The secret of Tiger Woods' success, according to former coach Butch Harmon:

His work ethic on his golf swing, his work ethic in the gym, his mental toughness, his discipline, the way he budgets his time. On top of that, he probably has more talent than anybody that has ever played.

So he's got that going for him, which is nice.

[via Bloomberg]

And, of course, the obligatory Caddyshack video, this time on the Dalai Lama's golf tricks:

One of the trickier questions in the business of calculating default risk -- the likelihood of a firm missing payments on a credit note -- is in the feedback dynamics of the thing. Sure, you can estimate interest coverage, capital requirements, etc., but all those things presume that everything else stays more or less static, which is rarely the case, and even less likely during extreme market duress, such as that faced by Bear Stears.

One way of asking the question is as follows: How does your default risk change based on the number of times you have been perceived to have default risk? What is the feedback?

A recent paper looks at this subject using a stochastic urn moel, one where you pull a ball from an imaginary urn, and then, based on the color of the ball take a particular action. Specifically, the ball color tells you the likelihood of default -- none, risky, or default in this simplified three-level model -- and then there is a reinforcement mechanism that kicks in based on the number of times you have been in the risky state.

Got it? It's fairly straightforward, at least conceptually, even if the mathematics of these Polya urn processes can be a bear (no pun intended). Analytics aside, the results are interesting, with the stochastic urn model doing a better job than more traditional default models in matching actual defaults. The following graph shows that nicely, with the traditional Z-score model not doing nearly as nice a job UbGesm (the urn model) in tracking against actual defaults.

One of the trickier questions in the business of calculating default risk -- the likelihood of a firm missing payments on a credit note -- is in the feedback dynamics of the thing. Sure, you can estimate interest coverage, capital requirements, etc., but all those things presume that everything else stays more or less static, which is rarely the case, and even less likely during extreme market duress, such as that faced by Bear Stears.

One way of asking the question is as follows: How does your default risk change based on the number of times you have been perceived to have default risk? What is the feedback?

A recent paper looks at this subject using a stochastic urn moel, one where you pull a ball from an imaginary urn, and then, based on the color of the ball take a particular action. Specifically, the ball color tells you the likelihood of default -- none, risky, or default in this simplified three-level model -- and then there is a reinforcement mechanism that kicks in based on the number of times you have been in the risky state.

Got it? It's fairly straightforward, at least conceptually, even if the mathematics of these Polya urn processes can be a bear (no pun intended). Analytics aside, the results are interesting, with the stochastic urn model doing a better job than more traditional default models in matching actual defaults. The following graph shows that nicely, with the traditional Z-score model not doing nearly as nice a job as UbGesm (the urn model) in tracking against actual defaults.

Many people, myself included, worry about the politicization of the U.S. Federal Reserve. To what extent have recent decisions -- the bailout of Bear Stearns, introducing new lending facilities, etc. -- been driven by markets and economic need, versus being driven, to some extent, by political considerations?

It's a tough question to answer, but one way of backing in is to understand how much time the Fed's senior officials spend in private meetings with politician and political appointees. According to ace Fed watchers at the Financial Markets Center, Alan Greenspan met with senior political officials in the 1996-2000 period about twice a week. They deemed that frequency "apolitical". Post 2000, however, Greenspan's time with political sorts escalated, with him meeting at Treasury and with the President an average of 3.1-times per week.

How has current Fed chief Ben Bernanke fared in maintaining Fed political neutrality during the credit crisis? Well, according to the aforementioned FMC, in his first year in office Bernanke averaged 2.2 political meetings a week, which is in-line with what we saw from Greenspan in his early days. He was, to that way of thinking, being fairly apolitical, at least as evidenced by the amount of time he spent with ear-bending politicians and their appointees.

But that has seemingly changed. According to data I recently received via an FOIA request for Ben Bernanke's daybook covering the 11/07-03/08 period, he is spending considerably more time with political sorts than he did in his early term. Instead of averaging twice a week, he is now averaging 3.1-times week, a 50% increase, or right up there with amount of pol-time Alan Greenspan did during the period from 2000 forward.

Are these mandarins, or junior no-name senators from East Wherever? No. Bernanke meets weekly, and often twice-weekly, with Treasury Secretary Paulson, even having had dinner with him on a Saturday not long ago. Good for him, of course, because Paulson never invites me over, but it is unusual stuff.

To to clear, I'm not saying Fed chiefs should never meet with politicians. Far from it. It is a useful source of information, and the Fed is, even at arm's length, a quasi-governmental body. I am saying, however, that a further politicization of the Fed -- at least as evidenced by a material increase in the frequency of meetings with key officials -- is something worth watching, especially during a time of crisis.

Wish I had more time to look at the results of this paper, because its results strike me as entertainingly implausible -- not to mention sort of creepy and unhygienic -- but I'm at least intrigued:

Experts Online: An Analysis of Trading Activity in a Public Internet Chat Room

BRUCE MIZRACH
Rutgers, The State University of New Jersey - Department of Economics
SUSAN WEERTS
Rutgers, The State University of New Jersey - Department of Economics

---

March 16, 2008

Abstract:
We analyze the trading activity in an Internet chat room over a four-year period. The data set contains nearly 9,000 trades from 676 traders. We find these traders are more skilled than retail investors analyzed in other studies. 55% make profits after transaction costs, and they have statistically significant alphas of 0.17% per day after controlling for the Fama-French factors and momentum. Traders hold their winners 25% longer than their losers. 42% trade both long and short, with equal success rates, and almost double the profit per trade when short. The estimates show a strong influence from other traders, with a buy (sell) order 40.7% more likely to be of the same sign if there has been a recent post. Traders improve their skill over time, earning an extra $189 per month for each year of trading experience. They also gain expertise in trading particular stocks. Traders who raise their Herfindahl index by 0.1 raise their profitability by $46 per trade.

In case people hadn't seen it, here is a screen capture of the iPhone 2.0 microcode containing a reference to the presence of Infineon's 3G baseband chipset in that upcoming product.

Nice catch by the folks at Ziphone.

I'm out for the balance of the day in meetings. Behave yourselves, especially those of you along the torch route in San Francisco.

Quote of the day comes in the dizzying Perils of Pauline-style adventure that is MSFT's attempt to buy YHOO.

Recall: At the end of Episode 26 the evil MSFT had forlorn YHOO strapped to the tracks, saying YHOO has only three minutes to give up the gold's location before a freight train rushes through and crushes YHOO flat. Cue whistle in the middle distance as the credits roll.

But wait! As Episode 27 begins, mute and legless beggar AOL has appeared in a wheelchair! It is frantically signing "I'll help!" as it lurches its way across the rocky ground. And then, however, curses! The fat and corrupt NWS starts rolling boulders in AOL's wheelchair's path, painfully slowing its progress to YHOO. Meanwhile stationmaster GOOG has woken up from a drunken stupor and is trying to switch the rusty tracks, sending the oncoming train in another direction.

And then the end credits roll, saying "Stay Tuned for Episode 28 ...."

Got all that? It's, you know, complicated. Anyway, here is the quote of the day:

...Yahoo might have difficulty convincing its shareholders that a Yahoo-AOL combination is attractive.

Gosh, you think? Thanks.

[via WSJ]