AMRO：使用人工智能预测联邦基金利率：LSTM、GRU和大型语言模型方法（英文版）

Forecasting the US federal funds rate is important since it impacts global financial conditions, and in turn the real economy. This working paper examines whether artificial intelligence (AI) models could forecast policy rates accurately by inferring the implicit decision rules the US Federal Open Markets Committee (FOMC) follows when setting the policy rate. We examine two recurrent neural networks (RNNs), long short-term memory (LSTM) and gated recurrent unit (GRU), and a large zero-shot la