14
Dic

The art of being lucky: And get paid for it

Escrito el 14 Diciembre 2008 por Antonio Rivela Rodríguez en Uncategorized

As I said in my prior blog, this week We will be discussing the concept of randomness.

..And why would I care about being lucky? … well … that´s the reason why many hedge fund managers/traders have been paid so far. They got lucky for couple of years (track record discussed in our last blog) and now they will get paid for a while…

They call it alpha. We call it: … mmm… Randomness.

Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets is a book written by Nassim Nicholas Taleb, a philosopher of randomness about the fallibility of human knowledge.

The book was selected by Fortune as one of “The Smartest Books of All Time”.

The book’s name, Fooled by Randomness, has also become an idiom in English used to describe when someone sees a pattern where there is just random noise.

Taleb sets forth the idea that modern humans are often unaware of the very existence of randomness.

They tend to explain random outcomes as non-random.

Human beings overestimate causality, e.g., we see Mosques in the clouds instead of understanding that there are just random clouds that appear to our eyes as Mosques (or something else);
tend to view the world as more explainable than it really is, i.e., we look for explanations even when there are none.

Other randomness misperceptions discussed:

* Survivorship bias. We see the winners and “learn” from them, while forgetting the huge unseen cemetery of losers.

In finance, Survivorship bias is the tendency for failed companies to be excluded from performance studies because they no longer exist. It often causes the results of studies to skew higher because only companies which were successful enough to survive until the end of the period are included.
For example, a mutual fund company’s selection of funds today will include only those that have been successful in the past.

Many losing funds are closed and merged into other funds to hide poor performance. This is how 90% of extant funds can truthfully claim to have performance in the first quartile of their peers: the other three quarters of funds have closed.

In 1996 Elton, Gruber, & Blake showed that survivorship bias is larger in the small-fund sector than in large mutual funds (presumably because small funds have a high probability of folding). They estimate the size of the bias across the U.S. mutual fund industry as 0.9% per annum, where the bias is defined and measured as: “Bias is defined as average α for surviving funds minus average α for all funds”
(Where α is the risk-adjusted return over the S&P 500. This is the standard measure of mutual fund out-performance).

* Skewed distributions. Many real life phenomena are not 50:50 bets like tossing a coin, but have various unusual and counter-intuitive distributions.

Benford’s law, also called the first-digit law, states that in lists of numbers from many real-life sources of data, the leading digit is distributed in a specific, non-uniform way.

According to this law, the first digit is 1 almost one third of the time, and larger digits occur as the leading digit with lower and lower frequency, to the point where 9 as a first digit occurs less than one time in twenty. The basis for this “law” is that the values of real-world measurements are often distributed logarithmically, thus the logarithm of this set of measurements is generally distributed uniformly.

This counter-intuitive result has been found to apply to a wide variety of data sets, including electricity bills, street addresses, stock prices, population numbers, death rates, lengths of rivers, physical and mathematical constants, and processes described by power laws (which are very common in nature). The result holds regardless of the base in which the numbers are expressed, although the exact proportions change.

Example: a 99:1 bet where you almost always win, but when you lose you lose all your savings. You can easily be fooled by “I won this bet 50 times”.

Per Taleb: “Option sellers, it is said, eat like chickens and go to the bathroom like elephants” (option sellers earn a steady small income from selling the options, but when a disaster happens they lose a fortune).

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