Building Financial Models - Book Review

John Tjia’s Building Financial Models is the book if you’d like to learn how to create an integrated financial statement projection model. Not just a spreadsheet for financial calculations and analysis but one where the income statement, the balance sheet and cash flow statement are interconnected using Excel formulae.

Tija’s book covers important areas of financial modeling with the following chapters:

  • Financial projection model
  • Best Practices
  • Setting the stage
  • Accounting for modeling
  • The Model building toolbox: F keys and ranges
  • The Model building toolbox: functions
  • Building a pilot model
  • Circular references and iterative calculations
  • Variations on balancing plugs
  • Preparing to build a full model
  • Building an integrated model: Part 1
  • The cash flow statement
  • The cash sweep
  • Ratios
  • Forecasting guidelines
  • Discounted cash flow valuations
  • Introduction to Visual Basic Applications
  • A VBA primer
  • Tips and Tricks

This book will help you build a fluid financial projection model that is user friendly and sound technically. The concepts and tools in this book will help you develop custom models for a company of any size. you can also input values to test the model for sensitivity analysis.

Tjia is a financial modeler with prior experience as credit analyst and investment manager at J.P. Morgan and Co. It was there that he developed the first personal computer based projection and valuation models. He has developed models for credit, merger, leveraged buyouts, bank and project finance analysis. He has also trained several analysts in financial modeling as the head of J.P.Morgan’s Models Group.

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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.