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Title:Algoritmično trgovanje kriptovalut : diplomsko delo
Authors:ID Podkoritnik, Jan (Author)
ID Fister, Iztok (Mentor) More about this mentor... New window
ID Fister, Dušan (Comentor)
Files:.pdf VS_Podkoritnik_Jan_2022.pdf (2,96 MB)
MD5: B7FC9F5C8F607ED23A4F77418818664F
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V nalogi smo predstavili trg kriptovalut, splošno teorijo trgovanja in tehnične analize. Opisali smo algoritmično trgovanje in pripadajoče strategije. Implementirali smo aplikacijo, ki omogoča avtomatizirano trgovanje in testiranje izbranih strategij na podlagi preteklih podatkov. Izbrali smo nekaj tehničnih indikatorjev, implementirali strategijo trgovanja in poskušali na podlagi izvedenih testov s pomočjo aplikacije ugotoviti, ali je mogoče biti dobičkonosen. Na koncu smo predstavili analizo rezultatov, pridobljenih s testiranjem.
Keywords:kriptovalute, algoritmično trgovanje, C#, tehnična analiza
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[J. Podkoritnik]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF (X, 70 f.))
PID:20.500.12556/DKUM-82931 New window
UDC:004.7:336.74(043.2)
COBISS.SI-ID:140211971 New window
Publication date in DKUM:25.10.2022
Views:784
Downloads:156
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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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:09.09.2022

Secondary language

Language:English
Title:Algorithmic trading of cryptocurrencies
Abstract:In this thesis we introduce the cryptocurrency market, general trading theory and technical analysis. We have described algorithmic trading and related strategies. We implemented an application that allows automated trading and testing of selected strategies based on historical data. We selected some technical indicators, implemented a trading strategy and tried to determine whether it is possible to be profitable based on the tests carried out with the help of the application. Finally, we present an analysis of the results obtained from the tests.
Keywords:cryptocurrencies, algorithmic trading, C#, technical analysis


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