Motivation Trading has gotten a lot faster over the last two decades. The term "short-run trader" used to refer to people who traded multiple times a day. Now, it refers to algorithms that trade multiple times a second. Some people are worried … [Continue reading]
The Tension Between Learning and Predicting
1. Motivation Imagine we're traders in a market where the cross-section of returns is related to $V \geq 1$ variables: \begin{align*} r_s = \alpha^\star + {\textstyle \sum_v} \, \beta_v^{\star} \cdot x_{s,v} + … [Continue reading]
Why Bayesian Variable Selection Doesn’t Scale
1. Motivation Traders are constantly looking for variables that predict returns. If $x$ is the only candidate variable traders are considering, then it's easy to use the Bayesian information criterion to check whether $x$ predicts returns. … [Continue reading]
The Bayesian Information Criterion
1. Motivation Imagine that we're trying to predict the cross-section of expected returns, and we've got a sneaking suspicion that $x$ might be a good predictor. So, we regress today's returns on $x$ to see if our hunch is … [Continue reading]
A Model of Rebalancing Cascades
1. Motivating Examples Trading strategies can interact with one another to amplify small initial shocks to fundamentals: Quant Crisis, Aug 2007: "During the week of August 6, 2007, a number of [quantitative hedge funds] experienced … [Continue reading]