1. Fat Tails Tail Dependence Micro Correlations Fat Tails Cooke and Kousky nsf# 0960865 http://www.rff.org/Events/Pages/Introductio n-Climate-Change-Extreme-Events.aspx

2. “Nice” distributions don’t surprise Tallest so far Next record Someday, you’ll meet a taller person Next record

3. But Not:

4. Catastrophes are Different! Stock market Hurricanes Insurance

5. Nice distribution Women’s height [cm] Bigger is less bigger Mean excess Average height above heloise Mean excess curve decreasing

6. Fat Tails: Natural disasters Average above Heat1 Mean excess curve increasing Worse is more worse Mean Excess

7. Fat Tail heuristics US crop insurance claims mean excess Variance is finite Variance is Infinite US crop insurance claims running average Historical averages ‘average out’

8. Fat Tail Heuristics US Flood Claims per $ Income by County and Year Historical averages just keep growing

9. Katrina cost 100$B What’s the chance that the Next Katrina will cost >200$B? Probability that next extreme > 2 x current extreme 100 samples2500 samples Thin tail (exponential) 0.020.0008 Super Fat0.5

10. Ask someone from St. Tammany County, LA: ‘After Katrina, flood loss claims in your county totaled $240 per dollar income (2000 dollars); in the next flood at least as bad as Katrina, what do you expect your (2000) dollar loss per dollar income to be?”

11. Answer: $4,000 US Flood Claims per $ Income by County and Year

12. Sobering Data Tail Risk Show http://www.rff.org/News/Features/Pages/Und erstanding-Fat-Tailed-Distributions-and-What- They-Mean-for-Policy.aspx Background on Fat Tail Distributions