A hybrid model for high-frequency stock market forecasting

作者：

Highlights：

• A model to overcome the random walk dilemma for high-frequency financial time series.

• A gradient-based training algorithm with automatic time phase adjustment.

• An experimental analysis using time series from Brazilian high-frequency stock market.

摘要

•A model to overcome the random walk dilemma for high-frequency financial time series.•A gradient-based training algorithm with automatic time phase adjustment.•An experimental analysis using time series from Brazilian high-frequency stock market.

论文关键词：Artificial neuron,Descending gradient-based learning,Forecasting,High-frequency stock market

论文评审过程：Available online 17 January 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.01.004