Gold Investment Model on RNN and Finding Best Investment Strategy on PSO

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dc.contributor.authorKanchanakantikul, Pakamas
dc.contributor.authorNootyaskool, Supakit
dc.date.accessioned2026-08-06T10:34:47Z
dc.date.available2026-08-06T10:34:47Z
dc.date.issued2022-01-01
dc.description.abstractNowadays, Algorithm trading in community and stock is interesting research, while gold is also an investment option. This research presents two steps. Three inputs sequence consists of the gold price(sell), gold spot and crude oil. Output has an order sequence indicating buy, sell, and wait for the signal. Firstly, finding the best strategy from historical data by particle swarm optimization (PSO) compared with random search (RS). That will get buying, selling, or waiting signals in the gold trading market Secondly, creating gold investment by recurrent neural network (RNN) model. The experiment result showed RNN trading model based on PSO is better than RS, which has a profit of 79.667 percent.
dc.identifier.citationProceedings International Conference on Machine Learning and Cybernetics, 2022-September, 80-85, 2022
dc.identifier.doi10.1109/ICMLC56445.2022.9941321
dc.identifier.issn2160133X
dc.identifier.other2-s2.0-85142472863
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/12613
dc.sourceProceedings International Conference on Machine Learning and Cybernetics
dc.subjectalgorithm trading
dc.subjectgold market trading
dc.subjectparticle swarm optimization
dc.subjectrandom search
dc.subjectrecurrent neural network
dc.titleGold Investment Model on RNN and Finding Best Investment Strategy on PSO
dc.typeConference Paper

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