Thesis Details

Adaptive Trading Strategies for Cryptocurrencies

Bachelor's Thesis Student: Filip Marek Academic Year: 2021/2022 Supervisor: Homoliak Ivan, Ing., Ph.D.
Czech title
Adaptívní obchodní strategie pro kryptoměny
Language
English
Abstract

Cryptocurrency trading strategies are based on either rising or falling markets, however, they fail when applied to the wrong trend in a volatile market. This thesis explores the idea of cryptocurrency trading in rising and falling markets with adaptive strategies that can adjust to current market trends in order to maximize effectiveness. The problem is solved by analyzing the Bitcoin price, creating risk metric and focusing on the function's extrema. Both long-term and short-term options are explored. An extensible backtester program is created to evaluate the strategies and plot the time series. The results are compared to traditional approaches like HODL and rebalance, the profits can multiply more than three times using the right criteria. The thesis offers new ways of gaining profit to cryptocurrency investors, as well as giving readers insight into creating (adaptive) trading strategies and backtesting them in code. The output of the thesis is expected to be used by automated trading systems.

Keywords

Cryptocurrency, trading, investing, trading strategies, simulation, adaptive trading strategy, simulation tool, backtester, backtesting, Bitcoin risk metric, cryptocurrency data API

Department
Department of Intelligent Systems FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
13 June 2022
Reviewer
Perešíni Martin, Ing.
Committee
Janoušek Vladimír, doc. Ing., Ph.D. (DITS FIT BUT), předseda
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Honzík Jan M., prof. Ing., CSc. (DIFS FIT BUT), člen
Mrázek Vojtěch, Ing., Ph.D. (DCSY FIT BUT), člen
Rozman Jaroslav, Ing., Ph.D. (DITS FIT BUT), člen
Citation
FILIP, Marek. Adaptive Trading Strategies for Cryptocurrencies. Brno, 2022. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2022-06-13. Supervised by Homoliak Ivan. Available from: https://www.fit.vut.cz/study/thesis/24226/
BibTeX 
@bachelorsthesis{FITBT24226,
    author = "Marek Filip",
    type = "Bachelor's thesis",
    title = "Adaptive Trading Strategies for Cryptocurrencies",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2022,
    location = "Brno, CZ",
    language = "english",
    url = "https://www.fit.vut.cz/study/thesis/24226/"
}

Theses

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