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Economic Research-Ekonomska Istraživanja Volume 35, 2022 - Issue 1

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Building portfolios based on machine learning predictions

Tomasz Kaczmareka Department of Investment and Financial Markets, Poznań University of Economics and Business, Poznań, PolandCorrespondence[email protected]
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Katarzyna Pereza Department of Investment and Financial Markets, Poznań University of Economics and Business, Poznań, PolandView further author information

Pages 19-37 | Received 09 Oct 2020, Accepted 09 Jan 2021, Published online: 05 Feb 2021

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https://doi.org/10.1080/1331677X.2021.1875865
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Kristina Sutiene, Peter Schwendner, Ciprian Sipos, Luis Lorenzo, Miroslav Mirchev, Petre Lameski, Audrius Kabasinskas, Chemseddine Tidjani, Belma Ozturkkal & Jurgita Cerneviciene. (2024) Enhancing portfolio management using artificial intelligence: literature review. Frontiers in Artificial Intelligence 7.
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J. Margaret Sangeetha & K. Joy Alfia. (2024) Financial stock market forecast using evaluated linear regression based machine learning technique. Measurement: Sensors 31, pages 100950.
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Bernhard Heiden, Bianca Tonino-Heiden, Sabrina Singerl & Volodymyr Alieksieiev. 2024. Advances in Information and Communication. Advances in Information and Communication 642 655 .

Yilin Ma, Yudong Wang, Weizhong Wang & Chong Zhang. (2023) Prediction-based mean–variance portfolios with risk budgeting based on neural networks. Expert Systems with Applications 230, pages 120638.
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Gaurang Sonkavde, Deepak Sudhakar Dharrao, Anupkumar M. Bongale, Sarika T. Deokate, Deepak Doreswamy & Subraya Krishna Bhat. (2023) Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications. International Journal of Financial Studies 11:3, pages 94.
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Cheng Zhao, Shuyi Yang, Chu Qin, Jie Zhou & Longxiang Chen. (2023) A Novel Smart Beta Optimization Based on Probabilistic Forecast. Computers, Materials & Continua 75:1, pages 477-491.
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Haris Subekti & Deni Saepudin. (2022) Cross-Sectional Machine Learning Approach on Predicting Stock Return of LQ45 Index. Cross-Sectional Machine Learning Approach on Predicting Stock Return of LQ45 Index.

Raymundo Díaz, Efrain Solares, Victor de-León-Gómez & Francisco G. Salas. (2022) Stock Portfolio Management in the Presence of Downtrends Using Computational Intelligence. Applied Sciences 12:8, pages 4067.
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Tomasz Kaczmarek, Barbara Będowska-Sójka, Przemysław Grobelny & Katarzyna Perez. (2022) False Safe Haven Assets: Evidence From the Target Volatility Strategy Based on Recurrent Neural Network. Research in International Business and Finance 60, pages 101610.
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Efrain Solares, Francisco G. Salas, Victor De-Leon-Gomez & Raymundo Diaz. (2022) A Comprehensive Soft Computing-Based Approach to Portfolio Management by Discarding Undesirable Stocks. IEEE Access 10, pages 40467-40481.
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