Modeling Managers As EPS Maximizers [Paper] (with Itzhak Ben-David)
American Economic Review, Reject & Resubmit
Corporate-finance textbooks assume that firm managers aim to maximize the net present value (NPV) of discounted cash flows. But when you talk to the people in charge of large public corporations, they tell you that they make decisions to maximize their earnings per share (EPS). Perhaps firm managers should not be maximizing EPS. No matter. We take them at their word when they tell us that this is what they are doing, and we show how EPS maximization provides a single unified explanation for a wide range of empirical outcomes, such as firm leverage, share repurchases, M&A payment method, and cash accumulation.
Expected EPS x Trailing P/E [Coming Soon] (with Itzhak Ben-David)
When an earnings report includes a target price, the analyst is required to explain exactly how they calculated this number. We read through these explanations to understand how analysts price their own subjective earnings expectations. Contrary to what textbook models assume, most analysts do not apply present-value logic when creating one-year-ahead price forecasts. Instead, they typically multiply a company’s expected earnings per share (EPS) over the next twelve months times a trailing price-to-earnings ratio (P/E). We outline a simple model where this non-standard approach yields price targets that are correct on average because prices are largely backward looking. We show that our model can empirically account for why prices under-react to past earnings news and do not respond to changes in firm leverage.
Proving You Can Pick Stocks Without Revealing How [Paper]
It might seem like, if you don’t have enough money to trade on your own behalf, then you must reveal some information about how you pick stocks in order to prove that you can do it. And that would be bad news. Every piece of additional information that you reveal makes it a little bit easier reverse engineer your approach. Luckily for you, that conventional wisdom is wrong. In this paper, I show how you can construct a zero-cost zero-knowledge proof that you know about a profitable new way to pick stocks.
Model Identification vs. Market Efficiency [Paper]
When otherwise intelligent investors fail to correct an error, a researcher learns something about what these investors did not know. The investors must not have known about anything which would have allowed them to spot their mistake. If they had, they would have stopped making it. I show how a researcher can use this insight to identify how investors price assets by defining a special kind of error, called a “random anchoring error”, which investors will only fail to correct if they are not aware of any omitted variables. Random anchoring errors are instruments for identifying how mostly rational investors price assets.
White Papers
Survey Curious? Start-Up Guide and Best Practices for Running Surveys and Experiments Online [Paper] (with Abigail Bergman, Samuel Hartzmark, and Abigail Sussman)
You’re a financial economist who wants to run an online survey or experiment. But you don’t know where to get started. This paper provides the basic information you need to get started. We not only describe how to create a useful survey/experiment but also give click-by-click instructions for posting it online.