Fat Tails

Tail Dependence

Micro Correlations

Fat Tails

Cooke and Kousky nsf# 0960865

http://www.rff.org/Events/Pages/Introduction-Climate-Change-Extreme-Events.aspx

“Nice” distributions don’t surprise

Tallest so far

Next record

Someday, you’ll meet a taller person

Next record

But Not:

Catastrophes are Different!

Stock market

Hurricanes

Insurance

Nice distribution Women’s height [cm]

Bigger is less bigger Mean excess

Average height above heloise

Mean excess curve decreasing

Fat Tails: Natural disasters

Average above Heat1

Mean excess curve increasing

Worse is more worse Mean Excess

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’

Fat Tail Heuristics

US Flood Claims per $ Income by County and Year

Historical averages just keep growing

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 samples 2500 samples

Thin tail (exponential)

0.02 0.0008

Super Fat 0.5 0.5

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?”

Answer: $4,000

US Flood Claims per $ Income by County and Year

Sobering Data

• Tail Risk Show

http://www.rff.org/News/Features/Pages/Understanding-Fat-Tailed-Distributions-and-What-They-Mean-for-Policy.aspx

Background on Fat Tail Distributions