Automated cryptocurrency trading system
Hannam, Anthony (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023120734971
https://urn.fi/URN:NBN:fi:amk-2023120734971
Tiivistelmä
Cryptocurrency trading has been used for over a decade, and as technology improved, opportunities arose to automate trading for profit and analysis. This thesis describes the research, development, and implementation of an automated cryptocurrency trading system, sometimes also referred to as a trading bot.
Many traders perform manual steps to review market data and decide when to make a trade. This requires labour intensive actions of an individual, leading to time delays and potentially emotional decision making. This system aims to remove manual intervention, the time required to analyse and identify favourable market conditions for a trade, and reacts much faster than a person can.
Using Python language, third-party APIs, and a MongoDB database for data storage of data and trades, a working version of an automated trading bot was created in this study. The system will be an ongoing project and new features will be added after further analysis of trading results. The use of Python allows for machine learning and other analytics and reporting to be conducted easily.
This system was completed as the author’s personal project, and therefore represents individual research, analysis, code, and deployment. No AI tools were used in the development of this project.
Many traders perform manual steps to review market data and decide when to make a trade. This requires labour intensive actions of an individual, leading to time delays and potentially emotional decision making. This system aims to remove manual intervention, the time required to analyse and identify favourable market conditions for a trade, and reacts much faster than a person can.
Using Python language, third-party APIs, and a MongoDB database for data storage of data and trades, a working version of an automated trading bot was created in this study. The system will be an ongoing project and new features will be added after further analysis of trading results. The use of Python allows for machine learning and other analytics and reporting to be conducted easily.
This system was completed as the author’s personal project, and therefore represents individual research, analysis, code, and deployment. No AI tools were used in the development of this project.