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Simultaneous Confidence Intervals for Multi-way Clustered Stock Return Data

Author

Listed:
  • Tamalika Koley

    (Decision Sciences Area, Indian Institute of Management Lucknow)

  • Mrinal Jana

    (Centre for Quantitative Economics and Data Science, Birla Institute of Technology)

  • Gopal Krishna Basak

    (Indian Statistical Institute)

Abstract

The purpose of this study is to investigate how returns of stocks in different sectors are affected by the months of the year. An exploratory data analysis is performed to study the impact of months on different stocks. The findings encourage us to construct confidence intervals first by considering the fact that the residuals of the model exhibit correlation either across stocks or across months. We next build simultaneous confidence intervals by taking into account the correlation across both stocks and months on the residuals. This type of study can be used by investors to identify the riskiest assets and the ideal months to make investments. In order to account for market uncertainty, we design specific intervals for the stock returns and use the range that results from the duration of these intervals as a measure of stock volatility throughout our analysis. A study is conducted to compare the volatility of the US and Indian stock markets in order to get some understanding for investment purposes.

Suggested Citation

  • Tamalika Koley & Mrinal Jana & Gopal Krishna Basak, 2025. "Simultaneous Confidence Intervals for Multi-way Clustered Stock Return Data," Computational Economics, Springer;Society for Computational Economics, vol. 66(3), pages 2343-2365, September.
    • Handle: RePEc:kap:compec:v:66:y:2025:i:3:d:10.1007_s10614-024-10758-3
    DOI: 10.1007/s10614-024-10758-3
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