Mathematics, Год журнала: 2023, Номер 12(1), С. 29 - 29
Опубликована: Дек. 22, 2023
The significance of precise gold price forecasting is accentuated by its financial attributes, mirroring global economic conditions, market uncertainties, and investor risk aversion. However, predicting the challenging due to inherent volatility, influenced multiple factors, such as COVID-19, crises, geopolitical issues, fluctuations in other metals energy prices. These complexities often lead non-stationary time series, rendering traditional series modeling methods inadequate. Our paper presents a multi-objective optimization algorithm that refines interval prediction framework with quantile regression deep learning response this issue. This comprehensively responds gold’s dynamics uncertainties screening process various including pandemic-related indices, US dollar index, prices commodities. deep-learning models optimized algorithms deliver robust, interpretable, highly accurate predictions for handling non-linear relationships complex data structures enhance overall predictive performance. results demonstrate QRBiLSTM model, using MOALO algorithm, delivers excellent composite indicator AIS reaches −15.6240 −11.5581 at 90% 95% confidence levels, respectively. underscores model’s high accuracy potential provide valuable insights assessing future trends deterministic probabilistic captures new pandemic index sets benchmark volatile commodities like gold.
Язык: Английский