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Studying and Forecasting Trends for Cryptocurrencies Using a Machine Learning Approach

Möller, Johan LU (2018) In Bachelor's Theses in Mathematical Sciences NUMK01 20182
Mathematics (Faculty of Engineering)
Abstract
We consider a technique involving Neural Networks in order to try to predict trends for cryptocurrencies such as Bitcoin, Ethereum etc. In that respect the project involves construction, design and training of a deep learning Neural Network based on historical trading data for these cryptocurrencies. Subsequently we apply this trained network in order to better understand its ability to possibly forecast future trading trends.
Please use this url to cite or link to this publication:
author
Möller, Johan LU
supervisor
organization
course
NUMK01 20182
year
type
M2 - Bachelor Degree
subject
publication/series
Bachelor's Theses in Mathematical Sciences
report number
LUNFNA-4020-2018
ISSN
1654-6229
other publication id
2018:K15
language
English
id
8962155
date added to LUP
2018-10-25 15:59:16
date last changed
2018-10-25 15:59:16
@misc{8962155,
  abstract     = {{We consider a technique involving Neural Networks in order to try to predict trends for cryptocurrencies such as Bitcoin, Ethereum etc. In that respect the project involves construction, design and training of a deep learning Neural Network based on historical trading data for these cryptocurrencies. Subsequently we apply this trained network in order to better understand its ability to possibly forecast future trading trends.}},
  author       = {{Möller, Johan}},
  issn         = {{1654-6229}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Bachelor's Theses in Mathematical Sciences}},
  title        = {{Studying and Forecasting Trends for Cryptocurrencies Using a Machine Learning Approach}},
  year         = {{2018}},
}