Stock price forecasting is a long-standing challenge in computational finance, driven by the inherent randomness of markets and complex temporal patterns. While recent deep-learning models have raised forecasting accuracy by jointly modeling inter-stock and temporal price dynamics, they conflate inter-stock relationshi...
Heng-Yi Yang, Si-Da Lin, Yi-Yan Qi et al.· 0 citations
Quantitative trading is moving from isolated predictive models toward agentic workflows that combine reasoning, tool use, memory, and feedback. This survey reviews agentic quantitative trading across five stages: factor mining, signal discovery, portfolio construction, order execution, and risk management. We further e...
Feng-Rui Hua, Heng-Yi Yang, Xinqing Hao et al.· 1 citation
CostAda is introduced, a cost-calibrated adaptive controller built around a cost-calibrated frontier utility that reaches the strongest baseline's full-budget quality with at most half the budget on twelve of sixteen benchmark--backbone pairs while achieving the strongest mean final quality on all eight benchmarks unde...
Yansen Zhang, Yilu Liu, Tianyu Liu et al.· arXiv.org· 0 citations
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