Quantitative Finance: A Simulation-Based Introduction Using Excel

دسته بندی: اقتصاد ریاضی
ویرایش:  
نویسندگان: Davison. Matt  
سری:  
ISBN (شابک) : 9781439871683, 143987168X 
ناشر: Chapman and Hall/CRC 
سال نشر: 2014 
تعداد صفحات: 523 
زبان: English 
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) 
حجم فایل: 4 مگابایت 

قیمت کتاب (تومان) : 28,000

"Teach Your Students How to Become Successful Working QuantsQuantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not only enables students to practice with the basic techniques of financial mathematics, but it also helps them gain significant intuition about what the techniques mean, how they work, and what happens when they stop working.After introducing risk, return, decision making under uncertainty, and traditional discounted cash flow project analysis, the book covers mortgages, bonds, and annuities using a blend of Excel simulation and difference equation or algebraic formalism. It then looks at how interest rate markets work and how to model bond prices before addressing mean variance portfolio optimization, the capital asset pricing model, options, and value at risk (VaR). The author next focuses on binomial model tools for pricing options and the analysis of discrete random walks. He also introduces stochastic calculus in a nonrigorous way and explains how to simulate geometric Brownian motion. The text proceeds to thoroughly discuss options pricing, mostly in continuous time. It concludes with chapters on stochastic models of the yield curve and incomplete markets using simple discrete models.Accessible to students with a relatively modest level of mathematical background, this book will guide your students in becoming successful quants. It uses both hand calculations and Excel spreadsheets to analyze plenty of examples from simple bond portfolios. The spreadsheets are available on the book's CRC Press web page"--

"Preface It is necessary to thank many people at the end of a big project like writing a book. First, my thanks go to my patient editor Sunil Nair and his editorial assistants Rachel Holt and Sarah Gelson. Two anonymous reviewers made very thorough and useful comments on an earlier manuscript. Tao Luo and Sharon Wang typed and made figures for many versions of this book. Tao's valuable comments, mastery of visual basic, and untiring commitment were a particular help in both of the final pushes to completing this project. I have benefitted from teaching this material to many students over many years, beginning with many insightful master's and PhD students. Classroom versions of this content has been taught to the actuarial science, financial modeling, and applied mathematics students of AM3613b, AM9578b, AS9022a, SS4521 g, SS9521b, and SS3520b at Western University, to the HBA students of Bus4486 and MBA students of Bus9443 at the Richard Ivey School of Business, and to students at a course on interest rate models given at the Bank of Canada. Greg Sullivan and Kirk Cooper, then at Deutsche Bank Canada, were my first teachers in trading floor quant finance. Chris Essex, Henning Rasmussen, and Mark Reesor at Western, Adam Metzler at Wilfrid Laurier, Matt Thompson at Queens, Lindsay Anderson at Cornell, and Alejandro Garcia at the Office of the Superintendent of Financial Institutions, have all helped shape my thinking. Of course, any errors or omissions in this book are mine alone. The final thanks go to my wife Christine and my sons Liam and Shawn, without whom none of this would be worth doing"-- Read more...
Abstract: "Teach Your Students How to Become Successful Working QuantsQuantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not only enables students to practice with the basic techniques of financial mathematics, but it also helps them gain significant intuition about what the techniques mean, how they work, and what happens when they stop working.After introducing risk, return, decision making under uncertainty, and traditional discounted cash flow project analysis, the book covers mortgages, bonds, and annuities using a blend of Excel simulation and difference equation or algebraic formalism. It then looks at how interest rate markets work and how to model bond prices before addressing mean variance portfolio optimization, the capital asset pricing model, options, and value at risk (VaR). The author next focuses on binomial model tools for pricing options and the analysis of discrete random walks. He also introduces stochastic calculus in a nonrigorous way and explains how to simulate geometric Brownian motion. The text proceeds to thoroughly discuss options pricing, mostly in continuous time. It concludes with chapters on stochastic models of the yield curve and incomplete markets using simple discrete models.Accessible to students with a relatively modest level of mathematical background, this book will guide your students in becoming successful quants. It uses both hand calculations and Excel spreadsheets to analyze plenty of examples from simple bond portfolios. The spreadsheets are available on the book's CRC Press web page"--

"Preface It is necessary to thank many people at the end of a big project like writing a book. First, my thanks go to my patient editor Sunil Nair and his editorial assistants Rachel Holt and Sarah Gelson. Two anonymous reviewers made very thorough and useful comments on an earlier manuscript. Tao Luo and Sharon Wang typed and made figures for many versions of this book. Tao's valuable comments, mastery of visual basic, and untiring commitment were a particular help in both of the final pushes to completing this project. I have benefitted from teaching this material to many students over many years, beginning with many insightful master's and PhD students. Classroom versions of this content has been taught to the actuarial science, financial modeling, and applied mathematics students of AM3613b, AM9578b, AS9022a, SS4521 g, SS9521b, and SS3520b at Western University, to the HBA students of Bus4486 and MBA students of Bus9443 at the Richard Ivey School of Business, and to students at a course on interest rate models given at the Bank of Canada. Greg Sullivan and Kirk Cooper, then at Deutsche Bank Canada, were my first teachers in trading floor quant finance. Chris Essex, Henning Rasmussen, and Mark Reesor at Western, Adam Metzler at Wilfrid Laurier, Matt Thompson at Queens, Lindsay Anderson at Cornell, and Alejandro Garcia at the Office of the Superintendent of Financial Institutions, have all helped shape my thinking. Of course, any errors or omissions in this book are mine alone. The final thanks go to my wife Christine and my sons Liam and Shawn, without whom none of this would be worth doing"

Content: Introduction   Intuition about Uncertainty and Risk  Introduction  Individual Attitudes toward Risk  The St. Petersburg Paradox  Looking Forward to Chapter 3   The Classical Approach to Decision Making under Uncertainty  Map to the Future  Valuing Investment Opportunities: The Discounted Cash Flow Method  Discounted Cash Flow Method for Evaluating Investment Opportunities  Conclusions   Repaying Loans Over Time  Introduction  Repaying a Loan over Time: Excel  Repaying a Loan over Time: Mathematics  First-Order Difference Equations Solving the Loan Repayment Difference Equation  More Examples of Using Difference Equations to Find Loan Payments  Writing the Difference Equation in Forward versus Backward Forms  Bridges to the Future   Bond Pricing with Default: Using Simulations  Modeling a Defaultable Bond or Loan  Financial Insights  Simulating Loan Portfolios  What Happens if There Are a Large Number of Independent Loans?  Bridge to the Future   Bond Pricing with Default: Using Difference Equations  Risky Bonds  Using Difference Equations to Find C  Exploring the Insights Arising from Equation 7.5  Determining Recovery Rates  Determining the Probability of Default  A Bridge to the Future   Difference Equations for Life Annuities  Introduction   Tranching and Collateralized Debt Obligations  Collateralized Debt Obligations  Tranched Portfolios  The Detailed Calculation  Correlation of Two Identical Bonds  Conclusion   Bond CDOs: More Than Two Bonds, Correlation, and Simulation  Introduction  Using an Excel Simulation to Analyze CDOs with More Than Two Bonds  Collateralized Debt Obligations: An Example of Financial Engineering  The Binomial Simplification  Correlated Defaults   Fundamentals of Fixed Income Markets  What Are Bonds?  Getting Down to Quantitative Details  Simplest Bond Pricing Equation  How Bonds Are Traded in Canada  Clean and Dirty Bond Prices  Conclusion and Bridge to the Next  Yield Curves and Bond Risk Measures  Introduction  Constructing Yield Curves from Bond Prices  Bond Price Sensitivities to the Yield   Forward Rates  Introduction Relationships between Forward Rates and the Yield Curve  Yield Curves, Discount Factors, and Forward Rates  Interpreting Forward Curves   Modeling Stock Prices  What Are Stocks?  Simple Statistical Analysis of Real Stock Data   Mean Variance Portfolio Optimization  Selecting Portfolios  CAPM and Markowitz   A Qualitative Introduction to Options  Stock Option Definitions  Uses for Put and Call Options  Qualitative Behavior of Puts and Calls   Value at Risk (VaR) Introduction to Value at Risk  Pitfalls of VaR  Summary  Pricing Options Using Binomial Trees  Introduction Binomia l Model  Single-Period Binomial Tree Model for Option Pricing  Extending the Binomial Model to Multiple Time Steps  Multiple-Step Binomial Trees Summary  Random Walks  Introduction  Deriving the Diffusion Partial Differential Equation   Basic Stochastic Calculus Basics of Stochastic Calculus  Stochastic Integration by Examples  Conclusions and Bridge to Next Chapters   Simulating Geometric Brownian Motion  Simulating GBM Stock Prices at a Single Future Time  Simulating a Time Sequence of GBM Stock Prices  Summary   Black Scholes PDE for Pricing Options in Continuous Time  Introduction  Hedging Argument  Call Price Solution of the Black Scholes Equation Why Short Selling Is So Dangerous  Summary and Bridge to the Future   Solving the Black Scholes PDE  Solving the Black Scholes Partial PDE for a European Call  General European Option Payoffs: Risk-Neutral Pricing  Summary  Pricing Put Options Using Put Call Parity  Summary  Some Approximate Values of the Black Scholes Call Formula  Approximate Call Formulas at-the-Money  Approximate Call Values Near-the-Money  Approximate Call Values Far-from-the-Money   Simulating Delta Hedging  Introduction  How Does Delta Hedging Really Work?  Understanding the Results of the Delta Hedging Process  The Impact of Transaction Costs  A Hedgers Perspective on Option Gamma or, "Big Gamma" = "Big Money"  Bridge to the Future   Black Scholes with Dividends  Modeling Dividends  The Black Scholes PDE for the Continuously Paid Dividend Case  Pricing the Prepaid Forward on a Continuous Dividend Paying Stock  More Complicated Derivatives on Underlying Paying Continuous Dividends   American Options  Introduction and Binomial Pricing  American Puts  American Calls   Pricing the Perpetual American Put and Call  Perpetual Options: Underlying Pays No Dividends  Basic Perpetual American Call  Perpetual American Call/Put Model with Dividends  The Perpetual American Call, Continuous Dividends   Options on Multiple Underlying Assets  Exchange Options   Interest Rate Models  Setting the Stage for Stochastic Interest Rate Models  Pricing When You CANNOT Trade the Underlying Asset  Hedging Bonds in Continuous Time  Solving the Bond Pricing PDE  Vasicek Model  Summary   Incomplete Markets Introduction to Incomplete Markets  Trying to Hedge Options on a Trinomial Tree  Minimum Variance Hedging of a European Option with Default  Binomial Tree Model with Default Risk   Appendix 1: Probability Theory Basics-Experiments, Sample Outcomes, Events, and Sample Space  Appendix 2: Proof of De Moivre-Laplace Theorem Using MGF Appendix 3: Naming Variables in Excel Appendix 4: Building VBA Macros from Excel  Index  Exercises and References appear at the end of each chapter