Expected value is basically the average payoff from some sort of lottery, gamble or other situation with a randomly determined outcome.
|
|
- Geraldine Cole
- 5 years ago
- Views:
Transcription
1 Economics 352: Intermediate Microeconomics Notes and Sample Questions Chapter 18: Uncertainty and Risk Aversion Expected Value The chapter starts out by explaining what expected value is and how to calculate it, then shows why it isn t really a good way to analyze individuals decisions. Expected value is basically the average payoff from some sort of lottery, gamble or other situation with a randomly determined outcome. For example, if the probability that you will have a bike accident in a year is 0.02 and the loss from that accident would be $1000, then your expected loss from a bike accident in any one year is: E[loss] = 0.98*$ *$1000 = $20. For example, one of the bets offered on a craps table (a dice game that is correctly identified as the crack cocaine of the casino) is a field bet. This is a bet on one roll of the dice that results in the player winning $1 if the numbers 2, 3, 4, 9, 10 or 11 come up and winning $2 if 12 comes up, but losing $1 if any other number comes up. The expected payoff is: E[payoff] = $ $ $ = $ = $ You should know that the probabilities are based on there being 36 possible outcomes from rolling two dice, of which 1 results in a 2 being rolled, 2 rolls result in a 3, 3 rolls result in a 4 and so on. Now, a gamble with an expected payoff of 0 is a fair bet. The example in the book is flipping a coin and winning $1 if the coin comes up heads and losing $1 if the coin comes up tails. The expected payoff is zero. It seems reasonable that a person would be willing to accept a fair bet, but it isn t true. Imagine that you had the opportunity to bet your house on the flip of a coin. If the coin comes up heads you win an identical house or the cash value of your house. If the coin comes up tails, you lose your house. Despite the fact that this is a fair bet most people wouldn t choose to take it.
2 The example given in the book is the St. Petersburg paradox. This is a game with an infinite expected payoff that most people wouldn t pay very much to play. The conclusion from these two examples (betting your house on a coin flip and the St. Petersburg paradox) is that there must be more to understanding decisions under uncertainty than expected value. The more important thing is expected utility, and it is expected utility that people want to maximize. von-neumann-morgenstern Utility When a person faces some gamble, that gamble has an expected value, but it also has an expected utility. The expected utility of a gamble is the utility associated with an amount that, if received with certainty, would make a person just as well off as if she faced the gamble. That s sort of an awful explanation. Try this example. You have some amount of wealth. For the sake of argument let s say that it s $1,000,000. This wealth is fairly secure, but there is a 3% probability that some bad event will happen and you will lose all of your wealth. So you face a gamble that gives you expected wealth of: E[wealth] = $1,000,000* $0*0.03 = $970,000. Now, imagine that you could pay some amount that would allow you assure that you would not lose your wealth if the bad event happens. What is the maximum amount you would be willing to pay for that, and basically insure against the bad event? Let s imagine that you would be willing to pay, at most, $100,000 to eliminate the probability of losing all of your wealth. The payment of $100,000 would leave you with a wealth of $900,000 for sure. Put somewhat differently, you would be indifferent between the gamble with an expected value of $970,000 and having $900,000 for sure. So, the expected utility from facing the gamble is equal to the utility from having $900,000 for sure. Put somewhat differently (and this isn t in the book) $900,000 is the certainty equivalent of the gamble. It is the amount of money that, if received with certainty, gives you the same level of utility as your expected utility from the gamble. The standard assumption is that individuals maximize their expected utility when facing uncertainty.
3 Risk Aversion The usual assumption about sane people is that they like to avoid risk and uncertainty, especially when the potential loss is large relative to their total wealth. In terms of real world behavior, the person who puts down a $5 bet on a sporting event (seemingly liking risk with small amounts of money) will buy insurance against loss of their house and against large health care bills (seemingly avoiding risks potentially involving large amounts of money). One way of stating risk aversion is that if you face a gamble in which you have wealth level w 1 with probability p 1 and wealth level w 2 with probability p 2, you would prefer to have the expected level of wealth E[w] = w 1 p 1 + w 2 p 2 rather than face the risk. Put somewhat differently, the utility level associated with having the expected level of wealth for sure, U(E[w]), is greater than the expected utility level from facing the gamble, E[U(w)]. The standard diagram of this is below. Imagine that there are two levels of wealth that are equally likely. The curve shows the utility of wealth function for a risk averse individual. The levels of wealth associated with the gamble, w 1 and w 2 are equally likely, so the expected level of wealth is midway between w 1 and w 2. The utility associated with w 1 is U(w 1 ) and the utility associated with w 2 is U(w 2 ), and expected utility from facing the gamble is midway between these two utility levels. Now, the utility level associated with having the expected level of wealth, U(E[w]) for sure is greater than the expected utility of wealth from the gamble, E[U(w)]. Again, with the gamble, you have wealth of w 1 with probability 0.5 and you have wealth of w 2 with probability, so the expected wealth, E[w], is midway between these. With the gamble, you have utility of U(w 1 ) with probability 0.5 and you have utility of wealth of U(w 2 ) with probability 0.5, so the expected utility E[U(w)] is midway between these. In addition, if you were to be able to have the expected level of wealth, E[w], for sure, you would be better off than you were facing the gamble. Your level of utility would be U(E[w]).
4 A graph showing a standard utility of wealth curve and a person facing two levels of wealth, one high and one low. The graph also shows the expected level of wealth, the utility associated with the expected level of wealth and expected utility from facing the risk. For example, if we have w1=10,000 and w2=90,000, each with probability 0.5 and U(W)=W 0.5, then: E[W] = 0.5*10, *90,000 = 50,000 U(w1) = 10, = 100 U(w2) = 90, = 300 E[U(W)] = 0.5* *300 = 200 U(E[W]) = U(50,000) = 50, = So, if this person faces the risk of losing 80,000 on a coin flip and having wealth of 90,000 with probability 0.5 and wealth of 10,000 with probability 0.5, then their expected utility level is 200. If, however, they can avoid this risk and have the expected level of wealth, 50,000, for sure, their utility level rises to In addition, for the risk described above, we can describe the certainty equivalent of wealth as being that level of wealth that, if you received it with certainty, would make
5 you just as well off as if you faced the risk. In this case, we can calculate the certainty equivalent, CE, to be: U(CE) = CE 0.5 = 200 CE = = 40,000 So, this person would be indifferent between facing the risk (W=10,000 with probability 0.5 and W=90,000 with probability 0.5) and receiving 40,000 for sure, despite the fact that the expected wealth if facing the risk is 50,000. Put somewhat differently, the maximum amount that this person would be willing to pay for insurance that would allow them to avoid the risk would be 10,000, or the difference between the expected wealth (50,000) and the certainty equivalent of wealth, 40,000. Another example of this is given in Example 18.2 of the textbook. In terms of the above diagram this is: A graph showing the numbers from the above example. The textbook also uses this diagram to show that, holding E[W] constant, as the difference between w1 and w2 increases, expected utility falls. Put somewhat differently, a person who would take a small risk on a coin flip would not necessarily take a large risk on a coin flip. You might be willing to bet $1 on a coin flip, but you would not bet $100,000 on a coin flip.
6 The reason behind this is that risk aversion is associated with diminishing marginal utility of wealth. That is, the U(W) curve is positively sloped, so that more wealth makes you better off, but it flattens out as W increases, so that the additional utility associated with a marginal increase in wealth gets smaller and smaller as wealth increases. This means that the additional utility you get from a $1,000 increase in wealth is smaller than the loss of utility you would suffer from losing $1,000. Put more simply, in terms of utility of wealth, fair bets aren t worth it. Measuring Risk Aversion The presentation in the text gets fairly technical and even involves a Taylor expansion. I ll try to focus on the important stuff here. First, one measure of the degree to which a utility function reflects risk aversion is: U' ' (W) r (W) = > 0 U'(W) If a person is risk neutral, their U(W) function will be linear and U (W) = 0, so r(w)=0. As the degree of risk aversion increases, the second derivative of utility gets bigger (in absolute terms) and the utility function basically gets curvier and r(w) gets larger. As r(w) increases, a person becomes more and more risk averse. A person who is more risk averse is willing to pay more for insurance to avoid a risk. If utility of wealth is given by an exponential function: U(W) = e AW A>0 Then r(w) is independent of wealth, r(w) is constant and we have constant risk aversion. A person with constant risk aversion would be willing to pay the same amount to avoid a risk of a fixed amount regardless of their base level of wealth. This is strange. Constant risk aversion suggests that a person would be willing to pay the same amount for insurance against a $100,000 loss regardless of whether their base wealth was $100,000 or $10,000,000. It makes more sense to expect that as a person s wealth increases, their willingness to pay for insurance against some risk of a fixed dollar amount would fall. A more reasonable measure of risk aversion is relative risk aversion,
7 rr(w) = W r(w) = W U' '(W) U' (W) Two types of utility functions display constant relative risk aversion. They are: W A U(W) = A U(W) = ln W It is worth noting that ln W is the special case of the first of these when A=0. Constant relative risk aversion is nice because willingness to pay for insurance depends on how large the risk faced is relative to base wealth. As wealth increases, a person becomes more willing to take a risk of a fixed dollar amount. For example, a person with preferences characterized by constant relative risk aversion and wealth of $10,000 might not make a $100 bet, but the same person with a wealth of $1,000,000 would make the bet. As the bet becomes a smaller percentage of wealth, the person is more willing to make the bet. The State-Preference Approach to Choice Under Uncertainty This section discusses an approach to dealing with uncertainty in a context that is something like the usual consumer utility model. For the purposes of this section, the two goods are wealth in the good state of the world (like when your house doesn t burn down) and wealth in the bad state of the world (like when your house does burn down). States of the world are situations in the future that you might face, each of which will happen with some probability. The section here discusses two states of the world (a hurricane hits your town or doesn t hit your town), but it is more realistic (and mathematically difficult) to talk about multiple states of the world. For example, instead of saying that a hurricane hits your town or doesn t hit your town, a more realistic but challenging model might discuss the severity of the conditions when a hurricane comes ashore near your town. In any case, we ll restrict the analysis to only two states of the world. So, the two states of the world are the good state and the bad state. The levels of wealth associated with these are W g and W b and the probabilities of these states of the world occurring are π and 1-π.
8 There is a utility of wealth function, U(W), which is state independent. That is, a person has the same utility function regardless of which state of the world they find themselves in. Expected utility depends on a person s wealth in each state of the world, W g and W b, the associated levels of utility, U(W g ) and U(W b ), and the probabilities of each of these, π and 1-π: V(W g,w b ) = π U(W g ) + 1-π U(W b ) Now, a key to understanding this is that the wealth in each state of the world is something that a person purchases before they find out what state of the world they re in. So, before you find out whether or not your house burns down you spend your initial wealth, W, to purchase wealth in particular states of the world. This sounds weird, but it s basically like making bets or buying insurance. For example, imagine that the two states of the world are that a coin comes up heads and that it comes up tails. You start out with $100, but you can t keep it. You must use that $100 to purchase income in the case that the coin comes up heads and income in the case that the coin comes up tails. These levels of wealth, which the book calls contingent commodities because they are contingent on which state of the world actually occurs, must be purchased at some prices, p g and p b. The budget constraint is: W = p g W g + p b W b For example, in the above coin-flipping example, if markets for contingent commodities are fair, you should be able to buy $1 of wealth in the heads state of the world for $0.50. That is, you should be able to pay $0.50 before the coin flip to get $1 if the coin comes up heads. In this case, the price of W g (if the good state of the world is heads) would be 0.50, which is also π. Similarly, you should be able to buy $1 of wealth in the bad state of the world for $0.50, which is equal to 1- π. As another example, imagine that the good state of the world would occur with probability 0.8 and the bad state of the world with probability 0.2. In this case, if markets are fair (meaning, basically, that customers would pay the expected value to buy the contingent good) then, before it is known which state of the world happens, a person should be able to buy $1 in the good state of the world for $0.80 and $1 in the bad state of the world for $0.20. So, the price of $1 in any state of the world should be equal to the probability of that state of the world occurring, if markets are fair. The price of $1 in the good state of the world is π and the price of $1 in the bad state of the world is 1- π.
9 The unavoidable analogy here is to betting on a horserace. The amount that you need to bet in order to get $1 back is very low if you re betting on a horse with a small probability of winning, but will be close to $1 for a horse that everyone thinks is very likely to win. There is a bit of an assumption here that markets for contingent goods ($1 if the good state of the world happens and $1 if the bad state of the world happens) is fair and that everyone knows and agrees upon the probabilities of each state of the world. To put this all together, we have the utility function and budget constraint: V(W g, W b ) = π U(W g ) + 1-π U(W b ) W = p g W g + p b W b If a person maximizes utility then the ratio of the marginal utilities should be equal to the ratio of the prices: V W g V W b = ( ) π U' W g (1 π) U' W b p g = p b = π ( ) 1 π A bit of mutliplying yields: U' (W g ) U' (W b ) = 1 U'(W g ) = U'(W b ) And because the utility function is independent of the state of the world, we have W g = Wb That is, a utility maximizing person will make bets (also known as insurance contracts) so that their wealth in the good state of the world is equal to their wealth in the bad state of the world. This is a reflection of risk aversion in that, if insurance markets are fair, a person will choose to make contracts that will eliminate the risks that they face. Some Practice Try the following questions from the book: 18.1, 18.3, 18.4, 18.5, 18.7
10 1. For a person with U(W)=W 1/2 facing wealth of 90,000 with probability 0.9 and wealth of 0 with probability 0.1, calculate the following: a. expected wealth b. expected utility c. utility of expected wealth d. certainty equivalent of wealth Show each of these on a standard U(W) diagram. U' ' (W) 2. Calculate r ( W) = for the following utility functions: U'(W) a. U(W) = W b. U(W) = W 0.5 c. U(W) = ln W d. U(W) = -W -1 U' ' (W) 3. Calculate rr ( W) = W r(w) = W for the following utility functions: U' (W) a. U(W) = W b. U(W) = W 0.5 c. U(W) = ln W d. U(W) = -W -1
Lecture 11 - Risk Aversion, Expected Utility Theory and Insurance
Lecture 11 - Risk Aversion, Expected Utility Theory and Insurance 14.03, Spring 2003 1 Risk Aversion and Insurance: Introduction To have a passably usable model of choice, we need to be able to say something
More informationChapter 1. Utility Theory. 1.1 Introduction
Chapter 1 Utility Theory 1.1 Introduction St. Petersburg Paradox (gambling paradox) the birth to the utility function http://policonomics.com/saint-petersburg-paradox/ The St. Petersburg paradox, is a
More informationUnit 4.3: Uncertainty
Unit 4.: Uncertainty Michael Malcolm June 8, 20 Up until now, we have been considering consumer choice problems where the consumer chooses over outcomes that are known. However, many choices in economics
More informationChoice under risk and uncertainty
Choice under risk and uncertainty Introduction Up until now, we have thought of the objects that our decision makers are choosing as being physical items However, we can also think of cases where the outcomes
More informationUTILITY ANALYSIS HANDOUTS
UTILITY ANALYSIS HANDOUTS 1 2 UTILITY ANALYSIS Motivating Example: Your total net worth = $400K = W 0. You own a home worth $250K. Probability of a fire each yr = 0.001. Insurance cost = $1K. Question:
More informationECO 203: Worksheet 4. Question 1. Question 2. (6 marks)
ECO 203: Worksheet 4 Question 1 (6 marks) Russel and Ahmed decide to play a simple game. Russel has to flip a fair coin: if he gets a head Ahmed will pay him Tk. 10, if he gets a tail he will have to pay
More informationRisk aversion and choice under uncertainty
Risk aversion and choice under uncertainty Pierre Chaigneau pierre.chaigneau@hec.ca June 14, 2011 Finance: the economics of risk and uncertainty In financial markets, claims associated with random future
More informationChapter 18: Risky Choice and Risk
Chapter 18: Risky Choice and Risk Risky Choice Probability States of Nature Expected Utility Function Interval Measure Violations Risk Preference State Dependent Utility Risk-Aversion Coefficient Actuarially
More informationModels and Decision with Financial Applications UNIT 1: Elements of Decision under Uncertainty
Models and Decision with Financial Applications UNIT 1: Elements of Decision under Uncertainty We always need to make a decision (or select from among actions, options or moves) even when there exists
More informationModels & Decision with Financial Applications Unit 3: Utility Function and Risk Attitude
Models & Decision with Financial Applications Unit 3: Utility Function and Risk Attitude Duan LI Department of Systems Engineering & Engineering Management The Chinese University of Hong Kong http://www.se.cuhk.edu.hk/
More information05/05/2011. Degree of Risk. Degree of Risk. BUSA 4800/4810 May 5, Uncertainty
BUSA 4800/4810 May 5, 2011 Uncertainty We must believe in luck. For how else can we explain the success of those we don t like? Jean Cocteau Degree of Risk We incorporate risk and uncertainty into our
More informationEconomics Homework 5 Fall 2006 Dickert-Conlin / Conlin
Economics 31 - Homework 5 Fall 26 Dickert-Conlin / Conlin Answer Key 1. Suppose Cush Bring-it-Home Cash has a utility function of U = M 2, where M is her income. Suppose Cush s income is $8 and she is
More informationCHOICE THEORY, UTILITY FUNCTIONS AND RISK AVERSION
CHOICE THEORY, UTILITY FUNCTIONS AND RISK AVERSION Szabolcs Sebestyén szabolcs.sebestyen@iscte.pt Master in Finance INVESTMENTS Sebestyén (ISCTE-IUL) Choice Theory Investments 1 / 65 Outline 1 An Introduction
More informationUtility and Choice Under Uncertainty
Introduction to Microeconomics Utility and Choice Under Uncertainty The Five Axioms of Choice Under Uncertainty We can use the axioms of preference to show how preferences can be mapped into measurable
More informationMaking Hard Decision. ENCE 627 Decision Analysis for Engineering. Identify the decision situation and understand objectives. Identify alternatives
CHAPTER Duxbury Thomson Learning Making Hard Decision Third Edition RISK ATTITUDES A. J. Clark School of Engineering Department of Civil and Environmental Engineering 13 FALL 2003 By Dr. Ibrahim. Assakkaf
More informationBEEM109 Experimental Economics and Finance
University of Exeter Recap Last class we looked at the axioms of expected utility, which defined a rational agent as proposed by von Neumann and Morgenstern. We then proceeded to look at empirical evidence
More informationE&G, Chap 10 - Utility Analysis; the Preference Structure, Uncertainty - Developing Indifference Curves in {E(R),σ(R)} Space.
1 E&G, Chap 10 - Utility Analysis; the Preference Structure, Uncertainty - Developing Indifference Curves in {E(R),σ(R)} Space. A. Overview. c 2 1. With Certainty, objects of choice (c 1, c 2 ) 2. With
More informationMicroeconomics 3200/4200:
Microeconomics 3200/4200: Part 1 P. Piacquadio p.g.piacquadio@econ.uio.no September 25, 2017 P. Piacquadio (p.g.piacquadio@econ.uio.no) Micro 3200/4200 September 25, 2017 1 / 23 Example (1) Suppose I take
More informationHow do we cope with uncertainty?
Topic 3: Choice under uncertainty (K&R Ch. 6) In 1965, a Frenchman named Raffray thought that he had found a great deal: He would pay a 90-year-old woman $500 a month until she died, then move into her
More informationECON 581. Decision making under risk. Instructor: Dmytro Hryshko
ECON 581. Decision making under risk Instructor: Dmytro Hryshko 1 / 36 Outline Expected utility Risk aversion Certainty equivalence and risk premium The canonical portfolio allocation problem 2 / 36 Suggested
More informationAnswers to chapter 3 review questions
Answers to chapter 3 review questions 3.1 Explain why the indifference curves in a probability triangle diagram are straight lines if preferences satisfy expected utility theory. The expected utility of
More informationMICROECONOMIC THEROY CONSUMER THEORY
LECTURE 5 MICROECONOMIC THEROY CONSUMER THEORY Choice under Uncertainty (MWG chapter 6, sections A-C, and Cowell chapter 8) Lecturer: Andreas Papandreou 1 Introduction p Contents n Expected utility theory
More informationProblem Set 2. Theory of Banking - Academic Year Maria Bachelet March 2, 2017
Problem Set Theory of Banking - Academic Year 06-7 Maria Bachelet maria.jua.bachelet@gmai.com March, 07 Exercise Consider an agency relationship in which the principal contracts the agent, whose effort
More informationPrice Theory Lecture 9: Choice Under Uncertainty
I. Probability and Expected Value Price Theory Lecture 9: Choice Under Uncertainty In all that we have done so far, we've assumed that choices are being made under conditions of certainty -- prices are
More informationCONVENTIONAL FINANCE, PROSPECT THEORY, AND MARKET EFFICIENCY
CONVENTIONAL FINANCE, PROSPECT THEORY, AND MARKET EFFICIENCY PART ± I CHAPTER 1 CHAPTER 2 CHAPTER 3 Foundations of Finance I: Expected Utility Theory Foundations of Finance II: Asset Pricing, Market Efficiency,
More informationExpected utility theory; Expected Utility Theory; risk aversion and utility functions
; Expected Utility Theory; risk aversion and utility functions Prof. Massimo Guidolin Portfolio Management Spring 2016 Outline and objectives Utility functions The expected utility theorem and the axioms
More informationInvestment and Portfolio Management. Lecture 1: Managed funds fall into a number of categories that pool investors funds
Lecture 1: Managed funds fall into a number of categories that pool investors funds Types of managed funds: Unit trusts Investors funds are pooled, usually into specific types of assets Investors are assigned
More informationConcave utility functions
Meeting 9: Addendum Concave utility functions This functional form of the utility function characterizes a risk avoider. Why is it so? Consider the following bet (better numbers than those used at Meeting
More informationCopyright (C) 2001 David K. Levine This document is an open textbook; you can redistribute it and/or modify it under the terms of version 1 of the
Copyright (C) 2001 David K. Levine This document is an open textbook; you can redistribute it and/or modify it under the terms of version 1 of the open text license amendment to version 2 of the GNU General
More informationUncertainty. Contingent consumption Subjective probability. Utility functions. BEE2017 Microeconomics
Uncertainty BEE217 Microeconomics Uncertainty: The share prices of Amazon and the difficulty of investment decisions Contingent consumption 1. What consumption or wealth will you get in each possible outcome
More informationKey concepts: Certainty Equivalent and Risk Premium
Certainty equivalents Risk premiums 19 Key concepts: Certainty Equivalent and Risk Premium Which is the amount of money that is equivalent in your mind to a given situation that involves uncertainty? Ex:
More informationManagerial Economics
Managerial Economics Unit 9: Risk Analysis Rudolf Winter-Ebmer Johannes Kepler University Linz Winter Term 2015 Managerial Economics: Unit 9 - Risk Analysis 1 / 49 Objectives Explain how managers should
More informationChapter 23: Choice under Risk
Chapter 23: Choice under Risk 23.1: Introduction We consider in this chapter optimal behaviour in conditions of risk. By this we mean that, when the individual takes a decision, he or she does not know
More informationEconomic Risk and Decision Analysis for Oil and Gas Industry CE School of Engineering and Technology Asian Institute of Technology
Economic Risk and Decision Analysis for Oil and Gas Industry CE81.9008 School of Engineering and Technology Asian Institute of Technology January Semester Presented by Dr. Thitisak Boonpramote Department
More informationInsurance, Adverse Selection and Moral Hazard
University of California, Berkeley Spring 2007 ECON 100A Section 115, 116 Insurance, Adverse Selection and Moral Hazard I. Risk Premium Risk Premium is the amount of money an individual is willing to pay
More informationNotes 10: Risk and Uncertainty
Economics 335 April 19, 1999 A. Introduction Notes 10: Risk and Uncertainty 1. Basic Types of Uncertainty in Agriculture a. production b. prices 2. Examples of Uncertainty in Agriculture a. crop yields
More informationConsumer s behavior under uncertainty
Consumer s behavior under uncertainty Microéconomie, Chap 5 1 Plan of the talk What is a risk? Preferences under uncertainty Demand of risky assets Reducing risks 2 Introduction How does the consumer choose
More informationExpected Utility and Risk Aversion
Expected Utility and Risk Aversion Expected utility and risk aversion 1/ 58 Introduction Expected utility is the standard framework for modeling investor choices. The following topics will be covered:
More informationName. Final Exam, Economics 210A, December 2014 Answer any 7 of these 8 questions Good luck!
Name Final Exam, Economics 210A, December 2014 Answer any 7 of these 8 questions Good luck! 1) For each of the following statements, state whether it is true or false. If it is true, prove that it is true.
More informationECON FINANCIAL ECONOMICS
ECON 337901 FINANCIAL ECONOMICS Peter Ireland Boston College April 10, 2018 These lecture notes by Peter Ireland are licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International
More informationDecision Theory. Refail N. Kasimbeyli
Decision Theory Refail N. Kasimbeyli Chapter 3 3 Utility Theory 3.1 Single-attribute utility 3.2 Interpreting utility functions 3.3 Utility functions for non-monetary attributes 3.4 The axioms of utility
More informationMicroeconomics of Banking: Lecture 2
Microeconomics of Banking: Lecture 2 Prof. Ronaldo CARPIO September 25, 2015 A Brief Look at General Equilibrium Asset Pricing Last week, we saw a general equilibrium model in which banks were irrelevant.
More informationECE 302 Spring Ilya Pollak
ECE 302 Spring 202 Practice problems: Multiple discrete random variables, joint PMFs, conditional PMFs, conditional expectations, functions of random variables Ilya Pollak These problems have been constructed
More informationChoice Under Uncertainty (Chapter 12)
Choice Under Uncertainty (Chapter 12) January 6, 2011 Teaching Assistants Updated: Name Email OH Greg Leo gleo[at]umail TR 2-3, PHELP 1420 Dan Saunders saunders[at]econ R 9-11, HSSB 1237 Rish Singhania
More information. This would be denoted. P (heads-up) = 1 2.
Epected utility There is a fundamental difference between a cup of coffee and maybe having a cup of coffee; that is to say, there is an important distinction between being given a cup of coffee and someone
More information1. A is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes,
1. A is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. A) Decision tree B) Graphs
More informationCS 5522: Artificial Intelligence II
CS 5522: Artificial Intelligence II Uncertainty and Utilities Instructor: Alan Ritter Ohio State University [These slides were adapted from CS188 Intro to AI at UC Berkeley. All materials available at
More informationManagerial Economics Uncertainty
Managerial Economics Uncertainty Aalto University School of Science Department of Industrial Engineering and Management January 10 26, 2017 Dr. Arto Kovanen, Ph.D. Visiting Lecturer Uncertainty general
More informationExpectimax and other Games
Expectimax and other Games 2018/01/30 Chapter 5 in R&N 3rd Ø Announcement: q Slides for this lecture are here: http://www.public.asu.edu/~yzhan442/teaching/cse471/lectures/games.pdf q Project 2 released,
More informationProblem Set. Solutions to the problems appear at the end of this document.
Problem Set Solutions to the problems appear at the end of this document. Unless otherwise stated, any coupon payments, cash dividends, or other cash payouts delivered by a security in the following problems
More informationRandom variables. Discrete random variables. Continuous random variables.
Random variables Discrete random variables. Continuous random variables. Discrete random variables. Denote a discrete random variable with X: It is a variable that takes values with some probability. Examples:
More informationChapter 05 Understanding Risk
Chapter 05 Understanding Risk Multiple Choice Questions 1. (p. 93) Which of the following would not be included in a definition of risk? a. Risk is a measure of uncertainty B. Risk can always be avoided
More informationMock Examination 2010
[EC7086] Mock Examination 2010 No. of Pages: [7] No. of Questions: [6] Subject [Economics] Title of Paper [EC7086: Microeconomic Theory] Time Allowed [Two (2) hours] Instructions to candidates Please answer
More informationPh.D. Preliminary Examination MICROECONOMIC THEORY Applied Economics Graduate Program August 2017
Ph.D. Preliminary Examination MICROECONOMIC THEORY Applied Economics Graduate Program August 2017 The time limit for this exam is four hours. The exam has four sections. Each section includes two questions.
More informationFinance 527: Lecture 35, Psychology of Investing V2
Finance 527: Lecture 35, Psychology of Investing V2 [John Nofsinger]: Welcome to the second video for the psychology of investing. In this one, we re going to talk about overconfidence. Like this little
More informationECON 312: MICROECONOMICS II Lecture 11: W/C 25 th April 2016 Uncertainty and Risk Dr Ebo Turkson
ECON 312: MICROECONOMICS II Lecture 11: W/C 25 th April 2016 Uncertainty and Risk Dr Ebo Turkson Chapter 17 Uncertainty Topics Degree of Risk. Decision Making Under Uncertainty. Avoiding Risk. Investing
More information12.2 Utility Functions and Probabilities
220 UNCERTAINTY (Ch. 12) only a small part of the risk. The money backing up the insurance is paid in advance, so there is no default risk to the insured. From the economist's point of view, "cat bonds"
More informationTotal /20 /30 /30 /20 /100. Economics 142 Midterm Exam NAME Vincent Crawford Winter 2008
1 2 3 4 Total /20 /30 /30 /20 /100 Economics 142 Midterm Exam NAME Vincent Crawford Winter 2008 Your grade from this exam is one third of your course grade. The exam ends promptly at 1:50, so you have
More informationIntroduction to Economics I: Consumer Theory
Introduction to Economics I: Consumer Theory Leslie Reinhorn Durham University Business School October 2014 What is Economics? Typical De nitions: "Economics is the social science that deals with the production,
More informationExercises for Chapter 8
Exercises for Chapter 8 Exercise 8. Consider the following functions: f (x)= e x, (8.) g(x)=ln(x+), (8.2) h(x)= x 2, (8.3) u(x)= x 2, (8.4) v(x)= x, (8.5) w(x)=sin(x). (8.6) In all cases take x>0. (a)
More informationExpected Utility Theory
Expected Utility Theory Mark Dean Behavioral Economics Spring 27 Introduction Up until now, we have thought of subjects choosing between objects Used cars Hamburgers Monetary amounts However, often the
More informationCS 4100 // artificial intelligence
CS 4100 // artificial intelligence instructor: byron wallace (Playing with) uncertainties and expectations Attribution: many of these slides are modified versions of those distributed with the UC Berkeley
More informationProbability, Expected Payoffs and Expected Utility
robability, Expected ayoffs and Expected Utility In thinking about mixed strategies, we will need to make use of probabilities. We will therefore review the basic rules of probability and then derive the
More informationECMC49S Midterm. Instructor: Travis NG Date: Feb 27, 2007 Duration: From 3:05pm to 5:00pm Total Marks: 100
ECMC49S Midterm Instructor: Travis NG Date: Feb 27, 2007 Duration: From 3:05pm to 5:00pm Total Marks: 100 [1] [25 marks] Decision-making under certainty (a) [10 marks] (i) State the Fisher Separation Theorem
More informationif a < b 0 if a = b 4 b if a > b Alice has commissioned two economists to advise her on whether to accept the challenge.
THE COINFLIPPER S DILEMMA by Steven E. Landsburg University of Rochester. Alice s Dilemma. Bob has challenged Alice to a coin-flipping contest. If she accepts, they ll each flip a fair coin repeatedly
More informationDepartment of Economics The Ohio State University Final Exam Questions and Answers Econ 8712
Prof. Peck Fall 016 Department of Economics The Ohio State University Final Exam Questions and Answers Econ 871 1. (35 points) The following economy has one consumer, two firms, and four goods. Goods 1
More informationUncertain Outcomes. CS 188: Artificial Intelligence Uncertainty and Utilities. Expectimax Search. Worst-Case vs. Average Case
CS 188: Artificial Intelligence Uncertainty and Utilities Uncertain Outcomes Instructor: Marco Alvarez University of Rhode Island (These slides were created/modified by Dan Klein, Pieter Abbeel, Anca Dragan
More informationLearning Objectives = = where X i is the i t h outcome of a decision, p i is the probability of the i t h
Learning Objectives After reading Chapter 15 and working the problems for Chapter 15 in the textbook and in this Workbook, you should be able to: Distinguish between decision making under uncertainty and
More informationUtility Homework Problems
Utility Homework Problems I. Lotteries and Certainty Equivalents 1. Consider an individual with zero initial wealth and a utility function U(W) = 1 exp[-0.0001w]. Find the certainty equivalent for each
More informationCS 343: Artificial Intelligence
CS 343: Artificial Intelligence Uncertainty and Utilities Instructors: Dan Klein and Pieter Abbeel University of California, Berkeley [These slides are based on those of Dan Klein and Pieter Abbeel for
More informationA. Introduction to choice under uncertainty 2. B. Risk aversion 11. C. Favorable gambles 15. D. Measures of risk aversion 20. E.
Microeconomic Theory -1- Uncertainty Choice under uncertainty A Introduction to choice under uncertainty B Risk aversion 11 C Favorable gambles 15 D Measures of risk aversion 0 E Insurance 6 F Small favorable
More informationMA 1125 Lecture 14 - Expected Values. Wednesday, October 4, Objectives: Introduce expected values.
MA 5 Lecture 4 - Expected Values Wednesday, October 4, 27 Objectives: Introduce expected values.. Means, Variances, and Standard Deviations of Probability Distributions Two classes ago, we computed the
More informationECMC49F Midterm. Instructor: Travis NG Date: Oct 26, 2005 Duration: 1 hour 50 mins Total Marks: 100. [1] [25 marks] Decision-making under certainty
ECMC49F Midterm Instructor: Travis NG Date: Oct 26, 2005 Duration: 1 hour 50 mins Total Marks: 100 [1] [25 marks] Decision-making under certainty (a) [5 marks] Graphically demonstrate the Fisher Separation
More informationBest Reply Behavior. Michael Peters. December 27, 2013
Best Reply Behavior Michael Peters December 27, 2013 1 Introduction So far, we have concentrated on individual optimization. This unified way of thinking about individual behavior makes it possible to
More informationd. Find a competitive equilibrium for this economy. Is the allocation Pareto efficient? Are there any other competitive equilibrium allocations?
Answers to Microeconomics Prelim of August 7, 0. Consider an individual faced with two job choices: she can either accept a position with a fixed annual salary of x > 0 which requires L x units of labor
More information3.1 The Marschak-Machina triangle and risk aversion
Chapter 3 Risk aversion 3.1 The Marschak-Machina triangle and risk aversion One of the earliest, and most useful, graphical tools used to analyse choice under uncertainty was a triangular graph that was
More informationReview for the Second Exam Intermediate Microeconomics Fall 2010
Review for the Second Exam Intermediate Microeconomics Fall 2010 1. Matt recently moved to New York City. To model his behavior, assume he only consumes rental housing (H) and a composite good (X, P X
More informationTECHNIQUES FOR DECISION MAKING IN RISKY CONDITIONS
RISK AND UNCERTAINTY THREE ALTERNATIVE STATES OF INFORMATION CERTAINTY - where the decision maker is perfectly informed in advance about the outcome of their decisions. For each decision there is only
More information14.13 Economics and Psychology (Lecture 5)
14.13 Economics and Psychology (Lecture 5) Xavier Gabaix February 19, 2003 1 Second order risk aversion for EU The agent takes the 50/50 gamble Π + σ, Π σ iff: B (Π) = 1 2 u (x + σ + Π)+1 u (x σ + Π) u
More informationECON FINANCIAL ECONOMICS
ECON 337901 FINANCIAL ECONOMICS Peter Ireland Boston College Spring 2018 These lecture notes by Peter Ireland are licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International
More informationLecture 11: The Demand for Money and the Price Level
Lecture 11: The Demand for Money and the Price Level See Barro Ch. 10 Trevor Gallen Spring, 2016 1 / 77 Where are we? Taking stock 1. We ve spent the last 7 of 9 chapters building up an equilibrium model
More informationECON FINANCIAL ECONOMICS
ECON 337901 FINANCIAL ECONOMICS Peter Ireland Boston College April 3, 2018 These lecture notes by Peter Ireland are licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International
More informationWhat do Coin Tosses and Decision Making under Uncertainty, have in common?
What do Coin Tosses and Decision Making under Uncertainty, have in common? J. Rene van Dorp (GW) Presentation EMSE 1001 October 27, 2017 Presented by: J. Rene van Dorp 10/26/2017 1 About René van Dorp
More informationCHAPTER 6: RISK AVERSION AND CAPITAL ALLOCATION TO RISKY ASSETS
CHAPTER 6: RISK AVERSION AND CAPITAL ALLOCATION TO RISKY ASSETS PROBLEM SETS 1. (e) 2. (b) A higher borrowing is a consequence of the risk of the borrowers default. In perfect markets with no additional
More informationEco 300 Intermediate Micro
Eco 300 Intermediate Micro Instructor: Amalia Jerison Office Hours: T 12:00-1:00, Th 12:00-1:00, and by appointment BA 127A, aj4575@albany.edu A. Jerison (BA 127A) Eco 300 Spring 2010 1 / 32 Applications
More informationLecture 2 Basic Tools for Portfolio Analysis
1 Lecture 2 Basic Tools for Portfolio Analysis Alexander K Koch Department of Economics, Royal Holloway, University of London October 8, 27 In addition to learning the material covered in the reading and
More informationLecture Notes #3 Page 1 of 15
Lecture Notes #3 Page 1 of 15 PbAf 499 Lecture Notes #3: Graphing Graphing is cool and leads to great insights. Graphing Points in a Plane A point in the (x,y) plane is graphed simply by moving horizontally
More informationRational theories of finance tell us how people should behave and often do not reflect reality.
FINC3023 Behavioral Finance TOPIC 1: Expected Utility Rational theories of finance tell us how people should behave and often do not reflect reality. A normative theory based on rational utility maximizers
More informationProject Risk Analysis and Management Exercises (Part II, Chapters 6, 7)
Project Risk Analysis and Management Exercises (Part II, Chapters 6, 7) Chapter II.6 Exercise 1 For the decision tree in Figure 1, assume Chance Events E and F are independent. a) Draw the appropriate
More informationChoice under Uncertainty
Chapter 7 Choice under Uncertainty 1. Expected Utility Theory. 2. Risk Aversion. 3. Applications: demand for insurance, portfolio choice 4. Violations of Expected Utility Theory. 7.1 Expected Utility Theory
More informationChoose between the four lotteries with unknown probabilities on the branches: uncertainty
R.E.Marks 2000 Lecture 8-1 2.11 Utility Choose between the four lotteries with unknown probabilities on the branches: uncertainty A B C D $25 $150 $600 $80 $90 $98 $ 20 $0 $100$1000 $105$ 100 R.E.Marks
More information6.042/18.062J Mathematics for Computer Science November 30, 2006 Tom Leighton and Ronitt Rubinfeld. Expected Value I
6.42/8.62J Mathematics for Computer Science ovember 3, 26 Tom Leighton and Ronitt Rubinfeld Lecture otes Expected Value I The expectation or expected value of a random variable is a single number that
More informationProbabilities. CSE 473: Artificial Intelligence Uncertainty, Utilities. Reminder: Expectations. Reminder: Probabilities
CSE 473: Artificial Intelligence Uncertainty, Utilities Probabilities Dieter Fox [These slides were created by Dan Klein and Pieter Abbeel for CS188 Intro to AI at UC Berkeley. All CS188 materials are
More informationmon ey (m¾n ) n. , pl.
1 mon ey (m¾n ) n., pl. mon eys or mon ies. 1. A commodity, such as gold, or an officially issued coin or paper note that is legally established as an exchangeable equivalent of all other commodities,
More information(a) Ben s affordable bundle if there is no insurance market is his endowment: (c F, c NF ) = (50,000, 500,000).
Problem Set 6: Solutions ECON 301: Intermediate Microeconomics Prof. Marek Weretka Problem 1 (Insurance) (a) Ben s affordable bundle if there is no insurance market is his endowment: (c F, c NF ) = (50,000,
More informationSTAT 201 Chapter 6. Distribution
STAT 201 Chapter 6 Distribution 1 Random Variable We know variable Random Variable: a numerical measurement of the outcome of a random phenomena Capital letter refer to the random variable Lower case letters
More informationANASH EQUILIBRIUM of a strategic game is an action profile in which every. Strategy Equilibrium
Draft chapter from An introduction to game theory by Martin J. Osborne. Version: 2002/7/23. Martin.Osborne@utoronto.ca http://www.economics.utoronto.ca/osborne Copyright 1995 2002 by Martin J. Osborne.
More informationExpectimax Search Trees. CS 188: Artificial Intelligence Fall Expectimax Example. Expectimax Pseudocode. Expectimax Pruning?
CS 188: Artificial Intelligence Fall 2011 Expectimax Search Trees What if we don t know what the result of an action will be? E.g., In solitaire, next card is unknown In minesweeper, mine locations In
More informationu w 1.5 < 0 These two results imply that the utility function is concave.
A person with initial wealth of Rs.1000 has a 20% possibility of getting in a mischance. On the off chance that he gets in a mishap, he will lose Rs.800, abandoning him with Rs.200; on the off chance that
More informationECO303: Intermediate Microeconomic Theory Benjamin Balak, Spring 2008
ECO303: Intermediate Microeconomic Theory Benjamin Balak, Spring 2008 Game Theory: FINAL EXAMINATION 1. Under a mixed strategy, A) players move sequentially. B) a player chooses among two or more pure
More information