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<p>This paper presents a solution to the challenge of predicting multiple potential outcome variables for stock market evolution using Bayesian Networks. We develop three models based on Bayesian networks and analyze their performance using seven criteria: Model Building, Model Complexity, Flexibility/Generality, Interpretability, Ease of Deployment, Extensibility, and ease of Development. The experiments employ daily data concerning stock market indices from three regions (G7, BRICS, Gulf Cooperation Countries), two commodities prices (WTI, Gold), VIX index, and cryptocurrency prices (Bitcoin, Ethereum, Dash, Monero, Ripple). The proposed holistic Bayesian network model outperforms the competing Bayesian networks models, and the results show that it allows predicting either one output variable given a set of inputs or a set of output variables given a set of input variables, making it important for financial analysts, investors and traders.</p>

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Comprehensive Stock Market Insight: Bayesian Networks for Multi-output Forecasting

  • 期刊论文

  • 发表日期：

    2025年1月22日

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  • Ali Ben Mrad,
  • Brahim Hnich,
  • Amine Lahiani,
  • Salma Mefteh-Wali

摘要

This paper presents a solution to the challenge of predicting multiple potential outcome variables for stock market evolution using Bayesian Networks. We develop three models based on Bayesian networks and analyze their performance using seven criteria: Model Building, Model Complexity, Flexibility/Generality, Interpretability, Ease of Deployment, Extensibility, and ease of Development. The experiments employ daily data concerning stock market indices from three regions (G7, BRICS, Gulf Cooperation Countries), two commodities prices (WTI, Gold), VIX index, and cryptocurrency prices (Bitcoin, Ethereum, Dash, Monero, Ripple). The proposed holistic Bayesian network model outperforms the competing Bayesian networks models, and the results show that it allows predicting either one output variable given a set of inputs or a set of output variables given a set of input variables, making it important for financial analysts, investors and traders.