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Neural Network for Valuing Bitcoin: Availability of Data, Code and Materials, Contributions

Written by @cryptosovereignty | Published on 2024/5/13

TL;DR
This study considers a bivariate jump-diffusion model to describe Bitcoin price dynamics and the number of Google searches affecting the price.

This paper is available on arxiv under CC 4.0 license.

Authors:

(1) Edson Pindza, Tshwane University of Technology; Department of Mathematics and Statistics; 175 Nelson Mandela Drive OR Private Bag X680 and Pretoria 0001; South Africa [edsonpindza@gmail.com];

(2) Jules Clement Mba, University of Johannesburg; School of Economics, College of Business and Economics and P. O. Box 524, Auckland Park 2006; South Africa [jmba@uj.ac.za];

(3) Sutene Mwambi, University of Johannesburg; School of Economics, College of Business and Economics and P. O. Box 524, Auckland Park 2006; South Africa [sutenem@uj.ac.za];

(4) Nneka Umeorah, Cardiff University; School of Mathematics; Cardiff CF24 4AG; United Kingdom [umeorahn@cardiff.ac.uk].

Availability of data, code and materials

Please contact the corresponding author for request.

Contributions

All authors contributed equally to the paper. All authors read and approved the final manuscript.

Declarations

Conflict of interest: All authors declare that they have no conflict of interest.

Ethical approval: This article does not contain any studies with human participants or animals performed by any of the authors.

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Written by
@cryptosovereignty
We believe everyone should have ultimate control and ownership over their cryptographic assets and digital transactions.

Topics and
tags
artificial-intelligence|jump-diffusion-model|black-scholes-equation|artificial-neural-network|neural-network-for-crypto|neural-network-for-bitcoin|neural-network-for-valuing-btc|multi-layer-perceptron
This story on HackerNoon has a decentralized backup on Sia.
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