1. Portfolio Management and the European Crisis
Mikhail Munenzon, CFA, CAIA, PRM, MIA
mikhailmunenzon@gmail.com
November 9, 2011
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2. Introduction
This article is meant to provide a roadmap on how to survive and thrive in a tail event (a low
probability but high impact event of uncertain magnitude). The trigger for it is the current European
crisis. However, principles outlined below are useful regardless of whether the euro actually crashes or
not, as they relate to a robust process that can be used to create quality, risk adjusted returns in a
market environment that includes tail events at differing intervals (our reality). A few comments on
what this article is not supposed to be. I’m not trying to make any forecasts as for every negative
viewpoint, one can find a seemingly valid positive viewpoint. Such arguments may be entertaining but
not practically relevant as the future (particularly of longer term duration) is unknowable1. This is also
not meant to be a long academic paper on a boring, minute subject with numerous footnotes and long
reference list (though happy to provide some recommendations to the interested reader). Rather I want
to argue against poor portfolio management practices I see (especially important if the sovereign crisis
continues to build) and provide practically relevant guidance to those practitioners, who appreciate that
reality is messy and complex. This reality is very different from the precise elegance of we are exposed
to in schools and what is underlying most risk models on the market currently. I also welcome
comments from and look forward to the dialogue with similarly minded practitioners.
Probabilities don’t matter
Too much time is spent on evaluating the probability of the euro crash. This probability should
be irrelevant to your portfolio management process! Let me illustrate. Someone tries to play the
Russian roulette (for those unfamiliar with this - you fire a revolver aimed at your head and which has
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A more extensive discussion of this point is beyond the scope of the article. However, two comments are in
order. If the future were knowable, we’d be able to take relevant actions as of now, therefore making potential
future negative events irrelevant (e.g., wars) or bringing future positive events faster to the present (e.g., life
saving medicine); neither is observed. Similarly, research on complex systems demonstrates inherent difficulties in
forecasting/controlling such systems over an extended period of time and even small time periods.
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3. only a single bullet; if you survive, you win and get the money). The odds are in your favor as there’s
only 1/6 (or even lower depending on the size of the revolver) chance of your death. However, only a
fool (or extremely bored/desperate person) would undertake such a gamble, as the impact of an
adverse scenario is catastrophic. Regardless of whether you survive the roulette, only a poor process
can lead you to participate in the game. Probability analysis of death plays no role at all. The real life
situations we face in markets are much more complex than this example: we don’t know probabilities
as we don’t know the rules of the game. Markets are complex, dynamic adaptive systems in which
many agents with different goals interact, affect and get affected by output (feedback loops) and
produce large nonlinearities (small changes in input may lead to large changes in ouput). We simply do
not know yet (and may never know) how to reliably model, forecast and control such systems, though
there’s ever increasing research shedding light on the underlying mechanisms of such systems. If a
serious sovereign crisis doesn’t occur in the next 12-24 months (those who think that we’ve already
experienced a European sovereign crisis, I suggest that we’ve experienced nothing but increasing
tremors but no earthquake yet), there will be those who’ll emerge with strong performance due to their
large risky asset exposures and will be applauded by the press for their insight and powerful probabilistic
skills used to position their clients’ portfolios while in fact, the fool just played the roulette and managed
to survive (for now). Focus on the potential impact of a tail event to your portfolio not its probability,
though also be skeptical of your ability to assess the magnitude of the event (more on that below).
Don’t rely on risk estimates from risk models, such as standard deviation or VaR. Such models embed a
dangerously precise probabilistic view of the world based on past history, which will be different in the
future. Additionally, their forward looking capabilities are poor precisely because markets are
constantly evolving and especially as the general perspective on which many such models are built is still
unrealistically Gaussian (normal) (more on this also below).
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4. We can’t know the future and we can’t even understand the past
‘They have the will and tools to do what’s necessary to avoid a crisis’. This is one of the more
annoying and infuriating statements I keep hearing. It is normally implied or expressed that ‘they’
are the elite, who in many cases are the very same people who contributed to current problems.
However, now, they are expected to have the vision and courage to do what is necessary. I suggest that
a healthy dose of skepticism is in order. We tend to be overconfident of our and our leaders’ ability to
understand what is happening and to control and avoid an adverse outcome. We fail to grasp of
potential impact of events occurring around us and create great stories explaining how clear and
preventable the event was, after the fact. SP500 actually rallied after the Nazi invasion of Poland on
Sep. 1, 1939 and it declined only a few percent after the Japanese attack on Pearl Harbor. Shouldn’t the
atrocities that occurred prior to those events have been obvious already? What about all the horrors
that were still about to follow? Historian Niall Ferguson demonstrated that government bond prices
remained stable right before the start of WWI, though many now think that the conflict was inevitable
based on the reading of events leading up to the war. Taleb in his book Black Swan shares an excellent
example from his friend. If you see an ice cube on the table and you have a proper understanding of the
relevant principles of physics, you may be able to forecast the future path of that ice cube – it will
gradually melt, though it will be very hard to predict position of water on the table or its shape.
However, imagine you only see a puddle of water on the table. Which ice cube was the cause? You
cannot answer that as any number of ice cubes (any size and shape) could have created that water.
Stress testing is in my view a very useful tool for thinking about the potential impact of various
historical scenarios on the portfolio. It is even more useful to thinking about scenarios have not yet
occurred. However, its importance cannot be exaggerated or lead to a false sense of security as reality
may turn out to be far messier than even your wildest imagination. Prior stress scenarios are not in any
way indicative of what may or should happen in the future but a very rough approximation of it (which is
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5. nonetheless still better than nothing). For example, a volatility arbitrage manager trading VIX in ‘07 who
managed his exposures on the assumption that VIX won’t exceed 50 based on historical stress tests
would have most likely gone out of business - VIX actually managed to exceed 80 in ‘08. Stress testing is
no panacea and must be supplemented with other methods.
Negative skew kills; it kills even faster if it is large and the crisis is large
I rarely see people who understand the concept, though one doesn’t need to understand any
complicated statistical formulas. In fact, many risk models are still run on the Gaussian distribution,
which assumes no skew of real world economic/financial data at all. Another illustration for the reader.
Would you rather buy or sell the following lottery ticket? Make 11 cents 90% of the time and lose $1
10% of the time (or make 2 cents 99% of the time and lose $1 1% of the time). Regardless of your
choice, the expected value remains the same (effectively zero). Most people prefer to buy the lottery as
they are naturally attracted to a consistent payoff (even if small), disregarding the loss that’s much
larger in magnitude than the typical gain. This loss will also wipe out many periods of gains and may
occur even before you had time to accumulate any meaningful profits from which to pay for your loss.
Please note that again, your analysis of probability is quite irrelevant in this case (and as before,
irrelevant in real life as we don’t even know true probabilities) - it’s the relationship between your gain
and loss that’s important. If you sold earthquake insurance in California today, a large earthquake may
occur tomorrow or in 10 years. And if it already occurred this year, it does not mean that it cannot
occur next year again.
Debt is a classic negative skew asset: its upside is limited and the downside is much larger than
the upside. Overlay a typical debt instrument with a complex structure which few, if any, can
understand, illiquidity and leverage and one is left with a huge, negative skew. Most financial prices
have negative skew; as a result, most portfolios have negative skew, especially if left unmanaged. The
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6. easiest way to improve your skew profile is to implement a stop loss program (more on that below). If
you have a large credit exposure, think about lowering it or locking in the level of your potential losses.
The same applies to passive exposures to other risky assets, such as equities or commodities. Avoid and
minimize leverage in your portfolio, especially if you already have large, passive exposures to negative
skew instruments. This includes strategies with explicit leverage, such as equity market neutral, option
writing or convertible arbitrage, or implicit leverage, such as that of distressed debt as the underlying is
experiencing financial difficulties. Similarly, improve liquidity of your portfolio to mitigate negative
skewness.
You can easily measure the skew of a performance time series of your underlying assets and
therefore come up with the skew of the portfolio; any analytical software package will have this
function. You should particularly focus on those managers/instruments which account for most of the
skew. However, a qualitative assessment is as important as a particular number you may get from
quantitative analysis, particularly if the instruments held have limited performance history while being
complex and illiquid. Just because something hasn’t crashed yet does not make it safe if its ingredients
are poor. Similarly, if you run stress tests and find that you lose more in stress than in a rally of the
same absolute magnitude, you have a skew in the portfolio.
Simplicity, flexibility and liquidity are great, especially in a crisis
Straightforward instruments/strategies are easy to manage and evaluate, minimizing chances of
error. Just like simple organisms, they are also far more likely to survive a major stress; it is large,
complex, inflexible structures that cannot handle a crisis. Adapt to the environment you are in; a tree
that bends will survive a hurricane but even a strong, inflexible tree will ultimately succumb to a wind
force that is even stronger. If you cannot access your capital, you are actually poor and ill prepared to
face the unexpected, regardless of how much you have invested. Having easy access to your invested
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7. capital allows you to change your mind and easily correct inevitable errors that arise from prior
decisions. Enough said.
You will lose a lot but you can’t know how much
Information about tail events is by definition limited even for economic data, which is quite
numerous compared to many other fields. As a result, the analysis of potential tail losses is inherently
unreliable because of data limitations. As importantly, a correct estimate of tail losses would imply
knowledge of the underlying mechanism of a complex market system producing such losses, which, as
noted above, we don’t have. In fact, just because the worst possible tail loss in the prior cycle may have
been (for example) 50% does not mean that the next crisis will not produce losses that are far greater
magnitude. It is prudent to be prepared for losses larger than those previously experienced.
On averaging down and stop losses
Averaging down is not a risk control mechanism! If you average down, this implies that you
think you know that your starting point is attractive relative to the bottom which will occur. As I argue
above, the future is unknowable. In fact, you may average down to zero. In a tail event, the priority
should be placed not on ensuring that you participate in the market bottom but on surviving first in
strong shape so that you have the cash to invest once the recovery takes hold. You will miss the bottom
but you are not sitting on large losses which you need to recover and therefore cannot afford to miss
any part of the rally that may occur. You are in a position of strength and can calmly take the time to
evaluate the situation without hasty, emotional decisions. There will be sufficient time to invest to
make money, especially as you are already starting ahead of many other players. A desire to participate
and catch the market bottom is a ‘retail’ mentality completely irrelevant to a robust investment process
producing strong, risk adjusted performance.
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8. The simplest and highly effective mechanism for risk control is a stop loss program. Perhaps
because it is so simple, I see it rarely practiced. In fact, it seems that the more degrees a person has, the
more he’s offended by it and less likely to use it. However, to ensure survival, you must curb portfolio
losses at some sensible level, regardless of any stories, excuses, explanations you can come up with after
the fact. For example, for each instrument in the portfolio, determine the level of a loss that is
meaningful (so that you are not acting on market noise) but not ruinous. Alternatively, if the overall
portfolio reaches some pre-determined loss level (e.g., 10%), you cut positions by some meaningful
amount (e.g., 50%). There are various approaches to stop losses but it is crucial to do something. It is
also important to establish such a program before losses start accumulating so that any emotion in the
design of such program is minimized in the decision making process.
On hedges
Another approach to controlling losses in the portfolio is to buy insurance or other relevant
hedges for the portfolio. For example, while pricing on equity put options is not likely to be attractive at
this point, one can still get long term, out of the money options on the euro at low implied volatilities.
Not surprisingly, insurance is cheapest when you least need it. However, just continuously buying put
options is not cost effective. While you may also explore CDS instruments to hedge various portfolio
exposures, it is not clear that they can provide the desired protection given the recent attempted
government interference with payout triggers. You should also explore strategies that may benefit from
increasing volatility while producing a quality, risk adjusted return in a broad set of scenarios, such as
macro, volatility arbitrage and trend following. If the managers don’t give up too much of gains in
environments unfavorable for them, such strategies will provide a cost effective hedge to the portfolio
while meaningfully improving its overall risk adjusted return profile. Even if the crash does not
materialize, they should be able to make money as long as markets move. You also can’t forget the
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9. most classic hedge of them all – cash. If you don’t need to have a tail exposure, cut it and move money
to cash. While government securities should do well in a tail event, please be sure that those securities
are not of the country experiencing sovereign crisis or likely to be affected by it. Gold’s record during
stress periods is actually surprisingly inconsistent; I encourage the reader to check empirical data.
On correlation and optimization
There are few academic finance tools that are more practically useless than correlation and
optimization. As markets are dynamic and non-linear, correlation is highly unstable as it is a linear
metric. Moreover, average relationships among assets are irrelevant for what happens in a crash. All
you need to know is that in a crash, all risky assets will go down in price, regardless of how uncorrelated
they may seem in normal times. Your optimized portfolio built with complicated math is based on
fitting historical average info, which won’t be relevant for the unknowable future and even less relevant
in crash scenarios. This is especially true as most portfolios are not even optimized to any practically
relevant tail risk measure but rather relative to volatilityi, which has very little use for real life risk
management. To add insult to injury, optimization is an inherently static tool while markets are dynamic
organisms.
On rally risk
Suppose you think that the crash is coming but you can’t be heavily defensive for a long time as
the portfolio may lag the market significantly in case of a rally (e.g., keep in mind that even during major
bear market, there are multiple rallies, even of 10%+). You may not have the luxury of sitting in cash
until the tail event occurs and need to deal with the messy reality as of now. You may lose some clients
or even all of them if you lag meaningfully and for an extended period of time if the market rallies. Of
course, there is also the possibility that the crash may not come at all. What to do? I suggest in such
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10. situations to think like a short term trader, rather than as a long term investor. Establish some market
exposures for the amounts you are comfortable with and with tight stop losses that you will re-set if the
rally continues. If the market continues to rally, you will at least partly participate and may even
consider adding to your position; if the market declines and hit your stop losses, the impact to the
portfolio will be limited. Of course, you should be prepared to be whipsawed if the market remains
trading in a wide range until the crisis materializes or the underlying problem is resolved – this is the
downside of active market participation as compared to a more passive defensive posture.
The roadmap
I will now attempt to summarize the points made above and add a few more comments for an
actionable portfolio management process. We do not know the future and we can even have difficulty
understanding the past. Therefore, you can safely save a ton of time by ignoring all the forecasters and
the ‘elite’ on TV, radio and in print, discussing the future or finding analogies with the past. It may be
entertaining but nothing more than that. Understand the negative skew in the portfolio and its sources.
Are there any instruments/strategies in the portfolio that are effectively a sale of insurance, particularly
levered sale of insurance (e.g., option writing, arbitrage of any sort)? Such exposures will suffer the
most in a tail event. Mitigate the negative skew through any of the following to reach your defined loss
limit: reduction of exposures, stop losses, addition of relevant hedges. With the rally experienced in
October, now may be a good time to cut some exposures. How much in losses can your clients actually
tolerate? Research indicates that gains and losses are not experienced proportionally: 1% gain ‘feels’
less strong than 1% loss. Similarly, regardless of what your client may tell you as to his loss tolerance, it
is likely to be overestimated. What is your portfolio return profile relative to your potential loss? If you
are on average making your clients 10% per year, you can’t lose much more than that as it will take a
long time to climb out of that drawdown (not to mention all the bad client conversations). Does the
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11. portfolio have simplicity, flexibility and liquidity to survive the stress or perhaps, it is heavily invested in
illiquid or complex instruments, such as distressed debt, structured products or private equity? Don’t
over rely on backward looking risk models, especially if they are based on limited historical data and
irrelevant statistical approaches. You can still have speculative portfolio but with the above steps
taken, its maximum loss potential will now effectively be controlled and appropriately sized for its
return potential.
Happy investing!
i
There is by now large literature (even by academics) on serious practical deficiencies of volatility as a risk metric
(assuming of course that risk can be reliably measured at all). The reader can even look up one of my papers on
the topic and some references to get started on the Social Science Research Network at www.ssrn.com
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