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How Evolution, Stories, and Irrationality

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How Evolution, Stories, and Irrationality † Designated as an Exemplary Final Project for 2020-21 HOW EVOLUTION, STORIES, AND IRRATIONALITY INFLUENCE DECISION MAKING IN FINANCIAL MARKETS: ANALYZING WHETHER WE CAN LEVERAGE OUR INNATE TRAITS AND HEURISTICS TO IMPROVE OUTCOMES Joseph E. McCarthy Faculty Advisor: Edward Tower Department of Economics December 2020 This project was submitted in partial fulfillment of the requirements for the degree of Master of Arts in the Graduate Liberal Studies Program in the Graduate School of Duke University. Copyright by Joseph Edward McCarthy 2020 ii Contents Abstract iv Acknowledgements v Chapter One: Introduction 1 Reconciling Rational Expectations and Behavioral Economics 1 Appropriate Level of Granularity 2 Adaptive Markets Hypothesis 4 Environmental, Psychological, and Methodological Influences on Prediction 7 Behavioral Approaches to Develop Better Outcomes in Financial Markets 10 Chapter Two: Human Evolutionary Development 13 Evolution and Natural Selection 13 Imagination and Language 16 Cooperation 21 Cultural Evolution, Behavioral Development, and Financial Markets 27 Chapter Three: Stories 32 Background on the Evolution of Stories 32 Stories, Marketing, and Propaganda 37 Narrative Economics 46 Chapter Four: Rationality, Irrationality, and Decision Making 58 Rational or Irrational? 58 Emotion and the Ventromedial Prefrontal Cortex 63 Biases and Heuristics 66 Overconfidence 73 Chapter Five: BDT and JDM Techniques to Improve Processes and Outcomes in the Markets 80 Can You Beat The Market? 80 Decision Making Strategies 83 "Superforecasters" 96 Team Development and Strategic Execution 103 "Select Crowds" vs "Good Judgment Project" 112 Chapter Six: Conclusion 116 References 119 iii Abstract One of the most commonly asked questions in investing is whether or not it is possible to achieve excess returns in the financial markets. To give a somewhat simple answer, for most investors a basic low-fee passive ("static") index fund portfolio is the best investment strategy since it outperforms nearly all advanced active indexing methodologies, such as "dynamic indexing," over the long-term due to factors such as high fees, high turnover, and poor asset selection (McCarthy and Tower, 2020b). Yet, even so, it does appear that it is possible to beat the market on a single trade through skill or luck as there are real inefficiencies and mispricings that occur among different investment vehicles at certain points in time (Lo, 2017; Malkiel, 2012; Ellis, 2017). This is especially evident in a number of endowment models, such as Yale's under David Swensen, which have successfully embraced risk through alternative investments – e.g., private equity – by focusing on longer time horizons and subsequently achieved very impressive results (Chambers, Dimson, and Kaffe, 2020; "Lessons from the endowment model," 2020). However, the fact that the financial markets are a zero-sum game with so many highly intelligent and highly informed investors constantly competing against one another makes it exceptionally difficult, and rare, to achieve excess returns over the long-term (Lo, 2017; Malkiel, 2012; Ellis, 2017). Indeed, the only way to truly beat the market on a regular basis is to constantly adapt your strategy in order to prevent your competitors from mimicking your successful techniques and thereby diluting your overall alpha (Lo, 2017; Malkiel, 2012; Ellis, 2017). Yet, even if we are able to consistently modify our approach as required, there are natural human biases relating to our evolutionary development; our collective stories; and our rationality / irrationality that can influence our decision making. In the following paper, I intend to provide an in-depth analysis of these three areas, and subsequently share a series of current best practices and frameworks from Behavioral Decision Theory (BDT) and Judgement and Decision Making (JDM) fields – e.g., "The Good Judgment Project" and "The Wisdom of Select Crowds" (Mannes, Soll, and Larrick, 2014; Mellers et al., 2014) – which if properly applied in a thoughtful and deliberate manner could offer a meaningful improvement in analysis, forecasting, decision making, and outcomes for both leaders and their organizations in the investing arena. iv Acknowledgments I wanted to express my deepest gratitude to my master's project supervisor Dr. Edward Tower for his mentorship, guidance, and generosity with his time. It's been an absolute privilege to have the opportunity to work with Dr. Tower and to watch how he conducts his research and uncovers new findings in the investing, economics, and finance arenas. I've had an amazing time working on this paper with you and I'm grateful for every second of this experience. I now feel like I finally have a basic grasp of the worlds of investing and economics, or at least maybe now I know that I don't know anything. Thank you so much as well to Kent Wicker and Jon Shaw for their direction and support on my exit examination committee, and for the classes that you taught us on "Self in the World" and "Evolution and Human Life." My grasp of graduate level writing and what it means to be human has increased exponentially because of those two courses. I would also like to share my sincerest gratitude to Anne Mitchell Whisnant, Kent Wicker, Donna Zapf, Lisa Robinson Bailey, and Dink Suddaby for all of their support and guidance throughout my time in the MALS program. It's been such a wonderful experience here at Duke from the second that I made that call to Dink two and half years ago to inquire about GLS. Thank you for taking such good care of us and making this such an incredible place to learn and grow. I'd also like to thank my friends Clayton, Jesse, Gus, Francis, Anthony, Carrie, Mike, and Chris for all of the deep and thoughtful conversations that we've had on so many abstract and theoretical concepts relating to this project. The insights that you shared throughout our discussions were incredibly valuable and I'm grateful for your patience and objectivity when discussing the real-world application of frameworks and models relating to behavioral decision theory and judgment and decision making. I'd like to dedicate this project to my Grandma and Grandpa McCarthy and my Grandpa Mangan. You are forever in our thoughts and prayers. We miss you so much, and we're forever thankful for your love and your kindness. Thank you for teaching us to be curious, inquisitive, objective, and empathetic. And, most importantly for your advice to always question the status quo. We love you all so much. You're always in our hearts. v Finally, and most importantly I wanted to thank my Mother, Father, and my sister Claire. You’re the best family anyone could ever ask for, and I'm eternally grateful to you for your kindness and support. Thank you so much for tolerating all of our conversations on choice theory, rational expectations, and narrative economics, and for guiding me back on target when I went off track. Your encouragement, advice, and direction has been more important than I can ever convey. I love you a ton. vi "It ain't what you don’t know that gets you into trouble. It's what you know for sure that just ain't so" (Anonymous). Chapter One: Introduction Reconciling Rational Expectations and Behavioral Economics The above quote is one of my favorites both for its folksy yet elegant simplicity and for its reminder to remain cautious, humble, and skeptical in whatever type of analysis or research you might perform. However, it's also highly relevant here for a research paper examining the influence of evolution, stories, and human irrationality / rationality on decision making and financial markets, as it has been falsely credited to Mark Twain – among others – over the years despite the fact that it never appears in any of his work ("It ain't what you don’t know that gets you into trouble. It's what you know for sure that just ain't so.", 2018). This is a simple example of what Nobel-prize winning psychologist Daniel Kahneman called, "theory-induced blindness,"1 and of how stories evolve and can anchor2 us on a particular belief without any factual basis. Yet, beyond the incorrect attribution of quotations, the stories that we tell; our potential for irrational decisions; and our baseline evolutionary traits can have a profound impact on our political policies, our religious beliefs, and our outcomes in the financial markets. To this point, an interesting question is whether it is possible to leverage our irrationality and our innate heuristics in order to improve outcomes in investments and financial markets. The choice of this topic for my master's project was inspired by a series of lessons and insights from classes on economics, investment strategies, behavioral decision theory, human evolution, and marketing. However, the primary 1 Theory-Induced Blindness: "once you have accepted a theory and used it as a tool in your thinking, it is extraordinarily difficult to notice its flaws. If you come upon an observation that does not seem to fit the model, you assume that there must be a perfectly good explanation that you are somehow missing. You give the theory the benefit of the doubt, trusting the community of experts who have accepted it" (Kahneman, 2011, p. 277). 2 Daniel Kahneman and Amos Tversky's anchoring effect is also very relevant in getting us to believe that this quotation was actually derived from Mart Twain: "It [the anchoring effect] occurs when people consider a particular value for an unknown quantity before estimating that quantity" (Kahneman, 2011, p. 119). This heuristic is highly influential in much of human behavior. Essentially we assign a greater value to what we hear first (especially when it comes from sources perceived as credible), and therefore, when we are initially told that the quote is from Twain we're primed to associate it with him moving forward making it difficult to disbelieve he was the source even after being definitively shown otherwise (Tversky and Kahneman, 1974).
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