Financial Modeling

Author: Simon Benninga

Publisher: MIT Press

ISBN:

Category: Business & Economics

Page: 1144

View: 762

A substantially revised edition of a bestselling text combining explanation and implementation using Excel; for classroom use or as a reference for finance practitioners.

Exct Worksheets and Solutions to Exercises to Accompany Financial Modelling 4e, Access Card

Author: Simon Benninga

Publisher:

ISBN:

Category: Business & Economics

Page:

View: 696

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.

Financial Models and Society

Villains or Scapegoats?

Author: Ekaterina Svetlova

Publisher: Edward Elgar Publishing

ISBN:

Category: Business & Economics

Page: 192

View: 181

This innovative book employs the social studies of finance approach which aims to enhance the dialogue between finance and sociology by addressing the blind spots of economic and financial theories. In so doing, it challenges the accusations made towards financial models in the aftermath of the last economic crisis and argues that they cannot be condemned indiscriminately. Their influence on markets and society is not straightforward, but determined by the many ways in which models are created and then used. Ekaterina Svetlova analyses the various patterns of the application of models in asset management, risk management and financial engineering to demonstrate that their power is far more fragile than widespread criticism would indicate.

Financial Modeling Under Non-Gaussian Distributions

Author: Eric Jondeau

Publisher: Springer Science & Business Media

ISBN:

Category: Mathematics

Page: 541

View: 835

This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.

World Economic Outlook, October 2001

The Information Technology Revolution

Author: International Monetary Fund. Research Dept.

Publisher: International Monetary Fund

ISBN:

Category: Business & Economics

Page: 296

View: 255

The World Economic Outlook, published twice a year in English, French, Spanish, and Arabic, presents IMF staff economists' analyses of global economic developments during the near and medium term. Chapters give an overview of the world economy; consider issues affecting industrial countries, developing countries, and economies in transition to market; and address topics of pressing current interest. Annexes, boxes, charts, and an extensive statistical appendix augment the text.

Modeling Techniques in Predictive Analytics

Business Problems and Solutions with R, Revised and Expanded Edition

Author: Thomas W. Miller

Publisher: FT Press

ISBN:

Category: Computers

Page: 384

View: 647

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

Modeling Techniques in Predictive Analytics with Python and R

A Guide to Data Science

Author: Thomas W. Miller

Publisher: FT Press

ISBN:

Category: Computers

Page: 448

View: 576

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

The Oxford Guide to Financial Modeling

Applications for Capital Markets, Corporate Finance, Risk Management and Financial Institutions

Author: Thomas S. Y. Ho

Publisher: Oxford University Press on Demand

ISBN:

Category: Business & Economics

Page: 735

View: 706

Presents the financial models of stock and bond options, exotic options, investment-grade and high-yield bonds, convertible bonds, mortgage-backed securities, credit derivatives, liabilities of financial institutions, the business model, and the corporate model. It also describes the applications of the models to corporate finance and relates the models to fair value accounting, enterprise risk management, and asset/liability management with illiquid instruments. Each chapter introduces a practical problem and then the financial models that provide the business solutions.

المؤمن الصادق

أفكار حول طبيعة الحركات الجماهيرية

Author: اريك هوفر

Publisher: العبيكان للنشر

ISBN:

Category: Psychology

Page: 319

View: 300

قالت (وول ستريت جورنال): «إذا أردتَ معلوماتٍ صحيحة مختصرة عن الدوافع التي تعمل في عقول المتعصبين وعن آليات الحركات الجماهيرية في أشد مستوياتها البدائية فأقترح عليك أن تقرأ هذا الكتاب». - بينما كان إريك هوفر يعمل على أرصفة تحميل السفن وتفريغها في سان فرانسيسكو في الأربعينيات من القرن الماضي كان يشغل وقت فراغه في كتابة البحوث الفلسفية، وهذا الكتاب (المؤمن الصادق) هو أول كتبه وأهمها، وقد قفز إلى قائمة أفضل الكتب مبيعاً، عندما استشهد به الرئيس أيزنهاور في إحدى ندواته التلفزيونية. إن الكتاب لا يزال منسجماً تمام الانسجام مع ظروف العالم اليوم، وهو وضروري لفهم مجريات الأحداث فيه؛ إذ يقدم صورة مثيرة للعقل المتعصب، ودراسة عميقة للطريقة التي يتحول بها الإنسان ليصبح متطرفاً. العبيكان للنشر