Working Papers
Working Papers
This paper studies how complexity impacts markets’ ability to aggregate information and distribute risks. I amend fundamental asset pricing theory to reflect agents’ imperfect knowledge about complex dividend distributions and test its clear-cut predictions in the laboratory. Market equilibria corroborate complexity-averse trading behavior. Despite being overpriced, markets efficiently share complex risks between buyers and sellers. While complexity induces noise in individual trading decisions, market outcomes remain theory-consistent. This striking feature reconciles with a random choice model, where bounds on rationality are reinforced by complexity. Furthermore, apparent self-awareness of estimation biases increases the efficiency and reduces the fluctuations of market-clearing prices.
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
Coupons, Competition, and Complexity: Security Design under Low Interest Rates
R&R
With Marc Chesney, Jonathan Krakow and Simon Straumann
We study the market for retail investment products in times of low interest rates. Combining experimental and field data, we show that decreasing interest rates drive investment demand but fail to rationalize the empirically observed increase in product complexity. In contrast, we provide evidence that banks strategically increase complexity to mitigate price competition. Because complex products bear higher down-side risk and are first-order dominated by simpler products, this strategic use of complexity results in higher uncompensated risk-taking by investors. Overall, our findings showcase how low interest rates can indirectly fuel excessive risk-taking.
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
Revise & resubmit at 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
Reject & resubmit at Journal of Economic Theory
With Peter Bossaerts, Elizabeth Bowman, Harvey Huang, Carsten Murawski, Anirud Suthakar, Shireen Tang and Nitin Yadav
We investigate how markets solve the standard but computationally hard problem of maximizing utility subject to a budget constraint with indivisibilities. In a first experiment with complete markets, we show that the theory of computation sheds light on which problems are hard for individuals to solve, and whether computational difficulty is reflected in price quality. Under computational complexity, complete markets are fairly ineffective in revealing important information, resulting in noisy prices. In a second experiment, inspired by the theory of oracles in computer science, we show that a reduction to only one traded asset can actually improve information dispersion. Our findings demonstrate how a market design that solely focuses on the transmission of incomplete but crucial information can lead to a more efficient spreading of knowledge in society (Hayek, 1945).
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
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.
Forthcoming in Management Science
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