ABOUT THIS BOOK
"Professional Financial Computing Using Excel and VBA is an admirable exposition that bridges the theoretical underpinnings of financial engineering and its application which usually appears as a "black-box" software application. The book opens the black-box and reveals the architecture of risk-modeling and financial engineering based on industry-standard stochastic models by utilizing Excel and VBA functionality to create a robust and practical modeling tool-kit. Financial engineering professionals who purchase this book will have a jumpstart advantage for their customized financial engineering and modeling needs."
Dr. Cameron Wicentowich
Vice President, Treasury Analytics
Canadian Imperial Bank of Commerce (CIBC)
"Spreadsheet modeling for finance has become a standard course in the curriculum of many Quantitative Finance programs since the Excel-based Visual Basic programming is now widely used in constructing optimal portfolios, pricing structured products and managing risks. Professional Financial Computing Using Excel and VBA is written by a unique team of finance, physics and computer academics and practitioners. It is a good reference for those who are studying for a Masters degree in Financial Engineering and Risk Management. It can also be useful for financial engineers to jump-start a project on designing structured products, modeling interest term structure or credit risks."
Dr. Jin Zhang
Director of Master of Finance Program and Associate Professor
The University of Hong Kong

"Excel has been one of the most powerful tools for financial planning and computing over the last few years. Most users utilize a fraction of its capabilities. One of the reasons is the limited availability of books that cover the advanced features of Excel for Finance. Professional Financial Computing Using Excel and VBA goes the extra mile and deals with the Excel tools many professionals call for. This book is a must for professionals or students dealing with financial engineering, financial risk management, computational finance or mathematical finance. I loved the way the authors covered the material using real life, hands-on examples."
Dr. Isaac Gottlieb
Temple University
Author, Next Generation Excel: Modeling in Excel for Analysts and MBAs


TABLE OF CONTENTS
Preface ix
CHAPTER 1 Financial Engineering and Computing 1

1.1 Financial Engineering and Spreadsheet Modeling 1

1.2 Lehman Brothers' Products for Retail Investors 3

1.3 Risk Management and Basel II 4

1.4 About the Book 4

1.5. Chapter Highlights 6

1.6 Other Remarks 7

CHAPTER 2 The GARCH(1,1) Model 9

2.1. The Model 9

2.2. Excel Implementation 10

2.3. Excel Plus VBA Implementation 15

CHAPTER 3 Finite Difference Methods 21

3.1. Difference Equations 21

3.2. Excel Implementation 24

3.3. VBA Implementation 28

3.4. Crank–Nicholson Scheme 33

CHAPTER 4 Portfolio Mean-Variance Optimization 37

4.1. Portfolio Selection 37

4.2. Excel Implementation 42

4.3. Excel Plus VBA Implementation 48

CHAPTER 5 Newton–Raphson Method 59

5.1. Newton–Raphson Method for Systems of Equations 59

5.2. VBA Routine 61

CHAPTER 6 Yield Curve Construction Using Cubic Spline 67

6.1. Cubic Spline Interpolation 67

6.2. Yield Curve Construction 75

6.3. Excel Plus VBA Implementation 77

CHAPTER 7 Binomial Option Pricing Model 85

7.1. Risk-Neutral Option Pricing

and the Binomial Tree 85

7.2. VBA Implementation 89

CHAPTER 8 The Black–Derman–Toy Model 95

8.1. The Term Structure Model and

the Black–Derman–Toy Tree 95

8.2. Excel Plus VBA Implementation 98

CHAPTER 9 Monte Carlo Option Pricing 109

9.1. TheMonte Carlo Method 109

9.2. Risk-Neutral Valuation 112

9.3. VBA Implementation 114

9.4. Exotic Options 124

9.5. American Options 132

CHAPTER 10 Portfolio Value-at-Risk 143

10.1. Portfolio Risk Simulation 143

10.2. Monte Carlo Simulation for Multiple-Asset Portfolios 152

10.3. Historical Simulation for Multiple-Asset Portfolios 160

10.4. VBA Implementation of Portfolio Risk Simulation 164

10.5. Drill Down of Portfolio Risk 180

CHAPTER 11 The Hull–White Model 189

11.1. Hull–White Trinomial Tree 189

11.2. Excel Plus VBA Implementation 196

11.3. The General Hull–White Model 203

11.4. Implementation of the General Hull–White Model 210

CHAPTER 12 CreditMetrics Model 221

12.1. The CreditMetrics Model 221

12.2. Individual (Segregate) Asset Valuation Framework 221

12.3 Monte Carlo Simulation in Detail 225

12.4. Excel and VBA Implementation 227

CHAPTER 13 KMV–Merton Model 243

13.1. KMV–Merton Model of Credit Risk 243

13.2. Excel and VBA Implementation 248

APPENDIX A VBA Programming 255

A.1 Introduction 255

A.2 A Brief History of VBA 255

A.3 Essential Excel Elements for VBA 256

A.3.1 Excel Cell Reference 257

A.3.2 Excel Defined Names 261

A.3.3 Excel Worksheet Functions 264

A.4 The VBA Development Environment (VBE) 266

A.4.1 The Developer Tab in the Ribbon 266

A.4.2 The Windows of VBE 268

A.4.3 The Project Explorer 272

A.4.4 The VBA Project Structure 273

A.4.5 The Procedure to Create a VBA Subroutine 275

A.4.6 The Procedure to Create a VBA Function 278

A.5 Basic VBA Programming Concepts 280

A.5.1 Variables and Data Types 285

A.5.2 Declaration and Assignment Statements 287

A.5.3 Flow Control Statements 293

A.6 VBA Arrays 300

A.7 Using Worksheet Matrix Functions in VBA 304

A.8 Summary 311

APPENDIX B The Excel Object Model 315

APPENDIX C VBA Debugging Tools 321

APPENDIX D Summary of VBA Operators 327

APPENDIX E Summary of VBA Functions 331

APPENDIX F Summary of VBA Statements 333

APPENDIX G Excel Array Formula 341

Index 349


ABOUT THE AUTHORS
Dr. Humphrey K. K. Tung received his BSc in Physics from the University of Alberta, both MSc and PhD in Theoretical Particle Physics from the University of Toronto. He was a quantitative analyst of C.ATS, a leading risk management software vendor in Silicon Valley. He is now a Visiting Assistant Professor in the Department of Economics and Finance of the City University of Hong Kong and has taught the option pricing and implementation for financial engineering program since 2003.
Mr. Donny Lai is proficient in information systems development, IT project management, and applied finance. He has worked in the IT industry for over 20 years and received his Master Degree of Applied Finance from the University of Western Sydney, Australia. With his profound experience in e-commerce and e-finance, he is teaching in the department of Computer Science, City University of Hong Kong and has taught programming, data analysis, and spreading modeling since 2005. His current research interests include advanced web technologies, mobile computing, and financial computing.

Dr. Michael Wong advised more than 20 banks on market risk management, credit risk management, Basel II credit ratings systems and due diligence for wealth management services. He served as a founding member of FRM Committee of Global Association of Risk Professionals (GARP) in 1998-2002 and trained more than 6,000 chief risk officers, senior risk managers and bank regulators in Hong Kong, Taiwan, China, Korea, Singapore, Malaysia, and Macau. He founded CTRISKS (www.ctrisks.com), an Asia-based credit rating agency and risk consulting firm. Dr. Wong has published more than 50 journal articles and book chapters, and authored four professional books. He is listed in Risk Who's Who, and awarded both Teaching Excellence Award and Best Doctoral Dissertation Award.

Stephen Ng is an executive director of Canadian Imperial Bank of Commerce, who is responsible for coordinating market risk management initiatives in the Asia Pacific region. Previously, he was a quantitative investment manager at ING Investment Management where he developed investment strategies and conducted quantitative research in FX, rates and credit. In addition, he worked at Diversified Credit Investments, Deutsche Bank and Morgan Stanley in the past. He earned his MS in Mathematical Finance from University of Southern California and his BA in Economics from University of California, Berkeley. He is also a CFA charterholder and a Certified Financial Risk Manager.