All posts by Jim Garven

My name is Jim Garven. I currently hold appointments at Baylor University as the Frank S. Groner Memorial Chair of Finance and Professor of Finance & Insurance. I also currently serve as an associate editor for Geneva Risk and Insurance Review. At Baylor, I teach courses in managerial economics, risk management, and financial engineering, and my research interests are in corporate risk management, insurance economics, and option pricing theory and applications. Please email your comments about this weblog to James_Garven@baylor.edu.

A Beloved Professor Delivers The Lecture of a Lifetime

Usually when I open the Wall Street Journal in the morning, I don’t expect to have an emotionally moving experience. This morning was different as I read Jeff Zaslow’s article entitled “A Beloved Professor Delivers The Lecture of a Lifetime”. I then went to the online version of the Wall Street Journal and found a related article by Jeff Zaslow entitled “The Professor’s Manifesto: What it Meant to Readers”. Both articles tell the story of Dr. Randy Pausch, a Carnegie Mellon University computer science professor who has pancreatic cancer and expects to live for just a few months. Just one week ago, Dr. Pausch gave what was billed as his “last lecture.”

Here are the (less than 5 minute) video versions of both articles:


A Beloved Professor Delivers The Lecture of a Lifetime

The Professor’s Manifesto: What it Meant to Readers

The full (1 hour, 25 minute) video of Dr. Pausch’s “last lecture” is available in Windows Media Player format from Carnegie Mellon University and also on Google Video.

The Tort Tax

Apparently, the total cost of the US tort system continues to grow. Relative to GDP, the “direct” or “static” costs of litigation — including damage awards, plaintiff attorneys’ fees, defense costs, administrative costs and deadweight costs from torts such as product liability cases, medical malpractice litigation and class action lawsuits, grew from 2.04% of GDP in 2001 to 2.44% of GDP in 2006. However, the total cost of tort is quite a bit higher than this because of the manner in which the tort system creates incentives for economically unproductive behavior. Yesterday’s Wall Street Journal article entitled “The Tort Tax” outlines various “dynamic” or “indirect” costs related to tort, and concludes that once these costs are taken into consideration, the actual total costs of tort are more like 6.4% of GDP; in 2006 dollars this comes to $865 billion (2006 GDP is estimated to be $13.45 trillion). This amount is equivalent to the total annual output of all six New England states, or the yearly sales of the entire U.S. restaurant industry. On a per capita basis, this comes out to $2,883 per year per American (note that the population of the United States is approximately 300 million).

It would be interesting to see what total tort costs (including both the direct and indirect costs as described above) are in countries other than the United States. The direct costs of tort are already very well documented. For example, the 2004 Economic Report of the President, notes that the direct costs of the U.S. tort system (as a percent of GDP) are more than 3 times greater than tort costs in the United Kingdom, and are also significantly higher than tort costs in most other industrialized countries.

Financial innovation and market risk premiums

The Wall Street Journal article entitled “The Risk Business” provides an excellent explanation concerning the impact of financial innovation on risk premiums in the global financial markets. The article asks why, in an undeniably dangerous world, risk premiums seem to have drained out of whole classes of financial assets. The answer is that financial innovation (in all its various forms, including the buying, selling, swapping, trading and securitization of risk) has actually made the financial markets much safer for investors by facilitating optimal risk sharing; consequently risk premiums have fallen substantially over time. This is good news, since with better risk sharing gives rise to a more robust and resilient global economy over time.

Actively versus passively managed investment accounts

A long-standing debate in the financial services industry concerns whether investors are better off in the long run with actively versus passively managed investment accounts. Active management is simply an attempt to “beat” the market as measured by a particular benchmark or index such as the S&P 500. One of the more famous active fund managers is Legg Mason’s Bill Miller, who until 2006 had managed to outperform the S&P 500 for 15 years in a row. In 2006, Mr. Miller significantly underperformed the S&P 500. Going forward, no one (including Mr. Miller) really has any way of predicting with any degree of certainty whether Mr. Miller will be able to revert back to systematically beating the market over time.

Notwithstanding Mr. Miller’s impressive historical performance record, it is important to note that typically only 10-20% of actively managed funds outperform the S&P 500 in any given year. Furthermore, the funds belonging to this elite group tend not to consistently replicate this performance in subsequent years; if anything, “winners” in any one period tend on average to subsequently be “losers”. Interestingly, to the extent that there is any persistence, it tends to be among funds which underperform the S&P 500 (e.g., see “Performance Persistence”).

I have worked out a simple numerical example (shown in the Addendum below) which shows that on average, active portfolio management can be expected to result in significantly worse investment performance than a passive (indexed) strategy, based upon the 10-20% odds mentioned above. In order to make money (on an after-transaction cost, risk-adjusted basis) with an active management strategy, over time one has to be significantly better than average in order to have any hope of outperforming an indexed strategy. The numerical example shown below implies that an investor would need to pick winners nearly 50% of the time in order to make active portfolio management worthwhile. Furthermore, I have implicitly assumed that each period represents a completely independent lottery; thus the analysis does not consider the possibility of persistence in one’s investment performance. In order to model persistency, one would need to make the probability of beating the market in any given year (notated below as “p”) a function of previous p’s; I will leave this to the reader as an exercise.

Addendum

Suppose there are four time periods. Let u represent an “up” move where you beat the market,1 and d represent a “down” move where you underperform the market. Thus u > 1, and d < 1.2 Also suppose that you want to invest $1 at t=0. The following table lists all possible portfolio values across all dates and states for four periods:

t=0

t=1

t=2

t=3

t=4

u4

u3

u2

u3d

u

u2d

1

ud

u2d2

d

ud2

d2

ud3

d3

d4

The probability of an up move is p, whereas the probability of a down move is (1-p). After 1 period, there are two possible outcomes; you either have an up move with probability p or a down move with probability p. After two periods, there are three possible outcomes; you either have two consecutive up moves with probability p2, two consecutive down moves with probability (1-p)2, or two moves involving up and down moves with probability 2p(1-p), etc. Taking this out to four periods yields the following set of probability distributions for 1, 2, 3, and 4 periods:

t=0

t=1

t=2

t=3

t=4

P4

p3

p2

4p3(1-p)

p

3p2(1-p)

1

2p(1-p)

6p2(1-p)

1-p

3p(1-p)2

(1-p)2

4p(1-p)3

(1-p)3

(1-p)4


Next, suppose that the odds of beating the market in any one year (p) is 20%, and that u = 1.1. Thus d = 1/1.1 = .91. The following table lists the portfolio values in each possible state occurring 1, 2, 3, and 4 periods from now combined with associated probabilities based upon the previous table:

t=0

t=1

t=2

t=3

t=4

$1.46

$1.33

0.160%

$1.21

0.80%

$1.21

$1.10

4.0%

$1.10

2.560%

$1.00

20%

$1.00

9.60%

$1.00

$0.91

32.0%

$0.91

15.360%

80%

$0.83

38.40%

$0.83

64.0%

$0.83

40.960%

51.20%

$0.75

40.960%


Note that the probabilities in each column sum to 100%. You can calculate the expected value of your actively managed portfolio relative to an indexed portfolio 1, 2, 3, and 4 periods from now by calculating the state contingent portfolio values by their probabilities; thus the expected values at each of these dates are:

Expected (relative) portfolio values

t=1

$0.9473

t=2

$0.8973

t=3

$0.8885

t=4

$0.8332

In other words, by following an active management strategy, on average you can expect to be significantly worse off than you would be if you follow a passive strategy. Furthermore, your underperformance grows worse over time (note that the indexed strategy by definition produces an expected value of $1.00 at each of these future dates).

Here is a copy of the spreadsheet that I used in order to perform these calculations. The reader can perform further sensitivity testing by changing the values of p, u, and d.

Endnotes

[1] By beating the market, I mean that one earns excess returns on an after-transaction cost, risk-adjusted basis by following an active management strategy rather than a passive (indexed) strategy. For example, suppose you invest in an actively managed technology fund which has transactions costs of 200 basis points per year and a portfolio beta of 2. If such a portfolio earns 12% when the market returns 8%, then this is not beating the market; e.g., if the riskless rate of interest is 5%, then the after transactions cost, risk adjusted return on this portfolio is 12% (gross portfolio return) – 2% (transactions costs) – 6% (risk premium = b(E(rm)-rf) = 2(8-5)) = 4%, whereas the passive (indexed) strategy returns ~ 5% on a risk adjusted, after transactions cost basis.

[2] For simplicity, assume that ud = 1; i.e., if you outperform (underperform) the market during the course of the next time period and underperform (outperform) the market during the subsequent time period, this means that your performance over two time periods is in line with the market.

Richard Posner on the effects of asymmetric personal taxation on the distribution of income

Richard Posner has a very interesting post concerning the effects of asymmetric personal taxation on the distribution of income. Specifically, he argues on the basis of Jensen’s inequality that high marginal personal tax rates discourage risk-taking; it therefore follows that if marginal personal tax rates are reduced (as has been the case over the past several years), such a policy encourages risk-taking by removing some of this asymmetry. In my business risk management course at Baylor University, I make a similar argument concerning how asymmetric corporate taxation creates incentives for firms to hedge risk and in some cases avoid risk altogether. Greg Mankiw also has some interesting points to make concerning Posner’s perspectives on this topic.

Baylor University's Finance Department Ranked 15th for Teaching Quality

Baylor students can be quite proud to know that the Hankamer School’s Department of Finance, Insurance, and Real Estate recently placed 15th out of 444 institutions for teaching quality, according to researchers from Western Kentucky University who conducted a study of finance programs. For more information concerning this study, see http://www.baylor.edu/business/index.php?id=38093.

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