Behavioral Finance

Time to Trade in Your Doctor for an Algo?

Artificial intelligence in the diagnosis of low-back pain and sciatica Mathew, B., Norris, D., Hendry, D., & Waddell, G. Spine, 13, 168-172 An online version [...]

Behavioral Bias Bingo: Decoy Effect

“When my information changes, I alter my conclusions. What do you do, sir?” - John Maynard Keynes How does the Decoy Effect work? Here is [...]

Behavioral Bias Bingo: Disposition Effect

Sell Winners Too Early and Hold Losers Too Long Researchers have explored the "disposition effect" for years, which describes how investors are more likely to sell [...]

Introduction to Behavioral Finance – Part 2: Limits of Arbitrage

In the first part of our series, “Introduction to Behavioral Finance – Part 1: Behavioral Bias,” we explored several market anomalies, and the first required condition for the real-life implementability of many quantitative strategies: the existence of human behavioral biases. In this Part 2 of our series, we consider a related question following from our Keynes example: given that certain behavioral biases can affect investors, how can it be that their effects persist in markets so we can take advantage of them? This would seem to contravene the notion of efficient markets, and leads to the second required condition for implementing a tradable strategy: limits to arbitrage.

Introduction to Behavioral Finance – Part 1: Behavioral Bias

In this blog post, Part 1 of our two part series on Behavioral Finance, we explore human behavioral biases, how they affect us as investors, and how they are reflected in the stock market. In Part 2 of our series, we will explore the second required ingredient for profiting from behavioral bias: Limits of Arbitrage. Human behavior is diverse and complex and, unfortunately, despite our best intentions, it is not always governed exclusively by rationality. In particular, our judgment and decision-making can be significantly affected by intuition, a form of abstract, automatic thinking that can override our reason. Decades of research in psychology have shown that intuition is often systematically biased, and follows identifiable patterns, causing us to reach conclusions that are predictable wrong, since they are based on our gut or instincts, rather than on logic. An important aspect of behavioral biases is that they affect us in areas of our lives where it is very important that we be purely rational, such as in investing. In this blog post, we highlight a number of behavioral biases, and specifically how they can affect investors. Before getting into the specifics, we wanted to review some background we hope will be informative, and put the biases into an appropriate investing context.

Behavioral Finance and Investing: Are you Trying Too Hard?

Everyone makes mistakes. It’s part of what makes us human. Because humans understand their actions are sometimes flawed, it was perhaps inevitable that the field of psychology would develop a rich body of academic literature to analyze why it is that human beings often make poor decisions. Although insights from academia can be highly theoretical, our everyday life experiences corroborate many of these findings at a basic level: “I know I shouldn’t eat the McDonalds BigMac, but it tastes so good.” Because we recognize our frequent irrational urges, we often seek the judgment of experts, to avoid becoming our own worst enemy. We assume that experts, with years of experience in their particular fields, are better equipped and incentivized to make unbiased decisions. But is this assumption valid? A surprisingly robust, but neglected branch of academic literature, has studied, for more than 60 years, the assumption that experts make unbias decisions. The evidence tells a decidedly one-sided story: systematic decision-making, through the use of simple quantitative models with limited inputs, outperforms discretionary decisions made by experts. This essay summarizes research related to the “models versus experts” debate and highlights its application in the context of investment decision-making. Based on the evidence, investors should de-emphasize their reliance on discretionary experts, and should instead approach investment decisions with systematic models. To quote Paul Meehl, an eminent scholar in the field, “There is no controversy in social science that shows such a large body of qualitatively diverse studies coming out so uniformly in the same direction as this one [models outperform experts].”

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