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Chapter 7 Why Diversification Is a Good Idea

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Title: Chapter 7 Why Diversification Is a Good Idea


1
Chapter 7Why Diversification Is a Good Idea
2
  • The most important lesson learned
  • is an old truth ratified.
  • - General Maxwell R. Thurman

3
Outline
  • Introduction
  • Carrying your eggs in more than one basket
  • Role of uncorrelated securities
  • Lessons from Evans and Archer
  • Diversification and beta
  • Capital asset pricing model
  • Equity risk premium
  • Using a scatter diagram to measure beta
  • Arbitrage pricing theory

4
Introduction
  • Diversification of a portfolio is logically a
    good idea
  • Virtually all stock portfolios seek to diversify
    in one respect or another

5
Carrying Your Eggs in More Than One Basket
  • Investments in your own ego
  • The concept of risk aversion revisited
  • Multiple investment objectives

6
Investments in Your Own Ego
  • Never put a large percentage of investment funds
    into a single security
  • If the security appreciates, the ego is stroked
    and this may plant a speculative seed
  • If the security never moves, the ego views this
    as neutral rather than an opportunity cost
  • If the security declines, your ego has a very
    difficult time letting go

7
The Concept of Risk Aversion Revisited
  • Diversification is logical
  • If you drop the basket, all eggs break
  • Diversification is mathematically sound
  • Most people are risk averse
  • People take risks only if they believe they will
    be rewarded for taking them

8
The Concept of Risk Aversion Revisited (contd)
  • Diversification is more important now
  • Journal of Finance article shows that volatility
    of individual firms has increased
  • Investors need more stocks to adequately
    diversify

9
Multiple Investment Objectives
  • Multiple objectives justify carrying your eggs in
    more than one basket
  • Some people find mutual funds unexciting
  • Many investors hold their investment funds in
    more than one account so that they can play
    with part of the total
  • E.g., a retirement account and a separate
    brokerage account for trading individual
    securities

10
Role of Uncorrelated Securities
  • Variance of a linear combination the practical
    meaning
  • Portfolio programming in a nutshell
  • Concept of dominance
  • Harry Markowitz the founder of portfolio theory

11
Variance of A Linear Combination
  • One measure of risk is the variance of return
  • The variance of an n-security portfolio is

12
Variance of A Linear Combination (contd)
  • The variance of a two-security portfolio is

13
Variance of A Linear Combination (contd)
  • Return variance is a securitys total risk
  • Most investors want portfolio variance to be as
    low as possible without having to give up any
    return

Total Risk
Risk from A
Risk from B
Interactive Risk
14
Variance of A Linear Combination (contd)
  • If two securities have low correlation, the
    interactive risk will be small
  • If two securities are uncorrelated, the
    interactive risk drops out
  • If two securities are negatively correlated,
    interactive risk would be negative and would
    reduce total risk

15
Portfolio Programming in A Nutshell
  • Various portfolio combinations may result in a
    given return
  • The investor wants to choose the portfolio
    combination that provides the least amount of
    variance

16
Portfolio Programming in A Nutshell (contd)
  • Example
  • Assume the following statistics for Stocks A, B,
    and C

Stock A Stock B Stock C
Expected return .20 .14 .10
Standard deviation .232 .136 .195
17
Portfolio Programming in A Nutshell (contd)
  • Example (contd)
  • The correlation coefficients between the three
    stocks are

Stock A Stock B Stock C
Stock A 1.000
Stock B 0.286 1.000
Stock C 0.132 -0.605 1.000
18
Portfolio Programming in A Nutshell (contd)
  • Example (contd)
  • An investor seeks a portfolio return of 12.
  • Which combinations of the three stocks accomplish
    this objective? Which of those combinations
    achieves the least amount of risk?

19
Portfolio Programming in A Nutshell (contd)
  • Example (contd)
  • Solution Two combinations achieve a 12 return
  • 50 in B, 50 in C (.5)(14) (.5)(10) 12
  • 20 in A, 80 in C (.2)(20) (.8)(10) 12

20
Portfolio Programming in A Nutshell (contd)
  • Example (contd)
  • Solution (contd) Calculate the variance of the
    B/C combination

21
Portfolio Programming in A Nutshell (contd)
  • Example (contd)
  • Solution (contd) Calculate the variance of the
    A/C combination

22
Portfolio Programming in A Nutshell (contd)
  • Example (contd)
  • Solution (contd) Investing 50 in Stock B and
    50 in Stock C achieves an expected return of 12
    with the lower portfolio variance. Thus, the
    investor will likely prefer this combination to
    the alternative of investing 20 in Stock A and
    80 in Stock C.

23
Concept of Dominance
  • Dominance is a situation in which investors
    universally prefer one alternative over another
  • All rational investors will clearly prefer one
    alternative

24
Concept of Dominance (contd)
  • A portfolio dominates all others if
  • For its level of expected return, there is no
    other portfolio with less risk
  • For its level of risk, there is no other
    portfolio with a higher expected return

25
Concept of Dominance (contd)
  • Example (contd)
  • In the previous example, the B/C combination
    dominates the A/C combination

B/C combination dominates A/C
Expected Return
Risk
26
Harry Markowitz Founder of Portfolio Theory
  • Introduction
  • Terminology
  • Quadratic programming

27
Introduction
  • Harry Markowitzs Portfolio Selection Journal
    of Finance article (1952) set the stage for
    modern portfolio theory
  • The first major publication indicating the
    important of security return correlation in the
    construction of stock portfolios
  • Markowitz showed that for a given level of
    expected return and for a given security
    universe, knowledge of the covariance and
    correlation matrices are required

28
Terminology
  • Security Universe
  • Efficient frontier
  • Capital market line and the market portfolio
  • Security market line
  • Expansion of the SML to four quadrants
  • Corner portfolio

29
Security Universe
  • The security universe is the collection of all
    possible investments
  • For some institutions, only certain investments
    may be eligible
  • E.g., the manager of a small cap stock mutual
    fund would not include large cap stocks

30
Efficient Frontier
  • Construct a risk/return plot of all possible
    portfolios
  • Those portfolios that are not dominated
    constitute the efficient frontier

31
Efficient Frontier (contd)
Expected Return
100 investment in security with highest E(R)
No points plot above the line
Points below the efficient frontier are dominated
All portfolios on the line are efficient
100 investment in minimum variance portfolio
Standard Deviation
32
Efficient Frontier (contd)
  • The farther you move to the left on the efficient
    frontier, the greater the number of securities in
    the portfolio

33
Efficient Frontier (contd)
  • When a risk-free investment is available, the
    shape of the efficient frontier changes
  • The expected return and variance of a risk-free
    rate/stock return combination are simply a
    weighted average of the two expected returns and
    variance
  • The risk-free rate has a variance of zero

34
Efficient Frontier (contd)
Expected Return
C
B
Rf
A
Standard Deviation
35
Efficient Frontier (contd)
  • The efficient frontier with a risk-free rate
  • Extends from the risk-free rate to point B
  • The line is tangent to the risky securities
    efficient frontier
  • Follows the curve from point B to point C

36
Capital Market Line and the Market Portfolio
  • The tangent line passing from the risk-free rate
    through point B is the capital market line (CML)
  • When the security universe includes all possible
    investments, point B is the market portfolio
  • It contains every risky assets in the proportion
    of its market value to the aggregate market value
    of all assets
  • It is the only risky assets risk-averse investors
    will hold

37
Capital Market Line and the Market Portfolio
(contd)
  • Implication for investors
  • Regardless of the level of risk-aversion, all
    investors should hold only two securities
  • The market portfolio
  • The risk-free rate
  • Conservative investors will choose a point near
    the lower left of the CML
  • Growth-oriented investors will stay near the
    market portfolio

38
Capital Market Line and the Market Portfolio
(contd)
  • Any risky portfolio that is partially invested in
    the risk-free asset is a lending portfolio
  • Investors can achieve portfolio returns greater
    than the market portfolio by constructing a
    borrowing portfolio

39
Capital Market Line and the Market Portfolio
(contd)
Expected Return
C
B
Rf
A
Standard Deviation
40
Security Market Line
  • The graphical relationship between expected
    return and beta is the security market line (SML)
  • The slope of the SML is the market price of risk
  • The slope of the SML changes periodically as the
    risk-free rate and the markets expected return
    change

41
Security Market Line (contd)
Expected Return
E(R)
Market Portfolio
Rf
1.0
Beta
42
Expansion of the SML to Four Quadrants
  • There are securities with negative betas and
    negative expected returns
  • A reason for purchasing these securities is their
    risk-reduction potential
  • E.g., buy car insurance without expecting an
    accident
  • E.g., buy fire insurance without expecting a fire

43
Security Market Line (contd)
Expected Return
Securities with Negative Expected Returns
Beta
44
Corner Portfolio
  • A corner portfolio occurs every time a new
    security enters an efficient portfolio or an old
    security leaves
  • Moving along the risky efficient frontier from
    right to left, securities are added and deleted
    until you arrive at the minimum variance portfolio

45
Quadratic Programming
  • The Markowitz algorithm is an application of
    quadratic programming
  • The objective function involves portfolio
    variance
  • Quadratic programming is very similar to linear
    programming

46
Markowitz Quadratic
Programming Problem
47
Lessons from Evans and Archer
  • Introduction
  • Methodology
  • Results
  • Implications
  • Words of caution

48
Introduction
  • Evans and Archers 1968 Journal of Finance
    article
  • Very consequential research regarding portfolio
    construction
  • Shows how naïve diversification reduces the
    dispersion of returns in a stock portfolio
  • Naïve diversification refers to the selection of
    portfolio components randomly

49
Methodology
  • Used computer simulations
  • Measured the average variance of portfolios of
    different sizes, up to portfolios with dozens of
    components
  • Purpose was to investigate the effects of
    portfolio size on portfolio risk when securities
    are randomly selected

50
Results
  • Definitions
  • General results
  • Strength in numbers
  • Biggest benefits come first
  • Superfluous diversification

51
Definitions
  • Systematic risk is the risk that remains after no
    further diversification benefits can be achieved
  • Unsystematic risk is the part of total risk that
    is unrelated to overall market movements and can
    be diversified
  • Research indicates up to 75 percent of total risk
    is diversifiable

52
Definitions (contd)
  • Investors are rewarded only for systematic risk
  • Rational investors should always diversify
  • Explains why beta (a measure of systematic risk)
    is important
  • Securities are priced on the basis of their beta
    coefficients

53
General Results
Portfolio Variance
Number of Securities
54
Strength in Numbers
  • Portfolio variance (total risk) declines as the
    number of securities included in the portfolio
    increases
  • On average, a randomly selected ten-security
    portfolio will have less risk than a randomly
    selected three-security portfolio
  • Risk-averse investors should always diversify to
    eliminate as much risk as possible

55
Biggest Benefits Come First
  • Increasing the number of portfolio components
    provides diminishing benefits as the number of
    components increases
  • Adding a security to a one-security portfolio
    provides substantial risk reduction
  • Adding a security to a twenty-security portfolio
    provides only modest additional benefits

56
Superfluous Diversification
  • Superfluous diversification refers to the
    addition of unnecessary components to an already
    well-diversified portfolio
  • Deals with the diminishing marginal benefits of
    additional portfolio components
  • The benefits of additional diversification in
    large portfolio may be outweighed by the
    transaction costs

57
Implications
  • Very effective diversification occurs when the
    investor owns only a small fraction of the total
    number of available securities
  • Institutional investors may not be able to avoid
    superfluous diversification due to the dollar
    size of their portfolios
  • Mutual funds are prohibited from holding more
    than 5 percent of a firms equity shares

58
Implications (contd)
  • Owning all possible securities would require high
    commission costs
  • It is difficult to follow every stock

59
Words of Caution
  • Selecting securities at random usually gives good
    diversification, but not always
  • Industry effects may prevent proper
    diversification
  • Although naïve diversification reduces risk, it
    can also reduce return
  • Unlike Markowitzs efficient diversification

60
Diversification and Beta
  • Beta measures systematic risk
  • Diversification does not mean to reduce beta
  • Investors differ in the extent to which they will
    take risk, so they choose securities with
    different betas
  • E.g., an aggressive investor could choose a
    portfolio with a beta of 2.0
  • E.g., a conservative investor could choose a
    portfolio with a beta of 0.5

61
Capital Asset Pricing Model
  • Introduction
  • Systematic and unsystematic risk
  • Fundamental risk/return relationship revisited

62
Introduction
  • The Capital Asset Pricing Model (CAPM) is a
    theoretical description of the way in which the
    market prices investment assets
  • The CAPM is a positive theory

63
Systematic and Unsystematic Risk
  • Unsystematic risk can be diversified and is
    irrelevant
  • Systematic risk cannot be diversified and is
    relevant
  • Measured by beta
  • Beta determines the level of expected return on a
    security or portfolio (SML)

64
Fundamental Risk/Return Relationship Revisited
  • CAPM
  • SML and CAPM
  • Market model versus CAPM
  • Note on the CAPM assumptions
  • Stationarity of beta

65
CAPM
  • The more risk you carry, the greater the expected
    return

66
CAPM (contd)
  • The CAPM deals with expectations about the future
  • Excess returns on a particular stock are directly
    related to
  • The beta of the stock
  • The expected excess return on the market

67
CAPM (contd)
  • CAPM assumptions
  • Variance of return and mean return are all
    investors care about
  • Investors are price takers
  • They cannot influence the market individually
  • All investors have equal and costless access to
    information
  • There are no taxes or commission costs

68
CAPM (contd)
  • CAPM assumptions (contd)
  • Investors look only one period ahead
  • Everyone is equally adept at analyzing securities
    and interpreting the news

69
SML and CAPM
  • If you show the security market line with excess
    returns on the vertical axis, the equation of the
    SML is the CAPM
  • The intercept is zero
  • The slope of the line is beta

70
Market Model Versus CAPM
  • The market model is an ex post model
  • It describes past price behavior
  • The CAPM is an ex ante model
  • It predicts what a value should be

71
Market Model Versus CAPM (contd)
  • The market model is

72
Note on the CAPM Assumptions
  • Several assumptions are unrealistic
  • People pay taxes and commissions
  • Many people look ahead more than one period
  • Not all investors forecast the same distribution
  • Theory is useful to the extent that it helps us
    learn more about the way the world acts
  • Empirical testing shows that the CAPM works
    reasonably well

73
Stationarity of Beta
  • Beta is not stationary
  • Evidence that weekly betas are less than monthly
    betas, especially for high-beta stocks
  • Evidence that the stationarity of beta increases
    as the estimation period increases
  • The informed investment manager knows that betas
    change

74
Equity Risk Premium
  • Equity risk premium refers to the difference in
    the average return between stocks and some
    measure of the risk-free rate
  • The equity risk premium in the CAPM is the excess
    expected return on the market
  • Some researchers are proposing that the size of
    the equity risk premium is shrinking

75
Using A Scatter Diagram to Measure Beta
  • Correlation of returns
  • Linear regression and beta
  • Importance of logarithms
  • Statistical significance

76
Correlation of Returns
  • Much of the daily news is of a general economic
    nature and affects all securities
  • Stock prices often move as a group
  • Some stock routinely move more than the others
    regardless of whether the market advances or
    declines
  • Some stocks are more sensitive to changes in
    economic conditions

77
Linear Regression and Beta
  • To obtain beta with a linear regression
  • Plot a stocks return against the market return
  • Use Excel to run a linear regression and obtain
    the coefficients
  • The coefficient for the market return is the beta
    statistic
  • The intercept is the trend in the security price
    returns that is inexplicable by finance theory

78
Importance of Logarithms
  • Taking the logarithm of returns reduces the
    impact of outliers
  • Outliers distort the general relationship
  • Using logarithms will have more effect the more
    outliers there are

79
Statistical Significance
  • Published betas are not always useful numbers
  • Individual securities have substantial
    unsystematic risk and will behave differently
    than beta predicts
  • Portfolio betas are more useful since some
    unsystematic risk is diversified away

80
Arbitrage Pricing Theory
  • APT background
  • The APT model
  • Comparison of the CAPM and the APT

81
APT Background
  • Arbitrage pricing theory (APT) states that a
    number of distinct factors determine the market
    return
  • Roll and Ross state that a securitys long-run
    return is a function of changes in
  • Inflation
  • Industrial production
  • Risk premiums
  • The slope of the term structure of interest rates

82
APT Background (contd)
  • Not all analysts are concerned with the same set
    of economic information
  • A single market measure such as beta does not
    capture all the information relevant to the price
    of a stock

83
The APT Model
  • General representation of the APT model

84
Comparison of the CAPM and the APT
  • The CAPMs market portfolio is difficult to
    construct
  • Theoretically all assets should be included (real
    estate, gold, etc.)
  • Practically, a proxy like the SP 500 index is
    used
  • APT requires specification of the relevant
    macroeconomic factors

85
Comparison of the CAPM and the APT (contd)
  • The CAPM and APT complement each other rather
    than compete
  • Both models predict that positive returns will
    result from factor sensitivities that move with
    the market and vice versa
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