The max EPS Paradigm For Corporate Finance [Paper] (with Itzhak Ben-David)
There are three classic problems in corporate finance: capital structure, real investment, and payout policy. The three papers below characterize the max EPS solution to each one. The max EPS approach delivers an optimal leverage ratio even in the absence of frictions, an investment rule based on comparing yields rather than using a risk-adjusted discount rate, and a payout policy where accretive buybacks are preferred to neutral dividends. Our max EPS model draws a bright line between growth and value. Growth stocks have earnings yields below the riskfree rate; value stocks have earnings yields above it. This single comparison leads the two kinds of firms to pursue different constellations of EPS-maximizing policies. This review article ties together these results to form a new max EPS paradigm for corporate-finance research.

EPS-Maximizing Capital Structure [Paper, Appendix] (with Itzhak Ben-David)
Textbook corporate-finance assumes that managers maximize NPV. However, in practice, the people running large public companies often seem more concerned with EPS growth. Perhaps this is a mistake. Or maybe EPS growth is a second-best proxy for value creation. Whatever the reason, we show that the simplest possible EPS-maximizing model predicts a number of important financing decisions, such as optimal leverage, new issuance, share repurchases, and cash holdings. The principle of EPS maximization leads to a novel microfoundation for distinguishing between value and growth stocks. There are two different routes to maximizing EPS, depending on whether a firm’s earnings yield is above the riskfree rate (value stocks) or below it (growth stocks). We find strong empirical support for our model’s key predictions.

Capital Budgeting For EPS Maximizers [Paper] (with Itzhak Ben-David)
To increase a company’s earnings, a project must generate enough income next year to pay for its own financing. Hence, EPS-maximizing managers only invest in accretive projects that have income yield above the firm’s cheapest financing option. This is the maxEPS analog to the positive-NPV rule. Maximizing EPS ≠ minimizing investment. EPS maximizers use real investment to arbitrage between asset and capital markets. This framework rationalizes the pervasive use of IRRs and payback periods. An IRR effectively measures how accretive a project will be. A payback period expresses the project’s income yield as a multiple. Empirically, our simple max EPS model explains M&A payment method and investment-cash flow sensitivity. It also predicts which firms tend to have a higher share of convertible debt and capitalized interest expense.

max EPS Payout Policy [Paper] (with Itzhak Ben-David)
Holding cash has a cost. For an EPS-maximizing CEO, that cost equals her firm’s earnings yield (EY). EPS maximizers retain cash when they can get an even higher yield by investing the money. Otherwise, they return cash to shareholders. This is the EPS-maximizing payout policy. Growth stocks (EY < rf) never return cash because they can clear their low earnings-yield hurdle by investing cash in riskfree bonds. Value stocks (EY > rf) face a higher hurdle, which makes cash their cheapest source of capital but also raises the opportunity cost of retention. Value stocks return cash when they cannot invest in enough accretive projects to make up for the higher cost. Dividends and repurchases both deliver the same shareholder value, but only repurchases can be accretive. So EPS-maximizing CEOs prefer to distribute cash via repurchases.

Expected EPS x Trailing PE: Pricing Without Discounting [Paper] (with Itzhak Ben-David)
Analysts explain how they calculate their price targets in the text of each report. We read what they write and find that most do not apply present-value logic. They typically multiply a company’s expected EPS (earnings per share) times its *trailing* PE (price-to-earnings) ratio. This has important implications for asset-pricing research even if analysts are not the marginal investor. All of asset-pricing theory currently starts by assuming that price equals expected discounted payoff. The one group of market participants who tells us their subjective payoff expectations does not generally use a discount rate to price them.

The Peoples’ Equity Risk Premium [Coming Soon] (with Itzhak Ben-David)
Many people calculate the equity risk premium (ERP) as an excess earnings yield, not an excess return. e.g., see here, here, here, here,… This approach doesn’t reflect present-value logic. Instead, the peoples’ ERP comes from thinking like an EPS-maximizing CEO. If stocks are expensive, equity financing must be cheap. High stock prices imply that shareholders are willing to provide a lot of equity capital in exchange for each $1 of a firm’s expected earnings. This funding-cost logic explains why popular accounts of the ERP tend to revolve around corporate policies (equity issuance, buy backs, etc) rather than discount rates. The Fed Model comes from misinterpreting the funding-cost logic behind the peoples’ ERP as a present-value statement.

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.