Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network
Methodology
2022-11-28 v1 Machine Learning
Computational Finance
Computation
Abstract
In this paper we propose a novel procedure to construct a confidence interval for multivariate time series predictions using long short term memory network. The construction uses a few novel block bootstrap techniques. We also propose an innovative block length selection procedure for each of these schemes. Two novel benchmarks help us to compare the construction of this confidence intervals by different bootstrap techniques. We illustrate the whole construction through S\&P and Dow Jones Index datasets.
Cite
@article{arxiv.2211.13915,
title = {Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network},
author = {Aryan Bhambu and Arabin Kumar Dey},
journal= {arXiv preprint arXiv:2211.13915},
year = {2022}
}