Risk Identification and Measurement参考.ppt

T3.* HN, Ch. 3 McGraw-Hill/Irwin Copyright ? 2004 by the McGraw-Hill Companies, Inc. All rights reserved. Chapter 3 Risk Identification and Measurement Identifying Business Risk Exposures Property Business income Liability Human resource External economic forces Identifying Individual Exposures Earnings Physical assets Financial assets Medical expenses Longevity Liability Probability Distributions Probability distributions Listing of all possible outcomes and their associated probabilities Sum of the probabilities must equal 1 Two types of distributions: discrete continuous Presenting Probability Distributions Two ways of presenting discrete distributions: Numerical listing of outcomes and probabilities Graphically Two ways of presenting continuous distributions: Density function (not used in this course) Graphically Example of a Discrete Probability Distribution Random variable = damage from auto accidents Possible Outcomes for Damages Probability $0 0.50 $200 0.30 $1,000 0.10 $5,000 0.06 $10,000 0.04 Example of a Discrete Probability Distribution Example of a Continuous Distribution Continuous Distributions Important characteristic of density functions Area under the entire curve equals one Area under the curve between two points gives the probability of outcomes falling within that given range Probabilities with Continuous Distributions Find the probability that the loss $5,000 Find the probability that the loss $2,000 Find the probability that $2,000 loss $5,000 Possible Losses Probability $5,000 $2,000 Risk Management Probability Distributions Ideally, a risk manager would know the probability distribution of losses Then assess how different risk management approaches would change the probability distribution Example: Which distribution would you rather have? Accident Cost No RM Prob Insurance Accident Cost + Insurance Cost Summary Measures of Loss Distributions Instead comparing entire d