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Neural Network for valuing Bitcoin options under jump-diffusion and market sentiment model

Author

Listed:
  • Edson Pindza
  • Jules Clement Mba
  • Sutene Mwambi
  • Nneka Umeorah

Abstract

Cryptocurrencies and Bitcoin, in particular, are prone to wild swings resulting in frequent jumps in prices, making them historically popular for traders to speculate. A better understanding of these fluctuations can greatly benefit crypto investors by allowing them to make informed decisions. It is claimed in recent literature that Bitcoin price is influenced by sentiment about the Bitcoin system. Transaction, as well as the popularity, have shown positive evidence as potential drivers of Bitcoin price. This study considers a bivariate jump-diffusion model to describe Bitcoin price dynamics and the number of Google searches affecting the price, representing a sentiment indicator. We obtain a closed formula for the Bitcoin price and derive the Black-Scholes equation for Bitcoin options. We first solve the corresponding Bitcoin option partial differential equation for the pricing process by introducing artificial neural networks and incorporating multi-layer perceptron techniques. The prediction performance and the model validation using various high-volatile stocks were assessed.

Suggested Citation

  • Edson Pindza & Jules Clement Mba & Sutene Mwambi & Nneka Umeorah, 2023. "Neural Network for valuing Bitcoin options under jump-diffusion and market sentiment model," Papers 2310.09622, arXiv.org.
    • Handle: RePEc:arx:papers:2310.09622
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    References listed on IDEAS

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    5. Dwyer, Gerald P., 2015. "The economics of Bitcoin and similar private digital currencies," Journal of Financial Stability, Elsevier, vol. 17(C), pages 81-91.
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