Is Information Risk Priced? New Evidence from Outer Space

Satellite images of the parking lots of U.S. retail firms provide information about the firms’ future earnings, and the limited access to these images produces information asymmetry between sophisticated and unsophisticated investors. We construct a cloud-based information risk (CIR) measure to capture this satellite information risk and investigate its asset pricing performance. We find that CIR positively predicts future stock returns of retail firms in the cross-section and that the predictability cannot be explained by weather reasons. We provide evidence that CIR indeed captures the information asymmetry among investors. The profitability of short selling is more pronounced on clear days. The return predictability of CIR is more pronounced in preannouncement periods. During cloudy days, parking lot traffic data from satellite images are harder to obtain, and the retail store sales estimated using parking lot data are noisier. We further show that high CIR is associated with low liquidity and that the decrease in liquidity purchases is greater than the decrease in liquidity sales. Our empirical analyses suggest that information asymmetry is priced and that CIR affects equity premiums through the liquidity channel, which are consistent with the theoretical predictions from a noisy rational expectations equilibrium model under imperfect competition. This paper was accepted by Kay Giesecke, finance. Funding: S. Wang acknowledges financial support from the National Natural Science Foundation of China [Grants 72373110 and 71902140] and Fundamental Research Funds for the Central Universities in China. Y. Wang acknowledges financial support from the National Natural Science Foundation of China [Grants 72342003 and 72071114]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00713 .

• 저널Management Science · 71(9) · 7707–7730
• 토픽Financial Markets and Investment Strategies · Finance
• DOI10.1287/mnsc.2023.00713
• 저자Xianfeng Hao, Shujing Wang, Yudong Wang, Liangyu Wu