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Regular version of the site

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Maksim Novikov
Machine Learning Methods Implementation in Ethereum Marker Forecasting
Business Informatics
(Bachelor’s programme)
2018
The study aims to provide abundant research description on topic “Machine Learning Methods Implementation in Ethereum Marker Forecasting”. Relevance of stated research topic is supported by demand in new efficient predictive tools and analytics, as well as crypto financial time series fluctuation predictions with machine learning techniques. Main goal of the study is to combine machine learning algorithms with fundamental mathematical hypotheses and trading practices to prove or refute statement that news have an influence on cryptocurrencies in general and Ethereum in particular.

Process of data collection and preprocessing is described within research body, as well as model fitting and tuning. Results are presented as a set of metrics, which indicate derived models efficiency.

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