Via Columbia Uni's Professor Andrew Gelman at his Statistical Modeling, Causal Inference, and Social Science blog, July 15:
Economist Gary Smith sends along this post with the above title and the subtitle, “Market prices are not invariably equal to intrinsic values.” Here’s Smith:
For a while, there was a popular belief among finance professors that the stock market is “efficient” in the sense that stock prices are always correct — the prices that an all-knowing God would set. Thus, investors can buy any stock, even a randomly selected stock, and be confident that they are paying a fair price.
This belief was based on seemingly overwhelming evidence that changes in stock prices are difficult to predict. Efficient market enthusiasts argued that if stock prices are always correct, taking into account all currently available information, then any changes in stock prices must be due to new information which, by definition, is impossible to predict. Therefore, the evidence that changes in stock prices are hard to predict proves that the stock market is efficient.
This argument is a common fallacy. The fact that A implies B does not mean that B implies A. . . Here, the fact that an efficient stock market implies that stock prices are impossible to predict does not mean that if stock prices are impossible to predict then the stock market must be efficient. . . .
For example, the crazy gyrations in bitcoin prices are ample evidence that financial markets are not efficient. Since bitcoins generate no income, their intrinsic value is zero, yet people have paid hundreds, thousands, and tens of thousands of dollars for bitcoins. One explanation is that the evidence is strong that bitcoin prices have been manipulated by pump-and-dump schemes in which the unscrupulous circulate boisterous rumors while they trade bitcoin back and forth among themselves at higher and higher prices, and then sell to the naive who are lured into the market by the rumors and seemingly ever-rising prices.
One fascinating test of the pump-and-dump theory is based on a remarkable relationship known as Benford’s law. . . .
We’ve talked about Benford’s law before—it’s even in Teaching Statistics: A Bag of Tricks—so I’ll skip a few paragraphs of Smith’s exposition and get to the part that’s new to me:
For example, if we compare the price of a company’s stock one day and the price several days later, the price several days later is determined by the product of the daily percentage changes and, so, is governed by Benford’s law. To test this, I [Smith] looked at the prices of all stocks traded on the New York Stock Exchange (NYSE) on July 6, 2021. For 29.1 percent of the stocks, the leading digit was 1, which is close to the 30.1 percent implied by Benford’s law. The number 9 was the leading digit for only 4.8 percent of the stocks, which is close to the 4.6 percent implied by Benford’s Law. Figure 1 shows the full theoretical and empirical distributions. The close correspondence is striking for such a relatively small data set.
Figure 2 compares the distribution of the leading digits of the price of Berkshire Hathaway stock since 1980. Again, the fit is not perfect but reasonably close....
....MUCH MORE, including the bitcoin bit.
Our last visit to the SMCISS blog:
February 8, 2021
Professor Gelman Is Not Impressed By The "Nudge" People
Andrew Gelman is Professor of statistics and political science at Columbia Uni., the guy who tells the other social scientists how to get their numbers right so they can at least give the appearance of being a science. He has a very tart tongue which, combined with a high level intellect is fun to watch taking on sacred cows and shibboleths. As long as you aren't the target of said intellect and/or sharp tongue.
Here he is looking at Cass Sunstein as Sunstein's new book rolls out....
An old favorite from 2018:
"Big Oregano Strikes Again"
I can't wait until he gets around to some of the spurious correlations propagated by the International Parsley Cartel....
And many more, use the 'search blog' box, upper left, if interested.
