基于ARIMA-LSTM模型的黄金价格趋势深度预测

Gold Price Trend Depth Prediction Based on ARIMA-LSTM Model

摘要: 金融时间序列预测对经济决策和投资意义重大，但金融市场的复杂性给预测模型构建带来挑战，而黄金价格走势备受关注，准确预测至关重要。本文针对现有组合模型不足，提出创新的非线性ARIMA-LSTM组合模型用于黄金价格预测。实证分析发现，ARIMA(3,1,5)模型、LSTM模型及GRU模型虽能捕捉时间序列特征但预测存在偏差，结果表明组合模型ARIMA-LSTM预测效果优于其他三种模型。通过MAE和RMSE评估，验证了ARIMA-LSTM模型在黄金价格预测中的优势，为金融决策提供新思路。

Abstract: Financial time series forecasting is of great significance to economic decision-making and investment, but the complexity of financial markets brings challenges to the construction of forecasting models, and the trend of gold price has attracted much attention, so accurate forecasting is crucial. This paper aims at the shortcomings of existing combination models, an innovative nonlinear ARIMA-LSTM combined model is proposed for gold price prediction. The empirical analysis shows that although ARIMA(3,1,5) model, LSTM model and GRU model can capture the features of time series, the prediction bias exists. The results show that the combined model ARIMA-LSTM has better prediction effect than the other three models. Through MAE and RMSE evaluation, the advantages of ARIMA-LSTM model in gold price prediction are verified, which provides new ideas for financial decision-making.