ResDIF, a Residual Disentanglement framework for Interpretable financial time series Forecasting inspired by Asset Pricing Theory, is proposed and demonstrates that ResDIF outperforms existing methods while providing actionable interpretability support for refined portfolio risk management.
Chengwei Fu, Gang Xiao, Yu-Chao Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
Financial time series forecasting tasks, specifically stock trend prediction and market attribution, are essential for quantitative investment and risk control. However, these tasks suffer from low signal-to-noise ratios and non-stationarity, stemming from the coupling of hierarchical drivers: market trends, sector rot...
Chengwei Fu, Gang Xiao, Yuchao Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
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