Financial Modeling For Equity Research: A Step-by-Step Guide to Earnings Modeling by John Moschella CFA CPA, John Moschella CFA CPA

This book demonstrates step-by-step how to create a financial model. The accompanying Excel files demonstrate the key concepts and can be used as templates to create an earning model for nearly any company. Readers without prior financial analysis experience will gain a fundamental understanding of exactly what modeling entails, and will learn how to create a basic form of an earnings model. Advanced readers will be introduced to more complex topics such as linking the financial statements, future period calibration, and incorporating macroeconomic variables into discounted valuation analysis through the equity risk premium and application of the capital asset pricing model. The Excel templates included with this book include: ? File 1 - Blank Model Template: Use this template to create your own earnings model. ? File 2 - Apple Inc Back of the Envelope Model: This beginner model features a basic Income Statement projection and is perfect for those who have not had prior modeling experience. ? File 3 - Apple Inc Tier 2 Earnings Model: This version of the model is more sophisticated and includes a breakdown of the company's products, which is used to project future earnings. ? File 4 - Apple Inc Tier 1 Earnings Model: The Tier 1 model is geared toward advanced analysts and includes financial statement integration, as well as a discounted cash flow valuation. ? File 5 - Equity Risk Premium (ERP) Model: Using this simple model you can quickly estimate the market ERP based on volatility, changes in interest rates, and market return expectations. You can then derive a discount rate using your ERP estimate, and the Capital Asset Pricing Model (CAPM). ? File 6 - Apple Inc Beta Calculation: This file demonstrates the calculation of beta, using an Excel-based regression. ? Files 7&8 - Regression Models: The final two files demonstrate how to run regression analysis to project inputs which could be incorporated into your earnings models. This book is well suited for... Business Students: Whether you are majoring in Finance, Accounting, Marketing, Entrepreneurship, or Management, learning the fundamentals of forecasting is critical to your academic development, and will help prepare you for a professional career. Sell-Side Equity Research Analysts: Need a fresh perspective for your models? Consider adding changes in volatility, interest rates, or corporate tax reform to your valuation approach. Or incorporate non-GAAP adjustments, and forecast the impact of new accounting standards into your models. Financial Planners and Wealth Management Professionals: Have your clients been asking your opinion of a stock in the headlines? This book will teach you how to build a model for nearly any company, allowing you to deliver comprehensive analysis to your clients. Buy-Side Analysts: Want a consensus-based model to compare to that of each analyst? This book demonstrates how to create one, and how to use it to perform quick reviews of consensus estimates, management's guidance, and run powerful scenario analysis ahead of an earnings release. Investor Relations Professionals: Gain valuable insight into how the analysts covering your company are modeling your results, and use this knowledge to predict what the analysts will ask on the conference calls. Private Equity/Venture Capital Analysts: Trying to value a new investment with unpredictable cash flows? Use this book as a guide to build a dynamic model, and incorporate various inputs to create upside/downside scenarios. ...as well as anyone else interested in learning how to use fundamental analysis to review an equity security's future prospects. Editorial Reviews From the Author Equity research is a difficult field, with a steep learning curve for new associates. The hours are long, clients are demanding, and modeling errors are unacceptable. When I first joined the semiconductor research team at a New York-based investment bank I struggled with the workload. Between the 100 hour workweeks during earnings season, getting up-to-speed with the fundamentals of a highly technical industry, and studying for the FINRA exams, there was no additional time to learn the basics of the day-to-day tasks, most importantly how to model a company's earnings.Most senior research analysts have little time for training, so new associates tend to teach themselves, as I did, by reverse-engineering their team's models. I wrote this book and designed the Excel templates as resources for new associates to assist in the financial modeling learning process. This book is based on my experience as a Sell-Side Research Associate, with input from the quantitative methods I used as a Risk Analyst, and a unique consideration of financial reporting from my time as a Public Accountant. The methods covered are primarily geared toward sell-side earnings modeling, however, many of the topics are also applicable to careers in investment banking, asset management, or any other field which requires knowledge of forecasting or valuation.Remember modeling is part science and part art. The chapters to follow describe the modeling approach I use in practice. There are many different methods, variations, and techniques you can use to forecast earnings. If you have prior modeling experience, feel free to incorporate your own spin on the steps as you work through each section. If you are new to modeling, you may find some of the concepts difficult at first, but if you follow each step you will be able to build an earnings model for nearly any company. About the Author John has more than a decade of experience analyzing companies in various capacities. After earning a BSBA in Finance, MS in Accounting and MBA from Northeastern University, he began his professional career at PricewaterhouseCoopers (PwC) in New York as an Assurance Associate in the Financial Services practice. He also participated in a rotational assignment in the Financial Service Research Institute at PwC where he studied bank mergers during the financial crisis.After PwC, John spent five years at UBS Investment Bank where he worked first as a Capital Specialist, and then as an Equity Research Associate. In his research role, he maintained earnings models for companies in the Semiconductor and Semiconductor Equipment Industries, contributed to research reports, and participated in investor conferences.John moved to General Electric Capital Corp in early 2014 as a Lead Risk Analyst where he built regression models to predict asset losses based on various macroeconomic scenarios. After the sale of the majority of GE Capital's assets, John started a consulting firm which provides capital planning support to investment banks, in addition to running Gutenberg Research.About Gutenberg ResearchGutenberg Research is a web-based, interactive earnings modeling community, which provides professional analysis based on modern portfolio theory and fundamental valuation techniques, with the mission of making earnings models available to all investors.ÂThe Gutenberg name and philosophy are inspired by the fifteenth century visionary and inventor of the printing press, Johannes Gutenberg. Gutenberg's press forever altered the state of communication and flow of information through the mass production of books, changing literacy from a luxury of an elite few, to a right of the masses. The Gutenberg Research community is building an inventory of models which all investors can access for free.