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This chapter delves into revenue trend forecasting for Bharat Petroleum Corporation Limited (BPCL) through regression analysis and deseasonalized index analysis. Leveraging insights from prior oil and gas industry research, the study employs advanced analytical techniques to construct robust forecasting models. Data from the CMIE Prowess database covering 56 quarters is analyzed, with regression models including linear and polynomial regressions utilized to predict BPCL's revenue for the subsequent five quarters. Deseasonalized index analysis is implemented to mitigate seasonal fluctuations, while graphical analysis and evaluation metrics gage the forecast reliability. The findings underscore the importance of advanced analytics in revenue forecasting for oil companies, offering valuable insights for strategic decision-making.

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Forecasting Revenue Trends: Leveraging Regression and Deseasonalized Index Analysis

  • 会议论文

  • 发表日期：

    2025年

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  • Shrey Arora,
  • Krishna Kumar Singh,
  • Ajay Singh

摘要

This chapter delves into revenue trend forecasting for Bharat Petroleum Corporation Limited (BPCL) through regression analysis and deseasonalized index analysis. Leveraging insights from prior oil and gas industry research, the study employs advanced analytical techniques to construct robust forecasting models. Data from the CMIE Prowess database covering 56 quarters is analyzed, with regression models including linear and polynomial regressions utilized to predict BPCL's revenue for the subsequent five quarters. Deseasonalized index analysis is implemented to mitigate seasonal fluctuations, while graphical analysis and evaluation metrics gage the forecast reliability. The findings underscore the importance of advanced analytics in revenue forecasting for oil companies, offering valuable insights for strategic decision-making.