Working Papers

• The FOMC Announcement Premium Asymmetry (Job Market Paper)
• [PDF] [SSRN]
Excess equity returns around Federal Open Market Committee (FOMC) meetings are concentrated in recessions. On FOMC announcement days, the difference between stock returns in recessions and expansions is 73-119 basis points (bps). For reference, the unconditional difference between the announcements and all other trading days is 21 bps. The asymmetry remains statistically significant after accounting for the elevated volatility in economic downturns. The pre-announcement drift and the compensation for bearing risk on announcement days are also much more pronounced in recessions. Overall, the state-dependent equity market behavior around FOMC news releases reflects the asymmetric risk accumulation over the business cycle.


• Properties of Financial Texts
• [PDF] [Internet Appendix, PDF] [SSRN]
Statistical properties of unstructured data are largely unknown. I find that counts of words (positive, negative, text length), their combinations, and measures constructed from them are often non-stationary. For most of these time series, the ADF test rejects the null hypothesis of unit root presence. On the other hand, the KPSS test rejects trend stationarity. Visual evidence aligns with the KPSS outcome. This pattern is more pronounced for daily data. A direct comparison between conventional frequency-based measure of news sentiment and a stationary counterpart demonstrates the economic impact. Predicting market returns with a non-stationary word frequency measure results in contradictory empirical findings. Forecast errors and prediction beta are higher in recessions than expansions at the same time. After accounting for the stationarity, the magnitude of beta decreases by over 50%, implying that the sentiment's influence on the equity market returns has been severely overstated.



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Work-in-Progress

Titles, descriptions, and content of this research are subject to change without prior notice.


• Trade Secrets Impairment

with Alexander Michaelides, Andreas Milidonis, and Yupana Wiwattanakantang

More information coming soon.


• Financial Texts and Strategic Information Sequencing
I propose a new methodology for quantifying topic importance based on the order and context of words within a text. It captures strategic information sequencing (intentional emphasis or obfuscation) and allows to evaluate the interdependence between individual topics. The procedure does not require dimensionality reduction and tangibly reduces measurement error. To accompany the measure, I also introduce a test (based on Zipf’s law) to assess whether the out-of-context word usage affects topic identification. To validate the methodology, I recover a subset of financially constrained firms sensitive to the interest rate movements from the Item 1A "Risk Factors" section of 10-K filings. These firms earn higher returns compared to the companies that are either constrained or sensitive to the interest rates, demonstrating the interdependence of financial risks. Altogether, empirical findings show that the measure provides different insights compared to the word frequencies.


• Cybersecurity Risk Disclosure and Pricing
Cybersecurity risk exposure and managerial decision to disclose it strongly depend on the firm’s industry and size. After accounting for the industry-level effects, only small firms have statistically significant cyber risk alpha. For small firms, a potential incident is a tail event; large firms are either too big to fail or self-insure.