Author:Yingjie Niu, Jinqiang Yang, Zhentao Zou

Abstract: We extend a production-based asset pricing model by introducing learning about disaster risk. The information is not perfect, and Bayesian learning is adopted to update beliefs about the likelihood of rare disasters. We show that disaster learning reconciles key stylized facts about macroeconomic quantities and financial markets. For macroeconomic quantities, during the crisis, the decline in aggregate investments is much worse than that of output, whereas the decline in aggregate consumption is moderate relative to that of output. Additionally, the model endogenously features lower consumption volatility and higher investment volatility than that of output. For financial markets, belief updating over a rare disaster produces a higher equity premium, lower risk-free rate, and more volatile stock returns. Finally, we show that jump intensity uncertainty accounts for a substantial fraction of the total welfare cost of rare disasters.

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This paper was published  in the September 2024 issue (Vol. 220) of the internationally top-tier theoretical economics journal Journal of Economic Theory. The first author is Dr. Yingjie Niu, Assistant Professor at the School of Finance, Shanghai University of Finance and Economics. The second author is Professor Jinqiang Yang, also from the School of Finance, Shanghai University of Finance and Economics. The corresponding author is Dr. Zhentao Zou, School of Economics and Management, Wuhan University.

https://www.sciencedirect.com/science/article/pii/S0022053124000784