Mathematical Techniques in Finance

Mathematical Techniques in Finance
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Explore the foundations of modern finance with this intuitive mathematical guide In Mathematical Techniques in Finance: An Introduction , distinguished finance professional Amir Sadr delivers an essential and practical guide to the mathematical foundations of various areas of finance, including corporate finance, investments, risk management, and more. Readers will discover a wealth of accessible information that reveals the underpinnings of business and finance. You’ll learn about: Investment theory, including utility theory, mean-variance theory and asset allocation, and the Capital Asset Pricing Model Derivatives, including forwards, options, the random walk, and Brownian Motion Interest rate curves, including yield curves, interest rate swap curves, and interest rate derivativesComplete with math reviews, useful Excel functions, and a glossary of financial terms, Mathematical Techniques in Finance: An Introduction is required reading for students and professionals in finance.

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Amir Sadr. Mathematical Techniques in Finance

Table of Contents

List of Tables

List of Illustrations

Guide

Pages

Mathematical Techniques in Finance

Preface

BACKGROUND

BOOK STRUCTURE

Bonds

Stocks, Investments

Forwards, Futures

Risk‐Neutral Option Pricing

Option Pricing

Interest Rate Derivatives

Exercises and Python Projects

Acknowledgments

About the Author

Acronyms

CHAPTER 1 Finance

1.1 FOLLOW THE MONEY

1.2 FINANCIAL MARKETS AND PARTICIPANTS

1.3 QUANTITATIVE FINANCE

CHAPTER 2 Rates, Yields, Bond Math

2.1 INTEREST RATES

2.1.1 Fractional Periods

2.1.2 Continuous Compounding

2.1.3 Discount Factor, PV, FV

2.1.4 Yield, Internal Rate of Return

2.2 ARBITRAGE, LAW OF ONE PRICE

2.3 PRICE‐YIELD FORMULA

EXAMPLE 1

2.3.1 Clean Price

2.3.2 Zero‐Coupon Bond

2.3.3 Annuity

2.3.4 Fractional Years, Day Counts

2.3.5 U.S. Treasury Securities

2.4 SOLVING FOR YIELD: ROOT SEARCH

2.4.1 Newton‐Raphson Method

2.4.2 Bisection Method

2.5 PRICE RISK

2.5.1 PV01, PVBP

2.5.2 Convexity

2.5.3 Taylor Series Expansion

EXAMPLE 2

2.5.4 Expansion Around

2.5.5 Numerical Derivatives

2.6 LEVEL PAY LOAN

EXAMPLE 3

2.6.1 Interest and Principal Payments

2.6.2 Average Life

2.6.3 Pool of Loans

2.6.4 Prepayments

2.6.5 Negative Convexity

2.7 YIELD CURVE

2.7.1 Bootstrap Method

2.7.2 Interpolation Method

EXAMPLE 4

2.7.3 Rich/Cheap Analysis

2.7.4 Yield Curve Trades

EXERCISES

PYTHON PROJECTS

CHAPTER 3 Investment Theory

3.1 UTILITY THEORY

3.1.1 Risk Appetite

3.1.2 Risk versus Uncertainty, Ranking

3.1.3 Utility Theory Axioms

3.1.4 Certainty‐Equivalent

3.1.5 X‐ARRA

3.2 PORTFOLIO SELECTION

3.2.1 Asset Allocation

3.2.2 Markowitz Mean‐Variance Portfolio Theory

3.2.3 Risky Assets

3.2.4 Portfolio Risk

3.2.5 Minimum Variance Portfolio

EXAMPLE 1

3.2.6 Leverage, Short Sales

3.2.7 Multiple Risky Assets

3.2.8 Efficient Frontier

3.2.9 Minimum Variance Frontier

EXAMPLE 2

3.2.10 Separation: Two‐Fund Theorem

3.2.11 Risk‐Free Asset

3.2.12 Capital Market Line

3.2.13 Market Portfolio

Example 3

3.3 CAPITAL ASSET PRICING MODEL

3.3.1 CAPM Pricing

3.3.2 Systematic and Diversifiable Risk

3.4 FACTORS

3.4.1 Arbitrage Pricing Theory

3.4.2 Fama‐French Factors

3.4.3 Factor Investing

3.4.4 PCA

3.5 MEAN‐VARIANCE EFFICIENCY AND UTILITY

3.5.1 Parabolic Utility

3.5.2 Jointly Normal Returns

3.6 INVESTMENTS IN PRACTICE

3.6.1 Rebalancing

3.6.2 Performance Measures

3.6.3 Z‐Scores, Mean‐Reversion, Rich‐Cheap

3.6.4 Pairs Trading

EXAMPLE 4

3.6.5 Risk Management

REFERENCES

EXERCISES

PYTHON PROJECTS

CHAPTER 4 Forwards and Futures

4.1 FORWARDS

4.1.1 Forward Price

4.1.2 Cash and Carry

4.1.3 Interim Cash Flows

4.1.4 Valuation of Forwards

4.1.5 Forward Curve

EXAMPLE 1

4.2 FUTURES CONTRACTS

4.2.1 Futures versus Forwards

4.2.2 Zero‐Cost, Leverage

4.2.3 Mark‐to‐Market Loss

4.3 STOCK DIVIDENDS

4.4 FORWARD FOREIGN CURRENCY EXCHANGE RATE

EXAMPLE 2

4.5 FORWARD INTEREST RATES

EXAMPLE 3

REFERENCES

EXERCISES

CHAPTER 5 Risk‐Neutral Valuation

5.1 CONTINGENT CLAIMS

5.2 BINOMIAL MODEL

EXAMPLE 1

5.2.1 Probability‐Free Pricing

5.2.2 No Arbitrage

5.2.3 Risk‐Neutrality

5.3 FROM ONE TIME‐STEP TO TWO

EXAMPLE 2

5.3.1 Self‐Financing, Dynamic Hedging

EXAMPLE 2 (Continued)

5.3.2 Iterated Expectation

5.4 RELATIVE PRICES

5.4.1 Risk‐Neutral Valuation

5.4.2 Fundamental Theorems of Asset Pricing

REFERENCES

EXERCISES

CHAPTER 6 Option Pricing

6.1 RANDOM WALK AND BROWNIAN MOTION

6.1.1 Random Walk

6.1.2 Brownian Motion

6.1.3 Lognormal Distribution, Geometric Brownian Motion

6.2 BLACK‐SCHOLES‐MERTON CALL FORMULA

EXAMPLE 1

6.2.1 Put‐Call Parity

6.2.2 Black's Formula: Options on Forwards

6.2.3 Call Is All You Need

6.3 IMPLIED VOLATILITY

EXAMPLE 2

6.3.1 Skews, Smiles

6.4 GREEKS

6.4.1 Greeks Formulas

6.4.2 Gamma versus Theta

6.4.3 Delta, Gamma versus Time

6.5 DIFFUSIONS, ITO

6.5.1 Black‐Scholes‐Merton PDE

6.5.2 Call Formula and Heat Equation

6.6 CRR BINOMIAL MODEL

6.6.1 CRR Greeks

6.7 AMERICAN‐STYLE OPTIONS

6.7.1 American Call Options

6.7.2 Backward Induction

6.8 PATH‐DEPENDENT OPTIONS

6.9 EUROPEAN OPTIONS IN PRACTICE

REFERENCES

EXERCISES

PYTHON PROJECTS

CHAPTER 7 Interest Rate Derivatives

7.1 TERM STRUCTURE OF INTEREST RATES

7.1.1 Zero Curve

7.1.2 Forward Rate Curve

7.2 INTEREST RATE SWAPS

7.2.1 Swap Valuation

EXAMPLE 1

7.2.2 Swap = Bone − 100%

7.2.3 Discounting the Forwards

7.2.4 Swap Rate as Average Forward Rate

7.3 INTEREST RATE DERIVATIVES

7.3.1 Black's Normal Model

7.3.2 Caps and Floors

EXAMPLE 2

7.3.3 European Swaptions

EXAMPLE 3

7.3.4 Constant Maturity Swaps

7.4 INTEREST RATE MODELS

7.4.1 Money Market Account, Short Rate

7.4.2 Short Rate Models

7.4.3 Mean Reversion, Vasicek and Hull‐White Models

7.4.4 Short Rate Lattice Model

7.4.5 Pure Securities

7.5 BERMUDAN SWAPTIONS

EXAMPLE 4

7.6 TERM STRUCTURE MODELS

7.7 INTEREST RATE DERIVATIVES IN PRACTICE

7.7.1 Interest Rate Risk

7.7.2 Value at Risk (VaR)

REFERENCES

EXERCISES

APPENDIX A Math and Probability Review. A.1 CALCULUS AND DIFFERENTIATION RULES

A.1.1 Taylor Series

A.2 PROBABILITY REVIEW

A.2.1 Density and Distribution Functions

A.2.2 Expected Values, Moments

A.2.3 Conditional Probability and Expectation

A.2.4 Jensen's Inequality

A.2.5 Normal Distribution

A.2.6 Central Limit Theorem

A.3 LINEAR REGRESSION ANALYSIS

A.3.1 Regression Distributions

APPENDIX B Useful Excel Functions

About the Companion Website

Index

WILEY END USER LICENSE AGREEMENT

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Founded in 1807, John Wiley & Sons is the oldest independent publishing company in the United States. With offices in North America, Europe, Australia and Asia, Wiley is globally committed to developing and marketing print and electronic products and services for our customers' professional and personal knowledge and understanding.

The Wiley Finance series contains books written specifically for finance and investment professionals as well as sophisticated individual investors and their financial advisors. Book topics range from portfolio management to e‐commerce, risk management, financial engineering, valuation and financial instrument analysis, as well as much more.

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Moving from equilibrium results, we next introduce statistical techniques such as regression, factor models, and PCA to find common drivers of asset returns and statistical measures such as the alpha and beta of portfolio performance. Trading strategies such as pairs trading and mean‐reversion trades are based on these methods. We conclude by showing the use of recurrence equations and optimization techniques for risk and money management leading to the gambler's ruin formula and Kelly's ratio.

In Chapter 4, we introduce the forward contract as the gateway product to more complicated contingent claims and options and derivatives. The basic cash‐and‐carry argument shows the method of static replication and arbitrage pricing. This method is used to compute forward prices in equities with discrete dividends or dividend yields, forward exchange rate via covered interest parity, and forward rates in interest rate markets.

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