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Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network

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  • Aryan Bhambu
  • Arabin Kumar Dey

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 $500$ and Dow Jones Index datasets.

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  • Aryan Bhambu & Arabin Kumar Dey, 2022. "Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network," Papers 2211.13915, arXiv.org.
    • Handle: RePEc:arx:papers:2211.13915
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    File URL: http://arxiv.org/pdf/2211.13915
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    1. Shankhyajyoti De & Arabin Kumar Dey & Deepak Gauda, 2020. "Construction of confidence interval for a univariate stock price signal predicted through Long Short Term Memory Network," Papers 2007.00254, arXiv.org.
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