Table of Contents

Forecasting Bitcoin Price using Artificial Neural Network

Dhruba Banjade, University of Texas at Arlington


NEUROECONOMICS eJOURNAL

"Forecasting Bitcoin Price using Artificial Neural Network" Free Download

DHRUBA BANJADE, University of Texas at Arlington
Email:

Forecasting Bitcoin prices is a big challenge today because of difficulties to exactly know the parameters upon which the Bitcoin price depends. In this paper, I forecast the price using the artificial neural network (ANN) technique. Bitcoin market capitalization, volume, dollar to euro, dollar to pound exchange rates, gold price, and S&P 500 index does not support to predict the prices. However, the Bitcoin price lags with four inputs, ten hidden layers, and two hundred iterations provide a better result with root mean square (RMSE) equals to 10.20, and coefficient of determination (R2) equals to 0.96.

^top

About this eJournal

This eJournal distributes working and accepted paper abstracts focused on research where economic outcomes are the product of many individual decisions, constrained by scarcity, and equilibrium forces that simultaneously shape a person's social networks and the institutionally defined rules of the game. Decisions are made by computations in the brain which produce action-choices that directly affect the homeostatic wellbeing of the individual and choices that indirectly change wellbeing by changing an individual's future constraints, the scope of their social networks, and their message sending rights within the institutions they participate. Neuroeconomics broadly speaking is interested in the study of these computations and the resulting choices they produce. This includes experiments that attempt to understand the mechanisms of neuronal computations that produce action-choices, theories which predict how neuronal computations in socio-economic environments produce decisions, outcomes and wellbeing, and policy which use our understanding of neuoroeconomic behavior to either build or defend better solutions to societal problems.

Editors: Michael C. Jensen, Harvard University, and Kevin A. McCabe, George Mason University

Submissions

To submit your research to SSRN, sign in to the SSRN User HeadQuarters, click the My Papers link on left menu and then the Start New Submission button at top of page.

Distribution Services

If your organization is interested in increasing readership for its research by starting a Research Paper Series, or sponsoring a Subject Matter eJournal, please email: sales@ssrn.com

Distributed by

Economics Research Network (ERN), a division of Social Science Electronic Publishing (SSEP) and Social Science Research Network (SSRN)

Directors

ERN SUBJECT MATTER EJOURNALS

MICHAEL C. JENSEN
Harvard Business School, SSRN, National Bureau of Economic Research (NBER), European Corporate Governance Institute (ECGI), Harvard University - Accounting & Control Unit
Email: mjensen@hbs.edu

Please contact us at the above addresses with your comments, questions or suggestions for ERN-Sub.

Advisory Board

Neuroeconomics eJournal

ANDREW W. LO
Harris & Harris Group Professor, Massachusetts Institute of Technology (MIT) - Sloan School of Management, National Bureau of Economic Research (NBER), Principal Investigator, Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

P. READ MONTAGUE
Professor, Baylor University - Department of Neuroscience

VERNON L. SMITH
Professor of Economics and Law, Chapman University - Economic Science Institute, Chapman University School of Law