Working Papers
Working Papers
Complex risks differ from simple risks in revealing only imperfect information about the underlying objective probabilities. This paper studies how complex risks are priced by and shared among heterogeneous investors. Leveraging decision theory under ambiguity, I derive robust predictions regarding the trading of complex risks and submit the theory to controlled laboratory testing. The experimental evidence corroborates the theoretical predictions. First, complexity aversion facilitates risk sharing: despite objective mispricing, markets share complex risks efficiently between buyers and sellers. Second, while complexity induces strictly dominated trading decisions, equilibrium outcomes overcome bounded rationality to accurately reflect average beliefs. This aggregate stability reconciles with a quantal response model that accounts for complexity-driven trading mistakes. Moreover, individuals’ awareness of their susceptibility to misjudge complex risks accelerates the incorporation of collective knowledge into equilibrium prices. Analyzing stock market opening auctions, I find support for the implied positive relation between trading concentration and price discovery.
Winner of the NASDAQ Award for the Best Paper on Asset Pricing, WFA 2019, Huntington Beach
Presented at: AFA 2018 (PhD Poster Session), RBFC 2018, FIRN 2018, Paris December Finance Meeting 2018, MPI Experimental Finance Workshop 2019, EF 2019, WFA 2019, Econometric Society Australasian Meeting 2019, EFA 2019
With Alexandre Ziegler
We investigate price discovery over the 24-hour trading day for equities, currencies, bonds, and commodities. Sizable price discovery occurs around the clock for most assets. For a given asset, intraday risk and return distributions are fairly similar, indicating a broadly constant risk-return-relationship during the day. Although the amount of price discovery varies significantly during the day and differs across assets, price discovery is generally efficient around the clock. Most assets do not exhibit the U-shaped intraday volatility pattern that has been documented for US equities, even if only main trading hours are considered. Intraday spikes in volatility are driven by the open or close of the market for the respective asset or other assets and by macroeconomic announcements. Both diffusion and jump risk are important drivers of intraday volatility patterns, and US macroeconomic news account for a sizable fraction of jump-driven volatility. For some – but not all – assets, the relationship between volume and volatility that can generally be observed during the trading day does not hold at the time of jumps, suggesting that traders anticipate large price moves at the time of scheduled announcements and market depth falls accordingly.
Accepted for publication in Management Science.
With Peter Bossaerts, Frans van den Bogaerde and Wenhao Yang
A key assumption of dynamic asset pricing theory is that agents have perfect foresight: for all future contingencies, they correctly foresee the corresponding equilibrium prices. Is it possible for prices to still reflect perfect foresight even if agents have imperfect foresight? We answer affirmatively, provided agents exhibit a mild form of narrow framing, which we refer to as dynamic narrow framing: while accounting for future endowments, agents ignore re-trading opportunities. This behavior vastly simplifies computations of optimal choices. With a controlled experiment, we verify that our behavioral assumption explains both prices and choices. Our findings allow us to re-interpret the successes and failures of traditional tests of asset pricing theory on historical data from the field.
Presented at: EF 2019, Econometric Society Australasian Meeting 2019, FIRN 2019, AEA 2022, SGF 2022, Helsinki Finance Summit 2022, Miami Behavioral Finance Conference 2022, FIRS 2023
Competition, Complexity, and Security Design: Evidence from Retail Investment Products
Accepted for publication in the Review of Finance.
With Marc Chesney, Jonathan Krakow and Simon Straumann
We investigate the role of strategic security design by analyzing the market for retail investment products. Focusing on a dominant yet understudied design feature, we provide evidence consistent with issuers strategically increasing product complexity to mitigate price competition. Since complex products yield lower returns, entail higher risk, and are first-order stochastically dominated by simpler products, rising market complexity increases uncompensated risk-taking, particularly among less sophisticated investors. Our findings suggest that complexity is shaped by issuers’ deliberate design choice to preserve product rents.
Featured in the "Rational Reminder" podcast, Episode 261
Winner of the Swiss Derivative Research Award 2021
Presented at: RBFC 2018, VGSF Finance Research Seminar, DGF 2021, Junior European Finance Seminar, FIRS 2022, SAFE 6th Household Finance Workshop, EFA 2022, SFS Cavalcade Asia-Pacific 2022, AEA 2023, SGF 2023, CEPR Household Finance Seminar, Berkeley Haas
Management Science, 2024, 70(6): 3381-3397.
With Peter Bossaerts, Kristian Rotaru and Kaitong Xu
Emotional involvement is known to be necessary but not sufficient for good decision-making in the face of uncertainty. It has been conjectured that emotional engagement in anticipation of risky outcomes constitutes "good" emotions. We introduce a new methodology to determine whether anticipatory emotional engagement is beneficial in the context of trading in financial markets. We focus on heart rate changes because they occur at a sufficiently high frequency to discern timing relative to events in the marketplace. After conservatively adjusting for multiple hypothesis testing, we find that participants whose heart rate changes anticipate their order submissions at inflated prices earn significantly more, while participants whose heart rate responds to their trades earn significantly less. By investigating co-integration between skin conductance response and the dynamics of individual portfolio values, we confirm the importance of emotional involvement in determining who makes or loses money.
Presented at: 9th Behavioural Finance and Capital Markets Conference
Journal of Behavioral and Experimental Finance, 2024, 42: 100906.
With Peter Bossaerts, Elizabeth Bowman, Harvey Huang, Michelle Lee, Carsten Murawski, Anirud Suthakar, Shireen Tang and Nitin Yadav
With three experiments, we study the design of financial markets to help spread knowledge about solutions to the 0-1 Knapsack Problem (KP), a combinatorial resource allocation problem. To solve the KP, substantial cognitive effort is required; random sampling is ineffective and humans rarely resort to it. The theory of computational complexity motivates our experiment designs. Complete markets generate noisy prices and knowledge spreads poorly. Instead, one carefully chosen security per problem instance causes accurate pricing and effective knowledge dissemination. This contrasts with information aggregation experiments. There, values depend on solutions to probabilistic problems, which can be solved by random drawing.
Presented at: Barcelona GSE Summer Forum 2019, EF 2019, Econometric Society Australasian Meeting 2019, CEPR European Summer Symposium in Financial Markets (morning session), Helsinki Finance Summit 2019, FIRN 2019, Paris December Finance Meeting 2019, 30th Annual Utah Winter Finance Conference