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Misunderstanding Risk

Don M. Chance, PhD, CFA William H. Wright, Jr. Endowed Chair for Financial Services Louisiana State University CFA South Africa Investment Conference 2009 9 September, 2009 Johannesburg, South Africa. Misunderstanding Risk. A Most Difficult Decision.

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Misunderstanding Risk

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  1. Don M. Chance, PhD, CFA William H. Wright, Jr. Endowed Chair for Financial Services Louisiana State University CFA South Africa Investment Conference 2009 9 September, 2009 Johannesburg, South Africa Misunderstanding Risk

  2. A Most Difficult Decision • What would you do if you found a suspicious growth inside a non-vital organ? • The doctor is unable to identify whether the lump is malignant or not without surgery • The doctor gives you a choice: • Remove the lump only, examine for the presence of cancer, and return for a second more extensive surgery if cancer is found • Remove the entire organ, which you can live without, a more drastic surgery Don M. Chance, Ph.D., CFA

  3. Making Decisions Under Risk • Not just in the financial world, but in life in general • We constantly make decisions under risk • Rarely are we ever presented certainty • How we make those decisions tells us a lot about the human appetite for risk and how we so often make risk mistakes Don M. Chance, Ph.D., CFA

  4. What is Risk? Don M. Chance, Ph.D., CFA

  5. Elements of the Definition of Risk? • Exposure to an event • Uncertain outcomes • (Usually) undesirability of one or more outcomes Don M. Chance, Ph.D., CFA

  6. Measuring Risk • Measures of risk • Probability or odds • Standard deviation • Worst case scenario • In investing • Maximum drawdown • Beta • Value-at-Risk Don M. Chance, Ph.D., CFA

  7. Probability as a Measure of Risk • We do not understand it • We misuse it • All too often we assume the bell curve and oftentimes we ignore the tails (the Black Swan effect) Don M. Chance, Ph.D., CFA

  8. A Simple (and somewhat silly) Example: The Monty Hall Problem Behind these doors are three prizes: a car and two worthless prizes. A contestant chooses one door. Door # 1 Door #2 Door #3 Don M. Chance, Ph.D., CFA

  9. The Monty Hall Problem (cont.) Let’s say the contestant chooses Door # 3. Monty then opens door # 1 to reveal one of the two worthless prizes and offers the contestant the opportunity to switch doors. $0 Door #2 Door #3 (the contestant’s choice) Should the contestant switch? Most people say it doesn’t matter. Don M. Chance, Ph.D., CFA

  10. But it matters a lot! You double your chance of winning by switching. Odds of winning by not switching: 1-in-3 Odds of winning by switching: 2-in-3 Don M. Chance, Ph.D., CFA

  11. A Tougher and More Serious Situation(described by GerdGigerenzer in the book Calculated Risks.) • One in every one-hundred 40-year old women has breast cancer • A mammogram detects 90% of all breast cancers and gives a false positive 9% of the time • A 40-year old women gets a positive mammogram. What is the probability she has breast cancer? • A sample of doctors believed it was very high (80-90%) Don M. Chance, Ph.D., CFA

  12. 10,000 40-year old women 100 with BC 9,900 without BC 90 have + m/m 10 have – m/m 891 have + m/m 9,909 have – m/m Don M. Chance, Ph.D., CFA

  13. Using Misleading Risk Information to Sell a Product A pharmaceutical company advertises that a new cholesterol- lowering drug reduces heart attack risk by 22%. (Also described in Calculated Risks) Don M. Chance, Ph.D., CFA

  14. 1,000 people with high cholesterol 1,000 people with high cholesterol Receive new drug Receive placebo 32 die of heart attack 968 do not die of heart attack 41 die of heart attack 959 do not die of heart attack 22% fewer heart attacks (9/41 = 22%) Don M. Chance, Ph.D., CFA

  15. The Correct Interpretation 9 out of 1,000 people were helped by the drug. In other words, of every 111 people who took the drug (1,000/9 = 111), one person was helped. Would you take or recommend a drug in which 111 people have to take it for one person to benefit? Don M. Chance, Ph.D., CFA

  16. O. J. Simpson: What He Taught Us About Risk Don M. Chance, Ph.D., CFA

  17. The Defense Claim 100,000 battered women in U. S 40 murdered by their batterer 99,960 not murdered by their batterer Odds that a battering led to a murder = 40/100,000 = 0.04% or 1-in-2,500 Don M. Chance, Ph.D., CFA

  18. The True Picture (not argued by the prosecution) 100,000 battered women in U. S 40 murdered by their batterer 5 murdered by someone else Odds that a battered and murdered woman was killed by her batterer = 40/45 = 89% Don M. Chance, Ph.D., CFA

  19. The Weather • We are continuously confronted with risk information about the weather • What does x% probability of rain mean? • What about hurricane prediction paths? • Why is the weather more predictable than most other uncertainties in life? Don M. Chance, Ph.D., CFA

  20. Political Polls • What does it mean to say that 51% favor candidate A and 49% favor candidate B? • What does a sample of 1,000 people out of a population of 100 million registered voters mean? • Why does the public opinion of politicians change so quickly? Don M. Chance, Ph.D., CFA

  21. Jury Duty • The American judicial system is terribly flawed in that it prohibits use of all information related to the risk • “Innocent until proven guilty” Don M. Chance, Ph.D., CFA

  22. Voting • Voting is an amazingly low-risk situation, yet we often act like it is a high-risk one • Elected officials are typically elected by a fairly uninformed populace • They constantly clamor for an even more uninformed populace to vote • Which is better? Large turnout of uninformed voters or small turnout of informed voters • Ballot measures Don M. Chance, Ph.D., CFA

  23. Mental Health and Emotional Instability • Identifying serial killers in advance • Examples, true and false • Virginia Tech shooting • Imams on a plane • Suspicious people Don M. Chance, Ph.D., CFA

  24. Predictors • Predictors are notoriously pessimistic • Airlines • Restaurants • Hospitals • Why? • And what about the weather forecaster? • What about economists? • Granville, Kaufman, Roubini • Politicians running for office against an incumbent • Predictors are almost useless, not because they cannot predict but because they engage in self-protecting bias Don M. Chance, Ph.D., CFA

  25. Evaluating Predictors • We too often succumb to the small sample fallacy • It takes an incredibly large sample to adequately evaluate predictive ability Don M. Chance, Ph.D., CFA

  26. What does it Mean to Make a Mistake in Making a Decision Under Risk? • Given the choices A and B, you choose A • Assume that A works out poorly and it is apparent that B would have worked out better • Was that a mistake? • Maybe • Maybe not, but perhaps a lesson can be learned (e.g., WMD in Iraq) Don M. Chance, Ph.D., CFA

  27. Common Risk Mistakes • Confusing ex post with ex ante • Inability to distinguish luck from skill or lack of it • Fearing risk less the further back bad outcomes occur • Overweighting highly improbable events and underweighting highly probable events Don M. Chance, Ph.D., CFA

  28. Common Risk Mistakes(continued) • Trusting government for risk information • Being irrational about risk • Assuming that if a “bad” outcome occurs, it would have been better to have made a different decision • Does the reward justify the risk? • Is the cost of risk reduction worth it? Don M. Chance, Ph.D., CFA

  29. Common Risk Mistakes(continued) • Expecting some decision makers to be 100% correct • Paying too much attention to predictions Don M. Chance, Ph.D., CFA

  30. The Loneliness of the Decision Maker • Sports • Killing a product: the Coca-Cola case • Decisions made by doctors • Presidents and leaders of countries • In understanding the decision maker, we need to appreciate the Heisenberg Uncertainty Principal (of social science) • Obama: “I was right about the war” • McCain: “I was right about the surge” • Changing one’s mind (flip-flopping) Don M. Chance, Ph.D., CFA

  31. Risk Information – So Misleading • Violence in Iraq? Violence in the U. S. • A new source of energy • School violence • Which is riskier? • a house with a gun or a house with a swimming pool • Lawn mowers or beds Don M. Chance, Ph.D., CFA

  32. How We (All too Often) Cope with Risk • Litigation (mostly in the U. S.) • Making someone else take the risk (as in sports) • Taking the safe route • Relying too much on others, such as the government, to make our decisions • Overstating the amount of information you have Don M. Chance, Ph.D., CFA

  33. Using Risk Ignorance to our Advantage • A personal story from my teen years • D-Day: 6 June, 1944 Don M. Chance, Ph.D., CFA

  34. Viewing the Risk as Though it were Someone Else’s • Torture Don M. Chance, Ph.D., CFA

  35. Making a Tough Decision Under Risk: The Prisoner’s Dilemma • Two people are arrested and charged with the same crime • The suspects are put into different rooms and separately interrogated • Each is given an offer • Testify against the other and receive immunity (cooperate) • If only one cooperates, that person is free and the other is punished • If both cooperate, each is given a lighter sentence • If neither cooperates, both will be punished Don M. Chance, Ph.D., CFA

  36. The Prisoner’s Dilemma Assuming that each prisoner has no idea what the other will do, each should independently decide to cooperate. Why? Don M. Chance, Ph.D., CFA

  37. How do We Manage Risk? • Panic • Forecast • Decide on how much risk we want, how much risk we have, the cost of changing the level of risk, and whether an adjustment is economically justified Don M. Chance, Ph.D., CFA

  38. Making Good Decisions under Risk • Some times we have too many choices • Get as much information as possible • Decide which risks are worth taking and which are not • For risks not worth taking, evaluate the cost of eliminating the risk and do so if supported by cost-benefit analysis • Be moderately pessimistic Don M. Chance, Ph.D., CFA

  39. What Should We do After the Fact? • Do not assume that a decision that turned out adversely was a bad risk management decision • A correct risk management decision was one that would be made again if the circumstances were identical • Do not evaluate the decisions of others without putting ourselves in their position Don M. Chance, Ph.D., CFA

  40. What Does This Mean for Investment Managers • Use probability and risk quantification but be sure you use it carefully • Respect the past but don’t obsess over it • The financial media knows no more than anyone else (and oftentimes a lot less) • Investment decisions that look bad after the fact can actually be good decisions Don M. Chance, Ph.D., CFA

  41. Risk is Good • Do you really want to know the future? • What would a financial world be like if there were no risk? Don M. Chance, Ph.D., CFA

  42. Thank you for having me here to speak. If you have any questions later: dchance@lsu.edu Feel free to email me for a copy of this presentation. Don M. Chance, Ph.D., CFA

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