Introduction
Valuable insights can
be derived from the same principle when making decisions for investing in
securities and betting at the race track. While I am a senior trustee at
Caltech, I do not claim to understand quantum mechanics. What I do recognize is
that in 1927 Werner Heisenberg identified a way of thinking now called the
Uncertainty Principle. He found that there is a fundamental limit to the
precision of measuring unequal objects. Stripping out all the math, which is
beyond me, the mere act of measuring the difference changes its precision.
Translating this to my dollars and sense world means that the value of a
comparison in terms of utility declines the more it is measured. In effect the
more popular an analytical relationship becomes the less valuable it is.
One
Successful Asset Manager’s Application
Marathon Asset
Management of London starts a section in its well-written monthly report
entitled: TOO MUCH INFORMATION, with a quote from T.S. Eliot. “Where is the
wisdom we have lost in knowledge? Where is the knowledge we have lost in
information?”
What Marathon is decrying
is the frequency that the modern publicly traded company is supplying
information to the market directly or through analysts and the media. This flow
of information is augmented by trade associations and others’ intra-period
industry data. Market prices move in the direction of the perceived value of
the information only to be reversed often on the interpretation of the
next morsel of information. This leads to stocks turning over much more rapidly
than in the past. I have noted that the increase in individual stock turnover
has led to a general increase in active mutual fund turnover. Unfortunately, this
trend has not added to investment returns.
Through June 9th on a year to date basis in the fund asset class identified as US Diversified Equity funds - with one exception - the two best performing groups were the Mid-Cap Value funds + 7.80% and Small- Cap Value funds +7.68% (S&P500 Index funds were up +4.23). What is more interesting to me is an almost double gain from the one exception of +13.00% for Equity Leverage funds. This suggests to me it is not the fund’s selection skills but the use of borrowings (margin) and derivatives. One would think we are describing hedge funds. However, two others fund performance statistics tell a more complete story: Dedicated Short Bias funds -14.20% and Alternative Long/Short Equity funds -0.10%. I have now transmitted to you too much information.
Through June 9th on a year to date basis in the fund asset class identified as US Diversified Equity funds - with one exception - the two best performing groups were the Mid-Cap Value funds + 7.80% and Small- Cap Value funds +7.68% (S&P500 Index funds were up +4.23). What is more interesting to me is an almost double gain from the one exception of +13.00% for Equity Leverage funds. This suggests to me it is not the fund’s selection skills but the use of borrowings (margin) and derivatives. One would think we are describing hedge funds. However, two others fund performance statistics tell a more complete story: Dedicated Short Bias funds -14.20% and Alternative Long/Short Equity funds -0.10%. I have now transmitted to you too much information.
Marathon would believe
that the information above is a dump not a filter in terms of data
discrimination, giving equal weight to each factor. There was no attempt to
fathom what is missing. (I have often found that what is missing from an
investment proposal is more important than what is provided.) The frequency of
information input or overload leaves little time for deep thinking and
pondering not only what is missing, but what weight one puts on each factor
considered and how much to value what is unknown. The last exercise is critical
to avoid the single biggest contributor to large losses, overconfidence. The
last step often leads to a decision not to do something. While not
axiomatic, lower turnover funds produce higher on average results over
long-term investment periods that we favor.
Unfolding Brexit
Pictures
We have one more
weekend before the referendum. I hope in next week's blog post to devote more
space to its impact and probabilities. However, in reaction to last week’s blog
plus some conversations I had at a meeting sponsored by the London Stock
Exchange on the value of listing funds at that exchange, there are three
thoughts that I would like to share:
1. Unless the spread
between the Remain and the Leaves is greater than 10 percentage points, the
odds favor other elections on this and related topics in the UK and within the
EU.
2. Regardless of the
result, the 2017 elections in both Germany and France will be impacted possibly
in different directions.
3. The use of foreign
political leaders and foreign media comments can prove that such outside
influences are counter-productive to the mass of voters.
Has
the Commodity Cycle Bottomed?
As noted above, the US Diversified Equity funds have produced low to middle single digit returns year to date.
There are ten sector funds that are showing on average double digit returns.
Not only are these Precious Metals funds +88.89% but also Energy, Base Metals, Agriculture
and Infrastructure funds. Clearly these are recovering from deep multi-year
bottoms. But when the average Sector fund is up+9.58% compared with the US Diversified
funds’ gain of 3.26% are the markets
telling us something? This is exactly the kind of question that Marathon and I are
both calling for some deep thinking. The data above was compiled by my old
firm, Lipper, Inc., part of Thomson Reuters.
A
Professional Analytical Pause
On most weekends I
draft these posts on Sunday, but this week because a significant concert of the
New Jersey Symphony Orchestra, I am beginning to draft Saturday afternoon. But
I am going to suspend my scribing to watch the 148th running of the
Belmont Stakes. For many track followers this is the single most important race
for three year-olds. Its importance is similar to the senior prom in many US
high schools. In both cases this one event will be remembered for a lifetime
and a point of passage for these equine adolescents. In almost all cases this
is the only time they will be asked to race for a mile and a half. The winner
will initially be highly valued as a sire of future champions.
I will be watching not
only from a racing standpoint, but also from an analytical viewpoint. Earlier
in the week the weather looked for rain at race time. In theory this would have
helped the favorite who has won in the rain several times in the past. The backers
of the favorite were hoping for a repeat set of conditions and therefore
results. This may be like picking a fund on the basis of superior past
performance in down markets. But in each case for the very moment the question
is how will the candidate do with a change in conditions?
Conclusions After
the Belmont
As is often the case,
lessons from one field have application in others. The race was won by a long shot
meaning the experts and the bulk of the betters were mistaken. The interesting
thing for me is the application of the Uncertainty Principle. It did rain right after the race, but
that did not appear to be the deciding factor why the favorite (while close
during the race) faded at the end of the race to finish almost last. If one
filtered all of the past performance data and only looked at what could have
been expected to be the interim best time at each leadership position, one
could have deducted that this year’s Belmont Stakes had too much early speed
and took the favorite too much effort to get to the front and couldn’t easily overcome
the early leaders. In addition, there were a couple of fresher closers at the
end.
From an investment
point of view there were some lessons:
Past performance needs to
be carefully analyzed and broken into components. The weight of past victories
in terms of money earned was not a deciding factor. Finally, betting on future
trends even when right, (the rain), the timing can be slightly off and not
workout as forecasted.
In Summary
We should recognize
that we live and must invest in an uncertain world. We need to focus on
critical subsets of information. Finally our confidence should be measured to
avoid overconfidence.
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Copyright © 2008 - 2016
A. Michael Lipper,
C.F.A.,
All Rights Reserved.
Contact author for limited redistribution permission.
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Contact author for limited redistribution permission.
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