Parallel architecture of CNN‐bidirectional LSTMs for implied volatility forecast-Reference-Cited by-同舟云学术

Parallel architecture of CNN‐bidirectional LSTMs for implied volatility forecast

Published:2022-02-03 Issue: Volume: Page:
ISSN:0277-6693
Container-title:Journal of Forecasting
language:en
Short-container-title:Journal of Forecasting

Author:

Choi Ji‐Eun¹^ORCID,Shin Dong Wan²^ORCID

Affiliation:

1. Department of Statistics Pukyong National University Pusan South Korea

2. Department of Statistics Ewha University Seoul South Korea

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Management Science and Operations Research,Statistics, Probability and Uncertainty,Strategy and Management,Computer Science Applications,Modeling and Simulation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/for.2844

Reference22 articles.

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4. Eapen J. Verma A. &Bein D.(2019).Novel deep learning model with CNN and Bi‐directional LSTM for improved stock market index prediction. In2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)(pp.264–270). Las Vegas NV USA.

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