Saturday, April 4, 2009

Game of shorting: Is it really easier to figure out losers?

Having been rejected a bailout, GM might file for bankruptcy. Was it easy to predict such an outcome 10 years ago? I feel we might have folks who will argue either way. Buffett made following observation on the auto industry in his 1999 talk at Sun Valley, Idaho (source: The Snowball by Alice Shroeder):

There were two thousand auto companies: the most important invention, probably, of the first half of the twentieth century. It had an enormous impact on people’s lives. If you had seen at the time of the first cars how this country would develop in connection with autos, you would have said, “This is the place I must be”. But of the two thousand companies, as of a few years ago, only three car companies survived. And, at one time or another, all three were selling for less than book value, which is the amount of money that had been put into the companies and left there. So auto companies had an enormous impact on America, but in the opposite direction on investors.

Now, sometimes it’s much easier to figure out the losers. And of course, the thing you should have been doing was shorting horses.
Buffett showed following slide:

1900 – 17 million
1998 – 5 million

And said, "Frankly, I am kind of disappointed that the Buffett family was not shorting horses throughout this entire period. There are always losers."

During my undergraduate curriculum of computer science and engineering, I used 6 programming languages: Fortran, Cobol, Pascal, C, Lisp and C++. Depending upon whom you talked to, you would have received a different response as to which language might be the winner. However, there was a consensus on which language is going to be the loser. It was: Cobol. Looking at the scenario two decades later, if we see return on investment on the technology, Cobol might very well be the winner.

So, is it really easy to predict the losers? The keyword in Buffett’s statement “sometimes it’s much easier to figure out the losers” is, I feel, “Sometimes”. And there lies the catch. Exactly when is it easier to identify losers? Would the answer lie in understanding a type of business moat called “switching cost”? Perhaps. But, for now, I would prefer to stay with the question.


  1. Vinay,

    Shorting involves getting 2 things right:
    1) identifying the short candidate
    2) the timing of the short sale

    Identifying the right short candidate does not necessarily mean predicting which company will be a loser. It just means finding companies where current market price is unlikely to be justified except in most optimistic scenarios. The high price along with broken business model makes a good short bet.

    So finding the short candidates is not that hard. What is hard is timing the short right.

    When you short a stock, your potential losses are unlimited. If the stock you shorted starts rising in price, you have to keep pumping new money in to meet margin requirements. Sometimes the sudden upswing in price causes so much pain that a mad rush to close out the short trade take place - a situation known as short squeeze.

    The danger of short squeeze is ever present even in developed markets and blue chip stocks. Recently a short squeeze in Volkswagon stock wiped out some well known hedge funds.

    During the internet bubble, many smart investors got burned shorting the dot-com companies - even when their analysis was correct and the companies they shorted went burst eventually. The key phrase here is 'eventually'.

    As John Maynard Keynes said: "The market can remain irrational longer than you can remain solvent."

  2. Thanks, Ravi. This was really useful.