Gold Investment Model on RNN and Finding Best Investment Strategy on PSO
| dc.contributor.author | Pakamas Kanchanakantikul | |
| dc.contributor.author | Supakit Nootyaskool | |
| dc.date.accessioned | 2026-05-08T19:23:11Z | |
| dc.date.issued | 2022-9-9 | |
| dc.description.abstract | Nowadays, 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.doi | 10.1109/icmlc56445.2022.9941321 | |
| dc.identifier.uri | https://dspace.kmitl.ac.th/handle/123456789/18900 | |
| dc.subject | Stock Market Forecasting Methods | |
| dc.title | Gold Investment Model on RNN and Finding Best Investment Strategy on PSO | |
| dc.type | Article |