Financial Economics 4: Portfolio Theory

Similar documents
Techniques for Calculating the Efficient Frontier

SDMR Finance (2) Olivier Brandouy. University of Paris 1, Panthéon-Sorbonne, IAE (Sorbonne Graduate Business School)

u (x) < 0. and if you believe in diminishing return of the wealth, then you would require

Final Exam Suggested Solutions

ECO 317 Economics of Uncertainty Fall Term 2009 Tuesday October 6 Portfolio Allocation Mean-Variance Approach

MS-E2114 Investment Science Lecture 5: Mean-variance portfolio theory

Solutions to questions in Chapter 8 except those in PS4. The minimum-variance portfolio is found by applying the formula:

FIN 6160 Investment Theory. Lecture 7-10

Portfolio models - Podgorica

LECTURE NOTES 3 ARIEL M. VIALE

General Notation. Return and Risk: The Capital Asset Pricing Model

Adjusting discount rate for Uncertainty

Financial Market Analysis (FMAx) Module 6

Economics 424/Applied Mathematics 540. Final Exam Solutions

PORTFOLIO THEORY. Master in Finance INVESTMENTS. Szabolcs Sebestyén

Mean-Variance Analysis

Capital Allocation Between The Risky And The Risk- Free Asset

CHAPTER 6: PORTFOLIO SELECTION

Financial Mathematics III Theory summary

Key investment insights

Midterm 1, Financial Economics February 15, 2010

Financial Economics 1: Time value of Money

Diversification. Finance 100

QR43, Introduction to Investments Class Notes, Fall 2003 IV. Portfolio Choice

Optimizing Portfolios

Chapter 11. Return and Risk: The Capital Asset Pricing Model (CAPM) Copyright 2013 by The McGraw-Hill Companies, Inc. All rights reserved.

MATH 4512 Fundamentals of Mathematical Finance

FIN Second (Practice) Midterm Exam 04/11/06

Introduction to Computational Finance and Financial Econometrics Introduction to Portfolio Theory

ECMC49F Midterm. Instructor: Travis NG Date: Oct 26, 2005 Duration: 1 hour 50 mins Total Marks: 100. [1] [25 marks] Decision-making under certainty

Mean-Variance Portfolio Theory

Sample Midterm Questions Foundations of Financial Markets Prof. Lasse H. Pedersen

Econ 422 Eric Zivot Fall 2005 Final Exam

Chapter 8: CAPM. 1. Single Index Model. 2. Adding a Riskless Asset. 3. The Capital Market Line 4. CAPM. 5. The One-Fund Theorem

CHOICE THEORY, UTILITY FUNCTIONS AND RISK AVERSION

Lecture 2: Stochastic Discount Factor

Financial Economics: Capital Asset Pricing Model

Chapter 6 Efficient Diversification. b. Calculation of mean return and variance for the stock fund: (A) (B) (C) (D) (E) (F) (G)

AMH4 - ADVANCED OPTION PRICING. Contents

The stochastic discount factor and the CAPM

Quantitative Portfolio Theory & Performance Analysis

Chapter 10. Chapter 10 Topics. What is Risk? The big picture. Introduction to Risk, Return, and the Opportunity Cost of Capital

Freeman School of Business Fall 2003

Portfolio Management

Microeconomics of Banking: Lecture 2

IAPM June 2012 Second Semester Solutions

FINC3017: Investment and Portfolio Management

Mathematics in Finance

Risk and Return. CA Final Paper 2 Strategic Financial Management Chapter 7. Dr. Amit Bagga Phd.,FCA,AICWA,Mcom.

Lecture IV Portfolio management: Efficient portfolios. Introduction to Finance Mathematics Fall Financial mathematics

Chapter 7: Portfolio Theory

OPTIMAL RISKY PORTFOLIOS- ASSET ALLOCATIONS. BKM Ch 7

Lecture 2 Basic Tools for Portfolio Analysis

Mean Variance Analysis and CAPM

Consumption- Savings, Portfolio Choice, and Asset Pricing

CHAPTER 9: THE CAPITAL ASSET PRICING MODEL

Chapter 8. Markowitz Portfolio Theory. 8.1 Expected Returns and Covariance

CHAPTER 14 BOND PORTFOLIOS

Review Session. Prof. Manuela Pedio Theory of Finance

Quantitative Risk Management

An Intertemporal Capital Asset Pricing Model

Principles of Finance Risk and Return. Instructor: Xiaomeng Lu

Markowitz portfolio theory

The mean-variance portfolio choice framework and its generalizations

Macroeconomics Sequence, Block I. Introduction to Consumption Asset Pricing

Models and Decision with Financial Applications UNIT 1: Elements of Decision under Uncertainty

Econ 424/CFRM 462 Portfolio Risk Budgeting

Lecture 10-12: CAPM.

Return and Risk: The Capital-Asset Pricing Model (CAPM)

Efficient Portfolio and Introduction to Capital Market Line Benninga Chapter 9

Risk and Return and Portfolio Theory

Return, Risk, and the Security Market Line

Risk and Return: From Securities to Portfolios

Smart Beta: Managing Diversification of Minimum Variance Portfolios

CHAPTER 9: THE CAPITAL ASSET PRICING MODEL

Choice under Uncertainty

FINC 430 TA Session 7 Risk and Return Solutions. Marco Sammon

Ambiguous Information and Trading Volume in stock market

This assignment is due on Tuesday, September 15, at the beginning of class (or sooner).

Financial Analysis The Price of Risk. Skema Business School. Portfolio Management 1.

Archana Khetan 05/09/ MAFA (CA Final) - Portfolio Management

Session 10: Lessons from the Markowitz framework p. 1

Utility Indifference Pricing and Dynamic Programming Algorithm

Midterm #2 EconS 527 [November 7 th, 2016]

Lecture 5. Return and Risk: The Capital Asset Pricing Model

Analytical Problem Set

Modern Portfolio Theory

3. Capital asset pricing model and factor models

Option Approach to Risk-shifting Incentive Problem with Mutually Correlated Projects

Application to Portfolio Theory and the Capital Asset Pricing Model

Lecture 8: Asset pricing

Applying Index Investing Strategies: Optimising Risk-adjusted Returns

Mathematics of Finance Final Preparation December 19. To be thoroughly prepared for the final exam, you should

The Markowitz framework

Risk and expected returns (2)

Lecture 8: Introduction to asset pricing

Micro Theory I Assignment #5 - Answer key

Optimization Problem In Single Period Markets

Elements of Economic Analysis II Lecture II: Production Function and Profit Maximization

Chapter 8. Portfolio Selection. Learning Objectives. INVESTMENTS: Analysis and Management Second Canadian Edition

Transcription:

Financial Economics 4: Portfolio Theory Stefano Lovo HEC, Paris

What is a portfolio? Definition A portfolio is an amount of money invested in a number of financial assets. Example Portfolio A is worth Eu 100, 000 and consists of Eu 5, 000 invested in Alcatel shares. Eu 0, 000 invested in Michelin shares. Eu 18, 000 invested in JP Morgan shares. Eu, 000 Invested in gold. Eu 15, 000 invested in German Treasury bills. Vector representation: X A = {x Al, x M, x Jp, x g, x Tb } = {0.5, 0., 0.18, 0., 0.15} Stefano Lovo, HEC Paris Portfolio Theory / 40

Notation Let S = {s 1, s,..., s N } be the set of financial assets available in the economy. Let {v 1, v,..., v N } be the amount of money invested in each one of the N assets to obtain portfolio A. Today the value of portfolio A is V A = N v i = v 1 + v + + v n. i=1 The composition of the portfolio A is X A = {x 1, x,..., x N } where and x i = v i V A. N x i = x 1 + x + + x n = 1 i=1 Stefano Lovo, HEC Paris Portfolio Theory 3 / 40

Some portfolios S = {s 1, s, s 3 } = {Alcatel, BMW, Treasury bill} 1 Only long positions V A = 5, 000 +, 000 + 10, 000 = 17, 000 X A = { 5,000 17,000,,000 17,000, 10,000 17,000 } {0.9, 0.1, 0.59} Stefano Lovo, HEC Paris Portfolio Theory 4 / 40

Some portfolios S = {s 1, s, s 3 } = {Alcatel, BMW, Treasury bill} 1 Only long positions V A = 5, 000 +, 000 + 10, 000 = 17, 000 X A = { 5,000 17,000,,000 17,000, 10,000 17,000 } {0.9, 0.1, 0.59} Short position V B = 15, 000 + 6, 000 4, 000 = 17, 000 X B = { 15,000 17,000, 6,000 17,000, 4,000 17,000 } {0.88, 0.353, 0.35} Stefano Lovo, HEC Paris Portfolio Theory 4 / 40

Short selling an asset Example Let X B = {0.88, 0.353, 0.35}, then portfolio B has a short position in asset s 3. Stefano Lovo, HEC Paris Portfolio Theory 5 / 40

Short selling an asset Example Let X B = {0.88, 0.353, 0.35}, then portfolio B has a short position in asset s 3. How to short sell an asset i At time 0: 1 You borrow the asset i from your broker. You sell the asset in the stock market at price P i (0). Stefano Lovo, HEC Paris Portfolio Theory 5 / 40

Short selling an asset Example Let X B = {0.88, 0.353, 0.35}, then portfolio B has a short position in asset s 3. How to short sell an asset i At time 0: 1 You borrow the asset i from your broker. You sell the asset in the stock market at price P i (0). At time 1: 1 You pay your broker whatever dividend the asset has paid at time 1. You buy the asset in the stock market at price P i (1). 3 You return the asset to your broker. The broker charges you a fee for lending you the asset and asks for a collateral. Stefano Lovo, HEC Paris Portfolio Theory 5 / 40

Portfolio return rate example Asset p i (0) p i (1) D i r i Alcatel 50 49 4 6% BMW 0 0 10% T.B. 100 100 % You invest Eu 100 into portfolio X C = {x Al, x BM, x TB } = {0.8, 0., 0}. What is the rate of return of your portfolio? At t = 1 portfolio C is worth 100 0.8(1+r Al )+100 0.(1+r BM ) = 80(1.06)+0(1.1) = 106.8 hence r C = 106.8 100 100 = 6.8% = 80(1.06)+0(1.1) (80+0) 100 = = 80 0.06+0 0.1 100 = 0.8 6% + 0. 10% = x Al r Al + x BM r BM Stefano Lovo, HEC Paris Portfolio Theory 6 / 40

Return rate of a portfolio Return rate on a long position (buy) on portfolio A: 1 At time 0 you buy the portfolio at X a = {x 1, x,..., x n }. At time 1 you receive dividends from each stock 3 At time 1 you resell the portfolio. The return rate r A on your investment in Portfolio A is r A = n r i x i = r 1 x 1 + r x + + r n x n. i=1 Stefano Lovo, HEC Paris Portfolio Theory 7 / 40

Uncertainty Theorem Let S = {s 1, s,..., s N } be the set of available assets. Let r 1, r,..., r N be N random variables representing the return rates on assets s 1, s,..., s N, respectively. Then, the rate of return of a portfolio A with composition X A = {x 1, x,..., x N } is a random variable r A := N x i r i i=1 Stefano Lovo, HEC Paris Portfolio Theory 8 / 40

Uncertainty Example The rate of return of a portfolio composed of risky asset is uncertain: S = {Alcatel, BMW } Portfolio A: X A = {0.8, 0.} Event r Al r BM r A The economy is booming 1% 0% 0.8 1%+0. 0%=13.6% The economy is in recession -3% -15% -0.8 3%-0. 15% =-5.4% Stefano Lovo, HEC Paris Portfolio Theory 9 / 40

Expected return on a portfolio Theorem The expected return rate on a portfolio with composition X = {x 1, x,..., x n } is: E [ r X = x1 E [ r 1 + x E [ r + + xn E [ r n = n x i E [ r i. i=1 Example S={Al,BM} X A ={0.8,0.} E [ r Al =1.5% E [ r BM =-4.5% E [ r A Event Prob r Al r BM r A Boom 0.3 1% 0% 13.6% Recession 0.7-3% -15% -5.4% = 0.3 13.6% 0.7 5.4% = 0.3% = 0.8 1.5% 0. 4.5% = 0.3% Stefano Lovo, HEC Paris Portfolio Theory 10 / 40

Expected return on a portfolio Theorem The expected return rate on a portfolio with composition X = {x 1, x,..., x n } is: E [ r X = x1 E [ r 1 + x E [ r + + xn E [ r n = n x i E [ r i. i=1 Example S={Al,BM} X A ={0.8,0.} E [ r Al =1.5% E [ r BM =-4.5% E [ r A Event Prob r Al r BM r A Boom 0.3 1% 0% 13.6% Recession 0.7-3% -15% -5.4% = 0.3 13.6% 0.7 5.4% = 0.3% = 0.8 1.5% 0. 4.5% = 0.3% Stefano Lovo, HEC Paris Portfolio Theory 11 / 40

Expected return on a portfolio: QCQ Assets s 1 s s 3 s 4 E [ r i 30% 5% 8% % What are the expected returns of the following portfolios? x 1 x x 3 x 4 X A 0 1 0 0 X B 0. 0.1 0.3 0.4 X C 0.3 0.8 0.6 0.7 X D 0.5 0. 0.8 0.1 Answers: E [r A = 5%, E [r B = 11.7%, E [r C = 3.4%, E [r D = 16.%. Stefano Lovo, HEC Paris Portfolio Theory 1 / 40

Variance of the return rate of a portfolio Theorem The variance of the return rate on a portfolio with composition X = {x 1, x,..., x n } is: σ X := Var [ r X = n n x i x j σ ij i=1 j=1 where σ ii = Var [ r i and σij := Cov [ r i, r j. for n = : σ X = x 1 σ 1 + x σ + x 1x Cov [ r 1, r Since x 1 + x = 1 and Cov [ r i, r j = ρ1, σ 1 σ, σ X = x 1 σ 1 + (1 x 1) σ + x 1(1 x 1 )ρ 1, σ 1 σ Stefano Lovo, HEC Paris Portfolio Theory 13 / 40

Variance of the return rate of a portfolio: example Example S = {s 1, s } s 1 s σ i 30% 1% ρ 1 0.56 If the composition of portfolio A is X A = {0.8, 0.}, then σ A = x 1 σ 1 + (1 x 1) σ + x 1(1 x 1 )ρ 1 σ 1 σ = = 0.8 0.3 + 0. 0.1 + 0.8 0. 0.56 0.3 0.1 = 0.05 σ A = σ A = 0.05 =.7% Stefano Lovo, HEC Paris Portfolio Theory 14 / 40

Summing-up about portfolios 1 Ingredients: Set of available assets S = {s 1, s,..., s n } Recipe: Portfolio composition X = {x 1, x,..., x n } satisfying n x i = 1. i=1 3 Gain: Expected return of a portfolio E [ r n X = x i E [ r i. i=1 4 Risk: variance of the portfolio s return Var [ r X = n n x i x j σ ij i=1 j=1 Stefano Lovo, HEC Paris Portfolio Theory 15 / 40

Risk aversion Definition A Mean-Variance investor is someone who likes high expected return portfolios and exhibits risk aversion. More precisely: Stefano Lovo, HEC Paris Portfolio Theory 16 / 40

Risk aversion Definition A Mean-Variance investor is someone who likes high expected return portfolios and exhibits risk aversion. More precisely: 1 The investor only cares about E [ r X and σ X. Stefano Lovo, HEC Paris Portfolio Theory 16 / 40

Risk aversion Definition A Mean-Variance investor is someone who likes high expected return portfolios and exhibits risk aversion. More precisely: 1 The investor only cares about E [ r X and σ X. For a given level of risk σx, he/she prefers the portfolio with the largest expected return E [ r X. Stefano Lovo, HEC Paris Portfolio Theory 16 / 40

Risk aversion Definition A Mean-Variance investor is someone who likes high expected return portfolios and exhibits risk aversion. More precisely: 1 The investor only cares about E [ r X and σ X. For a given level of risk σx, he/she prefers the portfolio with the largest expected return E [ r X. 3 For a given level of expected return E [ r X, he/she prefers the portfolio with the lowest risk σ X. Stefano Lovo, HEC Paris Portfolio Theory 16 / 40

Risk aversion Definition A Mean-Variance investor is someone who likes high expected return portfolios and exhibits risk aversion. More precisely: 1 The investor only cares about E [ r X and σ X. For a given level of risk σx, he/she prefers the portfolio with the largest expected return E [ r X. 3 For a given level of expected return E [ r X, he/she prefers the portfolio with the lowest risk σ X. 4 A Mean-Variance investor chooses the portfolio that maximizes the following utility function U (X) := E [ r X a σ X where a is the investor s personal degree of risk aversion. Stefano Lovo, HEC Paris Portfolio Theory 16 / 40

Risk aversion: Graphically Portfolio X is at least as good as portfolio X iff U(X) U(X ). E [ r X D B A C B C D A? D B? D A B C σ X Stefano Lovo, HEC Paris Portfolio Theory 17 / 40

Diversification Rule 0: Diversification of your investment allows to reduce the risk of your portfolio. Example E [ r 1 Cov [ r 1, r Event Prob. r 1 r ω 1 0.5 0% 5% ω 3 0.5 0% 15% ω 0.5 0% 5% ω 4 0.5 0% 15% = E [ r = 10%, σ1 = 10%, σ = 5% = ρ 1, = 0 If X = {0., 0.8}, then E [ r X = 10% σ X = 0. 0.1 + 0.8 0.05 = 4.47% < 5% Stefano Lovo, HEC Paris Portfolio Theory 18 / 40

Diversifying Example E [ r 1 Event Prob. r 1 r ω 1 0.5 0% 15% ω 3 0.5 0% 15% ω 0.5 0% 5% ω 4 0.5 0% 5% = E [ r = 10%, σ1 = 10%, σ = 5% ρ 1, = 1 If X = { 1 3, 3 }, then E [ r X = 10% (1 σ X = 3 0.1 ) ( + 3 0.05 ) 4 0.05 0.1 = 0 9 Stefano Lovo, HEC Paris Portfolio Theory 19 / 40

Minimum Variance Portfolio S = {s 1, s }. What is the composition of the portfolio (x 1, x ) that has the minimum variance? min x x 1,x 1 σ 1 + x σ + x 1x ρ 1 σ 1 σ s.t. x 1 + x = 1 x min 1 = σ (σ ρ 1 σ 1 ) σ 1 +σ ρ 1σ 1 σ, x min = 1 x min 1 σ min = (1 ρ 1 )σ 1 σ σ 1 +σ ρ 1σ 1 σ Remarks: If ρ 1 1, then x min 1 > 0 and x min > 0 If σ 1 > σ and ρ 1 is close enough to 1 then short sell s 1. If ρ 1 = ±1, then σ min = 0. Stefano Lovo, HEC Paris Portfolio Theory 0 / 40

Limit of risk reduction through diversification Definition The idiosyncratic risk on stock i is the uncertainty on r i linked to risk factors that are specific to firm i. Examples: changes in management, production process innovation, local strikes, etc. The systematic risk on stock i is the uncertainty on r i linked to risk factors that affect the whole economy and are common to other stocks. Examples: Wars, political change, general economic downturn, pandemics, etc. Theorem Diversification intended as buying a large number of different assets can eliminate the idiosyncratic risk but not the systematic risk. Stefano Lovo, HEC Paris Portfolio Theory 1 / 40

Limit of diversification σ X Idiosyncratic risk Systematic risk Number of securities Stefano Lovo, HEC Paris Portfolio Theory / 40

Portfolio choice Assumptions 1 S = {s 1, s,..., s n } Any assets i < n is a risky asset with return r i. 3 Asset n is a risk-free asset with r n = r f. (Ex. Treasury bill) 4 Investors are mean-variance investors. Implication: Choose thex = {x 1,..., x f } that maximizes U (X) := E [ r X a σ X subject to 1 = x 1 + x + + x f, E [ r X = n x i E [ r i, Var [ r X = i=1 n i=1 j=1 n x i x j σ ij. Stefano Lovo, HEC Paris Portfolio Theory 3 / 40

Efficient Portfolio Definition A portfolio A is said to be efficient if there exists no other portfolio B satisfying: σ B σ A and E [ r B E [ r A with at least one strict inequality. Portfolio choice methodology 1 Determine the set of couple risk-return (E [ r X, σ X ) reachable by combining the available assets S. Identify the set of portfolios that are efficient. 3 Among the set of efficient portfolios choose the one that best fits the investor s risk aversion. Stefano Lovo, HEC Paris Portfolio Theory 4 / 40

Return-risk region. Case 0 Just one risky asset: S = {s 1 } with E [ r 1 > 0 and σ 1 > 0. E [ ~ r X E [ ~ r1 σ 1 σ X Stefano Lovo, HEC Paris Portfolio Theory 5 / 40

Return-risk region. Case 1 One risky asset and one risk-free asset: S = {s 1, s f } with E [ r 1 > 0, σ 1 > 0, r f = r f < E [ r 1 and σ f = 0. E [ r X = x 1 E [ r 1 + (1 x1 )r f σx = x1 σ 1 E [ r X = r f ± E [ r 1 rf σ X σ 1 Example E [ r 1 = 0%, σ 1 = 0.01, r f = % and σ f = 0 What is the composition of a portfolio with E [ r X = 11%? What is the composition of a portfolio with risk σ X = %? The expected return on portfolio A is E [ r A = 40%. What is its risk σ A? Stefano Lovo, HEC Paris Portfolio Theory 6 / 40

Return-risk region. Case 1 One risky asset and one risk-free asset: S = {s 1, s f } { 0,1} E [ ~ r X E [ ~ r1 x > 0 1 x f > 0 { 1,0} x > 1 1 x f < 0 Short-sell s f r f Buy s 1 and s f x < 0 1 x f > 1 Short-sell s 1 σ 1 σ X Stefano Lovo, HEC Paris Portfolio Theory 7 / 40

Capital Allocation Line Theorem In Case 1 a risk-return combination corresponds to an efficient portfolio if and only if E [ r X = rf + λσ X where λ := E[ r 1 r f σ 1 E [ ~ r X E [ ~ r1 CAL r f σ 1 Stefano Lovo, HEC Paris Portfolio Theory 8 / 40 σ X

Return-risk region. Case Two risky assets : S = {s 1, s } with E [ r 1 > 0, σ 1 > 0, E [ r > 0, σ > 0. E [ r X = x 1 E [ r 1 + (1 x1 )E [ r σx = x1 σ 1 + (1 x 1) σ + x 1(1 x 1 )ρ 1 σ 1 σ. ( ) ( ) σx E[ r = X E[ r σ E[ r 1 E[ r 1 + E[ r 1 E[ r X σ E[ r 1 E[ r + + (E[ r X E[ r )(E[ r 1 E[ r X) (E[ r 1 E[ r ) ρ 1 σ 1 σ. Stefano Lovo, HEC Paris Portfolio Theory 9 / 40

Return-risk region. Case Two risky assets : S = {s 1, s } E [ ~ r X E[ ~r 1 x 1 > 0 x > 0 { 1,0} x 1 >1 x < 0 Short-sell s E[ r { 0,1} Buy s 1 and s Short-sell s 1 x 1 < 0 x >1 σ min σ σ 1 σ X Stefano Lovo, HEC Paris Portfolio Theory 30 / 40

Case with perfect positive correlation Show that if S = {s 1, s } and ρ = 1, then 1 the return risk region is as depicted below. find the composition, the expected return and the risk of the minimum Var portfolio 3 find the equation of the two lines. E [ ~ r X [ ~ { 1,0} E r1 E [ ~ r { 0,1} x > 0 1 x > 0 x < 0 1 x > 1 ρ 1 = 1 x > 1 1 x < 0 Short-sell s Buy s 1 and s Short-sell s 1 σ σ 1 σ X Stefano Lovo, HEC Paris Portfolio Theory 31 / 40

Return-risk region. Case with perfect negative correlation Show that if S = {s 1, s } and ρ = 1, then 1 the return risk region is as depicted below. find the composition, the expected return and the risk of the minimum Var portfolio. 3 find the equation of the two lines. E [ ~ r X [ ~ { 1,0} E r1 x1 > 0 x > 0 ρ 1 = -1 x > 1 1 x < 0 Short-sell s E [ ~ r { 0,1} x < 0 1 x > 1 Buy s 1 and s Short-sell s 1 σ σ 1 σ X Stefano Lovo, HEC Paris Portfolio Theory 3 / 40

Return-risk region. Case 3 Two risky assets and one risk-free asset: S = {s 1, s, s f } with E [ r 1 > 0, σ 1 > 0, E [ r > 0, σ > 0, r f = r f, σ f = 0. E [ ~ r X Tangency portfolio: { x T,1 x T,0} {αx T, α(1-x T ), 1- α } E[ ~r 1 { 1,0,0} r f [ E r { 0,1,0} {x 1,1-x 1, 0 } σ min σ σ 1 σ X Stefano Lovo, HEC Paris Portfolio Theory 33 / 40

Case 3: efficient portfolios Theorem In Case 3 a risk-return combination corresponds to an efficient portfolio if and only if: 1 where E [ r X = rf + λσ X λ := E [ r T rf σ T and E [ r T and σt are the expected return and risk of the tangency portfolio. It is obtained combining the tangency portfolio with the risk-free asset. Stefano Lovo, HEC Paris Portfolio Theory 34 / 40

Tangency Portfolio composition for Case 3: S = {s 1, s, s f } What is the composition of the tangency portfolio? E[ r T r max λ = max f x1 T x1 T σ T subject to E [ r T = x1 T E [ r 1 + (1 x T 1 )E [ r σ T = ( (x1 T σ 1) + ((1 x1 T )σ ) + x1 T (1 x 1 T )ρ 1,σ 1 σ ) 1 This gives x T 1 = (E [ r rf )ρ 1, σ 1 σ (E [ r 1 rf )σ (E [ r 1 + E [ r rf )ρ 1, σ 1 σ (E [ r 1 rf )σ (E [ r rf )σ 1 Stefano Lovo, HEC Paris Portfolio Theory 35 / 40

General case n 1 risky assets and one risk-free asset: S = {s 1,..., s n 1, s f } E [ ~ r X Tangency portfolio: Capital Allocation Line Efficient portfolio frontier E [ ~ r T r f σ min σ T σ X Stefano Lovo, HEC Paris Portfolio Theory 36 / 40

Security Market Line Relation Theorem For any asset or portfolio s i, E [ r i rf = β i ( E [ r T rf ) where β i := Cov[ r i, r T σ T E [ ~ r i E [ ~ r T r f β i Stefano Lovo, HEC Paris Portfolio Theory 37 / 40

Optimal Portfolio Theorem An investor with a mean-variance utility function and a risk aversion A will choose an efficient portfolio such that: x T = E[ r T r f Aσ T, x f = 1 x T E [ ~ r X E [ ~ r T Optimal portfolio Indifference courve CAL rf Tangency portfolio σ min σ T σ X Stefano Lovo, HEC Paris Portfolio Theory 38 / 40

Exercise Suppose that S = {s 1, s, s 3, s f } {E [ r 1, E [ r, E [ r 3, rf } = {9%, 3%, 1%, 1%} The tangency portfolio is X T = {1.48, 0.3, 0.78, 0} and σ T = 18%. Questions: 1 What is E [ r T? (Ans.: 1%) What are β 1, β, β 3? (Ans.: 0.4, 1.1, 0.1) 3 What is the composition of the optimal portfolio for an investor with risk aversion A = 4? (Ans.: 1.543 in the tangency portfolio and 0.543 in the risk free asset, that is X P = {.84, 0.463, 1.05, 0.543}) Stefano Lovo, HEC Paris Portfolio Theory 39 / 40

Summary Definition of efficient portfolio. Mean-Variance investors choose efficient portfolios. An efficient portfolio is composed of the tangency portfolio and the risk free asset. if X is efficient, then E [ r X = rf + E[ r T r f σ T The tangency portfolio satisfies σ x E [ r i rf = β i ( E [ r T rf ) where β i = Cov[ r T, r i σ T Stefano Lovo, HEC Paris Portfolio Theory 40 / 40