# Construction of confidence interval for a univariate stock price signal predicted through Long Short Term Memory Network

arXiv: https://arxiv.org/abs/2007.00254 · HTML: https://mlsanity.com/paper/2007.00254/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jul 2020.

## Built on by (most cited first, 2 of 2)

- [Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network](https://mlsanity.com/paper/2211.13915/) (2022)
- [RAGIC: Risk-Aware Generative Adversarial Model for Stock Interval Construction](https://mlsanity.com/paper/2402.10760/) (2024)

## Abstract (arXiv)

In this paper, we show an innovative way to construct bootstrap confidence interval of a signal estimated based on a univariate LSTM model. We take three different types of bootstrap methods for dependent set up. We prescribe some useful suggestions to select the optimal block length while performing the bootstrapping of the sample. We also propose a benchmark to compare the confidence interval measured through different bootstrap strategies. We illustrate the experimental results through some stock price data set.