A Comprehensive Framework for Forecasting Bitcoin Prices Using Statistical Distributions and Volatility Models: Implications for Risk-Education, Job Creation, and Wealth Development in Africa and Nigeria

Authors

  • Ekoh, L. A. Department of Educational foundations, Nnamdi Azikiwe University, Awka
  • Ezeja, E. Department of Statistics, Institute of Management and Technology, Enugu state
  • Eneh, C. Department of Agricultural Economics, University of Nigeria, Nsukka, Enugu state, Nigeria

Abstract

This paper outlines a framework for forecasting Bitcoin prices using various statistical distributions and volatility models, implemented within Python. The framework incorporates log-normal, normal, Pareto, Cauchy, exponential, and power law distributions, alongside
volatility clustering models to forecast Bitcoin prices. The paper also discusses the implications of this methodology for risk education, job creation, and wealth development in Africa, with a particular focus on Nigeria. By demonstrating the practical application of statistical forecasting tools, this study highlights how such techniques can be leveraged to enhance financial literacy and economic opportunities in emerging markets.

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Published

2024-09-26

Issue

Vol. 15 No. 2 (2024): Technoscience Review

Section

Articles

License

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