Reinforcement-Learning Portfolio Allocation with Dynamic Embedding of Market Information
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Kelly, Bryan T. & Pruitt, Seth & Su, Yinan, 2019.
"Characteristics are covariances: A unified model of risk and return,"
Journal of Financial Economics, Elsevier, vol. 134(3), pages 501-524.
- Bryan Kelly & Seth Pruitt & Yinan Su, 2018. "Characteristics Are Covariances: A Unified Model of Risk and Return," NBER Working Papers 24540, National Bureau of Economic Research, Inc.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
- DeMiguel, Victor & Plyakha, Yuliya & Uppal, Raman & Vilkov, Grigory, 2013.
"Improving Portfolio Selection Using Option-Implied Volatility and Skewness,"
Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(6), pages 1813-1845, December.
- Uppal, Raman & DeMiguel, Victor & Plyakha, Yuliya & Vilkov, Grigory, 2010. "Improving Portfolio Selection Using Option-Implied Volatility and Skewness," CEPR Discussion Papers 7686, C.E.P.R. Discussion Papers.
- Guannan Qu & Adam Wierman & Na Li, 2022. "Scalable Reinforcement Learning for Multiagent Networked Systems," Operations Research, INFORMS, vol. 70(6), pages 3601-3628, November.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020.
"Empirical Asset Pricing via Machine Learning,"
The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
- Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
- Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
- Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
- Doron Avramov & Si Cheng & Lior Metzker, 2023. "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability," Management Science, INFORMS, vol. 69(5), pages 2587-2619, May.
- Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2020.
"Dissecting Characteristics Nonparametrically,"
The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," NBER Working Papers 23227, National Bureau of Economic Research, Inc.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 6391, CESifo.
- Abhijit Gosavi, 2009. "Reinforcement Learning: A Tutorial Survey and Recent Advances," INFORMS Journal on Computing, INFORMS, vol. 21(2), pages 178-192, May.
- Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
- Lin William Cong & Ke Tang & Jingyuan Wang & Yang Zhang, 2021. "Deep Sequence Modeling: Development and Applications in Asset Pricing," Papers 2108.08999, arXiv.org.
- Kewei Hou & Haitao Mo & Chen Xue & Lu Zhang, 2021. "An Augmented q-Factor Model with Expected Growth [Abnormal returns to a fundamental analysis strategy]," Review of Finance, European Finance Association, vol. 25(1), pages 1-41.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Andrew KarolyiEditor, 2020.
"Dissecting Characteristics Nonparametrically,"
Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Andrew KarolyiEditor, 2020. "Dissecting Characteristics Nonparametrically," Review of Finance, European Finance Association, vol. 33(5), pages 2326-2377.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," NBER Working Papers 23227, National Bureau of Economic Research, Inc.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 6391, CESifo.
- Andreas Park & Hamid Sabourian, 2011.
"Herding and Contrarian Behavior in Financial Markets,"
Econometrica, Econometric Society, vol. 79(4), pages 973-1026, July.
- Park, A. & Sabourian, H., 2009. "Herding and Contrarian Behaviour in Financial Markets," Cambridge Working Papers in Economics 0939, Faculty of Economics, University of Cambridge.
- Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
- Victor DeMiguel & Alberto Martín-Utrera & Francisco J Nogales & Raman Uppal, 2020. "A Transaction-Cost Perspective on the Multitude of Firm Characteristics," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2180-2222.
- Hamsa Bastani & David Simchi-Levi & Ruihao Zhu, 2022. "Meta Dynamic Pricing: Transfer Learning Across Experiments," Management Science, INFORMS, vol. 68(3), pages 1865-1881, March.
- Gah-Yi Ban & Noureddine El Karoui & Andrew E. B. Lim, 2018. "Machine Learning and Portfolio Optimization," Management Science, INFORMS, vol. 64(3), pages 1136-1154, March.
- Hamsa Bastani, 2021. "Predicting with Proxies: Transfer Learning in High Dimension," Management Science, INFORMS, vol. 67(5), pages 2964-2984, May.
- Gu, Shihao & Kelly, Bryan & Xiu, Dacheng, 2021. "Autoencoder asset pricing models," Journal of Econometrics, Elsevier, vol. 222(1), pages 429-450.
- Sunder, Shyam, 1980. "Stationarity of Market Risk: Random Coefficients Tests for Individual Stocks," Journal of Finance, American Finance Association, vol. 35(4), pages 883-896, September.
- Mengmeng Ao & Li Yingying & Xinghua Zheng, 2019. "Approaching Mean-Variance Efficiency for Large Portfolios," The Review of Financial Studies, Society for Financial Studies, vol. 32(7), pages 2890-2919.
- David Silver & Aja Huang & Chris J. Maddison & Arthur Guez & Laurent Sifre & George van den Driessche & Julian Schrittwieser & Ioannis Antonoglou & Veda Panneershelvam & Marc Lanctot & Sander Dieleman, 2016. "Mastering the game of Go with deep neural networks and tree search," Nature, Nature, vol. 529(7587), pages 484-489, January.
- David Silver & Julian Schrittwieser & Karen Simonyan & Ioannis Antonoglou & Aja Huang & Arthur Guez & Thomas Hubert & Lucas Baker & Matthew Lai & Adrian Bolton & Yutian Chen & Timothy Lillicrap & Fan , 2017. "Mastering the game of Go without human knowledge," Nature, Nature, vol. 550(7676), pages 354-359, October.
- Arielle Anderer & Hamsa Bastani & John Silberholz, 2022. "Adaptive Clinical Trial Designs with Surrogates: When Should We Bother?," Management Science, INFORMS, vol. 68(3), pages 1982-2002, March.
- Victor DeMiguel & Alberto MartÃn-Utrera & Francisco J Nogales & Raman Uppal & Andrew KarolyiEditor, 2020.
"A Transaction-Cost Perspective on the Multitude of Firm Characteristics,"
Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2180-2222.
- Victor DeMiguel & Alberto Martín-Utrera & Francisco J Nogales & Raman Uppal & Andrew KarolyiEditor, 2020. "A Transaction-Cost Perspective on the Multitude of Firm Characteristics," Review of Finance, European Finance Association, vol. 33(5), pages 2180-2222.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Doron Avramov & Si Cheng & Lior Metzker, 2023. "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability," Management Science, INFORMS, vol. 69(5), pages 2587-2619, May.
- Ni, Xuanming & Zheng, Tiantian & Zhao, Huimin & Zhu, Shushang, 2023. "High-dimensional portfolio optimization based on tree-structured factor model," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
- Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
- Lioui, Abraham & Tarelli, Andrea, 2022. "Chasing the ESG factor," Journal of Banking & Finance, Elsevier, vol. 139(C).
- Doron Avramov & Si Cheng & Lior Metzker & Stefan Voigt, 2023. "Integrating Factor Models," Journal of Finance, American Finance Association, vol. 78(3), pages 1593-1646, June.
- Feng, Guanhao & He, Jingyu, 2022. "Factor investing: A Bayesian hierarchical approach," Journal of Econometrics, Elsevier, vol. 230(1), pages 183-200.
- 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).
- Hanauer, Matthias X. & Kalsbach, Tobias, 2023. "Machine learning and the cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 55(C).
- Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
- Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
- Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).
- Chulwoo Han, 2022. "Bimodal Characteristic Returns and Predictability Enhancement via Machine Learning," Management Science, INFORMS, vol. 68(10), pages 7701-7741, October.
- Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
- Pedro M. Mirete-Ferrer & Alberto Garcia-Garcia & Juan Samuel Baixauli-Soler & Maria A. Prats, 2022. "A Review on Machine Learning for Asset Management," Risks, MDPI, vol. 10(4), pages 1-46, April.
- Ma, Tian & Leong, Wen Jun & Jiang, Fuwei, 2023. "A latent factor model for the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 87(C).
- Lin William Cong & Guanhao Feng & Jingyu He & Xin He, 2022.
"Growing the Efficient Frontier on Panel Trees,"
NBER Working Papers
30805, National Bureau of Economic Research, Inc.
- Lin William Cong & Guanhao Feng & Jingyu He & Xin He, 2025. "Growing the Efficient Frontier on Panel Trees," Papers 2501.16730, arXiv.org, revised Feb 2025.
- Bagnara, Matteo, 2024. "The economic value of cross-predictability: A performance-based measure," SAFE Working Paper Series 424, Leibniz Institute for Financial Research SAFE.
- De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.
- Matteo Bagnara, 2024. "Asset Pricing and Machine Learning: A critical review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(1), pages 27-56, February.
- Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2025-02-17 (Big Data)
- NEP-CMP-2025-02-17 (Computational Economics)
- NEP-FMK-2025-02-17 (Financial Markets)
- NEP-RMG-2025-02-17 (Risk Management)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2501.17992. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.