Transformer Models in Financial Forecasting: Outperforming LSTMs

A 2026 analysis from Algo Finance finds that transformer-based models outperform LSTM networks in financial forecasting, with transformers achieving up to 15% higher accuracy in predicting stock price movements. The study, which evaluated models on historical market data, attributes the improvement to transformers' ability to capture long-range dependencies and parallelize training. This suggests a shift toward transformer architectures in quantitative finance.