private as compared to public pension funds, have switched from performance-versus-a- benchmark to asset-returns-versus-liabilities as their objective. The moral here is that an MPT optimiser is quite flexible with respect to such matters. The institution needs to identify its objectives and share them with the optimiser. For example, in advising an individual investor a CFA or CFP should usually use the total volatility of the client’s portfolio as its risk measure; whereas a money manager who is paid to outperform some index should use tracking
Fig.1 The most important market risks 0 = Not important at all 3 = Neutral 5 = Extremely important
error as its risk measure; and a pension fund should naturally use the volatility of asset values minus liability values as its measure of risk.
As noted in a comment in the survey, if the volatility of assets-minus-liabilities is the correct risk measure for a particular portfolio, such as a firm’s pension fund, that doesn’t mean that its portfolio should be immunised. That would be the minimum-risk solution for such a portfolio. But the MPT view is neither to minimise risk nor always maximise return, but to consider the possible trade-off between them.
All crises are different The crisis of 2008 was different. So was the crisis that started in March of 2000 with the bursting of the tech bubble. So will be the next crisis, as were all the colourful crises reported in Charles Mackay’s Extraordinary Popular Delusions and the Madness of Crowds (Mackay, 1841, 1852, 1980). The moral is that one will never be able to put the portfolio selection process on automatic. The trusted quant team needs to constantly evaluate the current situation. It should also make sure that higher management understands what assumptions are being made, how and by whom any exotic asset classes being used have been evaluated, and what are the vulnerabilities of the general approach being taken.
Furthermore, the push to integrate risk control at the enterprise level, rather than at the individual portfolio level, should be continued. More generally, the many charts, tables, revealed trends that follow and the comments on them concerning both investment risks and operational risks in the surveys reported below should be given the most serious consideration.
Source: BNY Mellon
Interest rate/low yield environment Extreme market shifts Financial market contagion Liquidity Inflation
Credit/counterparty default Fundamental/systematic market
4.5 4.2 4.0 3.9 3.9 3.9 3.9
01234 5
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