Dave Naffziger’s Blog

I just returned from a great talk by Dan Ariely, MIT professor and author of Predictably Irrational. Dan walked through a number of different aspects of our decision making process that are far from rational, yet in predictable ways.

I love behavioral economics and particularly enjoy learning about the patterns that we all fall victim to. He didn’t touch on many new concepts, but he did provide additional color around concepts such as our (in)ability to make decisions when faced with overwhelming choice.

Supermarket jam tasting (example from his talk)

A supermarket set up two jam tasting stations. One with 6 jams and one with 24 jams. People could taste as many jams as they wanted. They were then given a coupon and could buy jam. Here are the results of the experiment

The people that visited the 24 jam table were overwhelmed by choice.

Count the Passes
Here was a fun challenge from his presentation:

People apparently have a very hard time counting continuously for 30 seconds. So, the challenge is to see if you can count the number of times that the people wearing white shirts in this video pass the basketball (answer in the comments):

While this challenge wasn’t as directly tied to his research, he used it to show how there are predictable ways that our mind tricks us.

While I haven’t read his book yet (I will), I would expect it to be a very enjoyable read.

For some reason, I seem to read voraciously when my wife is out of town. I recently finished two books that I should have read a long time ago that were both recommended by friends. Jeff lent me John Battelle’s the Search and Rahul lent me Joel Spolsky’s Best Software Writing I

I’ve been a long time reader of both of their blogs, but for some reason figured that their books were for ‘other people’, particularly those less familiar with their online writings. Both were great books and it is kind of criminal that I took so long to get to them.

Joel’s book also triggered me to delve deeper into Clay Shirky’s and Michael Lopp’s writings. I’ve read bits and pieces of their thoughts before, but have now dug deep enough to truly appreciate their insights. Clay’s thoughts on social software are a must read for those developing social software and Michael’s blog (Rands in Repose) is a must read for software managers.

I know I’m a bit late recommending these two, but definitely dig in if you haven’t already.

I read Moneyball awhile back and thoroughly enjoyed Michael Lewis’ look into the ways that statistical analysis was slowly revolutionizing the qualitative methods that were used to recruit, draft and trade in baseball.

Lewis traces statistical analysis of baseball from its origins in Rotisserie leagues, through to todays big money sport. In particularly, Moneyball takes a look at the Oakland As under manager Billy Beane and their unlikely success (given their very small salary budgets). As the quant geek that I am, I had presumed that big league baseball was already studying such stats, so the book was an enjoyable look into the transformation of the sport.

Overall, a very easy to read and tremendously enjoyable for baseball fans and quant geeks alike.

— Written using the zoundry destop blog editing software

I thoroughly enjoyed Freakonomics - the authors provide a look at some popularly held beliefs about why things are they way they are.

Steven Levitt goes on to prove several fascinating points:
- teachers cheat on high stakes tests that their students take (and their cheating can be algorithmically discovered)
- car seats don’t save kids lives (I’ll probably still buy one though)
- and of course the finding that he is most notorious for: the legalization of abortion is responsible for the drop in crime in the 90s.

I love the way he approaches problems (believe no one), and the analytical approach & counter-approach that he takes. Overall, it is an incredibly enjoyable read.

Mandelbrot does a great job illustrating how traditional Gaussian models of financial markets don’t apply, and that in reality markets follow classical fractal models (chaotic).

He takes two approaches:
1. Statistical: For example the 1987 market collapse represents a change equivalent to 22 standard deviations. The odds of that happening are 10^50. In fact there were many swings greater than 5 standard deviations - way more than modern finance theory allows.

2. Graphical: He uses graphs and charts extensively to clearly illustrate what a proper Gaussian market would look like and what actual markets look like.

Although it has become widely accepted that markets are not a truly ‘random walk’, much of modern finance theory is based on this critical assumption. Everything from options pricing through to the capital asset pricing model (CAPM).

Most corporate investment decisions today are made from CAPM calculations that depend on Beta, an improper measure of risk. Mandelbrot’s book is a call to action of the finance research establishment to abandon the normal distribution and rebuild their theories with a more accurate depiction of the behavior of markets.

Well-written and well-worth a read for all involved professionally or personally in financial markets - they are far riskier than we have imagined.