Does data frequency mean better stock market forecasting performance? The German and US case study - Ferreira, N. B.; Mendes, D. A.; Mendes, V. (1st Artificial Intelligence in Finance Conference (AIIFC), 2024)
This paper aims to analyze if time series frequency is related to better forecast performance. We analyze two time series from G7 economies, NASDAQ and DAX, for 5 minutes, and daily frequency. The implemented algorithms are deep learning recurrent neural networks, particularly some variations of Long Short-Term Memory (LSTM) architectures (LSTM, BiLSTM). Random search hyperparameter tuning was used to obtain the model architecture that minimize the loss function. We obtained better results for the 5-minute intraday frequency for both time series, and the forecast improved by 1%.