Forex Trading Volatility Prediction using Neural Network Models
Statistical Finance
2021-12-06 v2 Machine Learning
Abstract
In this paper, we investigate the problem of predicting the future volatility of Forex currency pairs using the deep learning techniques. We show step-by-step how to construct the deep-learning network by the guidance of the empirical patterns of the intra-day volatility. The numerical results show that the multiscale Long Short-Term Memory (LSTM) model with the input of multi-currency pairs consistently achieves the state-of-the-art accuracy compared with both the conventional baselines, i.e. autoregressive and GARCH model, and the other deep learning models.
Cite
@article{arxiv.2112.01166,
title = {Forex Trading Volatility Prediction using Neural Network Models},
author = {Shujian Liao and Jian Chen and Hao Ni},
journal= {arXiv preprint arXiv:2112.01166},
year = {2021}
}