When you subscribed to OSAM Blog & Research, we promised to only send the best content that is worthy of your time. To level set, below is our Investor Curriculum. We believe these pieces, some old, some new, are foundational for new and seasoned investors alike.
Rather than spew out a cookie-cutter curriculum of Buffet, Graham, and Lynch (which are all excellent, and should be read), we want to take your investment muscles out for a jog. We hope that most of these are new reads for you.
The topics range from risk to creative destruction. We believe these topics are crucial to investing for the long-term benefit of our clients. If there is anything we missed, we would love suggestions and feedback.
Enjoy!
The OSAM Research Team
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Business Drivers:
Behind (almost) every stock is an actual business. Characteristics, factors, and metrics capture the cumulative behaviors and actions of management teams, customers, suppliers, and non-market forces. To understand business, we turn to some excellent entrepreneurs and operators for insight:
Why You Should Find Product Market Fit Before Sniffing Around for Venture Money
(podcast alternative)
Andy Rachleff
Amazon.com 1997 Letter to Shareholders
Jeff Bezos
Constellation Software, Inc. 2015 Shareholder Letter
Mark Leonard
The Outsiders: Eight Unconventional CEOs and Their Radically Rational Blueprint for Success
William Thorndike
Competitive Advantage & Capital Allocation
(podcast alternative)
Pat Dorsey
Building Modern Monopolies
Alex Moazed
Evaluating a Business:
Investing is all about creating meaningful assessments that differ from consensus. These pieces explore the dynamics of profitability, operating leverage, and financial leverage in the context of the perpetual force of reversion to the mean.
The Base Rate Book: Integrating the Past to Better Anticipate the Future
Michael Maubbousin
What You Learn About Business After 12,000 Deals Reviewed, 1,500 Deep Dives, 125 Site Visits, and 7 Portfolio Companies
Brent Beshore
Tim Cook’s Dashboard: Data Science in Business and Investing
Michael Recce
7 Powers: The Foundations of Business Strategy
Hamilton Helmer
Creative Destruction:
Marc Andreesen has been on the forefront of innovation for decades. In a 2006 WSJ op-ed piece, he penned a missive that would serve as his firm’s core investing philosophy. It is remarkable for its prescience and clarity. We have since seen Software Eat The World in multiple industries: autos, retail, and oil and gas, to name a few.
Why Software is Eating the World
Marc Andreesen
Peter Thiel, the storied founder of PayPal and Palantir, and an early Facebook investor, has a unique perspective on, well, everything. Zero to One holds a special place in our hearts because it is the embodiment of the anti-quant--summed up in the preface by this quote: "Indeed, the single most powerful pattern I have noticed is that successful people find value in unexpected places, and they do this by thinking about business from first principles instead of formulas." This book is full of wit and wisdom that applies well beyond startups and venture capital.
Zero to One
Peter Thiel
Factors:
Factors are our bread and butter. We’ve been researching them for decades and have built an extensive proprietary research platform to view them from multiple angles across time and geography. Our first recommendation is a result of that work—a unique view of the fundamental drivers of factors. In Factors from Scratch, we lay out a framework for understanding the mechanism that drives factor portfolios to perform over time.
Factors from Scratch: A look backward, and forward, at how, when, and why factors work
Jesse Livermore, Christopher Meredith, CFA, Patrick O’Shaughnessy, CFA
Our CEO Patrick O’Shaughnessy penned this whitepaper, which pulls back the curtain on the common industry practice of diluting factor advantages for the benefit of greater strategy capacity--read greater fee revenue. Whatever strategy you pursue, or hire someone to pursue, make sure the strategy you invest gives you the greatest likelihood for outperformance, not overpriced, watered down exposures.
Alpha or Assets? Factor Alpha vs. Smart Beta
Patrick O’Shaughnessy, CFA
The proliferation of factor investing has resulted in an explosion of factor products that we view as watered down factor exposure. To achieve differentiated returns, quantitative investors need to do more than just expose their portfolios to popular factors such as value and momentum. They need to implement strategies that can separate good outcomes from bad outcomes within those factors.
Alpha Within Factors
Jesse Livermore, Christopher Meredith, CFA, Patrick O’Shaughnessy, CFA
The Past, Present, and Future of Quant
Cliff Asness
Fallacies in Investing:
It is tragic that business schools the world over emphasize, to the neglect of all other techniques, the discounted cash flow (DCF) method. While there is nothing wrong with DCF, its high sensitivity to assumptions renders it virtually useless in many scenarios. Seth Klarman has a unique take:
An Excerpt from Margin of Safety
Seth Klarman
Professional investors learn the importance of benchmarks early in their career. They are the yardstick against which we are measured, but also a metric to be evaluated for systematic flaws that can be exploited over time. The next two pieces by Travis Fairchild and Chris Meredith, respectively, summarize our work on the flaws of traditional value and growth index construction. The validity of Price-to-Book as an investment signal may seems like esoteric minutiae until you realize that it is the determining characteristic for whether a stock is "value" or "growth" based on index definitions. Trillions of dollars change hands based on these definitions. It’s the biggest structural trend in markets that nobody cares about.
Negative Equity, Veiled Value, and the Erosion if Price-to-Book
Travis Fairchild, CFA
Price-to-Book’s Growing Blind Spot
Christopher Meredith, CFA
Decision-making:
Investing is all about choices. From an eligible universe of potential investments, an investor selects the ones he or she feels have the greatest potential to meet some investment objective. This process naturally requires comparative assessments across all alternatives, while maintaining objectivity and avoiding common pitfalls. This is hard to do, but Mauboussin sheds light on this process as well as anyone in this short article. A more extensive treatment is continued in his book, The Success Equation.
How Well Do You Compare?
Michael Mauboussin
The Success Equation
Michael Mauboussin
Philip Tertlock, in his book Superforecasting, identifies traits of experts that are actually successful in making predictions. He identifies a six-step framework for making better predictions. While we don’t believe this will provide a crystal ball, it will help investors better think about handicapping outcomes of potential investments.
Superforecasting: The Art and Science of Prediction
Philip Tetlock
Constructing Portfolios:
Most don't think of portfolio construction as a key source of value add, but it matters immensely. To assess whether or not the chosen strategy passes muster, you need a framework to think about the levers that can be tweaked to drive return. Does the strategy win very consistently over time, or will it have sporadic periods of huge and few wins. Does the manager exhibit skill in how they weight the portfolio? Ehren Stanhope lays out a framework to answer these questions in Dimensions of Return.
Dimensions of Return
Ehren Stanhope, CFA
Risk:
A key consideration in any investment process is how to incorporate risk management. The “how” is often dictated by the style of the investment process itself. A highly concentrated manager with ten stocks faces different risks than a 500 stock fundamentally-weighted smart beta portfolio. For our part, we believe sustained and substantial factor exposures drive strong returns over time. The risk problem for us is how to provide factor advantages while mitigating unrewarded active risk. We succinctly explain our approach here:
O’Shaughnessy Philosophy and Process: Risk Management
Howard Marks has a way with words. His views are not cloaked behind ephemeral finance-speak that carries an aura of complexity. In his 2015 memo, Risk Revisited Again, he includes updated thoughts on risk. In it, he poo-poos the academic definition of risk—volatility—as distinct from true risk—permanent loss. Using volatility, or its cousin, tracking error, as the sole definition of risk can give a false sense of comfort.
Risk Revisited Again
Howard Marks
While many investors think of the risk of specific investments, as we learned from the Global Financial Crisis, risk can build like a rising tide lifting all ships. Surowiecki provides a framework for evaluating whether or not the overall market is functioning effectively.
The Wisdom of Crowds
James Surowiecki
Tools:
This 5-part series is a 2-3 hour investment to gain a proper understanding of what Machine Learning is (in layman’s terms), how it works, and why its relevant in our current and future lives. Far from the current fad, we view Machine Learning as a sophisticated tool that can be used to solve certain investment problems—classification, building new data sets, and identifying complex patterns that traditional techniques struggle to see.
Machine Learning for Humans
Vishal Maini
Kevin Zatloukal is an ex-Google, ex-Microsoft programmer with a Ph.D. in computer science from MIT. He is the second member of our OSAM Research Partners program. He teaches computer science at the University of Washington. Kevin is exactly the kind of person we are looking for: he has deep interest in investing, but also lists skills such as SQL, Python, machine learning, and statistics as "familiar friends."
In his first paper as a Research Partner, Kevin, explores the application of machine learning in finance and investing. As ML’s use becomes widespread, it has the potential to change almost every part of society, both by automating routine activities and by improving performance in difficult activities. In all likelihood, investing will be no exception.
ML & Investing Part 1: From Linear Regression to Ensembles of Decision Stumps
By Kevin Zatloukal, Ph. D
