Stock Price Forecasting and Hypothesis Testing Using Neural Networks

• Tác giả: Kerda Varaku
• Ngôn ngữ: eng
• Ký hiệu phân loại: 006.32 Neural nets (Neural networks)
• Thông tin xuất bản: 2019
• Bộ sưu tập: Metadata
• ID: 163288

Tóm tắt

In this work we use Recurrent Neural Networks and Multilayer Perceptrons to predict NYSE, NASDAQ and AMEX stock prices from historical data. We experiment with different architectures and compare data normalization techniques. Then, we leverage those findings to question the efficient-market hypothesis through a formal statistical test.