Encyclopedia of Finance

Preface to the Third Edition
Preface to the Second Edition
Preface to the First Edition
Contents
About the Editors
Contributors
Part I: Terms and Essays
1 Terms and Essays
1.1 A
1.2 B
1.3 C
1.4 D
1.5 E
1.6 F
1.7 G
1.8 H
1.9 I
1.10 J
1.11 K
1.12 L
1.13 M
1.14 N
1.15 O
1.16 P
1.17 Q
1.18 R
1.19 S
1.20 T
1.21 U
1.22 V
1.23 W
1.24 X
1.25 Y
1.26 Z
References
Part II: Papers
2 Deposit Insurance Schemes
2.1 Introduction
2.2 The Inherent Fragility of Banks
2.3 The Benefits of Deposit Insurance Schemes
2.4 The Costs of Deposit Insurance Schemes
2.5 Differences in Deposit Insurance Schemes Across Countries
2.6 Lessons Learned from Banking Crises
2.7 Conclusions
References
3 Gramm-Leach-Bliley Act: Creating a New Bank for a New Millennium
3.1 Introduction
3.2 Major Provisions of the Gramm-Leach-Bliley Act
3.2.1 Financial Holding Companies
3.2.2 National Bank Financial Subsidiaries
3.3 Functional Regulation and Equal Treatment for Foreign Banks
3.3.1 Retention of Savings and Loan Holding Companies
3.3.2 Community Reinvestment Act Provisions
3.3.3 Other Components of GLBA
3.3.4 Potential Benefits to Banks and Their Customers
3.3.5 Potential Risk Elements to Banks and Their Customers
3.3.6 Implications for the Future
3.4 Conclusion
References
4 Pre-funded Coupon and Zero-Coupon Bonds: Cost of Capital Analysis
4.1 Introduction
4.2 Funding Options
4.2.1 Zero-Coupon Bonds
4.2.2 Pre-funded Bonds
4.3 Mccauley Duration and Value Loss
4.4 Numerical Example and Analysis
4.5 Conclusion
References
5 Intertemporal Risk and Currency Risk
5.1 Introduction
5.2 No Differences in Consumption Opportunity Set
5.2.1 Asset Pricing Model
5.2.1.1 Nonexpected Utility
5.2.1.2 Log-Linear Budget Constraint
5.2.1.3 Euler Equations
5.2.1.4 Substituting Consumption Out of the Asset Pricing Model
5.2.2 Empirical Evidence
5.3 Differences in Consumption Opportunity Set
5.3.1 Portfolio Choice in an International Setting
5.3.1.1 Kreps-Porteus Preferences
5.3.1.2 Optimal Consumption and Portfolio Allocation
5.3.2 International Asset Pricing Model Without Consumption
5.3.3 International Asset Pricing Model When PPP Deviate
5.4 Conclusion
References
6 Credit Derivatives
6.1 Introduction
6.2 Asset Swaps
6.3 Default Swaps
6.4 Total Return Swaps
6.5 Principal Protection
6.6 Credit Spread Options
6.7 Basket Default Swaps
6.8 Convertible Bonds
6.9 Conclusions
References
7 Foreign Exchange Risk Premium and Policy Uncertainty
7.1 Introduction
7.2 Data
7.3 FXRP Models Based on Time Series Information
7.3.1 Forward Premium Hypothesis
7.3.2 Conditional Variance
7.3.3 News-Based Exchange Rate Volatility Hypothesis
7.4 Predicting FXRP Based on Asset Return Differentials
7.4.1 Equity Risk Premium Differential Hypothesis
7.4.2 Real Interest Rate Differential Hypothesis
7.4.3 Equity Premium Differential Cum Real Interest Rate Differential Hypothesis
7.5 Effects of Policy Uncertainty
7.5.1 Economic Policy Uncertainty
7.5.2 Effect of Geopolitical Risk
7.6 Conclusions
References
8 Treasury Inflation-Protected Securities
8.1 Introduction
8.2 Size of Market
8.3 Reference CPI
8.4 Conversion from Real to Nominal Prices
8.5 Three-Month Lag Effect
8.6 Public Issuance
8.7 Tax Disadvantage: Phantom Income
8.8 TIPS as an Asset Class
8.9 Size of the Inflation Risk Premium
8.10 Cost of TIPS to the Treasury Since Inception
8.11 Liquidity Premiums
8.12 Observable Expected Real Rate
8.13 Information Content of Maturing TIPS
8.14 Inflation Information Aggregation
8.15 Price Discovery and Information Risk
8.16 Conclusion
References
9 Asset Pricing Models
9.1 The Capital Asset Pricing Model
9.2 Consumption-Based Asset Pricing Models
9.3 Multi-beta Asset Pricing Models
9.4 Relation to Mean-Variance Efficiency
9.5 Factor Models
9.6 Factor Models and the Arbitrage Pricing Model
9.7 Summary
References
10 Conditional Asset Pricing
10.1 Introduction
10.2 The Conditional Capital Asset Pricing Model
10.3 Evidence for Return Predictability
10.4 Tests of Conditional CAPMs
10.5 Multi-beta Conditional Asset Pricing Models
References
11 Conditional Performance Evaluation
11.1 Conditional Performance Evaluation
11.2 Examples
11.3 Conditional Market Timing
11.4 Conditional Weight-Based Performance Measures
11.5 Empirical Evidence Using Conditional Performance Evaluation
References
12 Working Capital and Cash Flow
12.1 Introduction
12.2 Definitions
12.2.1 Working Capital
12.2.2 Working Capital Management
12.2.3 Net Working Capital
12.3 An Overview of Corporate Working Capital
12.3.1 Money
12.3.2 Cash Management
12.3.3 The Components of Working Capital
12.4 Flow of Funds
12.4.1 Cash
12.4.2 Marketable Securities
12.4.3 Accounts Receivable
12.4.4 Inventories
12.4.5 The Accounting Perspective Versus the Financial Perspective
12.4.6 The Reasons for Holding Cash
12.4.7 Investing in Marketable Securities
12.4.8 Creating an Integrated Cash Management System
12.4.9 Cash Flow Cycle
12.5 Calculating the Cash Flow Cycle
12.6 The Matching Principle
12.7 A Conservative Versus an Aggressive Approach to the Matching Concept
12.8 Summary
References
13 Evaluating Fund Performance Within the Stochastic Discount Factor Framework
13.1 Introduction
13.2 Evaluating Performance
13.3 Estimation Issues
13.4 Conclusions
References
14 Duration Concepts, Analysis, and Applications
14.1 Introduction
14.2 Duration Formulation and Interpretation
14.3 Duration and Price Volatility
14.4 Convexity: A Duration Complication
14.5 Duration and Value at Risk
14.6 Duration and Immunization
14.7 Contingent Immunization
14.8 Duration of Foreign Bonds
14.9 Stochastic Process Risk: Immunization Complication
14.10 Effectiveness of Duration-Matched Strategies
14.11 Use of Financial Futures
14.12 Duration of Corporate Bonds
14.13 Macrohedging
14.14 Duration Gap
14.15 Other Applications of Duration Gaps
References
15 Loan Contract Terms
15.1 Introduction
15.2 Characteristics of the Lending Syndicate
15.3 Methodological Issues
15.3.1 Simultaneity
15.4 Measures of Risk
References
16 Chinese A and B Shares
References
17 Decimal Trading in the U.S. Stock Markets
References
18 The 1997 NASDAQ Trading Rules
References
19 Reincorporation
19.1 Introduction
19.2 Competition Among States for Corporate Charters
19.3 Why, When, and Where to Reincorporate
19.4 What Management Says
19.4.1 Reincorporations That Strengthen Takeover Defenses
19.4.2 Reincorporations That Reduce Director Liability
19.4.3 Other Motives for Reincorporations
19.5 Summary and Conclusions
References
20 Mean Variance Portfolio Allocation
20.1 Introduction
20.2 Mean-Variance Portfolio Selection
20.3 Mean-Variance Efficiency and Asset Pricing Models
20.3.1 Capital Asset Pricing Models
20.3.2 Arbitrage Pricing Theory
20.3.3 Intertemporal Capital Asset Pricing Model (ICAPM)
20.4 Estimation Errors and Portfolio Choice
References
21 Online Trading
21.1 Introduction
21.2 The Issues
21.3 Some New Portfolio Structure Models
21.4 Conclusion
References
22 A Critical Evaluation of the Portfolio Performance Indices Under Rank Transformation
22.1 Introduction
22.2 The Relationship Between Treynor, Sharpe, and Jensen´s Measures in the Simple CAPM
22.3 The Relationship Between the Treynor, Sharpe, and Jensen Measures in the Augmented CAPM
22.4 Conclusion
22.5 Notes
References
23 Corporate Failure: Definitions, Methods, and Failure Prediction Models
23.1 Introduction
23.2 The Possible Causes of Bankruptcy
23.3 Methods of Bankruptcy
23.3.1 Company Voluntary Arrangements
23.3.2 Administration Order
23.3.3 Administrative Receivership
23.3.4 Creditors´ Voluntary Liquidation
23.3.5 Members´ Voluntary Liquidation
23.3.6 Compulsory Liquidation
23.4 Prediction Model for Corporate Failure
23.4.1 Financial Ratio Analysis and Discriminant Analysis
23.4.2 Conditional Probability Analysis
23.4.3 Three CPA Models: LP, PM, and LM
23.5 The Selection of an Optimal Cut-Off Point
23.6 Recent Developments
23.7 Conclusion
References
24 Main Bank Relationships, Debt Structure, and Innovation in Japan
24.1 Introduction
24.2 Literature Review
24.2.1 The Nature of Innovation and the Roles of Debt on Innovation
24.2.2 Main Bank Relationship and Innovation
24.3 Data and Methodology
24.3.1 Data
24.3.2 Model Specification
24.4 Empirical Results
24.4.1 Summary Statistics
24.4.2 Univariate Tests
24.4.3 2SLS with Instrumental Variable
24.4.4 2SLS Regression Results
24.5 Robustness Checks
24.5.1 The Exogenous Shocks of Keiretsu Consolidation on Corporate Innovation
24.5.2 Propensity Score Matching
24.5.3 Other Measurements of Corporate Innovation
24.6 Conclusions
References
25 Term Structure: Interest Rate Models
25.1 Introduction
25.2 Interest Rate Movements: Historical Experiences
25.2.1 Lognormal Versus Normal Movements
25.2.2 Interest Rate Correlations
25.2.3 Term Structure of Volatilities
25.2.4 Mean Reversion
25.3 Equilibrium Models
25.3.1 The Cox-Ingersoll-Ross Model
25.3.2 The Vasicek Model
25.3.3 The Brennan and Schwartz Two-Factor Model
25.4 Arbitrage-Free Models
25.4.1 The Ho-Lee Model
25.4.2 The Black-Derman-Toy Model
25.4.3 The Hull-White Model
References
26 Review of REIT and MBS
26.1 Introduction
26.2 The REIT Background
26.3 The MBS Story
26.3.1 The Special Contributions of the Government-Sponsored Enterprises
26.3.2 Market Participants
26.3.3 MBS Pricing
26.3.4 The Impact of Securitization on Financial Institutions
26.4 Conclusion
References
27 Experimental Economics and the Theory of Finance
27.1 Introduction
27.2 Allias Paradox, PT, CPT, and RDEU: Claims and Implication to the Theory of Finance
27.2.1 Probability Distortions (or Decision Weights)
27.2.2 Change of Wealth Rather than Total Wealth
27.2.3 Integration of Cash Flows
27.2.4 Risk Seeking Segment of Preferences
27.3 Experimental Studies in Finance
27.3.1 Portfolio Diversification and Random Walk
27.3.2 The Equity Risk Premium Puzzle
27.3.3 The Shape of Preference
27.3.3.1 Prospect Stochastic Dominance (PSD)
27.3.3.2 Markowitz Stochastic Dominance (MSD)
27.3.4 Asset Allocation and the Investment Horizon
27.3.5 Diversification: The 1/n Rule
27.3.6 The CAPM: Experimental Study
27.4 Implication of the Experimental Findings to Finance
27.4.1 Arbitrage Models
27.4.2 Stochastic Dominance (SD) Rules
27.4.3 Mean-Variance (M-V) Rule and PT
27.4.4 Portfolios and Mutual Funds: Markowitz´s M-V Rule and PT - A Consistency or a Contradiction?
27.4.5 The Empirical Studies and Decision Weights
27.5 Conclusion
References
28 Merger and Acquisition: Definitions, Motives, and Market Responses
28.1 Introduction
28.2 Definition of ``Takeover,´´ ``Merger,´´ and ``Acquisition´´
28.3 Motives for Takeover
28.3.1 Efficiency Theories
28.3.2 Agency Theory
28.3.3 Free Cash Flow Hypothesis
28.3.4 Market Power Hypothesis
28.3.5 The Diversification Hypothesis
28.3.6 The Information Hypothesis
28.3.7 The Bankruptcy Avoidance Hypothesis
28.3.8 Accounting and Tax Effects
28.4 Methods of Takeover Financing and Payment
28.5 Market Reaction to Acquiring Firms
28.6 Conclusion
References
29 Multistage Compound Real Options: Theory and Application
29.1 Introduction
29.2 Real Options
29.2.1 Treatment of Nontraded Assets
29.2.2 Dividend-Like Yield
29.3 Hi-tech Value as a Call Option
29.4 Two-Stage Compound Option
29.5 Multistage Real Compound Call Option and Dividend-Like Yield
29.5.1 Multistage Real Compound Call Option
29.5.2 Estimation of the Dividend-Like Yield
29.5.2.1 CAPM Method
29.5.2.2 Cost of Carry Model
29.6 Algorithms for Computing Multivariate Normal Integrals and Solving the Root of Nonlinear Model
29.6.1 Monte Carlo Method
29.6.2 Drezner Method
29.6.3 Lattice Method
29.7 Simulative Analysis
29.7.1 Comparing Numerical Methods for Multivariate Normal Integral and Critical Value
29.7.2 Critical Values, Company Values Against Investment Modes
29.7.3 Sensitivity Analysis
29.7.3.1 Sensitivity Analysis of Dividend-Like Yield
29.7.3.2 Sensitivity Analysis of Volatility
29.7.3.3 Sensitivity Analysis of Risk-Free Rate
29.8 The Case Study: ProMos Technologies Inc.
29.8.1 The Model
29.8.2 Finding the Underlying Variable and Twin Securities
29.8.3 Exercise Price
29.8.4 Dividend-Like Yield
29.8.5 Volatility
29.8.6 Valuation of ProMos
29.9 Conclusion
29.9 Appendix
References
30 Market Efficiency Hypothesis
30.1 Definition
30.2 The Efficient Market Model
30.3 The Joint Hypothesis Problem
30.4 Three Categories of Testing Literature
30.4.1 Weak-Form Tests
30.4.2 Semi-Strong-Form Tests
30.4.3 Strong-Form Tests
30.5 Conclusion
References
31 The Microstructure/Micro-Finance Approach to Exchange Rates
31.1 Definition
31.2 Empirical Failure of Traditional Approaches to Exchange Rates
31.3 Why Microstructure Approach?
31.4 The Information Role of Order Flow
31.5 Conclusion
References
32 Arbitrage and Market Frictions
32.1 Introduction
32.2 A Basic Framework
32.3 Exact Replication and Prices under no Frictions
32.4 No Short Sales
32.5 A Simple Binomial Model
32.6 Other Types of Frictions
32.7 Conclusion
References
33 Fundamental Tradeoffs in the Publicly Traded Corporation
33.1 Introduction
33.2 Fundamental Benefits of the Publicly Traded Corporation
33.2.1 Economies of Scale
33.2.2 Reducing the Cost of Capital: Diversification and Liquidity
33.3 Fundamental Costs of the Publicly Traded Corporation
33.3.1 Principal-Agent Conflicts of Interest
33.3.2 Information Asymmetry
33.4 Mitigating the Costs
33.4.1 Government Laws and Regulations
33.4.2 Securities Traders, Analysts, and the Press
33.4.3 Ownership Structure
33.4.4 Board Oversight
33.4.5 Financial Institutions
33.4.6 Contract Devices
33.4.7 Signaling
33.5 Summary
References
34 The Mexican Peso Crisis
35 Methods for Portfolio Performance Evaluation
35.1 Introduction
35.2 Conventional Methods
35.2.1 Benchmark Comparison
35.2.2 Style Comparison
35.3 Risk-Adjusted Methods
35.3.1 Sharpe Ratio
35.3.2 Treynor Ratio
35.3.3 Jensen´s Alpha
35.3.4 Modigliani-Modigliani Measure
35.3.5 Treynor Squared
References
36 Call Auction Trading
36.1 Order Handling
36.2 Alternative Call Auction Designs
36.2.1 Price Scan Auctions
36.2.2 Sealed Bid Auctions
36.2.3 Open Limit Order Book
36.2.4 Crossing Networks
36.3 Order Batching and Price Determination
36.4 Relationship Between Limit and Market Orders
36.5 The Electronic Call Auction
References
37 Market Liquidity
References
38 Market Makers
References
39 Structure of Securities Markets
References
40 Accounting Scandals and Implications for Directors: Lessons from Enron
40.1 Introduction
40.2 The Competitive Environment and Incentives for Aggressive Accounting
40.3 Aggressive Accounting Practices
40.3.1 Effectiveness of ``Hedging´´ Transactions
40.3.2 Control and Risks Relating to Unconsolidated Entities
40.4 The Role of Corporate Governance
40.5 Conclusion
References
41 Agent-Based Models of Financial Markets
41.1 Introduction
41.2 Design Considerations
References
42 The Asian Bond Market
42.1 Introduction
42.2 The Asian Bond Market Launched by EMEAP Central Banks
42.3 The Asian Bond Market Initiative (ABMI)
42.4 The ABC Bond Corporation
42.5 Credit Enhancement
42.6 Securitized Asian Corporate Bonds
42.7 Efficient Financial Intermediaries
42.8 Is the Classic Form of Emerging Market Debt Crisis a Thing of the Past?
42.9 Recent Trends in Global Finance
42.9.1 Ample Liquidity
42.9.2 The Demand for Emerging Market Currency Bonds Is Rising
42.9.3 Asset Management
42.10 Asian Finances in the 1997 and 2021: A Comparison
42.10.1 From Capital Importer to Capital Exporter
42.10.2 Short-Term and Long-Term Capital Flows
42.10.3 Different Investor Motivations
42.10.4 Asian Regulators and Financial Market Stability
42.10.5 The Increasing Importance of Asian Financial Hubs
42.10.6 Geopolitics
42.11 Long-Term Trends
42.11.1 The Increasing Role of Large Projects
42.11.2 Yuan Internationalization
42.11.3 Financial Technology Transfer
42.11.4 State Financial Backing Is No Longer Assured for Chinese SOEs
42.12 Conclusion
References
43 Cross-Border Mergers and Acquisitions
43.1 Macroeconomic Factors
43.1.1 Favorable Acquisition Factors
43.1.1.1 Exchange Rates
43.1.1.2 Diversification
43.1.1.3 Current Economic Conditions in the Home Country
43.1.1.4 Acquisition of Technological and Human Resources
43.1.2 Unfavorable Acquisition Factors
43.1.2.1 Unavailability of Information
43.1.2.2 Inefficient Management
43.1.2.3 Monopolistic Power
43.1.2.4 Government Restrictions and Regulations
43.2 Microeconomic Factors
43.2.1 Undervaluation
43.2.2 Synergy Hypothesis
43.2.3 Maximizing the Value of the Firm
43.3 An Analytical View of Cross-Border Mergers and Acquisitions
References
44 Jump Diffusion Model
44.1 Introduction
44.2 Mixed-Jump Processes
44.3 Bernoulli Jump Process
44.4 Gauss-Hermite Jump Process
44.5 Jumps in Interest Rates
44.6 Affine Jump Diffusion Model
44.7 Geometric Jump Diffusion Model
44.8 Autoregressive Jump Process Model
44.9 Jump Diffusion Models with Conditional Heteroscedasticity
44.9.1 Conditional Jump Dynamics
44.9.2 ARCH/GARCH Jump Diffusion Model
44.10 Other Jump Diffusion Models
References
45 Networks, Nodes, and Priority Rules
45.1 Priority Rules
45.2 Literature on Priority Rules
45.3 Networks
45.3.1 The Network for Listed Stocks
45.3.2 The Network for OTC Stocks
45.3.3 Do Networks Need Priority Rules?
45.3.4 Liquidity Supplied by Limit Order Traders
45.3.5 A Final Note on the Need for Speed
45.4 Conclusion
References
46 The Momentum Trading Strategy
46.1 Introduction
46.2 The Implementation of Momentum Strategies
46.2.1 Cross-Sectional Momentum Strategies
46.2.2 Time-Series Momentum Strategies
46.3 Explanations for Momentum Profits
46.4 Momentum Profits Across Firms, Countries, and Times
46.4.1 Momentum Profits and Firm Characteristics
46.4.2 Momentum Profits and Country Characteristics
46.4.3 Momentum Profits and Market States
References
47 Equilibrium Credit Rationing and Monetary Non-neutrality in a Small Open Economy
47.1 Introduction
47.2 Bank Behavior and Credit Market
47.3 Macroeconomic Equilibrium
47.3.1 Case for Credit Rationing
47.3.2 Case for Non-rationing of Credit
47.4 Comparative Static Analysis
47.5 Conclusion
References
48 Policy Coordination Between Wages and Exchange Rates in Singapore
48.1 Introduction
48.2 Complementarity of Wages and Exchange Rates
48.3 Policy Games in Wage Growth and Exchange Rate Appreciation
48.4 Complementarity of Non-Nash Wage Growth and Exchange-Rate Appreciation
48.5 Conclusion
References
49 The Le Chatelier Principle of the Capital Market Equilibrium
49.1 Introduction
49.2 The Le Chatelier Principle of the Markowitz Model
49.3 Simulation Results
49.4 Policy Implications of the Le Chatelier´s Principle
49.5 Concluding Remarks
References
50 MBS Valuation and Prepayments
50.1 Introduction
50.2 The Model
50.2.1 Modeling Issues
50.2.1.1 Exogenous Prepayment
50.2.1.2 Endogenous Termination
50.2.1.3 Transaction Costs and Aggregation of Heterogeneous Mortgages
50.2.2 A Model for Pricing Mortgage-Backed Securities
50.2.2.1 Termination Decision of a Single Mortgagor
50.2.2.2 Valuation of a Pool of Mortgages
50.3 Estimation
50.3.1 Determination of the Expected Termination Probability
50.3.1.1 Procedure for Determining the Security Price
50.3.1.2 Deriving the Expected Termination Probability of Mortgage i
50.3.1.3 Determination of the Expected Termination Level of Pool j
50.3.2 Estimation Approach
50.3.2.1 Generalized Method of Moments (GMM)
50.3.2.2 Moment Restrictions
50.4 Conclusion
References
51 The Impacts of IMF Bailouts in International Debt Crises
51.1 Introduction
51.2 Literature Review
51.3 Suggestions for Future Research
51.4 Notes
References
52 Corporate Governance: Structure and Consequences
52.1 Introduction and Framework for This Chapter
52.2 Definition and Importance of Corporate Governance
52.2.1 What Is Meant by Corporate Governance?
52.2.2 Agency Problem and Corporate Governance
52.2.3 Need and Importance of Corporate Governance
52.2.4 Impact of Sarbanes-Oxley Act 2002 (SOX) on Corporate Governance
52.3 Important Elements of Corporate Governance
52.3.1 Corporate Governance Structure
52.3.1.1 Unitary Corporate Governance Structure
52.3.1.2 Two-Tier Corporate Governance Structure
52.3.2 Two-Tier Corporate Structure in the Chinese Firms
52.3.3 Independence of Corporate Boards in the Unitary System
52.3.3.1 Different Types of Directors
52.3.3.2 Corporate Board Independence and Corporate Failures
52.3.3.3 Positive Aspects of Corporate Board Independence
52.3.3.4 Negative Aspects of Corporate Board Independence
52.3.3.5 Corporate Board Independence and Ownership Structure
52.3.3.6 Role of Executive Directors on Corporate Boards of Public Companies
52.3.3.7 CEO Duality and Corporate Board Independence
52.3.3.8 Positive Aspects of CEO-Duality
52.3.3.9 Negative Aspects of CEO-Duality
52.3.3.10 CEO Duality and Institutional Shareholders
52.3.4 Specialization of Independent Directors
52.3.5 Nomination of Outside Directors: Investors´ Rights
52.3.6 Corporate Board Size
52.3.6.1 Effectiveness of Large Versus Small Corporate Boards
52.3.6.2 Corporate Board Size and Firm Performance
52.4 Functioning of Corporate Boards
52.4.1 The Committee Structure
52.4.2 Audit Committee
52.4.2.1 Establishment of an Audit Committee
52.4.2.2 Functions of an Audit Committee
52.4.2.3 Waiver of Preapproval of Nonaudit Services
52.4.2.4 Independence of an Audit Committee
52.4.2.5 Financial Expertise in an Audit Committee
52.4.2.6 Disclosures on Audit Committee
52.4.3 Nominating/Governance Committee
52.4.3.1 Composition of a Nominating Committee
52.4.3.2 Responsibilities of a Nominating Committee
52.4.3.3 Meetings and Attendance by the Company Officers
52.4.3.4 Annual Report
52.4.4 Compensation Committee
52.4.4.1 Need for Expertise on Compensation Committee
52.4.4.2 Responsibilities of a Compensation Committee
52.4.4.3 Compensation Committee Procedures
52.4.5 Frequency of Corporate Board Meetings and Board Effectiveness
52.4.6 Busy Directors
52.4.6.1 Executive of One Company Serving as a Director of Another Company
52.4.6.2 Limit on the Number of Directorships for a Director
52.4.7 Diversity: Female Directors
52.4.7.1 Positives for Female Directors
52.4.7.2 Trend in Female Directors on Company Boards
52.5 Internal Controls and Corporate Boards
52.5.1 Importance of Internal Controls
52.5.2 Administrative Versus Accounting Controls
52.5.3 Historical Perspective on Internal Controls
52.5.4 Internal Controls Under Sarbanes-Oxley Act (SOX), 2002
52.5.4.1 Section 302 of SOX on Internal Controls
52.5.4.2 Section 404 of SOX on Internal Controls
52.5.4.3 Applicability of Sections 302 and 404 of SOX
52.5.4.4 Criticism of Section 404 (b)
52.5.4.5 Response to Criticism of Section 404 (b) of SOX
52.5.4.6 Auditing Standards and Internal Controls
52.6 External Controls and Corporate Governance
52.6.1 Two Types of External Controls
52.6.1.1 External Independent Auditors
52.6.1.2 External Auditor´s Functions
Hiring of Auditors and Communication with the Firm
Independence of Auditors
52.6.2 Market Control Mechanism
52.6.2.1 Antitakeover Devices
52.6.2.2 Green Mail
52.6.2.3 Blank Check
Supermajority
52.6.2.4 A Classified or Staggered Board
52.6.2.5 Directors´ Duties
52.6.2.6 Golden Parachutes
52.6.2.7 Silver Parachutes
52.6.2.8 Poison Pill
52.6.3 Antitakeover Devices and Independent Outside Directors
52.6.3.1 Poison Pill and Firm Performance
52.6.4 Role of Institutional Investors in Corporate Governance
52.7 Impact of Corporate Governance on Firm Performance and Disclosures
52.7.1 Firm Performance and Corporate Governance
52.7.2 Managers-Shareholders´ Conflict
52.7.2.1 Free Cash Flow Problem
52.7.2.2 Risk Problem
52.7.2.3 The Horizon Problem
52.7.2.4 Consequences of Managers-Shareholders´ Conflict
52.7.3 Monitoring by Corporate Boards and Firm Performance
52.7.3.1 Independent Corporate Boards and Firm Performance
52.7.3.2 Financial Expertise on the Corporate Board and Firm Performance
52.7.3.3 Alignment of Managers´ Interests with Shareholders´ Interests and Firm Performance
52.7.4 Financial Disclosures and Corporate Governance
52.7.4.1 Transparency in Disclosures
52.7.4.2 Factors Influencing Transparency
52.7.5 Corporate Governance, Risk Assessment, and Risk Disclosures
References
53 A Survey Article on International Banking
53.1 Introduction
53.2 Aspects of International Banking History Since 1960
53.2.1 Japan
53.2.2 The United States
53.2.3 Europe
53.3 Trends in International Lending 1977 to 2011
53.3.1 International Banking and the Relationship to Economic Activity
53.3.2 The Dominance of Developed Country Financial Institutions in International Debt Markets
53.3.3 International Money Market Instruments and the Currency of Issue
53.3.4 International Notes and Bonds: By Type and Currency of Issue
53.3.5 The 2008-2009 Financial and European Sovereign Debt Crises
53.3.6 Balance Sheet Ratios for Global Banks
53.4 Basel III and the Regulatory Response to the Financial Crisis of 2008
53.4.1 A Brief History of International Banking Regulation
53.4.2 The Failure of Basel II to Prevent Financial Crisis
53.4.3 Basel III
53.5 Conclusion
References
54 Hedge Funds: Overview, Strategies, and Trends
54.1 Introduction
54.2 Hedge Fund Defined
54.3 History of Hedge Funds
54.4 Notable Hedge Fund Managers
54.5 Growth of the Hedge Fund Industry and Hedge Fund Performance
54.6 Common Types of Hedge Funds
54.7 Organization and Regulation of Hedge Funds
54.8 Sample Hedge Fund Strategies
54.8.1 Case 1: Dual Share Class Arbitrage
54.8.2 Case 2: Pairs Trading with Ford and General Motors
54.8.3 Case 3: Activist Investor Carl Icahn´s Forced Breakup of Motorola
54.9 Trends in Hedge Funds
54.9.1 Trend 1: Further Compression of Fees
54.9.2 Trend 2: Payment for Alpha, Not Beta
54.9.3 Trend 3: Increased Liquidity
54.9.4 Trend 4: Increased Transparency and Growth of Managed Account Hedge Funds
54.9.5 Trend 5: Continued Growth in Hedge Funds, Including Public Vehicles
54.9.6 Trend 6: Increased Regulation
54.10 Conclusion
References
55 An Appraisal of Modeling Dimensions for Performance Appraisal of Global Mutual Funds
55.1 Introduction
55.2 Performance Evaluation Methods
55.3 A Review on Various Models for Performance Evaluation
55.3.1 Jensen Model
55.3.2 Fama Model
55.3.3 Treynor and Mazuy Model
55.3.4 Statman Model
55.3.5 Choi Model
55.3.6 Elango Model
55.3.7 Chang, Hung and Lee Model
55.3.8 MM Approach
55.4 Conclusion
References
56 Structural Credit Risk Models: Endogenous Versus Exogenous Default
56.1 Introduction
56.2 The Basic Model
56.2.1 Black-Scholes-Merton (BSM)
56.2.2 Moody´s-KMV (MKMV)
56.3 Exogenous Default Models
56.3.1 Black and Cox (BC)
56.3.2 Longstaff and Schwartz (LS)
56.3.3 Collin-Dufresne and Goldstein (CDG)
56.4 Endogenous Default Models
56.4.1 Geske (G)
56.4.2 Leland/Leland and Toft (LT)
56.5 Conclusion
References
57 Arbitrage Opportunity Set and the Role of Corporations
57.1 Introduction
57.2 Limits to Investor Arbitrage
57.3 The Model
57.3.1 Investor Arbitrageurs
57.3.2 Shareholders of Corporations Engaging in Arbitrage
57.4 Expanding the Arbitrage Opportunity Set by Corporations
57.5 Implications of Corporate Arbitrage
57.6 Conclusion
57.6 Appendix A: Proofs of Propositions and Corollaries
A.1. Proof of Proposition 1
A.2. Proof of Proposition 2
A.3. Proof of Corollary 1
A.4. Proof of Proposition 4
A.5. Proof of Proposition 5
A.6. Proof of Corollary 2
57.6 Appendix B: Deriving the Propositions Under the Case of
References
58 Equity Premium Puzzle: The Distributional Approach
58.1 Introduction
58.1.1 The Lucas´ Asset Pricing Model (CCAPM) and Standard Preferences
58.1.2 Equity Premium Puzzle in Different Countries
58.2 Approaches to the Equity Premium Puzzle
58.2.1 Time and State Preferences
58.2.2 Habit Formation
58.2.3 Idiosyncratic and Uninsurable Risk
58.2.4 Disaster State and Survival Bias
58.2.5 Borrowing Constraints
58.2.6 Transaction Costs
58.2.7 Taxes
58.2.8 Incomplete Markets
58.3 Is There the Equity Premium Puzzle?
58.3.1 Adjusted Set of Measurements
58.3.2 Statistical Data Analysis
58.3.3 Merton´s Model: Conflict with the Equity Premium Puzzle
58.3.4 Rational Beliefs
58.3.5 The Equity Premium Puzzle, Looking Forward
58.4 Stable Distributions
58.5 Risk Measure
58.6 The Model
58.7 Calculations and Results Analysis
58.8 Conclusions
References
59 Understanding Ginnie Mae Reverse Mortgage H-REMICs: Its Programs and Cashflow Analysis
59.1 Introduction
59.2 The FHA Home Equity Conversion Mortgage (HECM) Program
59.2.1 HECM Versus HELOC
59.2.2 Qualifications and Payment Plans
59.2.3 Loan Amount: Principal Limit; Maximum Claim Amount (MCA)
59.2.4 Fees and Caps
59.2.5 HECM Prepayment Curve (PPC)
59.2.5.1 Ginnie Mae HECM Pooling (HMBS)
59.2.5.2 HECM Pool Characteristics
59.2.5.3 Cash Flows and Prepayments
59.2.5.4 H-REMIC Tranche Principal Types
59.2.6 H-REMIC Modeling Example: GNR 2011-H10
59.2.6.1 Assumptions for GNR 2011-H10
59.2.7 Payment Rules and Tranche Waterfall
59.2.7.1 Analysis
59.2.7.2 Conclusions and Further Study
59.2.8 Glossary (See Ginnie Mae MBS Guide 2011; NRMLA Website)
59.2 Appendix 1: Assumed Trust Assets GNR 2011-H10: HMBS Pools (See Ginnie Mae REMIC Offering Circulars 2010)
59.2 Appendix 2: HECM PPC Curve: CPR Percentage in Effect by HECM Age
59.2 Appendix 3: Example of Cashflow Payment Rules
59.2 Appendix 4: A Model for Estimating Repayment Speeds for HECMs
References
60 An Analysis of Risk Treatment in the Field of Finance
60.1 Introduction
60.2 Sharpe´s Classification
60.3 Treynor´s Classification
60.4 Advantages of Linear Penalization: PIRR and PIRR for Beta
60.5 Penalized Present Value
60.6 Final Thoughts and Conclusions
References
61 The Trading Performance of Dynamic Hedging Models: Time Varying Covariance and Volatility Transmission Effects
61.1 Introduction
61.2 Institutional Background and Data Sampling
61.3 Volatility Estimators and Competing Hedge Ratios
61.3.1 Constructing Out-of-Sample Hedge Ratios
61.4 Empirical Results
61.4.1 Descriptive Statistics and Preliminary Results
61.4.2 Results from Model Estimates
61.5 Out-of-Sample Hedging Performances
61.5.1 Details of the Hedging Scheme
61.5.2 Incremental Profit Results
61.6 Conclusion
61.7 Deriving the Reduced-Form of ESVL(CI)
References
62 Portfolio Insurance Strategies
62.1 Basic Concepts of Portfolio Insurance
62.2 Theory of Alternative Portfolio Insurance Strategies
62.2.1 Option-Based Portfolio Insurance (OBPI)
62.2.2 Constant Proportion Portfolio Insurance (CPPI)
62.2.3 Risk-Based Portfolio Insurance (RBPI)
62.2.3.1 VaR-Based Portfolio Insurance
62.2.3.2 ES-Based Portfolio Insurance
62.3 Market Developments
62.3.1 History of Portfolio Insurance
62.3.2 Recent Modifications in CPPI Mechanisms
62.3.2.1 Modifications in Floor
62.3.2.2 Modifications in Multiplier
62.3.2.3 Modifications in the Exposure to Risky Assets
62.3.3 Examples of CPPI Structured Products
62.4 Implications for Financial Market Stability
62.4.1 Amplification of Market Price Movements
62.4.2 Gap Risk
62.5 Empirical Comparison of Alternative Portfolio Insurance Strategies
62.5.1 Zhu and Kavee (1988)
62.5.2 Perold and Sharpe (1988)
62.5.3 Rendleman and O´Brien (1990)
62.5.4 Loria, Pham, and Sim (1991)
62.5.5 Do and Faff (2004)
62.5.6 Cesari and Cremonini (2003)
62.5.7 Herold, Maurer, and Purschaker (2005)
62.5.8 Hamidi, Jurczenko, and Maillet (2009)
62.5.9 Ho, Cadle, and Theobald (2011)
62.6 Conclusion
References
63 Time-Series and Cross-Sectional Tests of Asset Pricing Models
63.1 Introduction
63.2 Time-Series Tests
63.2.1 The Factor Model
63.2.2 Individual t-Test
63.2.3 Joint F-Test
63.3 Tests Based on Generalized Methods of Moments (GMM)
63.3.1 Introduction of the GMM
63.3.2 Overview of the GMM Estimation
63.3.3 Moments Conditions for the Asset Pricing Tests
63.3.4 The Hansen-Jagannathan Distance
63.3.5 An Equality Test for the HJ-Distance
63.4 Cross-Sectional Tests
63.4.1 A Risk Premia Estimation Through Two-Pass Regressions
63.4.2 The GLS Estimation of Risk Premia
63.4.3 The Errors-in-Variables Problem
63.4.3.1 Corrections for the Standard Errors
63.4.3.2 Corrections for the Risk Premium Estimate
63.5 Summary and Concluding Remarks
References
64 Unified Model Arbitrage-Free Term Structure of Flow Risks
64.1 Introduction
64.2 The Black-Scholes Model and the Ho-Lee Model
64.3 Examples of Term Structure of Flow Risk Drivers
64.3.1 Interest Rate Model
64.3.2 Credit Valuation Model
64.3.3 Liquidity Valuation Model
64.3.4 Energy Valuation Model
64.3.5 Inflation Contingent Claims Valuation Model
64.4 Modeling the Stochastic Process of the Unified Model
64.5 Implications of the Unified Model to Risk Management
64.5.1 Relevance of the Unified Model to the Financial Crisis 2008
64.5.2 Benchmark Securities and Model Calibration
64.5.3 Combining Interest Rate Risk, Credit Risk, and Liquidity Risk in Enterprise Risk Management
64.5.4 Financial Engineering Considerations
64.6 Conclusions
64.6 Appendix A: A General Form of the Arrow-Debreu Primitive Securities
64.6 Appendix B: Three-Factor Unified Model
References
65 A Comparison of Formulas to Compute Implied Standard Deviation
65.1 Introduction
65.2 An Exact Closed-Form Solution for the Implied Standard Deviation: A Special Case
65.3 An Implied Standard Deviation Formula Under a Single Call Option
65.4 Formulas for Implied Standard Deviation Under Different Exercise Prices
65.5 Accuracy of the ISD Models: Simulation Results
65.6 Conclusion
65.7 Appendix
References
66 Securities Transaction Taxes: Literature and Key Issues
66.1 Introduction
66.2 Theoretical Literature
66.2.1 Volatility
66.2.2 Liquidity and Volume
66.3 Empirical Literature
66.3.1 Volatility
66.3.2 Volume
66.3.3 Liquidity
66.4 Key Issues
66.5 Conclusion
References
67 Financial Control and Transfer Pricing
67.1 Introduction
67.2 Designing Responsibility Centers
67.2.1 Cost Centers
67.2.2 Revenue Centers
67.2.3 Profit Centers
67.2.4 Investment Centers
67.2.4.1 Return on Investment (ROI)
67.2.4.2 Residual Income (RI)
67.3 Transfer Pricing
67.3.1 Transfer Pricing Methods
67.3.1.1 Market Based Transfer Prices
67.3.1.2 Cost Based Transfer Prices
67.3.1.3 Variable Cost Transfer Prices
67.3.1.4 Standard Variable Cost Transfer Prices
67.3.1.5 Actual Variable Cost Transfer Prices
67.3.1.6 Full Cost Transfer Prices
67.3.1.7 Negotiated Transfer Prices
67.4 Some Theoretical Models of Transfer Pricing
67.4.1 Economic Models
67.4.2 Linear Programming Models
67.4.3 Shapely Value
67.5 Optimal Transfer Price
67.5.1 Minimum Transfer Price
67.5.2 Maximum Transfer Price
67.5.3 Idle Capacity and Transfer Price
67.5.4 No Idle Capacity and Transfer Price
67.5.5 Some Idle Capacity and Transfer Price
67.6 International Transfer Pricing
67.7 Limitations of Financial Control Systems
67.8 Conclusion
References
68 Alternative Models for Evaluating Convertible Bond: Review and Integration
68.1 Introduction
68.2 Deterministic Approach: Graphical Model
68.3 Static Stochastic Stock and/or Straight Bond Prices
68.4 Structural Models: Dynamic Stochastic Firm´s Market Value
68.5 Dynamic Stochastic Stock Price: Spread and Reduced-Form Approaches
68.6 Numerical Methods
68.6.1 Solving Partial Differential Equations
68.6.1.1 The Tree Approach
68.7 Conclusion
References
69 A Rationale for Hiring Irrationally Overconfident Managers
69.1 Introduction
69.2 A Model of Compensation Contracts and the Resulting Managerial Effort
69.3 The Simulation Procedures
69.4 Results and Discussion
69.5 Conclusion
69.5 Appendix A: Calibration of the Parameters of the Base Case Calculation
References
70 Current Versus Permanent Earnings for Estimating Alternative Dividend Payment Behavioral Model: Theory, Methods and Applica...
70.1 Introduction
70.2 Theoretical Determination of Firm´s Permanent and Transitory Earnings and Dividends
70.3 Alternative Methods for Decomposing Current EPS into Permanent and Transitory EPS Components
70.3.1 Darby´s (1974) Method
70.3.2 Lee and Primeaux´s (1991) Method
70.3.3 Garrett and Priestley´s (2000) Kalman Filter Method
70.3.4 Lambrecht and Myer´s (2012) Method
70.4 Empirical Results in Estimating Two Alternative Dividend Behavior Models
70.4.1 Darby´s Method and Lee and Primeaux´s Method
70.4.1.1 Results from 608 Individual Regressions
70.4.1.2 Results from Pooled Regression
70.4.2 Lambrecht and Myer´s Method
70.4.3 Combined Model
70.4.3.1 Results from 605 Individual Regressions
70.4.3.2 Results from Pooled Regression
70.5 Summary and Concluding Remarks
70.6 Cross-References
70.6 Appendix A: Detailed Definition of Permanent Income
70.6 Appendix B: Impacts of Measurement Errors on Estimated Regression Coefficients
70.6 Appendix C: EPS, DPS, and Payout Ratio for 608 Firms
References
71 Valuation of Interest Tax Shields
71.1 Introduction
71.2 Notation, Definitions, and Formulas
71.3 Two Influential Models
71.3.1 Modigliani-Miller Formula
71.3.2 Example
71.3.3 Miles-Ezzell Formula
71.3.4 Example
71.3.5 Weighted Average Cost of Capital and Required Asset Return
71.4 Other Models with Fixed Debt or Leverage Ratio
71.4.1 Example
71.4.2 Example
71.5 Models with Dynamic Debt Policies
71.5.1 Example
71.6 Conclusion
References
72 Usefulness of Cash Flow Statements
72.1 Introduction
72.2 FASB Rules for Cash Flow Statements
72.2.1 Operating Activities
72.2.2 Investing Activities
72.2.3 Financing Activities
72.3 Statement of Cash Flows: Methods
72.3.1 Johnson and Johnson Company: An Example
72.3.1.1 Cash Flow from Operating Activities
72.3.1.2 Cash Flow from Investing Activities
72.3.1.3 Cash Flow from Financing Activities
72.4 Problems with Cash Flow Statements
72.4.1 Arbitrariness of Classifications
72.4.1.1 Operating Versus Investing Activities
72.4.1.2 Operating Versus Financing Activities
72.4.1.3 Investing Versus Financing Activities
72.4.2 Direct Versus Indirect Method Controversy
72.4.3 Manipulation and Distortion of Cash Flow Statements
72.4.3.1 Manipulation of Payables
72.4.3.2 Financing and Securitization of Payables
72.4.3.3 Deferred Employee Compensation
72.4.4 Stock Buybacks
72.4.4.1 Marketable Securities
72.4.4.2 Dividend from Affiliated Companies
72.4.4.3 Income Taxes
72.4.4.4 Sale and Purchase of Assets
72.4.4.5 Non-cash Transactions
72.4.4.6 Free Cash Flows
72.5 Conclusion
References
73 Do CEO Gender and Marital Status Affect Firm´s R&D and Value? An Empirical Analysis Using Nonlinear Models
73.1 Introduction
73.2 Literature Review
73.3 Hypotheses
73.4 Empirical Analysis
73.4.1 R&D Investments
73.4.2 Firm Value
73.5 Conclusion
References
74 Three Alternative Methods for Estimating Hedge Ratios
74.1 Introduction
74.2 Alternative Theories Used for Deriving the Static Optimal Hedge Ratios
74.2.1 Minimum-Variance Hedge Ratio
74.2.2 Optimum Mean-Variance Hedge Ratio
74.2.3 Sharpe Hedge Ratio
74.2.4 Minimum Value-at-Risk Hedge Ratio
74.3 Applications of OLS, GARCH, and CECM Models to Estimate Optimal Hedge Ratio
74.3.1 OLS Method
74.3.2 GARCH Method
74.3.3 Cointegration and Error Correction Method (CECM)
74.3.4 Empirical Studies
74.4 Conclusion
74.4 Appendix A. Monthly Data of S&P500 Index and Its Futures (January 2005 - August 2020)
74.4 Appendix B. Applications of R Language in Estimating Three Different Optimal Hedge Ratios
References
75 Credit Risk Modeling: A General Framework
75.1 Introduction
75.2 Basic Setup
75.3 The Unified Model
75.3.1 The Jarrow-Turnbull Model
75.3.2 The Duffie-Singleton Model
75.3.3 The Extended Merton Model
75.3.4 The Geske-Johnson Model
75.4 Calibration and Model Comparison
75.4.1 A Two-Period Example
75.4.2 Multi-period Analysis
75.5 Conclusion
75.5 Appendix: Derivation of (18)
75.5
75.5 Derivation of (24)
75.5 Implementation of (24)
75.5 Closed Form Solution for v(0,Ti): Rabinovitch
References
76 Bankruptcy Prediction Studies Across Countries Using Multiple Criteria Linear Programming (MCLP) and Other Data Mining Appr...
76.1 Introduction
76.2 Background
76.3 Models of Multiple Criteria Linear Programming Classification
76.4 Data Collection and Research Design
76.5 Summary and Conclusions
References
77 Application of Difference-in-Differences Strategies in Finance: The Case of Natural Disasters and Bank Responses
77.1 Introduction
77.2 Motivation
77.3 Data
77.3.1 Natural Disasters
77.3.2 Deposit Rates
77.3.3 Deposit Data
77.3.4 Bank Variables
77.4 Matching Methods and Imbalance Measure
77.5 Research Design
77.6 Models and Empirical Results
77.6.1 Base Scenario - DID Model Without a Matching Method
77.6.2 Imbalance Measure, Common Trend Assumption, and DID Estimator
77.6.3 Different Matching Methods (PSM and CEM), Common Trend Assumption, and DID Estimator
77.7 Conclusions
77.7 Appendices
Appendix 1
Appendix 2
References
78 Financial Panel Data Models, Strict Versus Contemporaneous Exogeneity, and Durbin-Wu-Hausman Specification Tests
78.1 Introduction
78.2 Exogeneity, Strict Exogeneity, and Endogeneity
78.3 Linear Panel Data Models and Pooled LS Estimation
78.4 Unobservable Heterogeneity
78.5 Fixed Effects (FE) Models
78.6 Random Effects (RE) Models
78.7 Balanced Versus Unbalanced Panel Data
78.8 Durbin-Wu-Hausman (DWH) Tests
78.9 Testing Strict Exogeneity
78.10 Empirical Application
78.10.1 Example 1: Comparison of Pooled LS, Pooled LS with Cluster Robust SE, FE, RE (GLS), and RE (ML) Estimators Using Exper...
78.10.2 Example 2: FE and RE, Contemporaneous and Strict Exogeneity, DWH and Wooldridge Tests
78.11 Conclusion
78.12 Cross-References
References
79 Accruals and the Asymmetric Timeliness of Earnings: A Decomposition Analysis
79.1 Introduction
79.2 Theoretical Background and Hypothesis Developments
79.2.1 Earnings Conservatism in the UK
79.2.2 Asymmetric Timeliness of Earnings in Earnings Constructs
79.2.2.1 Limitations of Asymmetric Timeliness
79.2.3 Hypothesis Developments
79.3 Research Design
79.3.1 Earnings Components
79.3.2 The Asymmetric Timeliness Model for Earnings Components
79.4 Sample Selection
79.5 Empirical Results
79.5.1 Summary Statistics
79.5.2 Tests for H1a: Asymmetric Timeliness in Operating Cash Flow and Accrual Components
79.5.3 Tests for H1b: Evaluating the Application of Three Prominent Standards that Incorporate Asymmetric Verification Criteria
79.5.4 Tests for H1c: The Role of Dirty Surplus Flows in Asymmetric Timeliness
79.6 Further Analysis of New Measures
79.7 Conclusion
79.7 Appendix 1 The UK Financial Statements
References
80 Computing Technology for Financial Service
80.1 Introduction
80.1.1 Information Technology for Financial Services
80.1.2 Competitiveness Through IT Performance
80.2 Performance Enhancement
80.2.1 Compute-Intensive IT Systems
80.2.1.1 PicsouGrid
80.2.1.2 FinGrid
80.2.2 Data-Intensive IT Systems
80.2.3 Cloud-Enabled Big Data and Machine Learning IT Systems
80.2.3.1 Big Data and MapReduce Systems
80.2.3.2 Cloud-Enabled Hybrid Systems for Big Data and Machine Learning
80.3 Distributed and Parallel Financial Simulation
80.3.1 Financial Simulation
80.3.1.1 Option Pricing
80.3.1.2 Market Risk Measurement Based on VaR
80.3.2 Monte Carlo Simulation
80.3.2.1 Monte Carlo and Quasi-Monte Carlo Methods
80.3.2.2 Monte-Carlo Simulations for Option Pricing
80.3.2.3 Monte-Carlo Bootstrap for VaR
80.4 Case Study and Discussions
80.4.1 Case Study
80.4.1.1 Asian Options and Rainbow Options
80.4.1.2 Parallelization, Distribution, and Message Passing Interface (MPI)
80.4.1.3 Empirical Study for Data Grid System
80.4.2 System Platform Tests
80.4.2.1 Artificial Intelligence-Based High-Performance Computing Platform
80.4.2.2 Diskless Remote Boot Linux (DRBL) Cluster
80.4.2.3 Pacific Rim Applications and Grid Middleware Assembly (PRAGMA) Grid
80.4.2.4 At-Home Style PC Grid
80.4.2.5 RBNB Data Grid
80.5 Conclusion
References
81 Local Volatility Interest Rate Model
81.1 Introduction: Modeling Interest Rate Movements in a Low-Rate Regime
81.2 Part 1: Model Assumptions for Financial Simulations and Balance Sheet Strategies
81.2.1 COIVD 19: Challenges and Strategic Planning
81.2.2 Model Assumptions
81.2.3 Balance Sheet Strategies
81.2.4 The Validity of Interest Rate Models
81.3 Part 2: Interest Rate Model and Efficacy of Financial Simulations
81.3.1 Local Volatility Model
81.3.2 Rate Distribution Trend Analysis
81.3.2.1 Market Conditions
81.3.2.2 Volatility Curve
81.3.2.3 Negative Rates
81.3.3 Model Robustness: Historical Rate Distributions for Sample Dates Between March 2019 and March 2020
81.3.3.1 Empirical Evidence
81.4 Implications of Skewness: Mean and Median of Rate Distribution
81.4.1 Forward Rates and Expected Rates
81.4.2 The Skewness in Loan Pricing
81.4.3 Stress Test the Balance Sheet and Limitations of Current Interest Rate Models
81.4.4 Balance Sheet Enhance Return Strategies
81.5 Conclusions
81.5 Appendix A: Interest Rate Model: A Review
Ho-Lee Model
Normal Model Versus Lognormal Model
81.5 Appendix B: Local Volatility Model Description
References
82 Applications of Logistic Regression and Hazard Method in Accounting and Finance Research
82.1 Introduction
82.1.1 Hazard Models
82.1.1.1 Hazard Models: Some Basic Concepts
82.1.1.2 Parametric Hazard Models
82.1.1.3 Semiparametric Hazard Models
82.1.1.4 Logistic Regression
82.2 Literature Review
82.3 Empirical Application
82.4 Conclusion
References
83 Cube Root Utility Theory
83.1 Introduction
83.1.1 Initial Analysis
83.1.2 Review of the Literature
83.2 Qualified and Unqualified Utility Functions
83.3 Selecting the Most Desirable Radical Utility Function
83.4 Analysis of the Cube Root Utility Function
83.5 Analysis of the Utility Function with Favorable Outcomes, x>0
83.5.1 Marginal Utility Is Positive When x > 0
83.5.2 Analyzing Absolute Risk-Aversion (ARA) for Favorable Outcomes, x>0
83.5.3 Analyzing Relative Risk-Aversion (RRA) When x > 0
83.6 Analysis of the Utility Function with Unfavorable Outcomes, x<0
83.6.1 Analyzing Marginal Utility When x < 0
83.6.2 Analyzing Absolute Risk-Aversion (ARA) for x < 0
83.6.3 Analyzing Relative Risk-Aversion (RRA) When x < 0
83.7 A Taylor Series Expansion of α1x1/3
83.8 Summary and Conclusions
83.8.1 Summary Points About Cube Root Utility Theory
83.8.2 The Economics
83.8.3 Comparing Utility Functions
83.8 Appendix A - Further analysis of radical functions
References
84 A Global Comparative Study of Impact Investments Research in Academic Institutions
84.1 Introduction
84.2 The Terminology of Impact Investments and Related Activities
84.3 Data and Methodology
84.4 Results and Discussion
84.4.1 Evolution of the Field Over Time
84.4.2 Distribution of the Research Institutions (Public University, Private University, or Nonacademic Institution)
84.4.3 Relative Weight of the Academic Disciplines Involved in Impact Investment Research
84.4.3.1 Types of Analysis Used in Social Impact Investment Research
84.4.4 Funding
84.4.5 Academic Influence of Social Impact Investment Research
84.5 Conclusions
84.5 Appendix 1: List of Sponsors
84.5 Appendix 2: Impact Investment Literature Catalogued by Discipline
References
85 Financial Crisis, Capital Requirement, and Stress Tests: Evidence from the Extreme Value and Stable Paretian Estimates
85.1 Introduction
85.2 Literature Review
85.3 Methodology
85.4 VaR Models
85.5 Empirical Results
85.5.1 Investment Companies
85.5.2 US Banks
85.6 Conclusion
References
86 The Economics of and Accounting for Lease Transactions
86.1 Introduction
86.1.1 Nature and Use
86.1.1.1 General Nature of a Lease Arrangement
86.1.1.2 Use of Leases
86.2 Motivations for Leasing: Theory and Assumptions
86.2.1 Financing: Lease Vs. Purchase
86.2.2 Nonreporting Incentives: Transaction Costs, Flexibility, Borrowing Capacity, and Taxes
86.2.3 Financial Reporting Incentives
86.3 Accounting for Lease Transactions Under US GAAP and IFRS
86.3.1 Classification of Leases
86.3.2 Discussion of Important Assumptions, Estimates, and Inputs
86.3.2.1 Lease Term
86.3.2.2 Lease Payments and Residual Values
86.3.2.3 Discount Rate
86.3.2.4 Fair Value of the Underlying Leased Asset
86.3.3 Accounting and Reporting Requirements
86.3.3.1 Lessee
86.3.3.2 Lessor
86.3.4 Further Discussion of Lease Arrangements
86.3.5 Important Differences between US GAAP and IFRS
86.3.6 Impact of New Leasing Accounting Guidance
86.4 Conclusion
References
87 Pension Accounting, Inside Debt, and Capital Structure
87.1 Introduction
87.2 Pension Plan Freeze and Termination
87.3 Effects of ERISA and PBGC on Pension Management
87.4 Accounting for Pension Plans Under FAS 158 and IAS 19
87.5 Pension Assumptions and Earning Management
87.6 Pension Accounting Information and Value Relevance
87.7 Pension Plans and Capital Structure Decisions
87.7.1 Aggregate Pension Demand and Differential Taxation
87.7.2 Firm Valuation
87.7.3 Equilibrium with No Tax Shield Risk
87.7.4 Tax Shield Risk and Optimal Corporate Pension Policy
87.8 Conclusion
References
88 The Role of Earnings Management in Equity Valuation
88.1 Varied Managerial Incentives for Earnings Management
88.2 Various Tactics of Earnings Management via Accruals Manipulation
88.3 Various Tactics of Earnings Management via Real Activities Manipulation
88.4 Consequences and Determinants of Earnings Management
88.5 Trade-Off Between Accruals Manipulation and Real Activities Manipulation to Manage Earnings
88.6 How to Discern and Measure Earnings Management?
88.7 Introduction of Various Equity-Valuation Models
88.8 How to Adjust for the Effects of Accruals-Based and Real Earnings Management in Equity Valuation?
References
89 The Applications of Machine Learning in Accounting and Auditing Research
89.1 Machine Learning Technology
89.2 Differences Between Machine Learning and Statistical Modeling
89.3 Machine Learning Algorithms
89.4 Applications of Machine Learning in Accounting Research
89.4.1 The Evaluation of Information Content
89.4.2 The Estimation of Bankruptcy or Default Risks
89.4.3 The Enhancement of Accounting Estimates and Fundamental Analytics
89.5 Applications of Machine Learning in Auditing Research
89.5.1 Auditing Processes
89.5.2 Financial Misstatements/Misreporting/Frauds
89.5.3 Audit Quality
89.6 Machine Learning Tools
89.6.1 Scikit-Learn Module in Python
89.6.2 PyOD Module in Python
89.6.3 TensorFlow Platform
89.7 Conclusions: Perspectives for Future Research
References
90 Internal Capital Budgeting and Allocation in Financial Firms
90.1 Backgrounds of Internal Capital Budgeting
90.2 Issues Related to Internal Capital Budgeting
90.2.1 The Agency Problem
90.2.1.1 Managerial Issues
90.2.1.2 Information Asymmetry
90.2.2 Optimal Timing for Capital Budgeting
90.2.3 Relative Dependence on the External Capital Market
90.2.4 Type of Firm
90.2.5 Firm Boundary
90.2.6 Type of Market
90.2.7 Financial Shock
90.2.8 Capital Budgeting Methodologies
90.3 Internal Capital Budgeting of Financial Firms
90.3.1 Performance Measures for Financial Firms
90.3.2 The Regulatory Capital Requirement: Basel
90.3.2.1 Basel I
90.3.2.2 Basel II
90.3.2.3 Basel III
90.3.3 Economic Capital
90.4 Comparison Between Financial and Nonfinancial Firms
90.5 Conclusion
References
91 Job Security and CEO Compensation
91.1 Introduction
91.2 Literature Background and Hypothesis Development
91.3 Methodology and Data
91.3.1 Job Security Measures
91.3.2 Compensation Measures
91.3.3 Risk Preference Measures
91.3.4 CEO Labor Market Condition Measures
91.4 Empirical Analysis
91.4.1 Verification of Job Security Measures
91.4.2 Job Security and CEO Compensation
91.4.3 Job Security and CEO Compensation in Firms with Financial Constraints
91.4.4 Job Security under Different Risk Preferences
91.4.5 Job Security under Different Labor Market Conditions
91.4.6 Robustness Test
91.5 Conclusion
91.5 Appendix A: Variable Description
91.5 Appendix B: Robustness Tests for the General Case
91.5 Appendix C: Robustness Tests for Financially Distressed Firms
References
92 Tail-Risk Protection: Machine Learning Meets Modern Econometrics
92.1 Introduction
92.2 Background and Literature Review
92.2.1 Volatility as a Risk Measure?
92.2.2 Investors´ Preferences
92.2.3 Dynamic Tail Risk Protection Strategy
92.3 Trading Strategy
92.3.1 Tail Risk as a Risk Measure
92.3.2 Tail Risk Protection Strategy
92.4 Machine Learning Trader
92.4.1 Data
92.4.2 Neural Networks
92.4.2.1 Trader´s Function Mapping
92.4.3 Model Selection
92.4.3.1 Hidden Layers Architecture
92.4.3.2 Strategy Parameters and Final Decision
92.5 Auto-Regressive Models
92.5.1 ARMA-GARCH Type Models
92.5.1.1 ARMA-GARCH
92.5.1.2 ARMA-EVTGARCH
92.5.1.3 Model Selection, Calibration, and Exceedance Probability
92.5.2 CARL-vol Model
92.5.3 Local Parametric Approach (LPA)
92.6 Applications
92.6.1 Meta Strategy: Stacking
92.6.2 Benchmarks
92.6.3 Out-of-Sample Performance
92.6.3.1 Model Risk Evaluation
92.6.3.2 Backtest Performance
92.7 Conclusion
References
93 Structural Breaks in Financial Panel Data
93.1 Introduction
93.2 Structural Breaks in Panel Data: The Model
93.3 Structural Breaks in Panel Data: The Errors
93.4 Testing for Structural Change
93.5 Estimating the Date of the Break
93.6 Structural Breaks in Trade Credit Provision
93.7 Conclusions
93.8 Cross-References
References
94 More on Equilibrium Credit Rationing and Interest Rates: A Theory with New Evidence
94.1 Introduction
94.2 A Theoretical Framework
94.2.1 Model
94.2.2 Rationing by the Number of Loans
94.2.3 Rationing by the Size of Loans
94.3 Some Empirical Literature on Credit Rationing
94.4 Vector-Error Correction Model (1997-2010)
94.5 Conclusion
94.6 Cross-References
References
95 The Effect of Basel III on Banks´ Lending
95.1 Introduction
95.2 From Basel I to Basel II
95.2.1 Basel I
95.2.2 Basel II
95.2.3 Basel III
95.3 Capital Regulation and Banks´ Lending
95.4 Liquidity Regulation and Banks´ Lending
95.5 The Interaction Between Capital and Liquidity Regulations
95.6 Conclusion
References
96 Mortgage Analysis
96.1 Introduction
96.2 Mortgage Characteristics
96.3 Calculating Mortgage Cash Flows
96.4 Mortgage Sensitivity to Changes in Mortgage Rates
96.5 Prepayment
96.6 Conclusions
References
97 A History of Commercially Available Risk Models
97.1 Introduction
97.2 Risk and Returns of Portfolios
97.3 An Introduction to Modern Portfolio Theory: The Capital Asset Pricing Model (CAPM)
97.4 The Barra Risk Model
97.5 The APT Risk Model
97.6 The Axioma Statistical and Fundamental Risk Models
97.7 The MCM Horse Races: Who Has the Better Risk Models for Growth Variables?
97.8 Summary and Conclusions
97.8 Appendix 1: US-E3 Descriptor Definitions
97.8 Appendix 2 Barra US-E4, GEM4 Earnings Yields and Momentum Strategies
References
98 Short Selling Activity and Effects on Financial Markets and Corporate Decisions
98.1 Introduction
98.2 The Short-Selling Process, Institutional Structure, and Activities
98.2.1 Why Going Short?
98.2.2 The Security Lending Process
98.2.3 Short-Selling Activities in the Market
98.2.4 Short Sale Constraints
98.2.5 Short-Selling Costs and Rebate Rates
98.3 Theory of Short Sales
98.4 Literature Review
98.4.1 Short Sale Supply
98.4.2 Cross-Sectional Return Predictability
98.4.3 Time Series Return Predictability (Aggregate Short Interest)
98.4.4 Short Interest and Corporate Events/Firm Performance
98.4.5 Consequences of Short Selling
98.4.6 The Role of Short Interest in Other Asset Markets
98.4.7 Short Sale Ban in the History
98.5 Data and Empirical Evidence
98.5.1 Reg SHO Data - NYSE Short Sales (TAQ)
98.5.2 Supplemental Short Interest File (Compustat)
98.5.3 Markit Data Explorers (DXL) Equity Lending Data
98.5.4 WRDS European Short Data
98.5.5 Short Selling Metrics
98.5.6 Empirical Evidence
98.6 Future Research
98.6.1 CSR and Short Interest
98.6.2 The Information Role of Short Interest in Other Asset Markets
98.6.3 Heterogeneity in Short Sellers
98.6.4 Endogeneity Problem
98.6.5 International Evidence
98.7 Conclusion
References
99 Simultaneous Equation Models for Financial Planning and Forecasting
99.1 Introduction
99.2 Procedures for Financial Planning and Analysis
99.3 Percentage of Sales Method for Financial Planning and Forecasting
99.4 The Algebraic Simultaneous Equations Approach to Financial Planning and Analysis
99.5 Sensitivity Analysis
99.6 Francis and Rowell Model
99.6.1 The FR Model Specification
99.7 Summary
99.7 Appendix A - Description of Parameter Inputs Used to Forecast Johnson & Johnson´s Financial Statements and Share Price
99.7 Appendix B - Procedure of Using Excel to Implement the FinPlan Program
References
100 Alternative Errors-in-Variables Models and Their Applications in Finance Research
100.1 Introduction
100.2 Effects of Errors-in-Variables in Different Cases
100.2.1 Bivariate Normal Case
100.2.2 Multivariate Case
100.3 Estimation Methods when Variables Are Subject to Error
100.3.1 Classical Estimation Method
100.3.1.1 The Classical Method to a Simple Regression Analysis
100.3.1.2 The Classical Method to a Multiple Regression Analysis
100.3.1.3 The Constrained Classical Method
100.3.2 Grouping Method
100.3.3 Instrumental Variable Method
100.3.4 Mathematical Method
100.3.4.1 Bivariate Case
100.3.4.2 Multivariate Case
100.3.5 Maximum Likelihood Method
100.3.6 LISREL and MIMIC Methods
100.3.6.1 Structural Model (LISEREL Model)
100.3.6.2 MIMIC Model
100.3.7 Bayesian Approach
100.4 Applications of Errors-in-Variables Models in Finance Research
100.4.1 Cost of Capital
100.4.2 Capital Asset Pricing Model
100.4.3 Capital Structure
100.4.4 Measurement Error in Investment Equation
100.5 Conclusion
References
101 Optimal Payout Ratio under Uncertainty and the Flexibility Hypothesis: Theory and Empirical Evidence
101.1 Introduction
101.2 Review of the Literature
101.3 The Model
101.4 Optimum Dividend Policy
101.5 Relationship Between the Optimal Payout Ratio and the Growth Rate
101.6 Relationship Between Optimal Payout Ratio and Risks
101.6.1 Case 1: Total Risk
101.6.2 Case 2: Systematic Risk
101.6.3 Case 3: Total Risk and Systematic Risk
101.6.4 Case 4: No Change in Risk
101.7 Empirical Evidence
101.7.1 Sample Description
101.8 Univariate Analysis
101.8.1 Multivariate Analysis
101.8.2 Moving Estimates Process for Structural Change Model
101.9 Interaction Among Investment, Financing, and Dividend Policies
101.10 Summary and Concluding Remarks
101.10 Appendix A. Derivation of Eq. (19)
101.10 Appendix B. Derivation of Eq. (21)
101.10 Appendix C. Derivation of Eqs. (28) and (29)
101.10 Appendix D. Using Moving Estimates Process to Find the Structural Change Point in Eq. (36)
References
102 Mergers and Acquisitions: Principles and Practices
102.1 Introduction
102.2 Process and Theories, Data and Trends
102.2.1 M&A Theories/Models
102.2.1.1 Takeover Tactics
102.2.2 M&A Transactional Forms
102.3 M&A Financing
102.4 Restructuring and Divestitures
102.5 Leveraged Buyouts (LBOs)
102.6 Joint Ventures and Strategic Alliances
102.7 Anti-takeover Defenses
102.7.1 Anti-takeover Defense Measures
102.7.2 Shareholder´s Rights Plan or the Poison Pill
102.7.3 Charter and Bylaws Provisions
102.7.4 Reaction (Economic Defense)
102.7.5 Pac-Man
102.7.6 Golden Parachutes
102.7.7 White Knight and White Squire
102.7.8 Limitations on the Adoption of Anti-takeover Defense Measures
102.8 Deal Protection and Deal Certainty
102.9 The Board´s Role in M&A
102.9.1 Seminal Court Cases on Corporate Governance
102.10 The Legal and Regulatory Framework of M&As
102.10.1 State Anti-takeover Laws
102.10.2 Tender Offer
102.11 Cross-Border Mergers and Acquisitions
102.12 Valuation for Mergers and Acquisitions
102.12.1 The Income Approach
102.12.1.1 Free Cash Flows
102.12.1.2 Terminal Value
102.12.1.3 The Discount Rate
102.12.2 The Adjusted Present Value (``APV´´)
102.12.2.1 Flow to Equity (``FTE´´)
The Market Approach
102.12.3 Asset-Based Valuation
102.12.3.1 Liquidating Value
Accounting for Mergers and Acquisitions
102.13 Post-merger Integration
102.14 M&A Risk and Success
102.15 Closing Comments
References
103 Accrual Accounting and Risk: Abnormal Sales Growth, Accruals Quality, and Returns
103.1 Introduction
103.2 Background and Hypotheses Development
103.2.1 Abnormal Sales Growth and Accruals Quality
103.2.2 Abnormal Sales Growth and Abnormal Returns
103.3 Methods Used to Test Hypotheses
103.3.1 Model Used to Test H1
103.3.2 Model Used to Test H2
103.4 Sample and Descriptive Statistics
103.4.1 Sample Selection and Data
103.4.2 Sample Summary Statistics
103.5 Empirical Results
103.5.1 Results of Testing H1
103.5.1.1 Correlation Results
High-Growth Subsample
Low-Growth Subsample
103.5.1.2 Regression Results
Ordinary Least Square Regressions
Fama-MacBeth (1973) Regressions
103.5.2 Results on Ranked AG Portfolio Returns (H2)
103.6 Additional Tests
103.6.1 Robust Tests
103.6.1.1 Firm-Specific, Industry, and Year Effects
103.6.1.2 Unexpected Sales Growth (AG) and Volatility of Sales.
103.6.1.3 Alternative Econometric Methods
103.6.1.4 Firm-Level Abnormal Return
103.6.2 Additional Tests
103.6.3 Discussion
103.7 Summary and Conclusion
103.7 Appendix
Accruals Quality
Other Variables Used in Analyses
References
104 Applications of Book-Tax Difference in Accounting and Finance Research
104.1 Introduction
104.2 The Concept and Empirical Measures of Book-Tax Differences
104.3 Review of Iterature Related to Book-Tax Differences
104.4 The Concept and Empirical Measures of Book-Tax Conformity
104.5 Review of Literature Related to Book-Tax Conformity
104.6 Conclusion
References
105 Evaluating Portfolio Risk Management: A New Evidence from DCC Models and Wavelet Approach
105.1 Introduction
105.2 Methodology and Empirical Specifications
105.2.1 Data
105.2.2 Descriptive Statistics
105.2.3 Model Specifications
105.3 Empirical Results
105.3.1 Conditional Variance and Volatility Analysis
105.3.1.1 Symmetric and Asymmetric Univariate GARCH Analysis
105.3.1.2 Symmetric and Asymmetric Dynamic Conditional Correlation Analysis
105.3.2 Forecast Performance Evaluation
105.3.3 Application to Value-at-Risk
105.3.3.1 Backtesting VaR Measures
Unconditional Coverage
Conditional Coverage
Dynamic Quantile
105.4 Wavelet-Based Approach
105.5 Conclusion
References
106 Cash Conversion Cycle and Corporate Performance: Global Evidence
106.1 Introduction
106.2 Data and Methodology
106.2.1 Data
106.2.2 Methodology
106.3 Empirical Results
106.3.1 Preliminary Findings
106.3.1.1 Sample Description
106.3.1.2 Regression Results for Each Country
106.3.1.3 Regression Results for Each Industry
106.3.1.4 Differences in Corporate Performance Between High- and Low-CCC Firms
106.3.2 Regression Results
106.4 Endogeneity
106.4.1 Three-Stage Least Squares
106.4.2 Generalized Method of Moments
106.5 Robustness Checks
106.5.1 Macroeconomic Environment
106.5.2 Economic Development Status
106.5.3 Financial Crises
106.5.4 Corporate Governance
106.5.5 Financial Constraints
106.6 Conclusion
References
107 How Consistent Are the Judges of Portfolio Performance?
107.1 Introduction
107.2 Construction
107.3 The Friedman Test
107.3.1 Results
107.4 Conclusion
References
108 Risk Aversion and the Value of Information for Investors
108.1 Introduction
108.1.1 Outline of the Chapter
108.1.2 Some Clarifying Remarks
108.2 A General Framework
108.3 An Exposition of the Cabrales et al. Contribution
108.3.1 The Setting
108.3.2 Risk Aversion and Information Value in This Setting
108.3.3 Entropy and the Value of Information
108.3.4 CRRA Utility and Information Value
108.4 The CARA Case
108.4.1 The Simple Portfolio Problem
108.5 The CRRA Case and the Simple Portfolio Problem
108.5.1 Some Examples
108.5.1.1 The First Example
108.5.1.2 The Second Example
108.5.1.3 A Third Example
108.6 Concluding Remarks
References
109 A Fuzzy Real Option Valuation Approach To Capital Budgeting Under Uncertainty Environment
109.1 Introduction
109.2 Methods for Capital Budgeting and Investment Decision-Making
109.3 A Fuzzy Real Option Valuation
109.3.1 Real Option Valuation
109.3.2 Probability of Fuzzy Events
109.3.3 Prior Probability of Fuzzy Events
109.3.4 Posterior Probability of Fuzzy Events
109.3.5 A Fuzzy Real Option Valuation
109.4 N-Step Fuzzy Decision Tree
109.4.1 Fuzzy State
109.4.2 Fuzzy Sample Information
109.5 Conclusions
109.5 Appendix Supplementary Explanation for Fuzzy Set
The Definition of Fuzzy Set
Membership Function
Fuzzy Logic
The Operations of Fuzzy Set
Defuzzify
Fuzzy Decision
References
Appendix A: Derivation of Dividend Discount Model
.0 A.1 Summation of Infinite Geometric Series
.0 A.2 Dividend Discount Model
Appendix B: Derivation of DOL, DFL and DCL
B.1 DOL
B.2 DFL
B.3 DCL (Degree of Combined Leverage)
Appendix C: Derivation of Crossover Rate
Appendix D: Capital Budgeting Decisions with Different Lives
D.1 Mutually Exclusive Investment Projects with Different Lives
D.2 Equivalent Annual Cost
Appendix E: Derivation of Minimum-Variance Portfolio
Appendix F: Derivation of an Optimal Weight Portfolio Using the Sharpe Performance Measure
Appendix G: Applications of the Binomial Distribution to Evaluate Call Options
G1. What is an Option?
G2. The Simple Binomial Option Pricing Model
G3. The Generalized Binomial Option Pricing Model
Appendix H: Derivation of Modigliani and Miller (M&M) Proposition I and II with Taxes
H1. M&M Proposition I with Taxes
H2. M&M Proposition II with Taxes
Appendix I: Derivation of Capital Market Line (CML)
Appendix J: Derivation of Capital Market Line (SML)
Appendix K: Derivation of Black-Scholes Option Pricing Model
Appendix L: Hillier´s Statistical Distribution Method
References
Appendix M: Capital-Rationing Decision
Basic Concepts of Linear Programming
Capital Rationing
References
Appendix N: Noncentral χ2 and the Option Pricing Model
Reference
Appendix O: Impacts of Financing Decisions on Capital Budgeting Decisions
Equity-Residual Method
After-Tax, Weighted-Average, Cost-of-Capital Method
Arditti and Levy Method
Myers Adjusted-Present-Value Method
References
Index