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Editorial ReviewsFrom 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 Research
Gutenberg 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.
The 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.
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