I was just re-reading Paul Ormerod’s excellent book, Why Most Things Fail and came across a fun section on US monetary history.

The U.S. dollar bestrides the world. Acceptable in every country, fervently desired in most, it is a potent symbol of American economic strength and power. But it was not always so. Indeed, it was less than a hundred years ago that the U.S. Congress established the Federal Reserve Bank, the American equivalent of the Bank of England or European Central Bank.

For most of America’s history  from the English colonies established on the seaboard fringe of the continent over four hundred years ago to the early twentieth century, a wide and at times bizarre range of different types of money circulated within the United States itself. The monopoly of the dollar there is a comparatively recent event. The U.S. republic was established in 1783, but as late as the mid-nineteenth century, a tremendous array of different types of money circulated in America, with states and banks being free to issue their own notes. As late as 1860, there were some 9,000 different kinds of privately issued dollar bills circulating, around a third of which were counterfeit. On no less than six occasions in the first half of the nineteenth century, Congress passed acts allowing foreign coins-French, Spanish, British to circulate as legal tender.

Two attempts to establish a U.S. central bank, of the kind with which we are all now familiar, failed. Prosaically called the First and Second Banks of the United States, both had short lives, which ended by 1840. America then waited until 1907 (sic 1913) before the Federal Reserve Bank, with us today, was established.

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In my book, “The Nature of Value” (Columbia University Press spring 2013), I show how “hot” sectors work like lotteries enticing people in with big promises.  Hot sectors are often in exciting product lead innovation spaces.  Unfortunately great products don’t mean great businesses. Competitive dynamics determine the eventual business margins, not “great products”. You loved Facebook, but must learn the product is not the business model. This is the same as understanding that price is not value. Confusing great products with great businesses gets lots of people in heaps of trouble.

So lets pull a Charlie munger and think about the 2nd order effects of the entrants attracted to a hot product space. In a Lottery hot sector many firms are competing for the big fast growing market prize. Often times, each firm is priced to take it all. The result can be disaster as the hot sector matures and competition erodes the margins of even the fully grown survivors.

PV solar cells are an example of this effect. Each potential winning company originally competed with a $/watt product edge. They then discovered their edge usurped, margins crushed and threat of encroaching technologies still present even at large scales after years of growth.  PV solar firms were a classic case of one-trick innovations in a mostly commmodity market. Customers needed the cheapest $/watt and as long as the technology was robust didn’t differntiate between businesses.  The best manufacturer with a 10 year history was only as good as the ideas coming out of some garage or university yesterday.

Innovation is deeper than product alone, it is a profound process. Quantified research from The Doblin group, shows that innovation covers 10 seperate categories and that sustained margins are held by dominating as many capability categories uniquely as possible. Today’s great new mouse trap isn’t necessarily a business, its just a product innovation capability for some guy to riff on tomorrow. I know. I used to manage 70 science PhDs in Europe’s answer to the MIT media lab innovating in every field of science you can name.

The human desire to make it big fast often leads to disaster. I know this as well through painful personal experience as a software entrepreneur/ founder.  This innate human pattern of betting for the big payoff can be seen in studying pari-mutual horse racing odds and outcomes.  Where long shot bets are placed mostly for emotional kicks more than actual gains.  The insightful blog CSinvesting posted this article on the issue (see middle of post).

I have redacted a few graphics to give a visual summary of the paper by Eric Snowberg and Justin Wolfers.  The data shows the long-shot betting bias over 6.5million horse races. Betting the long shot is just a way to lose faster.

And for the international set, here is 50 years of data. Human nature isn’t changing any time soon.

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As a specialist in understanding sources of business value and applying that to investing I was interested to see how the Long/Short Hedge funds are doing. Running through some data from the EDHEC database, I created the charts below. The first chart is a visual showing the L/S hedge fund index vs. the S&P 500.  There isn’t a lot to see there. You would find that the L/S index outperformed the S&P 500 etc. There are of course back-fill, survivorship and other biases associated with any fund database which significantly lead to over stating performance. The L/S hedge fund index shows a .77 correlation with the S&P 500.

The more interesting graph is the one below.  It is a 60 month rolling annualized return alpha calculated by taking the last 60 months of hedge fund returns and subtracting the S&P 500 returns. This shows an annualized alpha experienced on a rolling 5 year period.  From the hedge fund index perspective it seems L/S hedge fund alpha has a negative trend and is due to hit zero by about 2019.

Now hedge fund alpha isn’t really running out, the more likely story is that over the last decade more and more managers having been piling into hedge funds recognizing them firstly as a great compensation class and then selling them to others as an asset class. The alpha hasn’t disappeared, but the number of the participants without alpha generating skill has likely grown so much as to mask the real alpha making it difficult to find the signal amongst the noise of the 2/20 crowd.

Generating long term positive returns means applying a stable allocation process over time and possessing a deep understanding of the source of value from that process. If you run a fund and want a good analyst or portfolio manager call this guy He has delivered 1,000 bps of alpha each year since starting out in 2007 without a down year and is looking for a place to put his analytical and portfolio management skills to work. Columbia University Press is publishing his book The Nature of Value later this year.

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