Downloadable Excel worksheets and solutions to end-of-chapter exercises accompany Financial Modeling, Fourth Edition, by Simon Benninga. Access codes are required to download the supplemental material. New print copies of this book include a card affixed to the inside back cover with a unique access code. If you purchased a used copy of this book, this is a separately purchased printed access card.
Merging theory and practice into a comprehensive,highly-anticipated text Corporate Finance continues its legacy as one of the mostpopular financial textbooks, with well-established content from adiverse and highly respected author team. Unique in its features,this valuable text blends theory and practice with a direct,succinct style and commonsense presentation. Readers will beintroduced to concepts in a situational framework, followed by adetailed discussion of techniques and tools. This latest editionincludes new information on venture finance and debt structuring,and has been updated throughout with the most recent statisticaltables. The companion website provides statistics, graphs, charts,articles, computer models, and classroom tools, and the freemonthly newsletter keeps readers up to date on the latesthappenings in the field. The authors have generously madethemselves available for questions, promising an answer inseventy-two hours. Emphasizing how key concepts relate to real-world situations iswhat makes Corporate Finance a valuable reference with realrelevance to the professional and student alike. Readers will gaininsight into the methods and tools that shape the industry,allowing them to: Analyze investments with regard to hurdle rates, cash flows,side costs, and more Delve into the financing process and learn the tools andtechniques of valuation Understand cash dividends and buybacks, spinoffs, anddivestitures Explore the link between valuation and corporate finance As the global economy begins to recover, access to the mostcurrent information and statistics will be required. To remainrelevant in the evolving financial environment, practitioners willneed a deep understanding of the mechanisms at work. CorporateFinance provides the expert guidance and detailed explanationsfor those requiring a strong foundational knowledge, as well asmore advanced corporate finance professionals.
Business Problems and Solutions with R, Revised and Expanded Edition
Author: Thomas W. Miller
Publisher: FT Press
To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
An accessible and thorough review of the internationalfinancial markets Life in the Financial Markets—How They Really Work AndWhy They Matter To You offers the financial servicesprofessional, and anyone interested in knowing more about theprofession, an entertaining and comprehensive analysis of thefinancial markets and the financial services industry. Written byDaniel Lacalle—a noted portfolio manager with EcoFin andwell-known media personality—the book goes beyond a simplesummary and offers solid advice on the future of the globalfinancial markets. This great resource also includes a review ofeffective strategies and forecasts the trends that representpotential opportunities for investors. The book reviews the recent history of the financial crisis andincludes information on hot topics such as derivatives and highfrequency trading. An in-depth section on investment banking iswritten from the perspective of a successful practitioner andprovides clarity on several complex and overly politicized elementsof the banking system. The author gives an expert's perspective onthe debt markets, monetary policies, and quantitative easing, andhelps explain the various issues surrounding sovereign debt, theEuro crisis, and austerity versus growth policies. Comprehensive inscope, this resource also offers an analysis of investment styles,from hedge funds to "long only" investments, as well as an in-depthlook at corporate communication and its impact on markets andinvestments. Offers an engaging and comprehensive analysis of the financialservices industry Includes information on the workings of the global financialsystem following the economic crisis Contains a review of complex banking systems Analyzes the various investment styles and answers the mostcommon questions pertaining to investing
Foundations of Real Estate Financial Modelling is specifically designed to provide an overview of pro forma modelling for real estate projects. The book introduces students and professionals to the basics of real estate finance theory before providing a step-by-step guide for financial model construction using Excel. The idea that real estate is an asset with unique characteristics which can be transformed, both physically and financially, forms the basis of discussion. Individual chapters are separated by functional unit and build upon themselves to include information on: Amortization Single-Family Unit Multi-Family Unit Development/Construction Addition(s) Waterfall (Equity Bifurcation) Accounting Statements Additional Asset Classes Further chapters are dedicated to risk quantification and include scenario, stochastic and Monte Carlo simulations, waterfalls and securitized products. This book is the ideal companion to core real estate finance textbooks and will boost students Excel modelling skills before they enter the workplace. The book provides individuals with a step-by-step instruction on how to construct a real estate financial model that is both scalable and modular. A companion website provides the pro forma models to give readers a basic financial model for each asset class as well as methods to quantify performance and understand how and why each model is constructed and the best practices for repositioning these assets.
WINNER of a Riskbook.com Best of 2004 Book Award! During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematical tools required for applications can be intimidating. Potential users often get the impression that jump and Lévy processes are beyond their reach. Financial Modelling with Jump Processes shows that this is not so. It provides a self-contained overview of the theoretical, numerical, and empirical aspects involved in using jump processes in financial modelling, and it does so in terms within the grasp of nonspecialists. The introduction of new mathematical tools is motivated by their use in the modelling process, and precise mathematical statements of results are accompanied by intuitive explanations. Topics covered in this book include: jump-diffusion models, Lévy processes, stochastic calculus for jump processes, pricing and hedging in incomplete markets, implied volatility smiles, time-inhomogeneous jump processes and stochastic volatility models with jumps. The authors illustrate the mathematical concepts with many numerical and empirical examples and provide the details of numerical implementation of pricing and calibration algorithms. This book demonstrates that the concepts and tools necessary for understanding and implementing models with jumps can be more intuitive that those involved in the Black Scholes and diffusion models. If you have even a basic familiarity with quantitative methods in finance, Financial Modelling with Jump Processes will give you a valuable new set of tools for modelling market fluctuations.
The importance of sound financial modelling skills, deep understanding of valuation methods and the assessment of outputs of valuations for finance professionals cannot be overemphasized The book aims to help a user deep dive into the art of financial modelling and valuation. The reader will be able to prepare/use existing models more competently, interpret the results and have greater comfort over the integrity and accuracy of the model's calculations. It seeks to disseminate the skill-set to prepare financial models for business cases, be it Mergers & Acquisitions, Venture Capital/ Private Equity or long-term Financial Forecasts of companies It is suited for an aspirant who seeks to learn the art of preparing financial models in a logical structured and disciplined manner. In turn, the user can go for correct valuation analyses, which in turn, fuels well-informed and appropriate strategic organizational decisions.
Comprehensive instruction on developing real-world financialmodels This book, designed for self-study, classroom use, and reference,presents a com-prehensive approach to developing simple tosophisticated financial models in all major areas of finance. Theapproach is based on the author's 20 years of experience ofdeveloping such models in the business world and teaching a popularMBA class in financial modeling. The book assumes only basicknowledge of Excel and teaches all advanced features of Excel andVBA from scratch using a unique simple method. A companion CDincludes all working versions of all the models presented in thebook and additional useful reference material. Chandan Sengupta (White Plains, NY) teaches finance in the MBAprogram at Fordham University's Graduate School of Business.Formerly, he was vice president of the Chase Manhattan Bank foreight years and senior financial advisor for Mobil Corporation for10 years. He is also the author of The Only Proven Road toInvestment Success (0-471-44307-7).