| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document

Title:Analiza trga kriptovalut s postopki slepega ločevanja izvorov : magistrsko delo
Authors:Mikolič, Jan (Author)
Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf MAG_Mikolic_Jan_2020.pdf (1,78 MB)
MD5: E1AAB835A9A649F5BE07C1D7B2FE2D95
 
Language:Slovenian
Work type:Master's thesis/paper (mb22)
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrskem delu izvedemo analizo trga kriptovalut z metodami slepega ločevanja izvorov. Osredotočimo se na algoritma FastICA in SOBI. Preizkusimo različne vrednosti vhodnih parametrov in stroškovnih funkcij. Ugotovimo, da je algoritem SOBI s številom zakasnitev 400 primernejši, saj izkorišča časovno strukturo zgodovinskih cen kriptovalut. Na podlagi mešalnega modela kriptovalute gručimo v skupine, na katere vplivajo podobni dejavniki. Predstavimo model za napovedovanje cen kriptovalut na podlagi izračunanih neodvisnih komponent. Zaključimo z ugotovitvijo, da napovedovanje cen kriptovalut zgolj na podlagi zgodovinskih podatkov o cenah najverjetneje ni možno ne glede na napovedovalni model in predhodne transformacije.
Keywords:kriptovalute, analiza neodvisnih komponent, slepo ločevanje izvorov, napovedovanje časovnih vrst, FastICA, SOBI
Year of publishing:2020
Place of performance:Maribor
Publisher:[J. Mikolič]
Number of pages:VIII, 49 str.
Source:Maribor
UDC:004.421:004.422.635(043.2)
COBISS_ID:23070998 New window
NUK URN:URN:SI:UM:DK:41OYS4GY
Views:796
Downloads:129
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
:
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:AddThis
AddThis uses cookies that require your consent. Edit consent...

Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:16.01.2020

Secondary language

Language:English
Title:Cryptocurrency Market Analysis with Blind Source Separation Algorithms
Abstract:In this master's thesis we perform cryptocurrency market analysis with blind source separation algorithms. We focus on algorithms FastICA and SOBI. Different input parameters and cost functions are tested. Algorithm SOBI with number of lags 400 proves to be the best choice as it exploits the time coherence of the cryptocurrency historical price data. Given the mixing model, we perform clustering and identify groups of cryptocurrencies which are under the influence of similar factors or sources. Further on, a forecasting model, based on calculated independent components, is presented. We conclude that cryptocurrency time series forecasting based on historical price data alone is most likely not possible, regardless of forecasting model or previous transformations used.
Keywords:cryptocurrencies, independent component analysis, blind source separation, time series forecasting, FastICA, SOBI


Comments

Leave comment

You have to log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica