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Professional Financial Computing Using Excel & VBA


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

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 (, 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.


CHAPTER 1 Financial Engineering and Computing.

1.1 Financial Engineering and Spreadsheet Modeling.

1.2 Lehman Brothers’ Products for Retail Investors.

1.3 Risk Management and Basel II.

1.4 About the Book.

1.5. Chapter Highlights.

1.6 Other Remarks.

CHAPTER 2 The GARCH(1,1) Model.

2.1. The Model.

2.2. Excel Implementation.

2.3. Excel Plus VBA Implementation.

CHAPTER 3 Finite Difference Methods.

3.1. Difference Equations.

3.2. Excel Implementation.

3.3. VBA Implementation.

3.4. Crank–Nicholson Scheme.

CHAPTER 4 Portfolio Mean-Variance Optimization.

4.1. Portfolio Selection.

4.2. Excel Implementation.

4.3. Excel Plus VBA Implementation.

CHAPTER 5 Newton–Raphson Method.

5.1. Newton–Raphson Method for Systems of Equations.

5.2. VBA Routine.

CHAPTER 6 Yield Curve Construction Using Cubic Spline.

6.1. Cubic Spline Interpolation.

6.2. Yield Curve Construction.

6.3. Excel Plus VBA Implementation.

CHAPTER 7 Binomial Option Pricing Model.

7.1. Risk-Neutral Option Pricing and the Binomial Tree.

7.2. VBA Implementation.

CHAPTER 8 The Black–Derman–Toy Model.

8.1. The Term Structure Model and the Black–Derman–Toy Tree.

8.2. Excel Plus VBA Implementation.

CHAPTER 9 Monte Carlo Option Pricing.

9.1. The Monte Carlo Method.

9.2. Risk-Neutral Valuation.

9.3. VBA Implementation.

9.4. Exotic Options.

9.5. American Options.

CHAPTER 10 Portfolio Value-at-Risk.

10.1. Portfolio Risk Simulation.

10.2. Monte Carlo Simulation for Multiple-Asset Portfolios.

10.3. Historical Simulation for Multiple-Asset Portfolios.

10.4. VBA Implementation of Portfolio Risk Simulation.

10.5. Drill Down of Portfolio Risk.

CHAPTER 11 The Hull–White Model.

11.1. Hull–White Trinomial Tree.

11.2. Excel Plus VBA Implementation.

11.3. The General Hull–White Model.

11.4. Implementation of the General Hull–White Model.

CHAPTER 12 CreditMetrics Model.

12.1. The CreditMetrics Model.

12.2. Individual (Segregate) Asset Valuation Framework.

12.3 Monte Carlo Simulation in Detail.

12.4. Excel and VBA Implementation.

CHAPTER 13 KMV–Merton Model.

13.1. KMV–Merton Model of Credit Risk.

13.2. Excel and VBA Implementation.

APPENDIX A VBA Programming.

A.1 Introduction.

A.2 A Brief History of VBA.

A.3 Essential Excel Elements for VBA.

A.3.1 Excel Cell Reference.

A.3.2 Excel Defined Names.

A.3.3 Excel Worksheet Functions.

A.4 The VBA Development Environment (VBE).

A.4.1 The Developer Tab in the Ribbon.

A.4.2 The Windows of VBE.

A.4.3 The Project Explorer.

A.4.4 The VBA Project Structure.

A.4.5 The Procedure to Create a VBA Subroutine.

A.4.6 The Procedure to Create a VBA Function.

A.5 Basic VBA Programming Concepts.

A.5.1 Variables and Data Types.

A.5.2 Declaration and Assignment Statements.

A.5.3 Flow Control Statements.

A.6 VBA Arrays.

A.7 Using Worksheet Matrix Functions in VBA.

A.8 Summary.

APPENDIX B The Excel Object Model.

APPENDIX C VBA Debugging Tools.

APPENDIX D Summary of VBA Operators.

APPENDIX E Summary of VBA Functions.

APPENDIX F Summary of VBA Statements.

APPENDIX G Excel Array Formula.