Working Papers
10- Valuation Models (November 2025), [NEW PAPER] with Francesca Bastianello and Marius Guenzel
[SSRN Version]
Valuation models lie at the core of both financial theory and practice, yet we lack systematic evidence on how professionals value assets, which models perform best, and why. To make progress on these questions, we analyze valuation models in 1.1 million equity analyst reports. While, on average, simpler multiples-based models generate more accurate forecasts than more complex discounted cash flow (DCF) models, this masks important heterogeneity: skilled analysts produce superior forecasts with DCF models, especially for hard-to-value firms, underscoring the importance of expertise when employing complex models. To establish that model-specific expertise matters, we exploit a quasi-exogenous shock that forced some analysts to switch valuation models, and show that their forecast accuracy subsequently declines relative to analysts with established experience using the new approach. This highlights a fundamental trade-off between simplicity and sophistication in valuation, where optimal method choice depends on analyst characteristics, such as skill. Finally, given their unconditional superior performance, we study how analysts determine multiples. Analysts use historical, current, and peer-based reference points to contextualize their choice of multiples, but they do not use these benchmarks mechanically when determining their prices. Moreover, we show that sensitivity analyses have become increasingly common, bull and bear scenarios are asymmetric and account for greater downside risk, and their inclusion is associated with more conservative forecasts.
9- Mental Models and Financial Forecasts (November 2025) [NEW VERSION], with Francesca Bastianello and Marius Guenzel - Reject & Resubmit at The Quarterly Journal of Economics
- 2025 Jack Treynor Prize Winner
- 2025 UCSD Brandes Center Best Paper Award
[SSRN Version]
We uncover the mental models financial professionals use to explain their quantitative forecasts, and show how they shape beliefs and return predictability. Using the near-universe of 2.1 million equity analyst reports, we collect the valuation methods analysts adopt to compute their price targets, together with their reasoning, measured as attention to topics, and their associated valuation channels, time horizons, and sentiments. To validate the reliability of our output, we introduce a multi-step LLM prompting strategy and new diagnostic tools. Consistent with a model of top-down and bottom-up attention, we then uncover three sets of facts. First, analysts’ mental models are sparse and rigid, and the choice of attention allocation and valuation methods are jointly determined by both analyst- and firm-characteristics. Second, analysts’ reasoning translates into their quantitative forecasts. Both attention and valuation methods contribute to differences in valuations over time and across analysts, but variation in attention plays a bigger role. Third, we study the extent to which different topics contribute to over and underreaction to information, and show how biases in analysts’ reasoning are reflected in asset prices. Analysts underreact to macroeconomic topics, and overreact to firm-related topics, and this contributes to return predictability.
8- Valuation Fundamentals (September 2024) [NEW VERSION COMING SOON], with John Graham - Reject & Resubmit at The Quarterly Journal of Economics
- 2024 Jack Treynor Prize Winner
[SSRN Version]
We study subjective valuation using a comprehensive sample of 78,000 analyst reports that contain detailed information on subjective discount rates and the entire term structure of cash flow growth expectations. We find that both growth expectations and subjective discount rates play an important role in explaining valuation fluctuations; and that the risk-free rate and subjective betas are the primary drivers of discount rate fluctuations over time. Analysts' subjective discount rates are unbiased predictors of future returns, and the relation of betas to future returns is closely related to risk premia, resulting in a steep security market line. To rationalize these findings, we show that analysts update key subjective inputs in a manner consistent with filtering estimation noise via Bayesian updating under imperfect information. Finally, analyst terminal growth rates track real GDP growth, but not inflation.
7- What Drives Very Long-Run Cash Flow Expectations? (April 2025) [NEW VERSION COMING SOON], with Marius Guenzel
- Best paper at the 2024 VSB Mid-Atlantic Research Conference
[SSRN Version]
Using a novel dataset combining terminal growth rate (TGR) expectations, textual belief discussions, and demographics, we establish four findings about forecasters’ truly long-run firm growth expectations. First, TGR expectations contain distinct information compared to shorter-horizon beliefs, correlate with firms’ realized long-run growth, and are not contaminated by expected returns. Second, unlike for short-run expectations, forecaster characteristics explain a large share of the TGR belief variation. Third, belief heuristics, such as local extrapolation, become prevalent when forming TGR expectations for geographically and culturally distant firms. Lastly, divergent TGR expectations reflect subjective differences in emphasis on similar topics, not in topics considered.
6- Resolving Estimation Ambiguity (September 2024), with Denis Sosyura and Michael Wittry
[SSRN Version]
Economic models develop conceptual frameworks for fundamental decisions but rarely prescribe a specific estimation approach. Using novel data on the inputs and assumptions in professional stock valuations, we study how financial analysts address estimation ambiguity when calculating a firm’s cost of capital. Analysts use the same return-generating model (CAPM) but diverge in their estimation choices for key inputs, such as equity betas. Such estimation choices are driven by idiosyncratic analyst-specific criteria, persist throughout their career and across brokerages, and generate large cross-analyst variation in discount rates for the same stock. The dispersion in discount rates is associated with higher market measures of investor disagreement, such as trading volume. Overall, we provide micro evidence on how financial experts resolve estimation uncertainty.
5- Heuristics in Managerial Budgets (January 2025), with Denis Sosyura
* This paper previously circulated under the title On a Spending Spree: The Real Effects of Heuristics in Managerial Budgets.
Media mentions: Lebow School of Business News Letter, Chicago Business Review
[SSRN Version]
Using granular data on managerial expenditures, we uncover heuristics in capital budgets, such as nominal rigidity, anchoring, and reset deadlines. Such heuristics are associated with managerial opportunism. Managers with budget surpluses increase spending before fiscal deadlines, and these projects underperform. Managers with budget shortfalls halt spending until refill dates, irrespective of investment options. These effects intensify at hierarchical firms with higher monitoring costs but weaken under strong principals. Replacing intermittent budgets with continuous, opportunity-driven capital rationing mitigates inefficiencies but raises managerial dissatisfaction and administrative costs, curbing performance gains. Overall, heuristics serve as practical tools balancing allocation efficiency with organizational frictions.
4- Capital Budgeting and Idiosyncratic Risk (November 2025) [NEW VERSION] - 2nd round Revise & Resubmit at The Journal of Financial Economics
[SSRN Version]
- Best paper at the 2019 FRA Conference in Las Vegas
- Best Ph.D. paper at the 2019 FRA Conference in Las Vegas
- Cubist Systematic Strategies Ph.D. Candidate Award at the 2020 WFA Conference in San Francisco
I show that managers discriminate against idiosyncratic risk in capital budgeting: marginal projects with greater idiosyncratic risk exposure are associated with higher required rate of return. To establish causality, I exploit quasi-exogenous within-region variation in project-specific idiosyncratic risk. I then decompose the measure of idiosyncratic risk into a good and a bad component and show that managers penalize projects for their exposure to downside risk. Finally, I explore how costly external financing, internal monitoring frictions, and CEOs’ personal exposure to idiosyncratic risk affect those adjustments. Overall, financial and operational frictions induce managers to account for idiosyncratic risk when determining projects’ required rate of return.
3- Self-Dealing in Corporate Investment (May 2024), with Denis Sosyura
* This paper previously circulated under the title CEO Pet Projects.
[SSRN Version]
- Best paper at the 2021 Raj & Kamla Gupta Governance Institute Conference (Drexel University)
- Top paper at the 2021 Global Finance Conference
- Best Paper at the 2021 International Corporate Governance Society Conference
Using hand-collected data on CEOs' personal assets, we find that CEOs prioritize corporate investment projects that increase the value of CEOs' private assets. Such projects are implemented sooner, receive more capital, and are less likely to be dropped. This investment strategy delivers large personal gains to the CEO but selects lower-NPV projects for the firm and erodes its investment efficiency. Consistent with value erosion, investment announcements by self-dealing CEOs generate negative announcement returns. CEO self-dealing is driven by public firms and disappears at smaller private firms run by their principals. Overall, we uncover CEOs' private gains in capital budgeting.
Articles Published in Refereed Journals
2- Strategic Learning and Corporate Investment (October 2024), with Michael Wittry - Forthcoming at The Journal of Finance
[SSRN Version]
We show that firms anticipate information spillover from peers' investment decisions and delay project exercise to learn from them. While this information improves project selection, the cost of waiting erodes these gains. To establish causality, we exploit local exogenous variation from the 1800s that shapes the number of peers that a firm can learn from today. The effect is most salient when information is scarce, costs of waiting are low, projects have low expected profitability, and the source information is more relevant. Finally, the anticipation of spillovers dampens aggregate investment, suggesting a role for this mechanism in macro-investment models.
1- Real Option Exercise: Empirical Evidence (August 2020), with Erik P. Gilje and Jérôme P. Taillard (Review of Financial Studies )
[SSRN Version] [RFS Version]
- Best paper at the 15th Annual Conference in Financial Economics at IDC-Herzliya (2018)
- Best paper at the 6th Annual USC Marshall Ph.D. Conference in Finance (2018)
We study when and why firms exercise real options. Using detailed project-level investment data, we find that the likelihood that a firm exercises a real option is strongly related to peer exercise behavior. Peer exercise decisions are as important in explaining exercise behavior as variables commonly associated with standard real option theories, such as volatility. We identify peer effects using localized exogenous variation in peer project exercise decisions and find evidence consistent with information externalities being important for exercise behavior.
Resting Papers
Discount Rate Uncertainty and Capital Investment (December 2021), with Hendrik Bessembinder