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Factor Models, Machine Learning, and Asset Pricing

Citations

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Cited by:

  1. Yonghe Lu & Yanrong Yang & Terry Zhang, 2024. "Double Descent in Portfolio Optimization: Dance between Theoretical Sharpe Ratio and Estimation Accuracy," Papers 2411.18830, arXiv.org.
  2. Nie, Chun-Xiao & Song, Fu-Tie, 2023. "Stable versus fragile community structures in the correlation dynamics of Chinese industry indices," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
  3. Daniele Massacci & Lucio Sarno & Lorenzo Trapani & Pierluigi Vallarino, 2025. "A General Randomized Test for Alpha," Tinbergen Institute Discussion Papers 25-045/III, Tinbergen Institute.
  4. Matteo Bagnara, 2024. "Asset Pricing and Machine Learning: A critical review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(1), pages 27-56, February.
  5. Islip, David & Kwon, Roy H. & Kim, Seongmoon, 2025. "Integration of support vector machines and mean-variance optimization for capital allocation," European Journal of Operational Research, Elsevier, vol. 322(3), pages 1045-1058.
  6. Vasant Dhar & Jo~ao Sedoc, 2025. "DBOT: Artificial Intelligence for Systematic Long-Term Investing," Papers 2504.05639, arXiv.org.
  7. Liao, Cunfei & Ma, Tian, 2024. "From fundamental signals to stock volatility: A machine learning approach," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).
  8. Alessi, Lucia & Ossola, Elisa & Panzica, Roberto, 2023. "When do investors go green? Evidence from a time-varying asset-pricing model," International Review of Financial Analysis, Elsevier, vol. 90(C).
  9. Fieberg, Christian & Liedtke, Gerrit & Zaremba, Adam & Cakici, Nusret, 2025. "A factor model for the cross-section of country equity risk premia," Journal of Banking & Finance, Elsevier, vol. 171(C).
  10. Nechvátalová, Lenka, 2025. "Autoencoder asset pricing models and economic restrictions — international evidence," International Review of Financial Analysis, Elsevier, vol. 107(C).
  11. Vafai, Nima & Rakowski, David, 2024. "The sources of portfolio volatility and mutual fund performance," International Review of Financial Analysis, Elsevier, vol. 91(C).
  12. Ma, Tian & Wang, Wanwan & Chen, Yu, 2023. "Attention is all you need: An interpretable transformer-based asset allocation approach," International Review of Financial Analysis, Elsevier, vol. 90(C).
  13. Giuseppe Matera, 2025. "Corporate Earnings Calls and Analyst Beliefs," Papers 2511.15214, arXiv.org, revised Nov 2025.
  14. Ma, Tian & Wang, Wanwan & Jiang, Fuwei, 2025. "Machine learning the performance of hedge fund," Journal of International Money and Finance, Elsevier, vol. 155(C).
  15. Ruixun Zhang, 2025. "Toward interpretable machine learning: evaluating models of heterogeneous predictions," Annals of Operations Research, Springer, vol. 347(2), pages 867-887, April.
  16. Yoontae Hwang & Yaxuan Kong & Stefan Zohren & Yongjae Lee, 2025. "Decision-informed Neural Networks with Large Language Model Integration for Portfolio Optimization," Papers 2502.00828, arXiv.org.
  17. Langlois, Hugues, 2023. "What matters in a characteristic?," Journal of Financial Economics, Elsevier, vol. 149(1), pages 52-72.
  18. Zhu, Zhoufan & Zhang, Ningning & Zhu, Ke, 2024. "Big portfolio selection by graph-based conditional moments method," Journal of Empirical Finance, Elsevier, vol. 78(C).
  19. Trent Spears & Stefan Zohren & Stephen Roberts, 2023. "View fusion vis-\`a-vis a Bayesian interpretation of Black-Litterman for portfolio allocation," Papers 2301.13594, arXiv.org.
  20. Sak, Halis & Huang, Tao & Chng, Michael T., 2024. "Exploring the factor zoo with a machine-learning portfolio," International Review of Financial Analysis, Elsevier, vol. 96(PA).
  21. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
  22. Penaranda, Francisco & Sentana, Enrique, 2024. "Portfolio management with big data," CEPR Discussion Papers 19314, C.E.P.R. Discussion Papers.
  23. Jiang, Hao & Li, Sophia Zhengzi & Yuan, Peixuan, 2025. "Granular information and sectoral movements," Journal of Economic Dynamics and Control, Elsevier, vol. 171(C).
  24. Junyi Ye & Bhaskar Goswami & Jingyi Gu & Ajim Uddin & Guiling Wang, 2024. "From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing," Papers 2403.06779, arXiv.org.
  25. Brian Godwin Lim & Dominic Dayta & Benedict Ryan Tiu & Renzo Roel Tan & Len Patrick Dominic Garces & Kazushi Ikeda, 2025. "Dynamic Factor Analysis of Price Movements in the Philippine Stock Exchange," Papers 2510.15938, arXiv.org.
  26. Liu, Yanchu & Zhou, Heyang & Yang, Haisheng, 2025. "Latent factor models for the Chinese commodity futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 93(C).
  27. Qingliang Fan & Ruike Wu & Yanrong Yang, 2024. "Shocks-adaptive Robust Minimum Variance Portfolio for a Large Universe of Assets," Papers 2410.01826, arXiv.org.
  28. Shanyan Lai, 2025. "Multilayer Perceptron Neural Network Models in Asset Pricing: An Empirical Study on Large-Cap US Stocks," Papers 2505.01921, arXiv.org, revised May 2025.
  29. Cong Wang, 2024. "Stock return prediction with multiple measures using neural network models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
  30. Juan Tenorio & Wilder Perez, 2024. "Monthly GDP nowcasting with Machine Learning and Unstructured Data," Papers 2402.04165, arXiv.org.
  31. Jozef Barunik & Matej Nevrla, 2022. "Common Idiosyncratic Quantile Factors and Asset Prices," Papers 2208.14267, arXiv.org, revised Mar 2026.
  32. Adel Javanmard & Jingwei Ji & Renyuan Xu, 2024. "Multi-Task Dynamic Pricing in Credit Market with Contextual Information," Papers 2410.14839, arXiv.org, revised Dec 2025.
  33. Alejandro Rodriguez Dominguez & Muhammad Shahzad & Xia Hong, 2025. "Multi-Hypothesis Prediction for Portfolio Optimization: A Structured Ensemble Learning Approach to Risk Diversification," Papers 2501.03919, arXiv.org, revised May 2025.
  34. van Cappelle, Tjeerd & Pokidin, Dmytro & Zwinkels, Remco C.J., 2025. "The cross section of stock returns in an artificial stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 239(C).
  35. Minshuo Chen & Renyuan Xu & Yumin Xu & Ruixun Zhang, 2025. "Diffusion Factor Models: Generating High-Dimensional Returns with Factor Structure," Papers 2504.06566, arXiv.org, revised Jan 2026.
  36. Yujie Ding & Shuai Jia & Tianyi Ma & Bingcheng Mao & Xiuze Zhou & Liuliu Li & Dongming Han, 2023. "Integrating Stock Features and Global Information via Large Language Models for Enhanced Stock Return Prediction," Papers 2310.05627, arXiv.org.
  37. Bagnara, Matteo, 2024. "The economic value of cross-predictability: A performance-based measure," SAFE Working Paper Series 424, Leibniz Institute for Financial Research SAFE.
  38. Giuseppe Buccheri & Fulvio Corsi & Emilija Dzuverovic, 2024. "From rotational to scalar invariance: Enhancing identifiability in score-driven factor models," Papers 2412.01367, arXiv.org.
  39. Chen, Ding & Guo, Biao & Zhou, Guofu, 2023. "Firm fundamentals and the cross-section of implied volatility shapes," Journal of Financial Markets, Elsevier, vol. 63(C).
  40. Kelvin J. L. Koa & Yunshan Ma & Ritchie Ng & Tat-Seng Chua, 2024. "Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models," Papers 2402.03659, arXiv.org, revised Feb 2024.
  41. He, Xubiao & Dong, Zhengwen & Teng, Min & Yang, Tingting, 2025. "Investor sentiment spillover from air pollution: Cross-industry influences on stock markets," Economic Modelling, Elsevier, vol. 152(C).
  42. Allen Yikuan Huang & Zheqi Fan, 2026. "Beyond Prompting: An Autonomous Framework for Systematic Factor Investing via Agentic AI," Papers 2603.14288, arXiv.org, revised Apr 2026.
  43. Mathieu Fournier & Kris Jacobs & Piotr Orłowski, 2024. "Modeling Conditional Factor Risk Premia Implied by Index Option Returns," Journal of Finance, American Finance Association, vol. 79(3), pages 2289-2338, June.
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