Financial Modeling (Coursera)

In this course you will learn how to build for your project a financial model with all reports and ratios that used in project finance. We will go through the path from a blank Excel workbook, discuss the best practice for financial modeling, dig into technical and financial aspects of the methods and ratios that we use in the model. Within the course we will work with a typical project finance model, but this model has a wide range of possible applications. The same structure and principles could be used for any project to create a new business, launch a product or for venture investments. You will see that the approach we use is universal and the model we build in the course can be your template for many future projects.

The course is aimed at students with some experience in Excel. We will not be learning the basics of spreadsheets or MS Excel interface, but all special functions and services will be presented and explained before we use them in our model. All stages the development of the model will be supplemented with Excel files, so by the end of the course you will have both new skills and ready professional financial models. During the last week of the course you will develop your capstone project – your own financial model.

Course 3 of 3 in the Quantitative Finance Specialization

Syllabus

WEEK 1

Introduction and general principles

Financial modeling process covers many issues related to the content of your model: forecasts, costs, investments, reports, and charts. During the work your attention will be focused on this data, and meantime the model will be generating thousands of cells with numbers and ratios, going through revisions and even being passed from one analyst to another. You should adhere commonly accepted rules and approaches to keep your model error-free, neat, and transparent. By the end of this module you will be able to setup your first model and add some elements that will serve as building blocks for the content for the model.

WEEK 2

Assumptions.

It is your assumptions that define reliability of your analysis, so the assumptions are one of the most important parts of a model. They fulfil two roles: provide data for the calculations and reports and link the model with research and analysis supporting your forecast. Every project is unique; there is no standard template for assumptions that fits them all. By the end of this module you will be able to create correct and transparent model for expected sales, costs, and CAPEX of a project.

WEEK 3

Reports and financing.

Financial reports help you present the projects in a standardized form which makes all communications with investors and partners easier and faster. By the end of this module you will be able to work with three main financial reports and understand relations between project assumptions and those reports, choose a target capital structure, model a loan and generate an acceptable schedule to repay the loan.

WEEK 4

Analysis and presentation.

Discounted cash flow analysis is a vital part of financial models for any capital investment – therefore the whole model is often called DCF model. Now, when we have a complete forecast of our project, we are ready to answer the key question – is it profitable?

However, one answer for one scenario is not enough. No project goes exactly as it was planned. In the model, we describe not certain future cash flows, but just a scenario that we believe is the most probable outcome of the project. Life can change these chances, and other participants of the project can see those scenarios differently. By the end of this module you will be able to calculate such important indicators as NPV or IRR, as well as to analyze the income expected beyond the range of your model, perform a fully-fledged what-if analysis and present a broad range of possible scenarios in one model.

WEEK 5

Capstone project.

This capstone project module will give you a taste of what financial analysts go through in real life when developing a financial model. You will choose a real or fictious project, collect necessary data and build a model from a template provided here. Finally, you will be required to submit your model for peer evaluation.