Analiza uspešnosti lastnega programa za avtomatizirano trgovanje kriptovalut v primerjavi s konkurenčnim

diplomsko delo

Alen Gojkošek (Author), Dijana Močnik (Mentor), Boštjan Šumak (Co-mentor)

Abstract

V diplomskem delu smo predstavili kripto trg in njegove udeležence, predvsem kripto kite. Razvili smo programsko rešitev za avtomatizirano trgovanje kriptovalute bitcoin, ki se je na podlagi podatkov o transakcijah kripto kitov odločala, kdaj bo kriptovaluto bitcoin kupila oziroma prodala. Cilj programa je bil visoka donosnost in neodvisnost od nihanja cen kriptovalut. Rezultate simulacije trgovanja z resničnimi zgodovinskimi podatki kriptovalut iz leta 2022 smo primerjali z rezultati konkurenčnega programa. Dosegli smo vse zastavljene cilje in v primerjalni analizi obeh programov ugotovili, da je naša programska rešitev uspešnejša in ima na dolgi rok manjše naložbeno tveganje.

Keywords

avtomatizirano trgovanje;bitcoin;kripto kiti;programski jezik Python;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2022
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[Al. Gojkošek]
UDC:	004.7:336.745(043.2)
COBISS:	130767875
Views:	36
Downloads:	8
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Performance analysis of our own automated software for cryptocurrency trading compared to a competitor's
Secondary abstract:	In our thesis, we presented the crypto market and its participants, especially crypto whales. We developed automated cryptocurrency trading program that decided when to buy and sell bitcoin, based on the crypto whales transactions. The goal of the program was high profitability and independence from the crypto market's volatility. We compared the results of simulated trading with real historical data of the cryptocurrencies from 2022 with the competitors program. All the goals we set were achieved. The comparative analysis of the two programs showed that our trading program was more successful and had lower investment risk in the long run.
Secondary keywords:	Automated trading;bitcoin;crypto whales;Python;
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Medijske komunikacije
Pages:	1 spletni vir (1 datoteka PDF (VI, 32 f.))
ID:	16294846