Advanced Modelling in Finance using Excel and VBA

Comprehensive instruction on developing real-world financial models This book, designed for self-study, classroom use, and reference, presents a com-prehensive approach to developing simple to sophisticated financial models in all major areas of finance. The approach is based on the author's 20 years of experience of developing such models in the business world and teaching a popular MBA class in financial modeling. The book assumes only basic knowledge of Excel and teaches all advanced features of Excel and VBA from scratch using a unique simple method. A companion CD includes all working versions of all the models presented in the book and additional useful reference material. Chandan Sengupta (White Plains, NY) teaches finance in the MBA program at Fordham University's Graduate School of Business. Formerly, he was vice president of the Chase Manhattan Bank for eight years and senior financial advisor for Mobil Corporation for 10 years. He is also the author of The Only Proven Road to Investment Success (0-471-44307-7).

"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

In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques, in this case credit. Credit Risk Modeling using Excel and VBA with DVD provides practitioners with a hands on introduction to credit risk modeling. Instead of just presenting analytical methods it shows how to implement them using Excel and VBA, in addition to a detailed description in the text a DVD guides readers step by step through the implementation. The authors begin by showing how to use option theoretic and statistical models to estimate a borrowers default risk. The second half of the book is devoted to credit portfolio risk. The authors guide readers through the implementation of a credit risk model, show how portfolio models can be validated or used to access structured credit products like CDO’s. The final chapters address modeling issues associated with the new Basel Accord.

This comprehensive guide offers traders, quants, and students the tools and techniques for using advanced models for pricing options. The accompanying website includes data files, such as options prices, stock prices, or index prices, as well as all of the codes needed to use the option and volatility models described in the book. Praise for Option Pricing Models & Volatility Using Excel-VBA «Excel is already a great pedagogical tool for teaching option valuation and risk management. But the VBA routines in this book elevate Excel to an industrial-strength financial engineering toolbox. I have no doubt that it will become hugely successful as a reference for option traders and risk managers.» —Peter Christoffersen, Associate Professor of Finance, Desautels Faculty of Management, McGill University «This book is filled with methodology and techniques on how to implement option pricing and volatility models in VBA. The book takes an in-depth look into how to implement the Heston and Heston and Nandi models and includes an entire chapter on parameter estimation, but this is just the tip of the iceberg. Everyone interested in derivatives should have this book in their personal library.» —Espen Gaarder Haug, option trader, philosopher, and author of Derivatives Models on Models «I am impressed. This is an important book because it is the first book to cover the modern generation of option models, including stochastic volatility and GARCH.» —Steven L. Heston, Assistant Professor of Finance, R.H. Smith School of Business, University of Maryland

Co-authored by two respected authorities on hedge funds and asset management, this implementation-oriented guide shows you how to employ a range of the most commonly used analysis tools and techniques both in industry and academia, for understanding, identifying and managing risk as well as for quantifying return factors across several key investment strategies. The book is also suitable for use as a core textbook for specialised graduate level courses in hedge funds and alternative investments. The book provides hands-on coverage of the visual and theoretical methods for measuring and modelling hedge fund performance with an emphasis on risk-adjusted performance metrics and techniques. A range of sophisticated risk analysis models and risk management strategies are also described in detail. Throughout, coverage is supplemented with helpful skill building exercises and worked examples in Excel and VBA. The book's dedicated website, www.darbyshirehampton.com provides Excel spreadsheets and VBA source code which can be freely downloaded and also features links to other relevant and useful resources. A comprehensive course in hedge fund modelling and analysis, this book arms you with the knowledge and tools required to effectively manage your risks and to optimise the return profile of your investment style.

This book provides a pragmatic, hands-on approach to reaching an intermediate level of sophistication as a financial modeler. Expanding on the first book, A Fast Tract to Structured Finance Modeling, Monitoring, and Valuation, the book will guide you step-by-step through using learned principals in new and more powerful applications. These applications will build on the knowledge of Excel and VBA gained, expand the use of Access for data management tasks, as well as PowerPoint and Outlook for reporting and presentation tasks.

The second book in Darbyshire and Hampton’s Hedge Fund Modelling and Analysis series, Hedge Fund Modelling and Analysis Using MATLAB® takes advantage of the huge library of built-in functions and suite of financial and analytic packages available to MATLAB®. This allows for a more detailed analysis of some of the more computationally intensive and advanced topics, such as hedge fund classification, performance measurement and mean-variance optimisation. Darbyshire and Hampton’s first book in the series, Hedge Fund Modelling and Analysis Using Excel & and VBA, is seen as a valuable supplementary text to this book. Starting with an overview of the hedge fund industry the book then looks at a variety of commercially available hedge fund data sources. After covering key statistical techniques and methods, the book discusses mean-variance optimisation, hedge fund classification and performance with an emphasis on risk-adjusted return metrics. Finally, common hedge fund market risk management techniques, such as traditional Value-at-Risk methods, modified extensions and expected shortfall are covered. The book’s dedicated website, www.darbyshirehampton.com provides free downloads of all the data and MATLAB® source code, as well as other useful resources. Hedge Fund Modelling and Analysis Using MATLAB® serves as a definitive introductory guide to hedge fund modelling and analysis and will provide investors, industry practitioners and students alike with a useful range of tools and techniques for analysing and estimating alpha and beta sources of return, performing manager ranking and market risk management.

Provides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS® and Excel® applications This book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field. The book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material. Using Statistics in the Social and Health Sciences with SPSS® and Excel® includes: • Use of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings • Inclusion of a data lab section in each chapter that provides relevant, clear examples • Introduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs Emphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS® and Excel® for analyzing data. Martin Lee Abbott, PhD, is Professor of Sociology at Seattle Pacific University, where he has served as Executive Director of the Washington School Research Center, an independent research and data analysis center funded by the Bill & Melinda Gates Foundation. Dr. Abbott has held positions in both academia and industry, focusing his consulting and teaching in the areas of statistical procedures, program evaluation, applied sociology, and research methods. He is the author of Understanding Educational Statistics Using Microsoft Excel® and SPSS®, The Program Evaluation Prism: Using Statistical Methods to Discover Patterns, and Understanding and Applying Research Design, also from Wiley.

The successful design and construction of iconic new buildings relies on a range of advanced technologies, in particular on advanced modelling techniques. In response to the increasingly complex buildings demanded by clients and architects, structural engineers have developed a range of sophisticated modelling software to carry out the necessary structural analysis and design work. Advanced Modelling Techniques in Structural Design introduces numerical analysis methods to both students and design practitioners. It illustrates the modelling techniques used to solve structural design problems, covering most of the issues that an engineer might face, including lateral stability design of tall buildings; earthquake; progressive collapse; fire, blast and vibration analysis; non-linear geometric analysis and buckling analysis . Resolution of these design problems are demonstrated using a range of prestigious projects around the world, including the Buji Khalifa; Willis Towers; Taipei 101; the Gherkin; Millennium Bridge; Millau viaduct and the Forth Bridge, illustrating the practical steps required to begin a modelling exercise and showing how to select appropriate software tools to address specific design problems.