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| financial modeling mit press: Financial Modeling Simon Benninga, Benjamin Czaczkes, 2000 Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. Financial Modeling bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial problems with spreadsheets. The CD-ROM contains Excel* worksheets and solutions to end-of-chapter exercises. 634 illustrations. |
| financial modeling mit press: Financial Modeling, fifth edition Simon Benninga, Tal Mofkadi, 2022-02-01 A substantially updated new edition of the essential text on financial modeling, with revised material, new data, and implementations shown in Excel, R, and Python. Financial Modeling has become the gold-standard text in its field, an essential guide for students, researchers, and practitioners that provides the computational tools needed for modeling finance fundamentals. This fifth edition has been substantially updated but maintains the straightforward, hands-on approach, with an optimal mix of explanation and implementation, that made the previous editions so popular. Using detailed Excel spreadsheets, it explains basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds. This new edition offers revised material on valuation, second-order and third-order Greeks for options, value at risk (VaR), Monte Carlo methods, and implementation in R. The examples and implementation use up-to-date and relevant data. Parts I to V cover corporate finance topics, bond and yield curve models, portfolio theory, options and derivatives, and Monte Carlo methods and their implementation in finance. Parts VI and VII treat technical topics, with part VI covering Excel and R issues and part VII (now on the book’s auxiliary website) covering Excel’s programming language, Visual Basic for Applications (VBA), and Python implementations. Knowledge of technical chapters on VBA and R is not necessary for understanding the material in the first five parts. The book is suitable for use in advanced finance classes that emphasize the need to combine modeling skills with a deeper knowledge of the underlying financial models. |
| financial modeling mit press: Financial Modeling, fifth edition Simon Benninga, Tal Mofkadi, 2022-02-08 A substantially updated new edition of the essential text on financial modeling, with revised material, new data, and implementations shown in Excel, R, and Python. Financial Modeling has become the gold-standard text in its field, an essential guide for students, researchers, and practitioners that provides the computational tools needed for modeling finance fundamentals. This fifth edition has been substantially updated but maintains the straightforward, hands-on approach, with an optimal mix of explanation and implementation, that made the previous editions so popular. Using detailed Excel spreadsheets, it explains basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds. This new edition offers revised material on valuation, second-order and third-order Greeks for options, value at risk (VaR), Monte Carlo methods, and implementation in R. The examples and implementation use up-to-date and relevant data. Parts I to V cover corporate finance topics, bond and yield curve models, portfolio theory, options and derivatives, and Monte Carlo methods and their implementation in finance. Parts VI and VII treat technical topics, with part VI covering Excel and R issues and part VII (now on the book’s auxiliary website) covering Excel’s programming language, Visual Basic for Applications (VBA), and Python implementations. Knowledge of technical chapters on VBA and R is not necessary for understanding the material in the first five parts. The book is suitable for use in advanced finance classes that emphasize the need to combine modeling skills with a deeper knowledge of the underlying financial models. |
| financial modeling mit press: Numerical Techniques in Finance Simon Benninga, 1989 Deals with corporate finance and portfolio problems |
| financial modeling mit press: Just Money Katrin Kaufer, Lillian Steponaitis, 2021-02-02 How to use finance as a tool to build a more equitable and sustainable society. Money defines our present and will shape our future. Every investment decision we make adds a chapter to the story of what our world will look like. Although the idea of mission-based finance has been around for decades, there is a gap between organizations' stated intention to do good and meaningful impact. Still, some are succeeding. In Just Money, Katrin Kaufer and Lillian Steponaitis take readers on a global tour of financial institutions that use finance as a force for good. |
| financial modeling mit press: Introduction to the Economics and Mathematics of Financial Markets Jaksa Cvitanic, Fernando Zapatero, 2004-02-27 An innovative textbook for use in advanced undergraduate and graduate courses; accessible to students in financial mathematics, financial engineering and economics. Introduction to the Economics and Mathematics of Financial Markets fills the longstanding need for an accessible yet serious textbook treatment of financial economics. The book provides a rigorous overview of the subject, while its flexible presentation makes it suitable for use with different levels of undergraduate and graduate students. Each chapter presents mathematical models of financial problems at three different degrees of sophistication: single-period, multi-period, and continuous-time. The single-period and multi-period models require only basic calculus and an introductory probability/statistics course, while an advanced undergraduate course in probability is helpful in understanding the continuous-time models. In this way, the material is given complete coverage at different levels; the less advanced student can stop before the more sophisticated mathematics and still be able to grasp the general principles of financial economics. The book is divided into three parts. The first part provides an introduction to basic securities and financial market organization, the concept of interest rates, the main mathematical models, and quantitative ways to measure risks and rewards. The second part treats option pricing and hedging; here and throughout the book, the authors emphasize the Martingale or probabilistic approach. Finally, the third part examines equilibrium models—a subject often neglected by other texts in financial mathematics, but included here because of the qualitative insight it offers into the behavior of market participants and pricing. |
| financial modeling mit press: When Things Don't Fall Apart Ilene Grabel, 2019-08-06 An account of the significant though gradual, uneven, disconnected, ad hoc, and pragmatic innovations in global financial governance and developmental finance induced by the global financial crisis. In When Things Don't Fall Apart, Ilene Grabel challenges the dominant view that the global financial crisis had little effect on global financial governance and developmental finance. Most observers discount all but grand, systemic ruptures in institutions and policy. Grabel argues instead that the global crisis induced inconsistent and ad hoc discontinuities in global financial governance and developmental finance that are now having profound effects on emerging market and developing economies. Grabel's chief normative claim is that the resulting incoherence in global financial governance is productive rather than debilitating. In the age of productive incoherence, a more complex, dense, fragmented, and pluripolar form of global financial governance is expanding possibilities for policy and institutional experimentation, policy space for economic and human development, financial stability and resilience, and financial inclusion. Grabel draws on key theoretical commitments of Albert Hirschman to cement the case for the productivity of incoherence. Inspired by Hirschman, Grabel demonstrates that meaningful change often emerges from disconnected, erratic, experimental, and inconsistent adjustments in institutions and policies as actors pragmatically manage in an evolving world. Grabel substantiates her claims with empirically rich case studies that explore the effects of recent crises on networks of financial governance (such as the G-20); transformations within the IMF; institutional innovations in liquidity support and project finance from the national to the transregional levels; and the “rebranding” of capital controls. Grabel concludes with a careful examination of the opportunities and risks associated with the evolutionary transformations underway. |
| financial modeling mit press: The Economics of Continuous-Time Finance Bernard Dumas, Elisa Luciano, 2017-10-27 An introduction to economic applications of the theory of continuous-time finance that strikes a balance between mathematical rigor and economic interpretation of financial market regularities. This book introduces the economic applications of the theory of continuous-time finance, with the goal of enabling the construction of realistic models, particularly those involving incomplete markets. Indeed, most recent applications of continuous-time finance aim to capture the imperfections and dysfunctions of financial markets—characteristics that became especially apparent during the market turmoil that started in 2008. The book begins by using discrete time to illustrate the basic mechanisms and introduce such notions as completeness, redundant pricing, and no arbitrage. It develops the continuous-time analog of those mechanisms and introduces the powerful tools of stochastic calculus. Going beyond other textbooks, the book then focuses on the study of markets in which some form of incompleteness, volatility, heterogeneity, friction, or behavioral subtlety arises. After presenting solutions methods for control problems and related partial differential equations, the text examines portfolio optimization and equilibrium in incomplete markets, interest rate and fixed-income modeling, and stochastic volatility. Finally, it presents models where investors form different beliefs or suffer frictions, form habits, or have recursive utilities, studying the effects not only on optimal portfolio choices but also on equilibrium, or the price of primitive securities. The book strikes a balance between mathematical rigor and the need for economic interpretation of financial market regularities, although with an emphasis on the latter. |
| financial modeling mit press: Computational Finance 1999 Yaser S. Abu-Mostafa, 2000 This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. Computational finance, an exciting new cross-disciplinary research area, draws extensively on the tools and techniques of computer science, statistics, information systems, and financial economics. This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. These methods are applied to a wide range of problems in finance, including risk management, asset allocation, style analysis, dynamic trading and hedging, forecasting, and option pricing. The book is based on the sixth annual international conference Computational Finance 1999, held at New York University's Stern School of Business. |
| financial modeling mit press: Credit Reporting Systems and the International Economy Margaret J. Miller, 2003 The first comprehensive review of credit reporting systems worldwide, including their institutional forms and evidence of their impact on financial markets. Credit reporting is a critical part of the financial system in most developed economies but is often weak or absent in developing countries. It addresses a fundamental problem of credit markets: asymmetric information between borrowers and lenders that can lead to adverse selection and moral hazard. The heart of a credit report is the record it provides of an individual's or a firm's payment history, which enables lenders to evaluate credit risk more accurately and lower loan processing time and costs. Credit reports also strengthen borrower discipline, since nonpayment with one institution results in sanctions with others. This book provides the first comprehensive review of credit reporting systems worldwide and documents the rapid growth in the industry. It offers empirical and theoretical evidence of the impact of credit reporting on financial markets, using examples from both developed and developing economies. Credit reporting, it shows, significantly contributes to predicting default risk of potential borrowers, which promotes increased lending activity. The book also covers the role of public policy in the development of credit reporting initiatives, including the role of public credit registries managed by central banks; and the role of legal, regulatory, and institutional factors in supporting credit reporting. |
| financial modeling mit press: Entrepreneurial Finance and Accounting for High-Tech Companies Frank J. Fabozzi, 2016-11-10 Financial aspects of launching and operating a high-tech company, including risk analysis, business models, U.S. securities law, financial accounting, tax issues, and stock options, explained accessibly. This book offers an accessible guide to the financial aspects of launching and operating a high-tech business in such areas as engineering, computing, and science. It explains a range of subjects—from risk analysis to stock incentive programs for founders and key employees—for students and aspiring entrepreneurs who have no prior training in finance or accounting. The book begins with the rigorous analysis any prospective entrepreneur should undertake before launching a business, covering risks associated with a new venture, the reasons startup companies fail, and the stages of financing. It goes on to discuss business models and their components, business plans, and exit planning; forms of business organization, and factors to consider in choosing one; equity allocation to founders and employees; applicable U.S. securities law; and sources of equity capital. The book describes principles of financial accounting, the four basic financial statements, and financial ratios useful in assessing management performance. It also explains financial planning and the use of budgets; profit planning; stock options and other option-type awards; methodologies for valuing a private company; economic assessment of a potential investment project; and the real options approach to risk and managerial flexibility. Appendixes offer case studies of Uber and of the valuation of Tentex. |
| financial modeling mit press: Designing Financial Systems in Transition Economies Anna Meyendorff, Anjan V. Thakor, 2002 This collection examines the design of financial systems for central and eastern European countries engaged in the transition to market-based economies. It highlights the need for better approaches to measuring performance and providing incentives in banking and for financial mechanisms to encourage private-sector growth. Written by leading European and North American scholars, the essays apply modern finance theory and empirical data to the development of new financial sectors. |
| financial modeling mit press: Principles of Finance with Excel Simon Benninga, 2011 Finance is a topic that requires much computation, and in todayâe(tm)s business world that computation is almost entirely done using Microsoft Excel. Despite this, existing finance textbooks continue to rely heavily on hand calculators, and business school students find that when they leave the academic environment they have to relearn finance using Excel. Addressing this issue, Principles of Finance with Excel is the only introductory finance text that comprehensively integrates Excel into the teaching and practice of finance. The second edition covers the same topics as standard financial textbooks, including portfolios, capital asset pricing models, stock and bond valuation, capital structure, and dividend and optional policy, and can therefore be used in any introductory course. However, this text also introduces Excel as it applies to finance students, demonstrating and explaining the implementation of finance concepts with Excel, and providing thorough coverage of all Excel topics including graphs, function data tables, dates in Excel, Goal Seek, and Solver. Combining classroom-tested pedagogy with the powerful functions of Excel, Simon Benninga, one of the most recognised names in financial modelling, shows students how spreadsheets can provide new and deeper insights into financial decision making. |
| financial modeling mit press: Financial Modelling with Jump Processes Peter Tankov, 2003-12-30 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 mathematic |
| financial modeling mit press: An Engine, Not a Camera Donald MacKenzie, 2008-08-29 In An Engine, Not a Camera, Donald MacKenzie argues that the emergence of modern economic theories of finance affected financial markets in fundamental ways. These new, Nobel Prize-winning theories, based on elegant mathematical models of markets, were not simply external analyses but intrinsic parts of economic processes. Paraphrasing Milton Friedman, MacKenzie says that economic models are an engine of inquiry rather than a camera to reproduce empirical facts. More than that, the emergence of an authoritative theory of financial markets altered those markets fundamentally. For example, in 1970, there was almost no trading in financial derivatives such as futures. By June of 2004, derivatives contracts totaling $273 trillion were outstanding worldwide. MacKenzie suggests that this growth could never have happened without the development of theories that gave derivatives legitimacy and explained their complexities. MacKenzie examines the role played by finance theory in the two most serious crises to hit the world's financial markets in recent years: the stock market crash of 1987 and the market turmoil that engulfed the hedge fund Long-Term Capital Management in 1998. He also looks at finance theory that is somewhat beyond the mainstream—chaos theorist Benoit Mandelbrot's model of wild randomness. MacKenzie's pioneering work in the social studies of finance will interest anyone who wants to understand how America's financial markets have grown into their current form. |
| financial modeling mit press: Probability Models for Economic Decisions, second edition Roger B. Myerson, Eduardo Zambrano, 2019-12-17 An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets. The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk. New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel. |
| financial modeling mit press: Design Structure Matrix Methods and Applications Steven D. Eppinger, Tyson R. Browning, 2012-05-25 An introduction to a powerful and flexible network modeling tool for developing and understanding complex systems, with many examples from a range of industries. Design structure matrix (DSM) is a straightforward and flexible modeling technique that can be used for designing, developing, and managing complex systems. DSM offers network modeling tools that represent the elements of a system and their interactions, thereby highlighting the system's architecture (or designed structure). Its advantages include compact format, visual nature, intuitive representation, powerful analytical capacity, and flexibility. Used primarily so far in the area of engineering management, DSM is increasingly being applied to complex issues in health care management, financial systems, public policy, natural sciences, and social systems. This book offers a clear and concise explanation of DSM methods for practitioners and researchers. |
| financial modeling mit press: FUNDAMENTAL MODELS IN FINANCIAL THEORY Doron Peleg, 2014-04-11 This book provides an innovative, integrated, and methodical approach to understanding complex financial models, integrating topics usually presented separately into a comprehensive whole. The book brings together financial models and high-level mathematics, reviewing the mathematical background necessary for understanding these models organically and in context. It begins with underlying assumptions and progresses logically through increasingly complex models to operative conclusions. Readers who have mastered the material will gain the tools needed to put theory into practice and incorporate financial models into real-life investment, financial, and business scenarios. Modern finance’s most bothersome shortcoming is that the two basic models for building an optimal investment portfolio, Markowitz’s mean-variance model and Sharpe and Treynor’s Capital Asset Pricing Model (CAPM), fall short when we try to apply them using Excel Solver. This book explores these two models in detail, and for the first time in a textbook the Black-Litterman model for building an optimal portfolio constructed from a small number of assets (developed at Goldman Sachs) is thoroughly presented. The model’s integration of personal views and its application using Excel templates are demonstrated. The book also offers innovative presentations of the Modigliani–Miller model and the Consumption-Based Capital Asset Pricing Model (CCAPM). Problems at the end of each chapter invite the reader to put the models into immediate use. Fundamental Models in Financial Theory is suitable for classroom use or as a reference for finance practitioners. |
| financial modeling mit press: Financial Economics Antonio Mele, 2022 Comprehensive overview of the current state of knowledge in financial economics, appropriate for graduate-level research-- |
| financial modeling mit press: Financial Analysis and Modeling Using Excel and VBA Chandan Sengupta, 2009-11-09 An updated look at the theory and practice of financial analysis and modeling Financial Analysis and Modeling Using Excel and VBA, Second Edition presents a comprehensive approach to analyzing financial problems and developing simple to sophisticated financial models in all major areas of finance using Excel 2007 and VBA (as well as earlier versions of both). This expanded and fully updated guide reviews all the necessary financial theory and concepts, and walks you through a wide range of real-world financial problems and models that you can learn from, use for practice, and easily adapt for work and classroom use. A companion website includes several useful modeling tools and fully working versions of all the models discussed in the book. Teaches financial analysis and modeling and illustrates advanced features of Excel and VBA, using a learn-by-doing approach Contains detailed coverage of the powerful features of Excel 2007 essential for financial analysis and modeling, such as the Ribbon interface, PivotTables, data analysis, and statistical analysis Other titles by Sengupta: Financial Modeling Using C++ and The Only Proven Road to Investment Success Designed for self-study, classroom use, and reference This comprehensive guide is an essential read for anyone who has to perform financial analysis or understand and implement financial models. |
| financial modeling mit press: The Economics of Risk and Time Christian Gollier, 2001 Updates and advances the theory of expected utility as applied to risk analysis and financial decision making. |
| financial modeling mit press: Financial Innovation and Risk Sharing Franklin Allen, Douglas Gale, 1994 Franklin Allen and Douglas Gale assemble some of their key papers along with a five-chapter overview that not only synthesizes their work but provides a historical and institutional review and a discussion of alternative approaches as well. |
| financial modeling mit press: Democratizing Innovation Eric Von Hippel, 2006-02-17 The process of user-centered innovation: how it can benefit both users and manufacturers and how its emergence will bring changes in business models and in public policy. Innovation is rapidly becoming democratized. Users, aided by improvements in computer and communications technology, increasingly can develop their own new products and services. These innovating users—both individuals and firms—often freely share their innovations with others, creating user-innovation communities and a rich intellectual commons. In Democratizing Innovation, Eric von Hippel looks closely at this emerging system of user-centered innovation. He explains why and when users find it profitable to develop new products and services for themselves, and why it often pays users to reveal their innovations freely for the use of all.The trend toward democratized innovation can be seen in software and information products—most notably in the free and open-source software movement—but also in physical products. Von Hippel's many examples of user innovation in action range from surgical equipment to surfboards to software security features. He shows that product and service development is concentrated among lead users, who are ahead on marketplace trends and whose innovations are often commercially attractive. Von Hippel argues that manufacturers should redesign their innovation processes and that they should systematically seek out innovations developed by users. He points to businesses—the custom semiconductor industry is one example—that have learned to assist user-innovators by providing them with toolkits for developing new products. User innovation has a positive impact on social welfare, and von Hippel proposes that government policies, including R&D subsidies and tax credits, should be realigned to eliminate biases against it. The goal of a democratized user-centered innovation system, says von Hippel, is well worth striving for. An electronic version of this book is available under a Creative Commons license. |
| financial modeling mit press: What's Your Digital Business Model? Peter Weill, Stephanie Woerner, 2018-04-17 Digital transformation is not about technology--it's about change. In the rapidly changing digital economy, you can't succeed by merely tweaking management practices that led to past success. And yet, while many leaders and managers recognize the threat from digital--and the potential opportunity--they lack a common language and compelling framework to help them assess it and guide them in responding. They don't know how to think about their digital business model. In this concise, practical book, MIT digital research leaders Peter Weill and Stephanie Woerner provide a powerful yet straightforward framework that has been field-tested globally with dozens of senior management teams. Based on years of study at the MIT Center for Information Systems Research (CISR), the authors find that digitization is moving companies' business models on two dimensions: from value chains to digital ecosystems, and from a fuzzy understanding of the needs of end customers to a sharper one. Looking at these dimensions in combination results in four distinct business models, each with different capabilities. The book then sets out six driving questions, in separate chapters, that help managers and executives clarify where they are currently in an increasingly digital business landscape and highlight what's needed to move toward a higher-value digital business model. Filled with straightforward self-assessments, motivating examples, and sharp financial analyses of where profits are made, this smart book will help you tackle the threats, leverage the opportunities, and create winning digital strategies. |
| financial modeling mit press: Financial Modeling Simon Benninga, 2008-01-01 Too often, finance courses stop short of making a connection between textbook financeand the problems of real-world business. Financial Modeling bridges this gapbetween theory and practice by providing a nuts-and-bolts guide to solving common financial modelswith spreadsheets. Simon Benninga takes the reader step by step through each model, showing how itcan be solved using Microsoft Excel. The long-awaited third edition of this standard text maintainsthe cookbook features and Excel dependence that have made the first and second editionsso popular. It also offers significant new material, with new chapters covering such topics as bankvaluation, the Black-Litterman approach to portfolio optimization, Monte Carlo methods and theirapplications to option pricing, and using array functions and formulas. Other chapters, includingthose on basic financial calculations, portfolio models, calculating the variance-covariance matrix,and generating random numbers, have been revised, with many offering substantially new and improvedmaterial. Other areas covered include financial statement modeling, leasing, standard portfolioproblems, value at risk (VaR), real options, duration and immunization, and term structure modeling.Technical chapters treat such topics as data tables, matrices, the Gauss-Seidel method, and tips forusing Excel. The last section of the text covers the Visual Basic for Applications (VBA) techniquesneeded for the book. The accompanying CD contains Excel worksheets and solutions to end-of-chapterexercises. |
| financial modeling mit press: Economics of Global Business Rodrigo Zeidan, 2018-11-13 A textbook with innovative real-world macroeconomic analyses of timely policy issues, with case studies and examples from more than fifty countries. This timely and refreshingly real–world focused textbook examines some of the world's most critical policy issues through a macroeconomics lens. After presenting analytical foundations, modeling tools, and theoretical perspectives, Economics of Global Business goes a step further than most other texts, with a practical look at the local and multinational tradeoffs facing economic policymakers in more than fifty countries. Topics range from income equality and the financial crisis to GDP, inflation and unemployment, and, notably, one of the first macroeconomic examinations of climate change. Written by a globetrotting economist who teaches and consults on three continents, Economics of Global Business aims not for definitive answers but rather to provide a better understanding of the context-dependent rationales, constraints, and consequences of economic policy decisions. The book covers long-run and short-run growth (with examples from the United States, China, the European Union, South Korea, Japan, Latin America, Africa, Australia, and Vietnam); financial crises and central banks; monetary and fiscal policies; government budgets; currency regimes; climate change and macroeconomics; income inequality; and globalization. All chapters rely on recent and historical examples of economic policy in action. The book is particularly suitable for use as an introduction to macroeconomics for business students. |
| financial modeling mit press: Hands-On Financial Modeling with Microsoft Excel 2019 Shmuel Oluwa, 2019-07-11 Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key FeaturesA non data professionals guide to exploring Excel's financial functions and pivot tablesLearn to prepare various models for income and cash flow statements, and balance sheetsLearn to perform valuations and identify growth drivers with real-world case studiesBook Description Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Microsoft Excel 2019 examines various definitions and relates them to the key features of financial modeling with the help of Excel. This book will help you understand financial modeling concepts using Excel, and provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. Starting with the key concepts of Excel, such as formulas and functions, you will learn about referencing frameworks and other advanced components of Excel for building financial models. Later chapters will help you understand your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. The book takes an intuitive approach to model testing, along with best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and you will have the skills you need to build financial models to extract the information required to make informed business decisions. What you will learnIdentify the growth drivers derived from processing historical data in ExcelUse discounted cash flow (DCF) for efficient investment analysisBuild a financial model by projecting balance sheets, profit, and lossApply a Monte Carlo simulation to derive key assumptions for your financial modelPrepare detailed asset and debt schedule models in ExcelDiscover the latest and advanced features of Excel 2019Calculate profitability ratios using various profit parametersWho this book is for This book is for data professionals, analysts, traders, business owners, and students, who want to implement and develop a high in-demand skill of financial modeling in their finance, analysis, trading, and valuation work. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models. The book assumes working knowledge with Excel. |
| financial modeling mit press: Engineering a Safer World Nancy G. Leveson, 2012-01-13 A new approach to safety, based on systems thinking, that is more effective, less costly, and easier to use than current techniques. Engineering has experienced a technological revolution, but the basic engineering techniques applied in safety and reliability engineering, created in a simpler, analog world, have changed very little over the years. In this groundbreaking book, Nancy Leveson proposes a new approach to safety—more suited to today's complex, sociotechnical, software-intensive world—based on modern systems thinking and systems theory. Revisiting and updating ideas pioneered by 1950s aerospace engineers in their System Safety concept, and testing her new model extensively on real-world examples, Leveson has created a new approach to safety that is more effective, less expensive, and easier to use than current techniques. Arguing that traditional models of causality are inadequate, Leveson presents a new, extended model of causation (Systems-Theoretic Accident Model and Processes, or STAMP), then shows how the new model can be used to create techniques for system safety engineering, including accident analysis, hazard analysis, system design, safety in operations, and management of safety-critical systems. She applies the new techniques to real-world events including the friendly-fire loss of a U.S. Blackhawk helicopter in the first Gulf War; the Vioxx recall; the U.S. Navy SUBSAFE program; and the bacterial contamination of a public water supply in a Canadian town. Leveson's approach is relevant even beyond safety engineering, offering techniques for “reengineering” any large sociotechnical system to improve safety and manage risk. |
| financial modeling mit press: Financial Modeling in Excel For Dummies Danielle Stein Fairhurst, 2017-04-24 Make informed business decisions with the beginner's guide to financial modeling using Microsoft Excel Financial Modeling in Excel For Dummies is your comprehensive guide to learning how to create informative, enlightening financial models today. Not a math whiz or an Excel power-user? No problem! All you need is a basic understanding of Excel to start building simple models with practical hands-on exercises and before you know it, you'll be modeling your way to optimized profits for your business in no time. Excel is powerful, user-friendly, and is most likely already installed on your computer—which is why it has so readily become the most popular financial modeling software. This book shows you how to harness Excel's capabilities to determine profitability, develop budgetary projections, model depreciation, project costs, value assets and more. You'll learn the fundamental best practices and know-how of financial modeling, and how to put them to work for your business and your clients. You'll learn the tools and techniques that bring insight out of the numbers, and make better business decisions based on quantitative evidence. You'll discover that financial modeling is an invaluable resource for your business, and you'll wonder why you've waited this long to learn how! Companies around the world use financial modeling for decision making, to steer strategy, and to develop solutions. This book walks you through the process with clear, expert guidance that assumes little prior knowledge. Learn the six crucial rules to follow when building a successful financial model Discover how to review and edit an inherited financial model and align it with your business and financial strategy Solve client problems, identify market projections, and develop business strategies based on scenario analysis Create valuable customized templates models that can become a source of competitive advantage From multinational corporations to the mom-and-pop corner store, there isn't a business around that wouldn't benefit from financial modeling. No need to buy expensive specialized software—the tools you need are right there in Excel. Financial Modeling in Excel For Dummies gets you up to speed quickly so you can start reaping the benefits today! |
| financial modeling mit press: Empirical Asset Pricing Wayne Ferson, 2019-03-12 An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals. |
| financial modeling mit press: Boom and Bust William Quinn, John D. Turner, 2020-08-06 Why do stock and housing markets sometimes experience amazing booms followed by massive busts and why is this happening more and more frequently? In order to answer these questions, William Quinn and John D. Turner take us on a riveting ride through the history of financial bubbles, visiting, among other places, Paris and London in 1720, Latin America in the 1820s, Melbourne in the 1880s, New York in the 1920s, Tokyo in the 1980s, Silicon Valley in the 1990s and Shanghai in the 2000s. As they do so, they help us understand why bubbles happen, and why some have catastrophic economic, social and political consequences whilst others have actually benefited society. They reveal that bubbles start when investors and speculators react to new technology or political initiatives, showing that our ability to predict future bubbles will ultimately come down to being able to predict these sparks. |
| financial modeling mit press: Adaptive Markets Andrew W. Lo, 2019-05-14 A new, evolutionary explanation of markets and investor behavior Half of all Americans have money in the stock market, yet economists can’t agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe. The debate is one of the biggest in economics, and the value or futility of investment management and financial regulation hangs on the answer. In this groundbreaking book, Andrew Lo transforms the debate with a powerful new framework in which rationality and irrationality coexist—the Adaptive Markets Hypothesis. Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency is incomplete. When markets are unstable, investors react instinctively, creating inefficiencies for others to exploit. Lo’s new paradigm explains how financial evolution shapes behavior and markets at the speed of thought—a fact revealed by swings between stability and crisis, profit and loss, and innovation and regulation. An ambitious new answer to fundamental questions about economics and investing, Adaptive Markets is essential reading for anyone who wants to understand how markets really work. |
| financial modeling mit press: Market Design Guillaume Haeringer, 2018-03-02 A broad overview of market mechanisms, with an emphasis on the interplay between theory and real-life applications; examples range from eBay auctions to school choice. This book offers an introduction to market design, providing students with a broad overview of issues related to the design and analysis of market mechanisms. It defines a market as a demand and a supply, without specifying a price system or mechanism. This allows the text to analyze a broad set of situations—including such unconventional markets as college admissions and organ donation—and forces readers to pay attention to details that might otherwise be overlooked. Students often complain that microeconomics is too abstract and disconnected from reality; the study of market design shows how theory can help solve existing, real-life problems. The book focuses on the interplay between theory and applications. To keep the text as accessible as possible, special effort has been made to minimize formal description of the models while emphasizing the intuitive, with detailed explanations and resolution of examples. Appendixes offer general reviews of elements of game theory and mechanism design that are related to the themes explored in the book, presenting the basic concepts with as many explanations and illustrations as possible. The book covers topics including the basics of simple auctions; eBay auctions; Vickrey–Clarke–Groves auctions; keyword auctions, with examples from Google and Facebook; spectrum auctions; financial markets, with discussions of treasury auctions and IPOs; trading on the stock market; the basic matching model; medical match; assignment problems; probabilistic assignments; school choice; course allocation, with examples from Harvard and Wharton; and kidney exchange. |
| financial modeling mit press: Modeling Financial Time Series with S-PLUS Eric Zivot, Jiahui Wang, 2013-11-11 The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the 2000 Outstanding Scholars of the 21st Century by International Biographical Centre. |
| financial modeling mit press: Semi-Supervised Learning Olivier Chapelle, Bernhard Scholkopf, Alexander Zien, 2010-01-22 A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems: state-of-the-art algorithms, a taxonomy of the field, applications, benchmark experiments, and directions for future research. In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in which all training examples are labeled) and unsupervised learning (in which no label data are given). Interest in SSL has increased in recent years, particularly because of application domains in which unlabeled data are plentiful, such as images, text, and bioinformatics. This first comprehensive overview of SSL presents state-of-the-art algorithms, a taxonomy of the field, selected applications, benchmark experiments, and perspectives on ongoing and future research.Semi-Supervised Learning first presents the key assumptions and ideas underlying the field: smoothness, cluster or low-density separation, manifold structure, and transduction. The core of the book is the presentation of SSL methods, organized according to algorithmic strategies. After an examination of generative models, the book describes algorithms that implement the low-density separation assumption, graph-based methods, and algorithms that perform two-step learning. The book then discusses SSL applications and offers guidelines for SSL practitioners by analyzing the results of extensive benchmark experiments. Finally, the book looks at interesting directions for SSL research. The book closes with a discussion of the relationship between semi-supervised learning and transduction. |
| financial modeling mit press: Healthcare Finance Andrew W. Lo, Shomesh E. Chaudhuri, 2022-11-15 Why healthcare finance? -- From the laboratory to the patient -- Present value relations -- Evaluating business opportunities -- Valuing bonds -- Valuing stocks -- Portfolio management and the cost of capital -- Therapeutic development and clinical trials -- Decision trees and real options -- Monte Carlo simulation -- Healthcare analytics -- Biotech venture capital -- Securitizing biomedical assets -- Pricing, value, and ethics -- Epilogue : a case study pf royalty pharma. |
| financial modeling mit press: Principles of Financial Modelling Michael Rees, 2018-03-19 The comprehensive, broadly-applicable, real-world guide to financial modelling Principles of Financial Modelling – Model Design and Best Practices Using Excel and VBAcovers the full spectrum of financial modelling tools and techniques in order to provide practical skills that are grounded in real-world applications. Based on rigorously-tested materials created for consulting projects and for training courses, this book demonstrates how to plan, design and build financial models that are flexible, robust, transparent, and highly applicable to a wide range of planning, forecasting and decision-support contexts. This book integrates theory and practice to provide a high-value resource for anyone wanting to gain a practical understanding of this complex and nuanced topic. Highlights of its content include extensive coverage of: Model design and best practices, including the optimisation of data structures and layout, maximising transparency, balancing complexity with flexibility, dealing with circularity, model audit and error-checking Sensitivity and scenario analysis, simulation, and optimisation Data manipulation and analysis The use and choice of Excel functions and functionality, including advanced functions and those from all categories, as well as of VBA and its key areas of application within financial modelling The companion website provides approximately 235 Excel files (screen-clips of most of which are shown in the text), which demonstrate key principles in modelling, as well as providing many examples of the use of Excel functions and VBA macros. These facilitate learning and have a strong emphasis on practical solutions and direct real-world application. For practical instruction, robust technique and clear presentation, Principles of Financial Modelling is the premier guide to real-world financial modelling from the ground up. It provides clear instruction applicable across sectors, settings and countries, and is presented in a well-structured and highly-developed format that is accessible to people with different backgrounds. |
| financial modeling mit press: Principles of Model Checking Christel Baier, Joost-Pieter Katoen, 2008-04-25 A comprehensive introduction to the foundations of model checking, a fully automated technique for finding flaws in hardware and software; with extensive examples and both practical and theoretical exercises. Our growing dependence on increasingly complex computer and software systems necessitates the development of formalisms, techniques, and tools for assessing functional properties of these systems. One such technique that has emerged in the last twenty years is model checking, which systematically (and automatically) checks whether a model of a given system satisfies a desired property such as deadlock freedom, invariants, and request-response properties. This automated technique for verification and debugging has developed into a mature and widely used approach with many applications. Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field. The book begins with the basic principles for modeling concurrent and communicating systems, introduces different classes of properties (including safety and liveness), presents the notion of fairness, and provides automata-based algorithms for these properties. It introduces the temporal logics LTL and CTL, compares them, and covers algorithms for verifying these logics, discussing real-time systems as well as systems subject to random phenomena. Separate chapters treat such efficiency-improving techniques as abstraction and symbolic manipulation. The book includes an extensive set of examples (most of which run through several chapters) and a complete set of basic results accompanied by detailed proofs. Each chapter concludes with a summary, bibliographic notes, and an extensive list of exercises of both practical and theoretical nature. |
| financial modeling mit press: Representation in Scientific Practice Revisited Catelijne Coopmans, Janet Vertesi, Michael E. Lynch, Steve Woolgar, 2014-01-03 A fresh approach to visualization practices in the sciences that considers novel forms of imaging technology and draws on recent theoretical perspectives on representation. Representation in Scientific Practice, published by the MIT Press in 1990, helped coalesce a long-standing interest in scientific visualization among historians, philosophers, and sociologists of science and remains a touchstone for current investigations in science and technology studies. This volume revisits the topic, taking into account both the changing conceptual landscape of STS and the emergence of new imaging technologies in scientific practice. It offers cutting-edge research on a broad array of fields that study information as well as short reflections on the evolution of the field by leading scholars, including some of the contributors to the 1990 volume. The essays consider the ways in which viewing experiences are crafted in the digital era; the embodied nature of work with digital technologies; the constitutive role of materials and technologies—from chalkboards to brain scans—in the production of new scientific knowledge; the metaphors and images mobilized by communities of practice; and the status and significance of scientific imagery in professional and popular culture. Contributors Morana Alač, Michael Barany, Anne Beaulieu, Annamaria Carusi, Catelijne Coopmans, Lorraine Daston, Sarah de Rijcke, Joseph Dumit, Emma Frow, Yann Giraud, Aud Sissel Hoel, Martin Kemp, Bruno Latour, John Law, Michael Lynch, Donald MacKenzie, Cyrus Mody, Natasha Myers, Rachel Prentice, Arie Rip, Martin Ruivenkamp, Lucy Suchman, Janet Vertesi, Steve Woolgar |
| financial modeling mit press: Financial Modeling, fourth edition Simon Benninga, 2014-04-18 A substantially revised edition of a bestselling text combining explanation and implementation using Excel; for classroom use or as a reference for finance practitioners. Financial Modeling is now the standard text for explaining the implementation of financial models in Excel. This long-awaited fourth edition maintains the “cookbook” features and Excel dependence that have made the previous editions so popular. As in previous editions, basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds are explained with detailed Excel spreadsheets. Sections on technical aspects of Excel and on the use of Visual Basic for Applications (VBA) round out the book to make Financial Modeling a complete guide for the financial modeler. The new edition of Financial Modeling includes a number of innovations. A new section explains the principles of Monte Carlo methods and their application to portfolio management and exotic option valuation. A new chapter discusses term structure modeling, with special emphasis on the Nelson-Siegel model. The discussion of corporate valuation using pro forma models has been rounded out with the introduction of a new, simple model for corporate valuation based on accounting data and a minimal number of valuation parameters. New print copies of this book include a card affixed to the inside back cover with a unique access code. Access codes are required to download Excel worksheets and solutions to end-of-chapter exercises. If you have a used copy of this book, you may purchase a digitally-delivered access code separately via the Supplemental Material link on this page. If you purchased an e-book, you may obtain a unique access code by emailing digitalproducts-cs@mit.edu or calling 617-253-2889 or 800-207-8354 (toll-free in the U.S. and Canada). Praise for earlier editions “Financial Modeling belongs on the desk of every finance professional. Its no-nonsense, hands-on approach makes it an indispensable tool.” —Hal R. Varian, Dean, School of Information Management and Systems, University of California, Berkeley “Financial Modeling is highly recommended to readers who are interested in an introduction to basic, traditional approaches to financial modeling and analysis, as well as to those who want to learn more about applying spreadsheet software to financial analysis. —Edward Weiss, Journal of Computational Intelligence in Finance “Benninga has a clear writing style and uses numerous illustrations, which make this book one of the best texts on using Excel for finance that I've seen.” —Ed McCarthy, Ticker Magazine |
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