- •Intended Audience
- •1.1 Financing the Firm
- •1.2Public and Private Sources of Capital
- •1.3The Environment forRaising Capital in the United States
- •Investment Banks
- •1.4Raising Capital in International Markets
- •1.5MajorFinancial Markets outside the United States
- •1.6Trends in Raising Capital
- •Innovative Instruments
- •2.1Bank Loans
- •2.2Leases
- •2.3Commercial Paper
- •2.4Corporate Bonds
- •2.5More Exotic Securities
- •2.6Raising Debt Capital in the Euromarkets
- •2.7Primary and Secondary Markets forDebt
- •2.8Bond Prices, Yields to Maturity, and Bond Market Conventions
- •2.9Summary and Conclusions
- •3.1Types of Equity Securities
- •Volume of Financing with Different Equity Instruments
- •3.2Who Owns u.S. Equities?
- •3.3The Globalization of Equity Markets
- •3.4Secondary Markets forEquity
- •International Secondary Markets for Equity
- •3.5Equity Market Informational Efficiency and Capital Allocation
- •3.7The Decision to Issue Shares Publicly
- •3.8Stock Returns Associated with ipOs of Common Equity
- •Ipo Underpricing of u.S. Stocks
- •4.1Portfolio Weights
- •4.2Portfolio Returns
- •4.3Expected Portfolio Returns
- •4.4Variances and Standard Deviations
- •4.5Covariances and Correlations
- •4.6Variances of Portfolios and Covariances between Portfolios
- •Variances for Two-Stock Portfolios
- •4.7The Mean-Standard Deviation Diagram
- •4.8Interpreting the Covariance as a Marginal Variance
- •Increasing a Stock Position Financed by Reducing orSelling Short the Position in
- •Increasing a Stock Position Financed by Reducing orShorting a Position in a
- •4.9Finding the Minimum Variance Portfolio
- •Identifying the Minimum Variance Portfolio of Two Stocks
- •Identifying the Minimum Variance Portfolio of Many Stocks
- •Investment Applications of Mean-Variance Analysis and the capm
- •5.2The Essentials of Mean-Variance Analysis
- •5.3The Efficient Frontierand Two-Fund Separation
- •5.4The Tangency Portfolio and Optimal Investment
- •Identification of the Tangency Portfolio
- •5.5Finding the Efficient Frontierof Risky Assets
- •5.6How Useful Is Mean-Variance Analysis forFinding
- •5.8The Capital Asset Pricing Model
- •Implications for Optimal Investment
- •5.9Estimating Betas, Risk-Free Returns, Risk Premiums,
- •Improving the Beta Estimated from Regression
- •Identifying the Market Portfolio
- •5.10Empirical Tests of the Capital Asset Pricing Model
- •Is the Value-Weighted Market Index Mean-Variance Efficient?
- •Interpreting the capm’s Empirical Shortcomings
- •5.11 Summary and Conclusions
- •6.1The Market Model:The First FactorModel
- •6.2The Principle of Diversification
- •Insurance Analogies to Factor Risk and Firm-Specific Risk
- •6.3MultifactorModels
- •Interpreting Common Factors
- •6.5FactorBetas
- •6.6Using FactorModels to Compute Covariances and Variances
- •6.7FactorModels and Tracking Portfolios
- •6.8Pure FactorPortfolios
- •6.9Tracking and Arbitrage
- •6.10No Arbitrage and Pricing: The Arbitrage Pricing Theory
- •Verifying the Existence of Arbitrage
- •Violations of the aptEquation fora Small Set of Stocks Do Not Imply Arbitrage.
- •Violations of the aptEquation by Large Numbers of Stocks Imply Arbitrage.
- •6.11Estimating FactorRisk Premiums and FactorBetas
- •6.12Empirical Tests of the Arbitrage Pricing Theory
- •6.13 Summary and Conclusions
- •7.1Examples of Derivatives
- •7.2The Basics of Derivatives Pricing
- •7.3Binomial Pricing Models
- •7.4Multiperiod Binomial Valuation
- •7.5Valuation Techniques in the Financial Services Industry
- •7.6Market Frictions and Lessons from the Fate of Long-Term
- •7.7Summary and Conclusions
- •8.1ADescription of Options and Options Markets
- •8.2Option Expiration
- •8.3Put-Call Parity
- •Insured Portfolio
- •8.4Binomial Valuation of European Options
- •8.5Binomial Valuation of American Options
- •Valuing American Options on Dividend-Paying Stocks
- •8.6Black-Scholes Valuation
- •8.7Estimating Volatility
- •Volatility
- •8.8Black-Scholes Price Sensitivity to Stock Price, Volatility,
- •Interest Rates, and Expiration Time
- •8.9Valuing Options on More Complex Assets
- •Implied volatility
- •8.11 Summary and Conclusions
- •9.1 Cash Flows ofReal Assets
- •9.2Using Discount Rates to Obtain Present Values
- •Value Additivity and Present Values of Cash Flow Streams
- •Inflation
- •9.3Summary and Conclusions
- •10.1Cash Flows
- •10.2Net Present Value
- •Implications of Value Additivity When Evaluating Mutually Exclusive Projects.
- •10.3Economic Value Added (eva)
- •10.5Evaluating Real Investments with the Internal Rate of Return
- •Intuition for the irrMethod
- •10.7 Summary and Conclusions
- •10A.1Term Structure Varieties
- •10A.2Spot Rates, Annuity Rates, and ParRates
- •11.1Tracking Portfolios and Real Asset Valuation
- •Implementing the Tracking Portfolio Approach
- •11.2The Risk-Adjusted Discount Rate Method
- •11.3The Effect of Leverage on Comparisons
- •11.4Implementing the Risk-Adjusted Discount Rate Formula with
- •11.5Pitfalls in Using the Comparison Method
- •11.6Estimating Beta from Scenarios: The Certainty Equivalent Method
- •Identifying the Certainty Equivalent from Models of Risk and Return
- •11.7Obtaining Certainty Equivalents with Risk-Free Scenarios
- •Implementing the Risk-Free Scenario Method in a Multiperiod Setting
- •11.8Computing Certainty Equivalents from Prices in Financial Markets
- •11.9Summary and Conclusions
- •11A.1Estimation Errorand Denominator-Based Biases in Present Value
- •11A.2Geometric versus Arithmetic Means and the Compounding-Based Bias
- •12.2Valuing Strategic Options with the Real Options Methodology
- •Valuing a Mine with No Strategic Options
- •Valuing a Mine with an Abandonment Option
- •Valuing Vacant Land
- •Valuing the Option to Delay the Start of a Manufacturing Project
- •Valuing the Option to Expand Capacity
- •Valuing Flexibility in Production Technology: The Advantage of Being Different
- •12.3The Ratio Comparison Approach
- •12.4The Competitive Analysis Approach
- •12.5When to Use the Different Approaches
- •Valuing Asset Classes versus Specific Assets
- •12.6Summary and Conclusions
- •13.1Corporate Taxes and the Evaluation of Equity-Financed
- •Identifying the Unlevered Cost of Capital
- •13.2The Adjusted Present Value Method
- •Valuing a Business with the wacc Method When a Debt Tax Shield Exists
- •Investments
- •IsWrong
- •Valuing Cash Flow to Equity Holders
- •13.5Summary and Conclusions
- •14.1The Modigliani-MillerTheorem
- •IsFalse
- •14.2How an Individual InvestorCan “Undo” a Firm’s Capital
- •14.3How Risky Debt Affects the Modigliani-MillerTheorem
- •14.4How Corporate Taxes Affect the Capital Structure Choice
- •14.6Taxes and Preferred Stock
- •14.7Taxes and Municipal Bonds
- •14.8The Effect of Inflation on the Tax Gain from Leverage
- •14.10Are There Tax Advantages to Leasing?
- •14.11Summary and Conclusions
- •15.1How Much of u.S. Corporate Earnings Is Distributed to Shareholders?Aggregate Share Repurchases and Dividends
- •15.2Distribution Policy in Frictionless Markets
- •15.3The Effect of Taxes and Transaction Costs on Distribution Policy
- •15.4How Dividend Policy Affects Expected Stock Returns
- •15.5How Dividend Taxes Affect Financing and Investment Choices
- •15.6Personal Taxes, Payout Policy, and Capital Structure
- •15.7Summary and Conclusions
- •16.1Bankruptcy
- •16.3How Chapter11 Bankruptcy Mitigates Debt Holder–Equity HolderIncentive Problems
- •16.4How Can Firms Minimize Debt Holder–Equity Holder
- •Incentive Problems?
- •17.1The StakeholderTheory of Capital Structure
- •17.2The Benefits of Financial Distress with Committed Stakeholders
- •17.3Capital Structure and Competitive Strategy
- •17.4Dynamic Capital Structure Considerations
- •17.6 Summary and Conclusions
- •18.1The Separation of Ownership and Control
- •18.2Management Shareholdings and Market Value
- •18.3How Management Control Distorts Investment Decisions
- •18.4Capital Structure and Managerial Control
- •Investment Strategy?
- •18.5Executive Compensation
- •Is Executive Pay Closely Tied to Performance?
- •Is Executive Compensation Tied to Relative Performance?
- •19.1Management Incentives When Managers Have BetterInformation
- •19.2Earnings Manipulation
- •Incentives to Increase or Decrease Accounting Earnings
- •19.4The Information Content of Dividend and Share Repurchase
- •19.5The Information Content of the Debt-Equity Choice
- •19.6Empirical Evidence
- •19.7Summary and Conclusions
- •20.1AHistory of Mergers and Acquisitions
- •20.2Types of Mergers and Acquisitions
- •20.3 Recent Trends in TakeoverActivity
- •20.4Sources of TakeoverGains
- •Is an Acquisition Required to Realize Tax Gains, Operating Synergies,
- •Incentive Gains, or Diversification?
- •20.5The Disadvantages of Mergers and Acquisitions
- •20.7Empirical Evidence on the Gains from Leveraged Buyouts (lbOs)
- •20.8 Valuing Acquisitions
- •Valuing Synergies
- •20.9Financing Acquisitions
- •Information Effects from the Financing of a Merger or an Acquisition
- •20.10Bidding Strategies in Hostile Takeovers
- •20.11Management Defenses
- •20.12Summary and Conclusions
- •21.1Risk Management and the Modigliani-MillerTheorem
- •Implications of the Modigliani-Miller Theorem for Hedging
- •21.2Why Do Firms Hedge?
- •21.4How Should Companies Organize TheirHedging Activities?
- •21.8Foreign Exchange Risk Management
- •Indonesia
- •21.9Which Firms Hedge? The Empirical Evidence
- •21.10Summary and Conclusions
- •22.1Measuring Risk Exposure
- •Volatility as a Measure of Risk Exposure
- •Value at Risk as a Measure of Risk Exposure
- •22.2Hedging Short-Term Commitments with Maturity-Matched
- •Value at
- •22.3Hedging Short-Term Commitments with Maturity-Matched
- •22.4Hedging and Convenience Yields
- •22.5Hedging Long-Dated Commitments with Short-Maturing FuturesorForward Contracts
- •Intuition for Hedging with a Maturity Mismatch in the Presence of a Constant Convenience Yield
- •22.6Hedging with Swaps
- •22.7Hedging with Options
- •22.8Factor-Based Hedging
- •Instruments
- •22.10Minimum Variance Portfolios and Mean-Variance Analysis
- •22.11Summary and Conclusions
- •23Risk Management
- •23.2Duration
- •23.4Immunization
- •Immunization Using dv01
- •Immunization and Large Changes in Interest Rates
- •23.5Convexity
- •23.6Interest Rate Hedging When the Term Structure Is Not Flat
- •23.7Summary and Conclusions
- •Interest Rate
- •Interest Rate
6.9Tracking and Arbitrage
The previous sections illustrated how to construct portfolios with any pattern of factor
betas from a limited number of securities. With more securities, the additional degrees
of freedom in the selection of portfolio weights make the task of targeting a specific
factor beta configuration even easier. Because a sufficiently large number of securities
in the portfolio makes it likely that these portfolios will have negligible firm-specific
risk, it is usually possible to construct portfolios that perfectly track investments that
have no firm-specific risk. This is done by forming portfolios of the pure factor port-
folios that have the same factor betas as the investment one wishes to track. The fac-
tor equations of the tracking portfolio and the tracked investment will be identical
except for the s. By assumption, there are no ˜terms in these factor equations. Hence,
the return of the tracking portfolio and the tracked investment can, at most, differ by
a constant: the difference in their s, which is the difference in their expected returns.
If the factor betas of the tracking portfolio and the tracked investment are the same
but their expected returns differ, then there will be an opportunity for arbitrage. For
example, if the tracking portfolio has a higher expected return, then investors can buy
that portfolio and sell short the tracked investment and receive risk-free cash in the
future without spending any money today.
Using Pure Factor Portfolios to Track the Returns of a Security
Example 6.8 illustrates how to use factor portfolios and the risk-free asset to track the
returns of another security.
Example 6.8:Tracking and Arbitrage with Pure FactorPortfolios
Given a two-factor model, find the combination of a risk-free security with a 4 percent return
and the two pure factor portfolios from Example 6.6 that tracks stock i, which is assumed
to have a factor equation of
r˜˜˜
.0862F.6F
12
Then, find the expected return of the tracking portfolio and determine if arbitrage exists.
Recall that the factor equations for the two pure factor portfolios (see Example 6.7) were
respectively given by
˜˜˜
R .06F0F
p112
˜˜˜
R .040FF
p212
-
Grinblatt
414 Titman: FinancialII. Valuing Financial Assets
6. Factor Models and the
© The McGraw
414 HillMarkets and Corporate
Arbitrage Pricing Theory
Companies, 2002
Strategy, Second Edition
198Part IIValuing Financial Assets
Answer:To track stock i’s two factor betas, place a weight of 2 on factor portfolio 1 and
a weight of .6 on factor portfolio 2.Since the weights now sum to 1.4, a weight of .4
must be placed on the risk-free asset.The expected return of this portfolio is the portfolio-
weighted average of the expected returns of the risk-free asset, factor portfolio 1, and fac-
tor portfolio 2, which is
.4(.04) 2(.06) .6(.04) .08
An arbitrage opportunity exists because this expected return of 8 percent differs from the
8.6 percent return of the tracked security, as indicated by the .086 intercept (and the com-
mon convention, discussed earlier, that the means of the factors are zero).
The Expected Return of the Tracking Portfolio
In Example 6.8, the tracking portfolio for stock i is a weighted average of the two fac-
tor portfolios and the risk-free asset. Factor portfolio 1 is used solely to generate the
target factor 1 beta. Factor portfolio 2 is used solely to generate the target sensitivity
to factor 2. The risk-free asset is used only to make the weights of the tracking port-
folio sum to one. Note that the expected return of this tracking portfolio is
Expected return (1 )r (r
) (r
)
i1i2f i1f 1i2f2
where is the factor beta of the tracked investment on factor j (and thus also the
ij
weight on pure factor portfolio j), and
is the risk premium of factor portfolio j (mak-
j
ing r
its expected return). The expression above for the expected return is also
f j
written in an equivalent form
Expected return r
f i11 i22
Result 6.5 generalizes Example 6.8 as follows:
-
Result
6.5
An investment with no firm-specific risk and a factor beta of on the jthfactor in a
ij
K-factormodel is tracked by a portfolio with weights of on factor portfolio 1, on
i1i2
K
factor portfolio 2,..., on factor portfolio K,and 1 on the risk-free asset.
iK ij
j 1
The expected return on this tracking portfolio is therefore
. . .
r
fi11i22iKK
where
,
, .. .
denote the risk premiums of the factor portfolios and ris the risk-
12Kf
free return.
Decomposing Pure Factor Portfolios into Weights on More Primitive Securities
Factor portfolios are themselves combinations of individual securities, like stocks and
bonds. In Example 6.8, the portfolio with weights of .4 on the risk-free security, 2
on factor portfolio 1, and .6 on factor portfolio 2, can be further broken down. Recall
from Example 6.6 that factor portfolio 1 has respective weights of (2, 1/3, 4/3) on
the three individual securities while factor portfolio 2 has corresponding weights of (3,
2/3, 4/3). Hence, a weight of 2 on factor portfolio 1 is really a weight of 4 on secu-
rity c, 2/3 on security g, and 8/3 on security s. Aweight of 0.6 on factor port-folio
2 is really a weight of 1.8 on security c, 0.4 on security g, and 0.8 on security s.
Summing the weights for each security found in Example 6.6 implies that at a more
basic level, our tracking portfolio in Example 6.8 consisted of weights of 2.2, 16/15,
Grinblatt |
II. Valuing Financial Assets |
6. Factor Models and the |
©
The McGraw |
Markets and Corporate |
|
Arbitrage Pricing Theory |
Companies, 2002 |
Strategy, Second Edition |
|
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|
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Chapter 6
Factor Models and the Arbitrage Pricing Theory
199
and 28/15 on securities c, g, and s, respectively, plus a weight of 0.4 on the risk-
free asset.21
Thus, it makes no difference in the last example whether one views the
tracking portfolio as being generated by stocks c, g, and s or by pure factor portfolios.
