Group 1 - The report emphasizes the importance of identifying the current market state, either "trend" or "oscillation," to aid in timing and stock selection strategies [2][6][48] - A two-phase, layered diagnostic algorithm is employed to define the index state, utilizing a "zig-zag" algorithm combined with breakpoint correction for historical performance analysis [2][9][10] - The study constructs six feature variables from price, volume, and volatility dimensions to capture market trend changes and emotional fluctuations, achieving over 80% accuracy in predicting future market states with various machine learning models [2][26][27] Group 2 - The report outlines a dynamic position management strategy based on model predictions, switching between "momentum" logic in trend states and "mean reversion" logic in oscillation states [2][46] - The decision tree model-driven strategy yielded a total return of 77.26% and a Sharpe ratio of 1.12 during the backtesting period from 2020 to 2025, significantly outperforming the buy-and-hold benchmark [2][49][70] - The report highlights the effectiveness of the decision tree model in accurately signaling market states, leading to robust returns and risk management during market downturns [2][46][70]

近日，浦发银行在伦敦证券交易所集团（LSEG）主办的2025年金融量化创新大赛中荣获"量化策略奖——最佳固收策略奖"。 本次比赛为伦敦证券交易所集团（LSEG）在中国举办的首届金融量化创新比赛，旨在激发国内金融机构在FICC（固定收益、外汇及大宗商品业务）领域 的量化投资潜力，推动策略设计、量化研究、数据探索方面的经验共享。自今年4月比赛启动以来，吸引了多家核心中资与外资机构参与。浦发银行在30 余项参赛成果中脱颖而出，荣获"最佳固收策略奖",并受邀在颁奖典礼上分享量化交易领域的实践经验。 随着国内金融市场的基础设施建设趋于完善、投资者类型日渐多元、传统交易难度逐步提升。浦发银行将持续推进"数智化"战略，积极自我革新，借助人 工智能等创新领域的先进实践，开展研究和部署量化交易策略，深入推进智能投研和量化交易建设，更好地践行债券市场核心做市商职责，为助力中国债 券市场发展贡献浦发力量。 ...