Too often, books on financial computing provide only quick-and-dirty implementations of financial models that have very little use in real-world applications. Professional Financial Computing Using Excel and VBA aims to provide real-world implementations of financial models that are robust, reusable, and flexible. The book covers a wide range of financial models in the areas of derivatives pricings, market and credit risk modeling, as well as advanced interest rate modeling.
Each of the chapters on model implementations starts with a review on all the necessary financial theory and concepts from a practitioner’s perspective. Step-by-step instructions on the implementation are then provided to explain the programming techniques involved for models with different complexities. Alternative approaches are also discussed to offer readers a comprehensive understanding of different techniques. The appendices provide an in-depth look at how to implement financial models using both Excel 2007 and VBA, and to discuss the essential programming practices and skills in structuring complex financial models through advanced VBA features.
This book is designed for self-study, reference, and classroom use for graduate programs in financial engineering and computing. All Excel and VBA codes illustrated in the book are included in the enclosed CD.
“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
About the Author
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.
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