Best Books on Financial Modelling

Financial Modeling by Simon Benninga

Financial Modeling by Simon Benninga

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 models with spreadsheets. Simon Benninga takes the reader step by step through each model, showing how it can be solved using Microsoft Excel. The long-awaited third edition of this standard text maintains the "cookbook" features and Excel dependence that have made the first and second editions so popular. It also offers significant new material, with new chapters covering such topics as bank valuation, the Black-Litterman approach to portfolio optimization, Monte Carlo methods and their applications to option pricing, and using array functions and formulas. Other chapters, including those on basic financial calculations, portfolio models, calculating the variance-covariance matrix, and generating random numbers, have been revised, with many offering substantially new and improved material. Other areas covered include financial statement modeling, leasing, standard portfolio problems, 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 for using Excel. The last section of the text covers the Visual Basic for Applications (VBA) techniques needed for the book. The accompanying CD contains Excel worksheets and solutions to end-of-chapter exercises.

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Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level (The Wiley Finance Series) by Michael Rees

Financial Modelling in Practice

Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level is a practical, comprehensive and in-depth guide to financial modelling designed to cover the modelling issues that are relevant to facilitate the construction of robust and readily understandable models.

Based on the authors extensive experience of building models in business and finance, and of training others how to do so this book starts with a review of Excel functions that are generally most relevant for building intermediate and advanced level models (such as Lookup functions, database and statistical functions and so on).  It then discusses the principles involved in designing, structuring and building relevant, accurate and readily understandable models (including the use of sensitivity analysis techniques) before covering key application areas, such as the modelling of financial statements, of cash flow valuation, risk analysis, options and real options. Finally, the topic of financial modelling using VBA is treated. Practical examples are used throughout and model examples are included in the attached CD-ROM.

Aimed at intermediate and advanced level modellers in Excel who wish to extend and consolidate their knowledge, this book is focused, practical, and application-driven, facilitating knowledge to build or audit a much wider range of financial models.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $39 (Regular $57)
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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.