most citedA Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks

4 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

q-fin.CP2023★ 1 cited

Stock Market Sentiment Classification and Backtesting via Fine-tuned BERT

Jiashu Lou

With the rapid development of big data and computing devices, low-latency automatic trading platforms based on real-time information acquisition have become the main components of…

q-fin.CP2022★ 2 cited

Bi-LSTM Price Prediction based on Attention Mechanism

Jiashu Lou, Leyi Cui, Ye Li

With the increasing enrichment and development of the financial derivatives market, the frequency of transactions is also faster and faster. Due to human limitations, algorithms an…

q-fin.CP2022★ 4 cited

A Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks

Jie Zou, Jiashu Lou, Baohua Wang +1

More and more stock trading strategies are constructed using deep reinforcement learning (DRL) algorithms, but DRL methods originally widely used in the gaming community are not di…

q-bio.MN2022

Reconstruction of gene regulatory network via sparse optimization

Jiashu Lou, Leyi Cui, Wenxuan Qiu

In this paper, we tested several sparse optimization algorithms based on the public dataset of the DREAM5 Gene Regulatory Network Inference Challenge. And we find that introducing…

cs.CV2022★ 1 cited

Palm Vein Recognition via Multi-task Loss Function and Attention Layer

Jiashu Lou, Jie zou, Baohua Wang

With the improvement of arithmetic power and algorithm accuracy of personal devices, biological features are increasingly widely used in personal identification, and palm vein reco…