{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:04:42Z","timestamp":1750309482713,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"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":[[2024,12,6]]},"DOI":"10.1145\/3709026.3709054","type":"proceedings-article","created":{"date-parts":[[2025,2,15]],"date-time":"2025-02-15T10:05:41Z","timestamp":1739613941000},"page":"505-512","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Application of Transformer-DDQN Model in Straddle Options Trading Strategy"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6954-8288","authenticated-orcid":false,"given":"Yiran","family":"Wan","sequence":"first","affiliation":[{"name":"College of Software, Nankai University, Tianjin, Tianjin, China"}]}],"member":"320","published-online":{"date-parts":[[2025,2,15]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Rasha AbdelKawy Walid\u00a0M Abdelmoez and Amin Shoukry. 2021. A synchronous deep reinforcement learning model for automated multi-stock trading. Progress in Artificial Intelligence 10 1 (2021) 83\u201397.","DOI":"10.1007\/s13748-020-00225-z"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-8201-6_5"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"crossref","unstructured":"Ronald\u00a0J Balvers and Yangru Wu. 2006. Momentum and mean reversion across national equity markets. Journal of Empirical Finance 13 1 (2006) 24\u201348.","DOI":"10.1016\/j.jempfin.2005.05.001"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","unstructured":"Menachem Brenner Ernest\u00a0Y Ou and Jin\u00a0E Zhang. 2006. Hedging volatility risk. Journal of Banking & Finance 30 3 (2006) 811\u2013821.","DOI":"10.1016\/j.jbankfin.2005.07.015"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"Alain\u00a0P Chaboud Benjamin Chiquoine Erik Hjalmarsson and Clara Vega. 2014. Rise of the machines: Algorithmic trading in the foreign exchange market. The Journal of Finance 69 5 (2014) 2045\u20132084.","DOI":"10.1111\/jofi.12186"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.5555\/2528260"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2015.7364089"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_3_1_10_2","volume-title":"Option, Future, and Other Derivatives","author":"C.Hull JoHn","year":"2008","unstructured":"JoHn C.Hull. 2008. Option, Future, and Other Derivatives. Prentice Hall."},{"key":"e_1_3_3_1_11_2","volume-title":"Technical Analysis of Stock Trends","author":"Edwards Robert\u00a0D.","year":"2007","unstructured":"Robert\u00a0D. Edwards, John Magee, and W.\u00a0H.\u00a0C. Bassetti. 2007. Technical Analysis of Stock Trends. AMACOM."},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/GCAT52182.2021.9587659"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"crossref","unstructured":"Abeyratna Gunasekarage and David\u00a0M Power. 2001. The profitability of moving average trading rules in South Asian stock markets. Emerging markets review 2 1 (2001) 17\u201333.","DOI":"10.1016\/S1566-0141(00)00017-0"},{"key":"e_1_3_3_1_14_2","volume-title":"Options investment management","author":"He Jinlin","year":"2022","unstructured":"Jinlin He. 2022. Options investment management. Southwestern University of Finance and Economics Press."},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Ali Hirsa Joerg Osterrieder Branka Hadji-Misheva and Jan-Alexander Posth. 2021. Deep reinforcement learning on a multi-asset environment for trading. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2106.08437 (2021).","DOI":"10.2139\/ssrn.3867800"},{"key":"e_1_3_3_1_16_2","unstructured":"Hsinan Hsu and Emily Ho. 2012. The Optimal Total Costs for Writing a Straddle. International Journal of Business and Economics 11 1 (2012) 13."},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"crossref","unstructured":"Taylan Kabbani and Ekrem Duman. 2022. Deep reinforcement learning approach for trading automation in the stock market. IEEE Access 10 (2022) 93564\u201393574.","DOI":"10.1109\/ACCESS.2022.3203697"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"crossref","unstructured":"Clemens Kownatzki Bluford Putnam and Arthur Yu. 2022. Case study of event risk management with options strangles and straddles. Review of Financial Economics 40 2 (2022) 150\u2013167.","DOI":"10.1002\/rfe.1143"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"crossref","unstructured":"Harvey Lapan Giancarlo Moschini and Steven\u00a0D Hanson. 1991. Production hedging and speculative decisions with options and futures markets. American Journal of Agricultural Economics 73 1 (1991) 66\u201374.","DOI":"10.2307\/1242884"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","unstructured":"Timothy\u00a0P Lillicrap Jonathan\u00a0J Hunt Alexander Pritzel Nicolas Heess Tom Erez Yuval Tassa David Silver and Daan Wierstra. 2015. Continuous control with deep reinforcement learning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1509.02971 (2015). 10.48550\/arXiv.1509.02971","DOI":"10.48550\/arXiv.1509.02971"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","unstructured":"Bryan Lim and Stefan Zohren. 2021. Time-series forecasting with deep learning: a survey. Philosophical Transactions of the Royal Society A 379 2194 (2021) 20200209. 10.1098\/rsta.2020.0209","DOI":"10.1098\/rsta.2020.0209"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","unstructured":"Mahdi Massahi and Masoud Mahootchi. 2024. A deep Q-learning based algorithmic trading system for commodity futures markets. Expert Systems with Applications 237 (2024) 121711. 10.1016\/j.eswa.2023.121711","DOI":"10.1016\/j.eswa.2023.121711"},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"Adrian Millea. 2021. Deep reinforcement learning for trading\u2014A critical survey. Data 6 11 (2021) 119.","DOI":"10.3390\/data6110119"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"publisher","unstructured":"Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra and Martin Riedmiller. 2013. Playing atari with deep reinforcement learning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1312.5602 (2013). 10.48550\/arXiv.1312.5602","DOI":"10.48550\/arXiv.1312.5602"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"crossref","unstructured":"Pratyush\u00a0Ranjan Mohapatra Ajaya\u00a0Kumar Parida Santosh\u00a0Kumar Swain and Santi\u00a0Swarup Basa. 2023. Gradient Boosting and LSTM Based Hybrid Ensemble Learning for Two Step Prediction of Stock Market. Journal of Advances in Information Technology 14 6 (2023).","DOI":"10.12720\/jait.14.6.1254-1260"},{"key":"e_1_3_3_1_26_2","volume-title":"Technical Analysis of the Futures Markets","author":"Murphy John\u00a0J.","year":"1986","unstructured":"John\u00a0J. Murphy. 1986. Technical Analysis of the Futures Markets. Prentice Hall Press."},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"crossref","unstructured":"Duy Nguyen Jingzhi Tie and Qing Zhang. 2014. An optimal trading rule under a switchable mean-reversion model. Journal of optimization theory and applications 161 (2014) 145\u2013163.","DOI":"10.1007\/s10957-012-0260-x"},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"crossref","unstructured":"Sathiyavathi\u00a0V Reshma\u00a0R Usha Naidu\u00a0S and SaiRamesh L. 2021. Stock market prediction using machine learning techniques. Advances in Parallel Computing Technologies and Applications 40 (2021) 331.","DOI":"10.3233\/APC210156"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"crossref","unstructured":"SP Shivaprasad E Geetha KL Raghavendra and M Rajeev. 2022. Choosing the right options trading strategy: Riskreturn trade-off and performance in different market conditions. Investment Management and Financial Innovations 19 2 (2022) 37\u201350.","DOI":"10.21511\/imfi.19(2).2022.04"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1002\/9781118662724"},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"crossref","unstructured":"Thibaut Th\u00e9ate and Damien Ernst. 2021. An application of deep reinforcement learning to algorithmic trading. Expert Systems with Applications 173 (2021) 114632.","DOI":"10.1016\/j.eswa.2021.114632"},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.1109\/RIVF55975.2022.10013787"},{"key":"e_1_3_3_1_33_2","doi-asserted-by":"crossref","unstructured":"Minh Tran Duc Pham-Hi and Marc Bui. 2023. Optimizing automated trading systems with deep reinforcement learning. Algorithms 16 1 (2023) 23.","DOI":"10.3390\/a16010023"},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10295"},{"key":"e_1_3_3_1_35_2","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan\u00a0N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_3_1_36_2","doi-asserted-by":"crossref","unstructured":"Jinxiao Wang Jiaxin Shi Dexin Han and Xiaoyu Zhao. 2019. Internet financial news and prediction for stock market: An empirical analysis of tourism plate based on LDA and SVM [J]. Journal of Advances in Information Technology Vol 10 3 (2019).","DOI":"10.12720\/jait.10.3.95-99"},{"key":"e_1_3_3_1_37_2","doi-asserted-by":"crossref","unstructured":"Christopher\u00a0JCH Watkins and Peter Dayan. 1992. Q-learning. Machine learning 8 (1992) 279\u2013292.","DOI":"10.1023\/A:1022676722315"},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"crossref","unstructured":"Xiao-Xu Yan Yuan-Biao Zhang Xin-Kun Lv Zi-Yu Li et\u00a0al. 2017. Improvement and test of stock index futures trading model based on Bollinger bands. International Journal of Economics and Finance 9 1 (2017) 78\u201387.","DOI":"10.5539\/ijef.v9n1p78"},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"publisher","unstructured":"Yiming Zhu. 2023. Stock Price Prediction based on LSTM and XGBoost Combination Model. Transactions on Computer Science and Intelligent Systems Research (2023) 94\u2013109. 10.62051\/z6dere47","DOI":"10.62051\/z6dere47"}],"event":{"name":"CSAI 2024: 2024 8th International Conference on Computer Science and Artificial Intelligence (CSAI)","acronym":"CSAI 2024","location":"Beijing China"},"container-title":["Proceedings of the 2024 8th International Conference on Computer Science and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3709026.3709054","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3709026.3709054","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:17:31Z","timestamp":1750295851000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3709026.3709054"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,6]]},"references-count":38,"alternative-id":["10.1145\/3709026.3709054","10.1145\/3709026"],"URL":"https:\/\/doi.org\/10.1145\/3709026.3709054","relation":{},"subject":[],"published":{"date-parts":[[2024,12,6]]},"assertion":[{"value":"2025-02-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}