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# Seeing Tomorrow: Rewriting the Rules of Risk

## by Ron S. Dembo and Andrew Freeman, 1998, John Wiley, 260 pages, hardcover, US\$27.95.   ISBN 0-471-24736-7.

Risk and decision-making continue to inspire new books.  This one is a particularly easy read.  Mathematical details are minimal.  There are many stories about decision failures; proper problem framing would have steered decision makers toward better choices.

This book prescribes a method to adjust values for attitude toward risk.  The authors are particularly concerned about Regret (which they capitalize).  The value of a risk situation is:
Value = U - lR
where U is the expected value Upside (positive outcomes from the benchmark reference), R is the expected  value Regret (negative outcomes from the benchmark), and l (Greek letter lambda) is the risk aversion constantl values > 1 represent risk aversion.

 Seeing Tomorrow is another book featuring a "prescriptive" form of decision analysis.  (A better one, I think, is Smart Choices, reviewed in an earlier Tip.)  These methods are helpful.  However, in my humble opinion, the method of adjusting for risk aversion is inferior to using an exponential utility function to express risk policy.  Another book that I recommend is Against the Gods.

The best part of Seeing Tomorrow is the stories.   Most of the transactions are drawn from banking, insurance, and mergers and acquisitions.  Decision failures happened because people failed to recognize or give adequate weighting to possible downside outcomes.  In several cases, losing the deal was often accompanied by more Regret than was appreciated beforehand.

Dembo and Freeman start early with a good definition:

 "Risk is a measure of the potential changes in value that will be experienced in a portfolio as a result of differences in the environment between now and some future point in time."

There are four key components in how the authors approach risk management:

• Time Horizon
• Scenarios (what events might unfold, and what would these do to the future value of investments?)
• Risk Measure (they advocate using Regret, the expected value or probability-weighted average of unfavorable outcomes at the time horizon)
• Benchmarks (reference for comparing our results)

The approach so far is excellent reading.  Their quantitative method might appear workable at first glance.  Upon deeper inspection, you might have the same problems as I found.

 The book twice uses an example where a person is faced with an 0.80 chance of gaining \$1000 and 0.20 chance of losing \$3000.  The authors suggest that the selling the upside, 0.20 chance of \$1000, might be worth \$300 to a decision-maker.   Simultaneously, this person might be willing to buy insurance for the 0.20 chance of -\$3000 downside for -\$100.  Thus the value is U-R = \$300-\$100=\$200. [l was not used in the equation this time.] [Coincidentally, this is the same as the expected value, 0.8(\$1000)+0.2(-\$3000)=\$200.] It believe that the fatal flaw in "the authors ground-breaking risk rules" (from the dustjacket) is that a rational (read conservative) person should be willing to pay more that \$600 to insure against (or eliminate) a 0.20 chance of losing \$3000.

I recommend reading this book for a broad discussion of risk and decision-making with colorful examples.  Please ignore the calculations. While I won't go so far as to call it "junk analysis," I believe that most people can find the mainstream decision analysis calculation methods to be more logical yet accessible.

—John Schuyler, September 1999

Copyright © 1999 by John R. Schuyler. All rights reserved. Permission to copy with reproduction of this notice.