The Econophysics Blog

This blog is dedicated to exploring the application of quantiative tools from mathematics, physics, and other natural sciences to issues in finance, economics, and the social sciences. The focus of this blog will be on tools, methodology, and logic. This blog will also occasionally delve into philosophical issues surrounding quantitative finance and quantitative social science.

Friday, March 31, 2006

Ticket Futures Market and Risk-Neutral Pricing

Alan Krueger, an economics professor at Princeton University, wrote an interesting article a while back on the emerging market for ticket futures -- i.e., like forwards/futures for pork bellies, companies are beginning to offer futures for tickets to sporting and other events in the uncertain future -- for the 'Economic Scene' column in the New York Times. You can read the piece at http://www.krueger.princeton.edu/02_02_2006.htm

Prof. Krueger offered an interesting example of pricing under uncertainty and risk using the example of a futures contract for a Super Bowl ticket. Here is an excerpt:
If fans are risk-averse, then ticket futures add economic value. To see this, suppose that there is a 10 percent chance of a fan's team reaching the Super Bowl and that a futures contract costs $250 while a ticket could be purchased the week of the game for $2,500. At these terms, a risk-loving fan intent on going to the Super Bowl if his team plays would wait to buy a ticket for $2,500, and a risk-averse fan would buy a futures contract for $250.

Indeed, a risk-averse fan would be willing to pay more than $250 for a futures contract in this situation. Like an insurance policy, ticket futures sell at a premium over their expected value because they help risk-averse buyers hedge against uncertainty.

To gauge the size of the premium, note that a fan could guarantee a ticket to the Super Bowl by buying a futures contract for every team in a conference; one is bound to make it. Call this expenditure the sure-thing price of a ticket. If fans were risk-neutral, the sure-thing price would equal the price that tickets are expected to cost at game time — say $2,500 this year. The excess of the sure-thing price over $2,500 gives a rough indication of the market valuation of insuring against risk.

Sunday, March 26, 2006

Financial Times on JP Morgan and Credit Derivatives

Financial Times Arts & Weekend section (March 24, 2006) had an interesting article on the role played by JP Morgan bankers (and ex-bankers) in the creation of the market for credit derivatives -- The Dream Machine. An interesting quote from that article:

And what of the future? Some of the leading figures, such as Masters, think there is room for more innovation in the credit derivatives world. For while the basic ideas are now so widely dispersed that they are almost “mass-market” for traders, she believes that “the point about that process is that when something becomes commoditised it lets you create second- or third-generation products”. That should make it easier for bankers to reassemble these derivatives in new and more complex ways - in much the same way that it becomes possible to create more complex computers when there is mass-market production of circuit boards. The next round of innovation, in other words, will be derivatives of credit derivatives, or even “derivatives cubed”.



"Mad Money" Should Make Average Investors Mad

According to a research paper by three Northwestern University researchers, the CNBC show, Mad Money (hosted by Jim Cramer), gives out stock picking advice that should make the average investor boiling mad (and, conversely, the savvy arbitraguer, extremely happy). The following is an excerpt from the paper:

Taken together, our results suggest that the aggregate losers in our event study are the Mad Money viewers who decide to buy the recommended securities when the markets open the following day, and that the winners are the market makers and arbitraguers who sell the overpriced recommended stocks on day 1, as well as the traders who sell the recommended stocks on days 2 through 12.

The paper can be downloaded from SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=870498

Tuesday, March 14, 2006

Harvard Magazine Article on Behavioral Economics & Finance

The March/April 2006 issue of Harvard Magazine has a cover story on behavioral economics and behavioral finance research (with the focus on the work being done at Harvard). You can read the article at http://www.harvardmagazine.com/on-line/030640.html .

It's a very interesting article that covers a wide variety of applications of behavioral finance and economics ranging from micro-finance / economic development to improving 401(k) pension plans. I'm particularly interested in Prof. David Laibson's work on delayed versus available rewards based on the 'primrose path' paradigm in psychology.

There are a couple of interesting sidebars to the article: one on neuroeconomics and the other on game theory. You can get to them via links on the main page of the article.

Friday, March 10, 2006

March Madness?: Basketball, Bookies, Point Shaving, and Forensic Economics

David Leonhardt, a New York Times columnist who writes about economics and quantitative approaches to analyzing sports, wrote a piece this Wednesday (Mar. 8) on Justin Wolfers' forensic economics research that strongly suggests that players on college basketball teams that are heavy favorites (according to the odds indicated by the point spreads in Las Vegas sports books) may be engaging in a form of cheating called 'point shaving.' (The article: Sad Suspicions About Scores in Basketball.)

Justin Wolfers is an economist at the Wharton School, University of Pennsylvania. His homepage is at http://bpp.wharton.upenn.edu/jwolfers/index.shtml . You can download his research directly at http://bpp.wharton.upenn.edu/jwolfers/Papers/PointShaving.pdf .

This type of forensic economics and forensic finance is incredibly interesting. It's already been popularized by Levitt and Dubner's Freakonomics, and the less well known book by Prof. Ray Fair (of Yale), Predicting Presidential Elections and Other Things (the title of the book doesn't do it justice; the book is really more about applications of econometrics to creative and interesting areas like the price of vintage wine as well as predicting presidential elections).

By the way, I crossed paths very briefly with Justin Wolfers when he was a graduate student at Harvard (he probably wouldn't remember me though). He seemed like a nice guy. It's worth noting that he had the pony tail back then too!



Monday, March 06, 2006

Real Estate Finance & Economics in the New York Times, the Economist, and Business Week (and a few words about Zillow)

Today's edition of the New York Times Magazine was devoted mostly to real estate. Three articles of interest for readers of the Econophysics Blog are: the Freakonomics column by Steven Levitt (an economist at the University of Chicago) & Stephen Dubner -- Endangered Species, a profile of Harvard economist Edward Glaeser -- Home Economics, and a polemic on the mortgage interest deduction by Roger Lowenstein -- Who Needs the Mortgage-Interest Deduction?

Another interesting resource related to all of this is the Freakonomics supplement to the column. It has links to original sources (including some interesting pieces of empirical research) and other resources for those interested in learning more about the workings of real estate finance and economics (and where it all might be heading).

The Economist, in last Thursday's (March 2) issue, published its annual global house price index (see diagram below for a sample from the index). The Economist has generally taken a pessimistic view of the rise in home prices (they subscribe to the 'real estate bubble' school of thought). The article in question makes a persuasive case that -- even without a bursting of the bubble -- problems can arise due to the run up in prices.


Business Week has an article showing data that indicates there are regional disparities in home prices even though the aggregate national data shows an overall gain in prices.

One development that I believe might prove to be revolutionary is Zillow.com -- a website that provides a model that purports to help people to quantitatively assess the value of real estate. It uses a sophisticated algorithm presumably based on statistical / econometric analysis of real estate values (which it calls the "Zestimator"). One of the main reasons people use real estate agents is because -- as middlemen with proprietary sources of information helpful in the valuation of properties -- their 'expertise' is presumably needed in properly assigning a price to real estate (either as a bid price or as an asking price). A resource like Zillow may help to reduce the power that real estate agents have over valuation issues. This is important -- according to econometric research done by Steven Levitt and others -- because real estate agents use their influence in pricing to the detriment of those they represent (and for their own gain when they represent themselves in real estate transactions).

I'm planning on having more to say about Zillow and real property valuation issues sometime in the near future. Stay tuned.

Saturday, March 04, 2006

Deal or No Deal: Risk Aversion, Loss Aversion, and Fair Odds (or lack thereof)

I saw last night's (Thursday, March 2, 2006) episode of NBC's TV game show Deal or No Deal. As the Freakonomics Blog has pointed out, the show provides an experiment of sorts that could be seen as an empirical 'test' of economists' ideas about risk aversion, risk neutrality, etc.

What I have noticed about the show -- especially last night's episode -- is that most of the deals that are offered by the 'banker' tend to be 'low-ball' offers until the later stages of the game (if the contestant lasts that long). What I mean by 'low-ball' is that the banker tends to not offer fair odds (by that I mean, in this context, what gambler's think of when they are being offered payoffs that match the statistical expected value). It is only in the latter stages of the game that the contestant is offered deals that are close to fair odds.

That is what happened to the first contestant on last night's episode. The deal that he accepted -- which I believe was for $250,000 -- exactly matched the mathematical expected value of having a 50% chance (which is the probability he was facing) of getting $500,000. It turned out to be a profitable move since the case he originally chose had some miniscule amount in it (rather than the $500,000). The contestant's final decision doesn't violate economists' ideas about risk neutral / risk averse decision making.

Up until that point, however, this particular contestant exhibited behavior that would confound both economists and common sense (a particularly strange situation since economics and common sense are often at odds with each other). If I remember correctly, prior to the final offered deal, the contestant had been offered a deal where he actually got slightly better than fair odds. If I recall correctly, he was offered a deal where he could get a sure deal for around $168,000 when he faced a 1/3rd chance of getting $500,000 (so the sure thing value exceeded the expected value of the payoff).

I'm not sure what to make of that kind of decision making under risk and time pressure. Behavioral economists often talk of 'loss aversion' as opposed to 'risk aversion'; with loss aversion, people are willing to take risks in order to minimize losses. It doesn't seem like the contestant was loss averse since he was willing to forgo a good sure thing (even passing up a better than fair odds deal) for the risky chance of getting the $500,000 (the higher amounts of $1 million and above were knocked off earlier). Neoclassical economists can't find much comfort in the contestant's decisions (at least not until the very end) since even they would have screamed for him to take the deal. Even an intellectually oriented gambler would have been baffled by the contestant's decisions. Only an irrational, compulsive gambler could have justified the decisions made by the contestant prior to the final decision point (when all but the craziest gambling addict would have approved of the decision).

It's worth noting, of course, that this was just one contestant. He may have been an anomaly. A more careful study of this show (in it's Italian version) has been done and can be downloaded from Francesco Trebbi's webpage (he was one of the co-authors).

One final thing to note, at least from a psychological perspective, is that the 'banker' may adjust his offers up or down based on the banker's perceptions of the contestant's attitude toward risk, loss, and gambling. For example, if the banker thinks that the contestant is likely to be very confident about his or her chances of winning, the banker may adjust his offer up slightly from whatever baseline the banker is using (of course, if the contestant is wrong about his/her confidence in his/her luckiness, then he/she will fall flat on his/her face). Just a thought. I'm not sure about it since I don't know the exact algorithm (if he has one; although, from what I saw from the last few offers on last night's show, it probably is based on expected value calculations) that the banker uses to come up with the dollar figure for the offer.

It may also be the case that the banker is instructed to make low-ball offers (considerably less than fair odds / expected value deals) in the early stages of the game in order to make the contestants tend to want to reject the earlier offers and spur them on to continuing on with the game. This could be done for ratings purposes. After all, NBC doesn't want to gamble on its profits by risking losing its viewers.