10 citations · 10 across the 6 of their papers we have counts for
7 papers
ReSGA: A Large Tail Risk Model for Learning Value-at-Risk and Expected Shortfall
Yichi Zhang, Ke Zhu, Zhoufan Zhu
Learning Value-at-Risk (VaR) and Expected Shortfall (ES) is important for managing financial risks effectively. Existing approaches with limited parameters are vulnerable to model…
Tensor dynamic conditional correlation model: A new way to pursuit "Holy Grail of investing"
Cheng Yu, Zhoufan Zhu, Ke Zhu
Style investing creates asset classes (or the so-called "styles") with low correlations, aligning well with the principle of "Holy Grail of investing" in terms of portfolio selecti…
Enhancement of price trend trading strategies via image-induced importance weights
Zhoufan Zhu, Ke Zhu
We open up the "black-box" to identify the predictive general price patterns in price chart images via the deep learning image analysis techniques. Our identified price patterns le…
FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models
Xin Guo, Haotian Xia, Zhaowei Liu +14
Large language models have demonstrated outstanding performance in various natural language processing tasks, but their security capabilities in the financial domain have not been…
Variance Control for Distributional Reinforcement Learning
Qi Kuang, Zhoufan Zhu, Liwen Zhang +1
Although distributional reinforcement learning (DRL) has been widely examined in the past few years, very few studies investigate the validity of the obtained Q-function estimator…
Big portfolio selection by graph-based conditional moments method
Zhoufan Zhu, Ningning Zhang, Ke Zhu
How to do big portfolio selection is very important but challenging for both researchers and practitioners. In this paper, we propose a new graph-based conditional moments (GRACE)…