Forecasting Bias: From Weather to Wall Street
Providers of forecasts often want to be right, but they also don’t enjoy surprising people on the downside. People don’t like nasty surprises. For instance, [...]
Providers of forecasts often want to be right, but they also don’t enjoy surprising people on the downside. People don’t like nasty surprises. For instance, [...]
Is Tiger Woods Loss Averse? Persistent Bias in the Face of Experience, Competition, and High Stakes Pope and Schweitzer A version of the paper can [...]
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 [...]
Confirmation bias leads to the selective use of information It is easy to obtain confirmations, or verifications, for nearly every theory - if we look [...]
“When my information changes, I alter my conclusions. What do you do, sir?” - John Maynard Keynes How does the Decoy Effect work? Here is [...]
Hard work ≠ Value "Imagine you play in a tennis tournament at your local club. As your opponents are of the same strength as you, [...]
Clinical intuition and test scores as a basis for diagnosis Klehr, R. Journal of Consulting Psychology, 13, 34-38 An online version of the paper can [...]
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 [...]
How do your feelings affect your decisions? "Humans perceive and act on risk in two fundamental ways. Risk as feelings refers to individuals' instinctive and [...]
We're often asked: Why does value investing work? You guys simply buy crappy high-risk companies. Of course you outperform. I typically agree with claims that [...]
Hindsight bias: How we overestimate our prediction abilities People tend to overestimate their own predictive power when events have already occurred. This is commonly known [...]
Financial advisers are ubiquitous in the US, where many investors hire them to assist with investing, financial planning and other types of financial decision-making. Advisers [...]
Hyperbolic discounting and Present bias Executive Summary: "Intertemporal tradeoffs are ubiquitous in decision making, yet preferences for current versus future losses are rarely explored in [...]
Human beings crave certainty and loath ambiguity. People naturally gravitate towards the "sure thing" versus another option where the outcome is uncertain. Sometimes this is [...]
Tonight is the NBA draft lottery. As a 76ers fan, I will be rooting for them to get the first overall selection. Of course gaining [...]
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.
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.
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].”
Would you trust a computer to drive your car? Google’s self-driving cars are now driving on city streets, and are rapidly becoming better drivers than [...]
A student in my class passed along a great quote from one of Buffett's annual letters. Warren Buffett outlines a great story told to him [...]
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