This paper demonstrates a severe small sample bias in the use of sample variances to test stock price variance bounds, under the maintained assumption that prices and dividends follow stationary and ergodic stochastic processes. This bias is due to the smoothness of the perfect foresight price, which is used to construct the variance bound. However, the small sample bias demonstrated here seems insufficient to explain the empirical apparent gross violations of the stock price variance inequality, in contrast to the result for variance bounds tested with bonds.
-
Faculty
- Academic Areas
- Awards & Honors
- Seminars
-
Conferences
- Accounting Summer Camp
- California Econometrics Conference
- California Quantitative Marketing PhD Conference
- California School Conference
- China India Insights Conference
- Homo economicus, Evolving
-
Initiative on Business and Environmental Sustainability
- Political Economics (2023–24)
- Scaling Geologic Storage of CO2 (2023–24)
- A Resilient Pacific: Building Connections, Envisioning Solutions
- Adaptation and Innovation
- Changing Climate
- Civil Society
- Climate Impact Summit
- Climate Science
- Corporate Carbon Disclosures
- Earth’s Seafloor
- Environmental Justice
- Finance
- Marketing
- Operations and Information Technology
- Organizations
- Sustainability Reporting and Control
- Taking the Pulse of the Planet
- Urban Infrastructure
- Watershed Restoration
- Junior Faculty Workshop on Financial Regulation and Banking
- Ken Singleton Celebration
- Marketing Camp
- Quantitative Marketing PhD Alumni Conference
- Rising Scholars Conference
- Theory and Inference in Accounting Research
- Voices
- Publications
- Books
- Working Papers
- Case Studies
- Postdoctoral Scholars
-
Research Labs & Initiatives
- Cities, Housing & Society Lab
- Corporate Governance Research Initiative
- Corporations and Society Initiative
- Golub Capital Social Impact Lab
- Initiative for Financial Decision-Making
- Policy and Innovation Initiative
- Rapid Decarbonization Initiative
- Stanford Latino Entrepreneurship Initiative
- Value Chain Innovation Initiative
- Venture Capital Initiative
- Behavioral Lab
- Data, Analytics & Research Computing