Chapter 1 For Whom? Why? And How?

      I wrote this book for equity fundamental analysts and portfolio managers, present and future. I am addressing the reader directly: I am talking to you, the investor who is deeply in the weeds of the industry and the companies you cover, investigating possible mispricings or unjustified divergences in valuation between two companies. You, the reader, are obsessed with your work and want to be better at it. If you are reading this, and think, that's me!, rest assured: yes, it's probably you. You were the undergraduate in Chemical Engineering from Toronto who went from a summer job at a liquor store to founding an $8B hedge fund. The deeply thoughtful Norwegian pension fund manager who kept extending our meeting asking questions. The successful energy portfolio manager who interviewed me for my first hedge fund job, and the new college graduate from a large state university in Pennsylvania taking a job as an associate in a financials team.

I imagine that these readers are at different stages in their careers. Since the companies they cover are fundamentally different, they do think in different ways. But they all share a feature: they all have valuable trading ideas but realize that having good ideas is useless without the knowledge of how to turn them into money. This is the objective of portfolio construction and risk management: how to put together a portfolio of holdings that will be profitable over time and will survive adversities. This book is a short, incomplete guide toward investment enlightenment.

      There is a second group of readers who will benefit from this book: the quantitative researchers who are, more and more, essential members of fundamental teams. There is not a strict separation between PMs and quantitative researchers. The quantitive researchers will find the appendix useful, if they want to implement programmatically the advanced tools the book describes.

1.1 What You Will Find Here

      The book introduces a few themes, and then revisits them by adding details. You will learn how to:

      The approach I follow is to offer recommendations and best practices that are motivated by theory and confirmed by empirical evidence and successful practice. While I rely heavily on the framework of factor modeling, I believe that even a reader who does not currently have access to a risk model can still get a lot out of it. Day-to-day, several portfolio managers run very successful books without checking their factor risk decomposition every minute. The reason is that they have converted insights into effective heuristics. Wherever I can, I will flesh out these rules of thumb, and explain how and when they work.

1.2 Asterisks; Or, How to Read This Book

      The mathematical requirements are minimal. Having taken an introductory course in Statistics should give the tools necessary to follow the text. Different readers have different objectives. Some want to get the gist of a book. Time is precious, only the thesis matters, its defense doesn't. Gettysburg Address: This new nation was conceived in Liberty, and dedicated to the proposition that all men are created equal. Hamlet: revenge is a futile pursuit. Moby Dick: please, don't hunt whales. To the CliffsNotes-oriented reader, to the secret agent perusing a book between Martinis: there is hope. Just read the sections that are not marked by a “

      If you always collect all the trophies when playing a video game, or if you felt compelled to finish War and Peace in high school and didn't regret it: please read all the chapters and sections marked by “

1.3 Acknowledgments

I thank Qontigo (formerly Axioma) for making available its US risk model; special thanks to Chris Canova and Sebastian Ceria. Samantha Enders, Purvi Patel, and Bill Falloon at Wiley guided the book composition from the first phone call to its publication. The following people read the book and provided corrections and feedback: Ashish Bajpai, Victor Bomers, Omer Cedar, Phil Durand, François Drouin, Ross Fabricant, Tom Fleming, Izabella Goldenberg, Ernesto Guridi, Dimitrios Margaritis, Chris Martin, Michael Medeiros, Gurraj Singh Sangha, Ashutosh Singh, David Stemerman, Thomas Twiggs, Davide Vetrale, and Bernd Wuebben. I also owe much to people with whom I discussed – and from whom I learned about – several of these topics. Although they are too many to mention them all, Ravi Aggarwal, Brandon Haley, Gustav Rydbeck, Fabian Blohm, Costis Maglaras, Sai Muthialu, Vishal Soni and Samer Takriti, and, again, Sebastian Ceria have taught me most of what I know. All remaining errors are mine.