Book Image

Hands-On Financial Modeling with Microsoft Excel 2019

By : Shmuel Oluwa
Book Image

Hands-On Financial Modeling with Microsoft Excel 2019

By: Shmuel Oluwa

Overview of this book

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 explores terminologies of financial modeling with the help of Excel. This book will 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 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 and covers best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and have the skills you need to build financial models to extract the information required to make informed business decisions.
Table of Contents (15 chapters)
Free Chapter
Section 1: Financial Modeling - Overview
Section 2: The Use of Excel - Features and Functions for Financial Modeling
Section 3: Building an Integrated Financial Model

Model Testing for Reasonableness and Accuracy

Preparing a financial model involves a lot of assumptions and subjective decisions. In order to reduce the effects of this subjectivity as much as possible, you will need to adopt certain procedures, some of which we have already mentioned, and carry out certain tests designed to highlight the most volatile assumptions and pay direct attention to those inputs to which the model is most sensitive.

In this chapter, we will cover the following topics:

  • Incorporating built-in tests and procedures
  • Troubleshooting
  • Understanding sensitivity analysis
  • Using direct and indirect methods
  • Understanding scenario analysis
  • Creating a simple Monte Carlo simulation model