A brief note today on what might be an arcane subject for some but
is a great example of the most basic question in risk management – are you
thinking about your risk questions in a way that fits the fundamental nature of
your data? Do you understand the fundamental nature of your
data? Our business incentivizes us to build complex and ingenious
models and data analysis systems in order to generate an edge or dodge a bullet.
But are we building our elaborate mental constructs on solid ground? Or on
quicksand?
I’ve spent a lot of time recently talking with clients about
measuring market risk across a wide range of asset classes and securities as
part of an adaptive investment strategy, and I get a lot of smart questions. One
of the best was deceptively simple – what do you think about using
implied volatility to measure risk? – and that’s the question I want to use
to illustrate a larger point.
First let’s unpack the question. Volatility is a measurement of how
violently the returns of a security jump around, and in professional investment
circles the word “volatility” is typically used as shorthand for risk – the
higher the volatility, the greater the embedded risk. There are some valid
concerns and exceptions to this conflation of the two concepts, but by and large
I think it’s a very useful connection.
Within the general concept of volatility there are two basic ways
of measuring it. You can look backwards at historical prices over some time
period to figure out how violently those prices actually jumped around – what’s
called “realized volatility” – or you can look forward at option prices for that
same security and figure out how violently investors expect
that prices will jump around in the future – what’s called “implied volatility”.
Both flavors of volatility have important uses, even though they mean something
quite different. For example, a beta measurement (how much a security’s price
moves relative to an underlying index) is based on realized volatility. On the
other hand, the VIX index – the most commonly reported gauge of overall market
risk or complacency – is entirely based on the implied volatility of short to
medium-term options on the S&P 500.
The big drawback to using realized or historical volatility is that
it is, by nature, backwards looking. It tells you exactly where you’ve been, but
only by extrapolation provides a signal for where you are going. In a business
where you always want to be looking forward, this is a problem. Using realized
volatility means that you will always be reacting to changes in the broad market
characteristics of your portfolio; you will never be proactive to looming
changes that might well be embedded within the “wisdom of the crowd” as found in
forward-looking options prices. If you’re relying on realized volatility, no
matter how sensitively or smartly you set the timing parameters, you will always be late. This was the point of the smart question I was
asked: isn’t there useful information in the risk expectations of
market participants, information that allows you to be proactive rather than
reactive … and shouldn’t you be using that information as you seek to balance
risk across your portfolio?
My answer: yes … and no. Yes, there is useful information in
implied volatility for many purposes. But no, not for the purpose of asset
allocation. Why not? Because we are living in the Golden Age
of Central Bankers, and that wreaks havoc on the fundamental nature of market
expectations data.
Here’s an example I’ve used before to illustrate this point, courtesy
of Ed Tom and the Credit Suisse derivatives strategy group. Figures 1 shows the
term structure (implied price level at different future times based on prices
paid for options) of the VIX index on October 15th, 2012.
If you recall, there was great consternation regarding the Fiscal
Cliff at this time, not to mention the uncertainty surrounding the November
elections. That consternation and uncertainty is reflected in the term
structure, as it is much steeper than is typical for a spot VIX level of 15,
indicating that the market is anticipating S&P 500 volatility to be
progressively higher to an unusual degree from January 2013 onwards. The way to
read this chart is that the market expects a VIX level of 18 three months in the
future (January 15), 19 three and a half months in the future (January 31), 20
four months in the future (February 15), and so on. All of these results are
higher than one would typically expect for future expectations of the VIX from
this starting point (essentially flat at 17).
Now take a look at Figure 2, which shows the Credit Suisse
estimation of the underlying distribution of VIX expectations for January 31,
2013.
The way to read this chart is that a lot of market participants
have a Bullish view (low VIX) for what the world will look like on January 31,
with a peak frequency (greatest number of bullish contracts) at 15 and a fairly
narrow distribution of expectations around that. Another group of market
participants clearly have a Bearish view (high VIX) of the world on January 31,
with a peak frequency around 24 and a fairly broad distribution around that.
So what’s the problem? The problem is that Figure 1, which is what
you would come up with based on public options data, says that the most likely
implied price for the VIX on January 31, 2013 is 19. But Figure 2, which is
based on the trading data that Credit Suisse collects, says that a VIX level of
19 is the least likely outcome. What Figure 2 tells
you is that almost no one expects that the outcome will end up
in the middle at a price of 19, even if that is the average implied price of all
the exposures.
Usually the average implied price of a security is also the most
likely estimated price outcome of the security. That is, if options on a
security imply an average price of 19 a few months from now, exposures will
generally form some sort of bell curve centered on the price of 19. The most
common estimation of the price would be 19, with fewer people estimating a
higher price and fewer people estimating a lower price. But in those situations
– like expectations of future VIX levels on October 15, 2012 – where there’s not
a single-peaked distribution, all of our math and all of our models and all of
our intuitively held assumptions go right out the window.
Unfortunately, these bi-modal market expectation structures are now
the rule rather than the exception in this, the Golden Age of the Central
Banker. Why? Because monetary policy since March, 2009 has explicitly
established itself as an emergency bridge for financial markets, a bridge
between the real world of an anemic, under-employed, under-utilized economy and
the hoped-for world of a vibrantly growing, robust economy. On its own terms,
this has been an entirely successful experiment, I suspect surpassing the
wildest dreams of Bernanke et al. Stock markets have been “bridged”, reflecting
what the world would look like if the global economy were off to the races,
while bond markets reflect what the world actually looks like with the global
economy sputtering in fits and starts. The problem today is that the experiment has been too successful. Whether you
are in Europe or the US or Japan or China or wherever, the only investment
questions that matter are whether central banks will continue their emergency
monetary policies and what happens if the bridges are removed. These are not
small, incremental policy questions. These are existential questions, reflecting binary expectations of the world with an
enormous chasm in-between. With a hat tip to Milton Friedman, we are all
bi-modal now.
So what’s the moral of this story for portfolio management? There
are four, I believe.
In the Golden Age of the Central Banker
…
1) the VIX is not a reliable measure of market
complacency. Remember that the VIX itself is an implied volatility
construct, built on the prices paid for options on the S&P 500 two to three
months in the future. We assume that whatever the VIX is reported to be, that’s
the consensus market expectation, with a lot of people holding that particular
view and progressively fewer people on either side of that number. This is not
necessarily the case, and when binary events raise their ugly heads it is almost
certainly not the case. A low VIX level might indicate a complacent market, or
it might indicate two sets of investors – one very complacent and one
non-complacent – who see the world entirely differently. You have no idea what
the underlying market expectations look like, and this makes all the difference
in determining what the VIX means.
2) the wisdom of crowds is nonexistent.
I believe in the efficiency of emergent behaviors. I believe that there is a
logical dynamic process to crowd behaviors. But I also believe that crowds are
extremely malleable when confronted by powerful individuals or institutions that
understand the strategic interaction of crowds and make a concerted effort to
master the game. There’s no inherent “wisdom” here, no emergent outcome where
the crowd acts like an enormous set of parallel microprocessors to arrive at
Truth with a capital T. The Common Knowledge Game is controlled by the
Missionary, and our current Missionaries – central bankers, politicians,
famous investors and media mouthpieces – know it.
3) fundamental risk/reward calculations for directional exposure to any security are
problematic on anything other than a VERY long time horizon.
Game-playing has always been a big part of the market environment, and it dominates successful directional bets on a very short
time horizon. Similarly, stock-picking on a fundamental basis has always
been a big part of the market environment and dominates successful directional
bets on a very long time horizon. Between the very short-term and the very
long-term you have this mish-mash of game-playing and stock-picking. One impact
of the pervasiveness of the Common Knowledge Game today is that it pushes out
the time horizon on which stock-picking on a fundamental basis can really shine.
If you’re in the stock-picking business the value of permanent capital has never
been greater.
4) I’d rather be reactive and right in my
portfolio than proactive and wrong. I started this note with an
acknowledgment of the weakness of risk assessments based on realized or
historical volatility – it’s inherently backwards looking and you will always, no matter how finely calibrated your system, be late to
respond to changing market conditions. But here’s the thing. This is what it means to be adaptive. You can’t be
adaptive without something to adapt TO. Will you miss the market turns? Will you
occasionally get whipsawed in your reactive process? Without a doubt. But you
won’t get killed. You won’t be on the wrong side of a binary bet that you really
didn’t need to make. You won’t discover that your pretty little sand box is
really filled with quicksand. The Golden Age of the Central
Banker is a time for survivors, not heroes. And that’s the real moral
of this story.
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