Extending machine learning prediction capabilities by explainable AI in financial time series prediction-Reference-Cited by-同舟云学术

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Extending machine learning prediction capabilities by explainable AI in financial time series prediction

Published:2023-01 Issue: Volume:132 Page:109876
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Çeli̇k Taha Buğra^ORCID,İcan Özgür,Bulut Elif

Publisher

Elsevier BV

Subject

Software

Reference54 articles.

1. Forecasting stock price movements with multiple data sources: Evidence from stock market in China;Zhou;Phys. Stat. Mech. Appl.,2020

2. Predicting next day direction of stock price movement using machine learning methods with persistent homology: Evidence from Kuala Lumpur Stock Exchange;Ismail;Appl. Soft Comput.,2020

3. Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process;Yun;Expert Syst. Appl.,2021

4. Short-term stock market price trend prediction using a comprehensive deep learning system;Shen;J. Big Data,2020

5. Predicting stock price movement using a DBN-RNN;Zhang;Appl. Artif. Intell.,2021

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3. Research on the Application Scenario Innovation in the Securities Industry based on Artificial Intelligence Technology;Proceedings of the 5th International Conference on Computer Information and Big Data Applications;2024-04-26

4. eXplainable Artificial Intelligence (XAI) for improving organisational regility;PLOS ONE;2024-04-24

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