This is similar to a scenario described by Michael Lewis, in The Big Short. In Lewis’ telling, Michael Burry noticed that there was a company (Liberty Interactive, if I remember correctly), that was in legal trouble. This legal trouble was fairly serious—it might have resulted in the liquidation of the company. However, if the company came through the legal trouble, it had good cash flow and was a decent investment.
Burry noticed that the company was trading at a steep discount to what cash flow analysis would predict its share price to be. He realized that what was occurring was that there was one group of investors who were betting that the company would survive its legal troubles, and trade at a “high” price, and there was another group of investors who thought that the stock was going to go to zero because of the legal trouble the company found itself in. Burry read the legal filings himself, came to the conclusion that it was probable that the company would survive its brush with the law, and invested heavily in it. As it turn out, his prediction was proven correct, and he made a nice return.
Burry’s position was a likely outcome. The short-sellers who thought that the stock would go to zero bet on another likely outcome. The only truly unlikely outcome is the one that the market, as a whole, was predicting when Burry made his investment. The price of the stock was an average of two viewpoints that, in a fundamental sense, could not be averaged. Either the company loses its court case, and the stock goes to zero. Or the company survives its court case (perhaps paying a fine in the process), and proceeds with business as usual. As a result, the current market price of the company is not a good guide to its long-term value, and it was possible, as Burry did, to beat the market.
I’m confused by this example. This seems exactly the kind of time where an averaged point estimate is the correct answer. Say there’s a 50% chance the company survives and is worth $100 and a 50% chance it doesn’t and is worth $0. In this case, I am happy to buy or sell the price at $50.
Doing research to figure out it’s actually an 80% chance of $100 means you can buy a bunch and make $30 in expected profit. This isn’t anything special though—if you can do research and form better beliefs than the market, you should make money. The different world models don’t seem relevant here to me?
Not sure if that’s what happened in that example, but you can bet that a price will rise above some threshold, or fall below some threshold, using options. You can even do both at the same time, essentially betting that the price won’t stay as it is now.
But whether you will make money that way depends on the price of options.
This is an example where the true distribution of future prices is bimodal (with the average between the modes). If all you can do is buy or sell stock, then you actually have to disagree with the market about the distribution to make money.
Without having information about the probability of default, there might still be something to do based on the vol curve.
As a result, the current market price of the company is not a good guide to its long-term value, and it was possible, as Burry did, to beat the market.
That doesn’t sound right. That tactic doesn’t make you more (or less) likely to beat the market than any other tactic.
The current price isn’t an accurate representation of its actual long-term value, but it’s an accurate representation of the average of its possible long-term values weighted by probability (from the market’s point of view).
So you might make a bet that wins more often than it loses, but when it loses it will lose a lot more than it wins, etc. You’re only beating the market when you get lucky, not on average; unless, of course, you have better insights than the market, but that’s not specific to this type of trade.
Someone disagree voted with this and I curious know why. (concretely: if you have information contradicting this, I’d like to here about that so I don’t incorrectly update on it)
This is similar to a scenario described by Michael Lewis, in The Big Short. In Lewis’ telling, Michael Burry noticed that there was a company (Liberty Interactive, if I remember correctly), that was in legal trouble. This legal trouble was fairly serious—it might have resulted in the liquidation of the company. However, if the company came through the legal trouble, it had good cash flow and was a decent investment.
Burry noticed that the company was trading at a steep discount to what cash flow analysis would predict its share price to be. He realized that what was occurring was that there was one group of investors who were betting that the company would survive its legal troubles, and trade at a “high” price, and there was another group of investors who thought that the stock was going to go to zero because of the legal trouble the company found itself in. Burry read the legal filings himself, came to the conclusion that it was probable that the company would survive its brush with the law, and invested heavily in it. As it turn out, his prediction was proven correct, and he made a nice return.
Burry’s position was a likely outcome. The short-sellers who thought that the stock would go to zero bet on another likely outcome. The only truly unlikely outcome is the one that the market, as a whole, was predicting when Burry made his investment. The price of the stock was an average of two viewpoints that, in a fundamental sense, could not be averaged. Either the company loses its court case, and the stock goes to zero. Or the company survives its court case (perhaps paying a fine in the process), and proceeds with business as usual. As a result, the current market price of the company is not a good guide to its long-term value, and it was possible, as Burry did, to beat the market.
I’m confused by this example. This seems exactly the kind of time where an averaged point estimate is the correct answer. Say there’s a 50% chance the company survives and is worth $100 and a 50% chance it doesn’t and is worth $0. In this case, I am happy to buy or sell the price at $50.
Doing research to figure out it’s actually an 80% chance of $100 means you can buy a bunch and make $30 in expected profit. This isn’t anything special though—if you can do research and form better beliefs than the market, you should make money. The different world models don’t seem relevant here to me?
Not sure if that’s what happened in that example, but you can bet that a price will rise above some threshold, or fall below some threshold, using options. You can even do both at the same time, essentially betting that the price won’t stay as it is now.
But whether you will make money that way depends on the price of options.
This is an example where the true distribution of future prices is bimodal (with the average between the modes). If all you can do is buy or sell stock, then you actually have to disagree with the market about the distribution to make money.
Without having information about the probability of default, there might still be something to do based on the vol curve.
That doesn’t sound right. That tactic doesn’t make you more (or less) likely to beat the market than any other tactic.
The current price isn’t an accurate representation of its actual long-term value, but it’s an accurate representation of the average of its possible long-term values weighted by probability (from the market’s point of view).
So you might make a bet that wins more often than it loses, but when it loses it will lose a lot more than it wins, etc. You’re only beating the market when you get lucky, not on average; unless, of course, you have better insights than the market, but that’s not specific to this type of trade.
Someone disagree voted with this and I curious know why. (concretely: if you have information contradicting this, I’d like to here about that so I don’t incorrectly update on it)