{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T12:05:02Z","timestamp":1783166702286,"version":"3.54.6"},"publisher-location":"New York, NY, USA","reference-count":52,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671668","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"1211-1221","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3002-0743","authenticated-orcid":false,"given":"Jihyeong","family":"Jeon","sequence":"first","affiliation":[{"name":"Seoul National University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7749-0919","authenticated-orcid":false,"given":"Jiwon","family":"Park","sequence":"additional","affiliation":[{"name":"Seoul National University &amp; DeepTrade Technologies Inc., Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9887-2390","authenticated-orcid":false,"given":"Chanhee","family":"Park","sequence":"additional","affiliation":[{"name":"Seoul National University &amp; DeepTrade Technologies Inc., Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8774-6950","authenticated-orcid":false,"given":"U","family":"Kang","sequence":"additional","affiliation":[{"name":"Seoul National University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmoneco.2019.08.016"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11156-022-01099-z"},{"key":"e_1_3_2_2_3_1","volume-title":"Jamie Ryan Kiros, and Geoffrey E Hinton","author":"Ba Jimmy Lei","year":"2016","unstructured":"Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016. Layer normalization. arXiv preprint arXiv:1607.06450 (2016)."},{"key":"e_1_3_2_2_4_1","volume-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271","author":"Bai Shaojie","year":"2018","unstructured":"Shaojie Bai, J Zico Kolter, and Vladlen Koltun. 2018. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271 (2018)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/0022-0531(92)90099-4"},{"key":"e_1_3_2_2_6_1","volume-title":"An algorithm for the machine calculation of complex Fourier series. Mathematics of computation","author":"Cooley James W","year":"1965","unstructured":"James W Cooley and John W Tukey. 1965. An algorithm for the machine calculation of complex Fourier series. Mathematics of computation, Vol. 19, 90 (1965), 297--301."},{"key":"e_1_3_2_2_7_1","volume-title":"Bert: Pre-training of deep bidirectional Transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional Transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-019-03383-z"},{"key":"e_1_3_2_2_9_1","volume-title":"Addressing Function Approximation Error in Actor-Critic Methods. In International Conference on Machine Learning. https:\/\/api.semanticscholar.org\/CorpusID:3544558","author":"Fujimoto Scott","year":"2018","unstructured":"Scott Fujimoto, Herke van Hoof, and David Meger. 2018. Addressing Function Approximation Error in Actor-Critic Methods. In International Conference on Machine Learning. https:\/\/api.semanticscholar.org\/CorpusID:3544558"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/530"},{"key":"e_1_3_2_2_11_1","volume-title":"An introduction to wavelets and other filtering methods in finance and economics","author":"Genccay Ramazan","unstructured":"Ramazan Genccay, Faruk Selccuk, and Brandon J Whitcher. 2001. An introduction to wavelets and other filtering methods in finance and economics. Elsevier."},{"key":"e_1_3_2_2_12_1","volume-title":"Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor. ArXiv","author":"Haarnoja Tuomas","year":"2018","unstructured":"Tuomas Haarnoja, Aurick Zhou, P. Abbeel, and Sergey Levine. 2018. Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor. ArXiv, Vol. abs\/1801.01290 (2018). https:\/\/api.semanticscholar.org\/CorpusID:28202810"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_2_14_1","volume-title":"Complex-valued neural networks","author":"Hirose Akira","unstructured":"Akira Hirose. 2012. Complex-valued neural networks. Vol. 400. Springer Science & Business Media."},{"key":"e_1_3_2_2_15_1","volume-title":"Denoising diffusion probabilistic models. Advances in neural information processing systems","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. Advances in neural information processing systems, Vol. 33 (2020), 6840--6851."},{"key":"e_1_3_2_2_16_1","volume-title":"A comparison of LSTMs and attention mechanisms for forecasting financial time series. arXiv preprint arXiv:1812.07699","author":"Hollis Thomas","year":"2018","unstructured":"Thomas Hollis, Antoine Viscardi, and Seung Eun Yi. 2018. A comparison of LSTMs and attention mechanisms for forecasting financial time series. arXiv preprint arXiv:1812.07699 (2018)."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1111\/0022-1082.00207"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482483"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-6261.1993.tb04702.x"},{"key":"e_1_3_2_2_20_1","volume-title":"A deep reinforcement learning framework for the financial portfolio management problem. arXiv preprint arXiv:1706.10059","author":"Jiang Zhengyao","year":"2017","unstructured":"Zhengyao Jiang, Dixing Xu, and Jinjun Liang. 2017. A deep reinforcement learning framework for the financial portfolio management problem. arXiv preprint arXiv:1706.10059 (2017)."},{"key":"e_1_3_2_2_21_1","volume-title":"Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, Vol. 25 (2012)."},{"key":"e_1_3_2_2_22_1","volume-title":"Deep learning. nature","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. nature, Vol. 521, 7553 (2015), 436--444."},{"key":"e_1_3_2_2_23_1","volume-title":"Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971","author":"Lillicrap Timothy P","year":"2015","unstructured":"Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra. 2015. Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971 (2015)."},{"key":"e_1_3_2_2_24_1","volume-title":"Nature","volume":"518","author":"Mnih Volodymyr","year":"2015","unstructured":"Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis. 2015. Human-level control through deep reinforcement learning. Nature, Vol. 518, 7540 (2015), 529--533."},{"key":"e_1_3_2_2_25_1","volume-title":"Advances in Neural Information Processing Systems","volume":"11","author":"Moody John","year":"1998","unstructured":"John Moody and Matthew Saffell. 1998. Reinforcement learning for trading. Advances in Neural Information Processing Systems, Vol. 11 (1998)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557363"},{"key":"e_1_3_2_2_27_1","volume-title":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 1309--1318","author":"Jang Jun-Gi","year":"2021","unstructured":"Yong-chan Park, Jun-Gi Jang, and U Kang. 2021. Fast and accurate partial fourier transform for time series data. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 1309--1318."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-405X(88)90021-9"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jempfin.2006.07.002"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2018.2872600"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482494"},{"key":"e_1_3_2_2_32_1","volume-title":"International conference on machine learning. Pmlr, 387--395","author":"Silver David","year":"2014","unstructured":"David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, and Martin Riedmiller. 2014. Deterministic policy gradient algorithms. In International conference on machine learning. Pmlr, 387--395."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData55660.2022.10020720"},{"key":"e_1_3_2_2_34_1","volume-title":"Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track.","author":"Sun Shuo","year":"2023","unstructured":"Shuo Sun, Molei Qin, Haochong Xia, Chuqiao Zong, Jie Ying, Yonggang Xie, Lingxuan Zhao, Xinrun Wang, Bo An, et al. 2023. TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning. In Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"Shuo Sun Xinrun Wang Wanqi Xue Xiaoxuan Lou and Bo An. 2023. Mastering Stock Markets with Efficient Mixture of Diversified Trading Experts. In KDD. ACM 2109--2119.","DOI":"10.1145\/3580305.3599424"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557283"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"e_1_3_2_2_38_1","volume-title":"Attention is all you need. Advances in neural information processing systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599351"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"crossref","unstructured":"Haozhe Wang Chao Du Panyan Fang Li He Liang Wang and Bo Zheng. 2023. Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learning. In KDD. ACM 2314--2325.","DOI":"10.1145\/3580305.3599254"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/551"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5445"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330647"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16142"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16144"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"crossref","unstructured":"Mengyuan Yang Xiaolin Zheng Qianqiao Liang Bing Han and Mengying Zhu. 2022. A Smart Trader for Portfolio Management based on Normalizing Flows. IJCAI.","DOI":"10.24963\/ijcai.2022\/557"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5462"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611976700.60"},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467297"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098117"},{"key":"e_1_3_2_2_51_1","volume-title":"Deep learning for portfolio optimization. The Journal of Financial Data Science","author":"Zhang Zihao","year":"2020","unstructured":"Zihao Zhang, Stefan Zohren, and Stephen Roberts. 2020. Deep learning for portfolio optimization. The Journal of Financial Data Science (2020)."},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"crossref","unstructured":"Lifan Zhao Shuming Kong and Yanyan Shen. 2023. DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting. In KDD. ACM 3492--3503.","DOI":"10.1145\/3580305.3599315"}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Barcelona Spain","acronym":"KDD '24","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671668","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671668","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:06:00Z","timestamp":1750291560000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671668"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":52,"alternative-id":["10.1145\/3637528.3671668","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671668","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}