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Welcome!
I am an Assistant Professor of Finance at the University of Kansas School of Business. My research interests include empirical asset pricing, macro-finance, and financial econometrics.
Contact
Contact
Email: mghaderi@ku.edu | CV | SSRN | Google Scholar
Publications
Publications
Learning, Slowly Unfolding Disasters, and Asset Prices (with Mete Kilic and Sang Byung Seo)
Journal of Financial Economics 143 (1): 527-549, January 2022. (Internet Appendix)
An earlier version of this paper was circulated under the title "Slowly Unfolding Disasters."
Why Do Rational Investors Like Variance at the Peak of a Crisis? A Learning-Based Explanation (with Mete Kilic and Sang Byung Seo)
Journal of Monetary Economics 142: 103513, March 2024. (Internet Appendix)
Is There a Macro-Announcement Premium? (with Sang Byung Seo)
Management Science, Accepted. (Internet Appendix)
Working Papers
Working Papers
Learning and Subjective Beliefs About Good and Bad Inflation Ranges (with Sang Byung Seo and Ivan Shaliastovich)
An earlier version of this paper was circulated under the title "Learning, Subjective Beliefs, and Time-Varying Preferences for Different Inflation Ranges."
Abstract: We identify desirable/undesirable inflation outcomes under subjective beliefs by comparing survey-based and risk-adjusted distributions of inflation. Intuitively, investors dislike inflation at both extremes, preferring a range in the middle. This "good inflation" region, which investors associate with lower-than-average marginal utility, varies substantially over time in position and width, revealing time-varying preferences across inflation ranges. Different ranges contribute to the inflation risk premium with mixed signs, offsetting each other and often masking important insights into the pricing of inflation risk. We rationalize these empirical patterns using a model where investors learn and update beliefs about hidden deflationary and inflationary recession states.
Presented at: Syracuse University, Virtual Household Finance Seminar, University of Wisconsin-Madison, Federal Reserve Board of Governors, Michigan State University, Cancun Derivatives and Asset Pricing Conference, World Symposium on Investment Research, DePaul University, Columbia Workshop in New Empirical Finance, Silicon Prairie Conference, SKK Business School, PBC School of Finance, Northern Finance Association, Tepper-LEAF Conference (Scheduled)
Pricing of Corporate Bonds: Evidence From a Century-Long Cross-Section (with Sebastien Plante, Nikolai Roussanov, and Sang Byung Seo)
Northern Finance Association Best Paper Award in Asset Pricing
Abstract: We construct a new historical corporate bond database spanning 128 calendar years to address longstanding data limitations hampering corporate bond research. By hand-collecting monthly corporate bond quotes from three archival print sources, we complement existing datasets and create an extensive database dating back to 1895, comprising nearly 110,000 unique bonds and 8 million observations. Leveraging this expanded sample, we find that the lack of priced risks in corporate bonds documented by recent studies stems from their reliance on short samples. With greater statistical power, we show that prominent bond and stock factors as well as several nontraded macroeconomic factors are significantly priced with theoretically consistent signs. At the same time, the predictive power of corporate bond spreads for real activity is largely robust in the longer sample, except when prewar data are included. Our database, covering major economic episodes like the Great Depression, not only helps validate previous empirical findings but aims to facilitate further research by serving as a CRSP counterpart for corporate bonds.
Presented at: Federal Reserve Board of Governors, Cancun Derivatives and Asset Pricing Conference, Wharton Brownbag, Wisconsin Brownbag, Macro-Finance Society Workshop, FIRS, INSEAD, Asian Finance Association, CICF, Bristol OTC Conference, Northern Finance Association, American Finance Association (Scheduled)
Can Time‐Varying Risk Premia and Household Heterogeneity Explain Credit Cycles?
Eastern Finance Association Best Doctoral Paper Award in Investments, 2021
Abstract: Using micro-level household mortgage data, I measure dispersion in the credit quality of borrowers in the housing market and show that it forecasts regional real economic activity. I provide empirical evidence that associates the predictive power of dispersion with heterogeneity in the exposure of households' labor income to economy-wide shocks. I explain these observations in a model featuring time-varying risk premia, incomplete markets, and household heterogeneity. Due to risk aversion, the consumption and investment responses of households have a convex association with their labor income exposure to aggregate risks. As a result, dispersion forecasts the aggregate output more strongly in more heterogeneous regions, consistent with the data.
Presented at: University of Houston, University of Kansas, University of Georgia, Cornerstone Research, SWFA 2021, EFA 2021, AREUEA 2022
Teaching
Teaching
School of Business, University of Kansas, Lawrence, KS
FIN 410 - Investment Theory and Applications
Bauer College of Business, University of Houston, Houston, TX
FINA 4330 - Corporate Finance
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