Tag Archives: stock

Trading Options – Stock Market

Empirica follows a very particular investment strategy. It trades options, which is to say that it deals not in stocks and bonds but with bets on stock and bonds. Imagine, for example the General Motors stock is trading at $50, and imagine that you are a major investor on Wall Street. An options trader comes up to you with a proposition. What if, within the next three months, he decides to sell you a share of GM at $45? how much would you charge for agreeing to buy it at that price? you would look at the history of GM and see that in a three-month period it rarely dropped 10 percent, and obviously the trader is only going to make you buy his Gm at $45 if the stock drops below that point. So you say you’ll make that promise, or sell that option, for relative small fee, say, a dime. You are betting on the high probability that GM stock will stay relatively calm over the next three month, and if you are right, you’ll pocket the diem as pure profit. The trader, on the other hand, is betting on the unlikely even that GM stock will drop a lot, and if it happens, his profits are potentially huge. If the trader bought a million options from you at a dime each and Gm drops to $35, he’ll buy a million shares at $35 and turn around and force you to buy them at $45, making himself suddenly very rich and substantially poor.

The particular transaction is called, in the argot of Wall Street, an out-of the-money option. But an option can configured in vast number of ways. you could sell the trader a GM option at $30, or, if you wanted to bet against GM stock going up, you could sell a GM option at $60. You could sell or buy options on bonds, on the S&P index, on foreign currencies, or mortgages, or on the relationship among any number of financial instruments of your choice; you can bet on the market booming, or the market crashing, os the market staying the same. Options allow investors to gamble heavily and turn one dollar into ten. They also allow investors to hedge their risk. The reason your pension fund may not be wiped out in the next crash is that it has protected itself by buying options.

What drives the options game is the notion that the risks represented by all these bets can be quantified; that by looking at past behavior of GM, you can figure out exact chance of GM hitting $45 in the next three months, and whether at $1 that option isa good or bad investment. The process is also like the way insurance companies analyze actuarial statistics in order to figure out how much the charge for a life-insurance premium, and to make those calculation every investment bank has, on staff, a team of PhDs, physicists from Russia, applied mathematicians from China, and computer scientist from India. On Wall Street, those PhDs are called quants.

Nassim Taleb and his team at Empiricia are quants. But they reject the quant orthodoxy, because they don’t believe that things like the stock market behave in the way that physical phenomena like mortality statistic do. Physical events, whether death rates or poker game, are the predictable function of a limited and stable set of factors, and tend to follow what statisticians call a normal distribution, a bell curve. but do ups and own of the market follow a bell curve? the economist Eugene Fama once studied stock prices and pointed out that if they followed a normal distribution, you’d expect a really big jump, what he specified as movement five standard deviation from the mean, once every seven thousand years. In fact, jumps of that magnitude happen in the stock market every three or four years, because investors don’t behave with any kind of statistical orderliness. They changed their mind. They do stupid things. They copy one another. They panic. Fama concluded that if you charted the ups and downs of the stock market, the graph would have a “fat tail, meaning that at the upper and lower ends of the distribution there would be many more outlying events than statisticians used to modeling the physical world would have imagined.

What the Dog Saw and other adventures – Malcolm Gladwell