University of Twente Student Theses
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Particle swarm optimization of custom bitcoin trading algorithm
Jaworski, M.Z. (2022) Particle swarm optimization of custom bitcoin trading algorithm.
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| Abstract: | Relative Strength Index (RSI) is a well-known technical indicator, which outputs are frequently used by traders and algorithms alike as a part of their decision process. Unfortunately, it is also suspect to generating numerous false signals, which reduces its performance. In this study we attempt to mitigate this issue by assembling a custom RSI based trading algorithm, referred to as 3-IRSI. Consequently, Particle Swarm Optimization (PSO) is applied in order to find optimal Bitcoin trading setups. Its performance is then compared against PSO optimized RSI and one other commonly used algorithm, as well as buy-and-hold strategy. Experiment results are presented in the form of descriptive statistics and demonstrate that the resulting algorithm is capable of outperforming its peers. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/89445 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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