Markets
never repeat themselves but they often rhyme. This rally feels like the same
sonnet we experienced in 1987. As in a sonnet, it is following a strict rhyme
scheme and specific structure.
In 1987 the rally began
gaining steam in the spring when it already seemed overbought and extended.
The rally had initially started in October 1986 at DOW 1400, but during the
spring of 1987 it began to accelerate. It not only didn't correct, but
continued to gain momentum. Despite all the pundits saying it was about to
correct, it just kept going up. By early fall the bears had capitulated and
the public was scrambling to avoid missing further gains. They were quickly
rewarded as the market moved even higher. No bad news, overextended
fundamentals or technical warnings could stop the rise. The DOW was soon over
2700 for an approximate 93% rise.
Then suddenly in October 1987,
out of nowhere, the crash hit. It was stunning. The market gave back 22.6% in
one day. What was later called Black Monday left a pale over the US that was
palpable. In a matter of days the market surrendered the entire gains it had
achieved over the previous year.
Before you write me off too
quickly as trying to draw too close a comparison, let me tell you why it
really feels the same. It isn't just the rise or rhyme; it's the reason for
both.
Since March 2009 the current
rally has moved from a 666 low on the S&P 500 to a recent high of 1220,
for an 83% increase in just over a year. The rises are similar to 1987 but so
are the critical elements of risk and how risk has shifted to the innocent.
Before I discuss how this risk has been shifted through Dynamic Hedging,
Capital Arbitrage and Regulatory Arbitrage, let me first briefly talk about
the realities of risk versus perceptions.
REALITIES OF RISK
USING STATISTICS TO SHOW US
HOW THE INNOCENT GET LULLED INTO GETTING 'MUGGED'!
Let's say there's a
statistically unlikely event that takes place 1% of the time. As an example,
suppose, just for argument's sake, that if you go for a walk in a particular
Chicago neighborhood, statistically the police tell you, 1% of the time you
will get mugged in this neighborhood.
So, if you go out for a walk
one time, you have a 99% chance of not getting mugged and a 1% chance of
getting hurt. But suppose you go out for one walk every day for 10 days, the
chance that you will get hit on one of those occasions rises. The way it's
calculated is by figuring the odds that the LIKELY event will obtain at every
single iteration and then subtracting that from 100%. The equation is:
D = 1-(1-P)^N
Where:
D=cumulative percentage chance
of disaster
P= Percentage Chance of disaster on each opportunity (iteration)
N=number of iterations
So, if you go out for 10
walks, your chance of getting into trouble is:
1-(1-.01)^10 = 9.6%.
And if you go out for a walk
every day for, say, 90 days, your chance of getting hurt is
1-(1-.01)^90 = 59.5%.
The graph above shows what the
series looks like. (1)
And in this scenario, if you
go out for a walk every trading day of the year (about 252 times) the odds
are about 92% that you will meet your demise.
But the funny thing about our
human nature is that if, say, you went out for 252 walks in our Chicago
neighborhood and came back 252 times, without having had any violent
encounters with our Chicago's city folk, you would assume that experience was
teaching you that there was very little danger. Indeed it might be, if you
didn't already know the likelihood of getting mugged.
As human beings we are especially primed to generalize
from experience (that's science), but most especially to generalize from our
most recent experiences (which is less reliable science--or anecdotal
evidence). So, the more walks we go on without getting mugged the less likely
we FEEL it to be that we will ever get mugged, irrespective of what
statistics might tell us. As our risk increases, statistically speaking,
we feel safer and safer.
We are all familiar with the
expression "tempting fate." One has to wonder if we might be
somewhere fairly far along on the curve charted above, feeling safer and
safer carrying all these economic loads, but with an ever greater and greater
chance of developing the incidence of one or another severe,
"dislocating," and "unlikely" event. (1)
LAW OF COMPOUNDING NUMBERS
20% Gains for 3 years then a 20% loss results in = 8.4% CAGR
20% Gains for 3 years then a 35% loss results in = 2.9% CAGR
See the illusion?
Our government is doing us no
favors with an
artificial extend and pretend strategy that makes us feel safer and which
consequentially starts the public spending and investing again. Based on
risk, it is both premature and dangerous to your financial health.
DYNAMIC HEDGING
PORTFOLIO INSURANCE
When
the investigations were made by the government into the causes of the 1987
crash, it was discovered that it was primarily because of the wide
implementation of what was then called Portfolio Insurance. It was the rage
in the late 80's as a way of removing risk from portfolios. At its core,
Portfolio Insurance involved trend following methodologies. Consequentially,
the more stocks moved up, the more your portfolio called for more buying. It
was self re-enforcing. It also worked in reverse and consequentially the
sudden crash. The investigations prompted the introduction of circuit
breakers into exchanges to limit downside moves in any given period of time.
SON-OF-PORTFOLIO INSURANCE
Though Portfolio lost its
appeal after the 1987 crash, it was replaced by what many at the time
referred to as the son-of-portfolio insurance. It was called Dynamic Hedging.
Dynamic hedging is a technique that is widely used by derivatives
dealers to hedge
gamma
or vega
exposures. Because it involves adjusting a hedge as the underlier
moves -- often several times a day -- it is "dynamic. Dynamic hedging is
delta hedging
of a non-linear position with linear instruments like spot positions, futures
or forwards. The deltas of
the non-linear position and linear hedge position offset, yielding a zero
delta overall. However, as the underlier's value moves up or down, the delta
of the non-linear position changes while that of the linear hedge does not.
The deltas no longer offset, so the linear hedge has to be adjusted (increased
or decreased) to restore the delta hedge. This continual adjusting of the
linear position to maintain a delta hedge is called dynamic hedging. (2)
Dynamic Hedging was a major
contributor to the tech bubble run-up in the late 1990's, the 2002-2007
run-ups and the present rally. It is one of the reasons this rally feels so
similar and is being driven for similar reasons. But there is more.
The risks are even greater
today because Dynamic Hedging has allowed other advancements to be layered on
top of it.
With the post tech bubble
crash in 2000 and the subsequent advent of the housing bubble explosion from
2002 to 2007 we saw the emergence of Capital Arbitrage.
CAPITAL ARBITRAGE
I am defining Capital
Arbitrage here (as opposed to the slightly different Regulatory Arbitrage) as
the price difference in the cost of capital through the reduction of risk via
various methods including removing debt obligations (risk) from the balance
sheet. The price difference in capital costs is reflected in a lower interest
coupon or basis point spread.
The advancements in securitization and
financial engineering have allowed this to happen in a dramatic fashion over
the last decade. Consequentially, the ability to extend credit prior to the
financial crisis was almost exponential in its growth - all of which was
hedged through Dynamic Hedging and through newer techniques such as Credit
Default Swaps (CDS). Capital arbitrage fostered yet another bubble until the
reversal once again happened and we had the expected explosive momentum to
the downside.
The table below is a
simplified summary of a lot of the work outlined in recent Extend
& Pretend series articles and the Sultans
of Swap series. It illustrates that almost all forms of standard
accounting practiceS&Procedures have been circumvented through modern
Capital Arbitrage techniques. Whether Corporate accounting with its cost
/accrual structure, Financial and bank accounting with its reserve and
capital ratios or Government accounting with its cash account accounting, it
doesn't matter, they have all been systematically exploited.
There is only one goal,
obscure debt or financial obligations, commitments, guarantees or contingent
liabilities. This is to allow improvement or maintenance in the cost of
capital and thereby allow further increases and gearing (leverage).
REGULATORY ARBITRAGE
Today we have layered yet
another layer of risk onto the already existing structure. It is called
Regulatory Arbitrage.
Regulatory arbitrage is any
transaction that has little or no economic impact on a financial institution
while either increasing its capital or decreasing its required capital. Just
as trading arbitrage
identifies and exploits inconsistencies in market prices, regulatory
arbitrage identifies and exploits inconsistencies in capital regulations.
Regulatory arbitrage undermines the effectiveness of capital regulations. It
is one of the primary motivators for regulators to continually improve
capital requirements. (3)
This new strategy is again intended to remove risks but in
this case you are transferring it to a sovereign government in a number of
fashions. Whether debt or contingent liability obligations, the strategy
involves the sovereign government assuming responsibility and being forced to
create the credit to further the arbitrage.
It is highly sophisticated
with many elements but like the previous stages, it will end badly and likely
violently. This time the probability is that it ends when sovereign
governments fail or are unable to attract investors at satisfactory rates
(i.e. Greece now having to pay over 9% on 10 Year Treasuries versus an
expected 3.5%). Credit rating downgrades and forced increases in collateral calls
will be the catalyst. We are now seeing just the tip of this iceberg
throughout the southern European countries (PIIGS).
We have 'saved' the following
by the public assuming the liabilities after all the profits were earned and
distributed.
|
1.
|
Fannie Mae /
Freddie Mac Agencies
|
1.5 - 2+T
|
|
2.
|
AIG
|
180B
|
|
3.
|
GM / GMAC
|
45B
|
|
4.
|
TARP - Banks
|
700B
|
|
5.
|
FDIC -
Regional Banks
|
??
|
|
===
|
|
|
|
~ $3
Trillion
|
|
|
CONCLUSION
When markets stop functioning
any algorithm breaks down. Trading algorithms are based on certain
fundamental assumptions that have proven invalid over long periods of time.
The false assumptions include:
- Continuous
market liquidity
- Continuity
of markets
- Counterparty
Risk
The exposure these
'discontinuities' create is well respected but to my knowledge it is still
not able to be modeled effectively. The trick therefore is to make as much
money as possible before 'time' delivers the proverbial 'fat tail'. In
layman's language, as former Citigroup CEO Charles Prince so famously
quipped- it is a game of musical chairs and "you must get up and dance
while the music is playing". If you don't 'dance' your competitor will
have the competitive advantage to be able to use an improved stock price to
take you out. It forces fiduciary risk taking. As in a child's game, it takes
enforced rules or the cheating begets cheating.
If the Legislators and
Regulators won't address excessive fiduciary risk taking - then the market
will in a violent and unexpected fashion - with the innocent as the
casualties.
For the complete research
report go to: Extend
& Pretend
Sign Up for the next release
in the Extend & Pretend series: Commentary
SOURCES:
(1) John Hussman's Analysis - (Unable to find link - noted it down years
ago - sorry John)
(2) Dynamic
Hedging - The Risk Glossary.com
(3) Regulatory
Arbitrage - The Risk Glossary.com
The last Extend & Pretend
article: EXTEND
& PRETEND - Uncle Sam, You Sly Devil!
