Spotlight News Driven Quantitative Trading Based on Trajectory Optimization
Authors: Mengyuan Yang, Mengying Zhu, Qianqiao Liang, Xiaolin Zheng, MengHan Wang
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on three realworld datasets demonstrate our proposed model s superiority over the state-of-the-art NQT methods. |
| Researcher Affiliation | Collaboration | Mengyuan Yang1 , Mengying Zhu1 , Qianqiao Liang2 , Xiaolin Zheng1 , Meng Han Wang3 1Zhejiang University, Hangzhou, China 2MYbank, Ant Group, Hangzhou, China 3e Bay Inc., Shanghai, China |
| Pseudocode | Yes | Algorithm 1: Spotlight Trader s pipline |
| Open Source Code | No | The paper states: "We elaborate on the generation of trajectory-level offline data and provide the offline dataset in our Git Hub repository3." The associated footnote 3 points to "https://github.com/Yangmy412/Spotlight Trader Offline Dataset". This explicitly states the repository contains the *dataset*, not the source code for the model's methodology itself. |
| Open Datasets | Yes | We conduct experiments on three real-world datasets1. Twitter-SP500 is a public dataset consist stocks in S&P 500 index from U.S. market and tweets from Twitter. ... 1Data is collected from https://github.com/yumoxu/stocknet-dataset, http://www.51ifind.com.cn/, and https://aylien.com/. ... We elaborate on the generation of trajectory-level offline data and provide the offline dataset in our Git Hub repository3. 3https://github.com/Yangmy412/Spotlight Trader Offline Dataset |
| Dataset Splits | Yes | We divide each dataset into non-overlapping offline and online datasets, and the statistics of the datasets are presented in Table 1. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., GPU models, CPU types, memory) used to run the experiments. |
| Software Dependencies | No | The paper mentions software tools like "Fin BERT" and "Chinese-Fin BERT" with a GitHub link to FinBERT, but it does not specify version numbers for these or other key software dependencies (e.g., Python, PyTorch, TensorFlow) required for replication. |
| Experiment Setup | No | The parameter setting and implement details will be presented in a longer version of this paper. |