Studying and Forecasting Trends for Cryptocurrencies Using a Machine Learning Approach
(2018) In Bachelor's Theses in Mathematical Sciences NUMK01 20182Mathematics (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:
http://lup.lub.lu.se/student-papers/record/8962155
- author
- Möller, Johan LU
- supervisor
- organization
- course
- NUMK01 20182
- year
- 2018
- 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}}, }