Constructing Financial Sentimental Factors in Chinese Market Using Techniques of Natural Language Processing
Switch branches/tags
Nothing to show
Clone or download
Latest commit 3931146 Oct 16, 2018
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
codes add docs Aug 30, 2018
docs add docs Aug 30, 2018
figure add docs Aug 30, 2018
paper v4.3 Sep 21, 2018
README.md update README.md Aug 13, 2018
stopwords Add files via upload Oct 16, 2018

README.md


Constructing Financial Sentimental Factors in Chinese Market Using Techniques of Natural Language Processing

Introduction

Natural language processing, as one of the most promising fields of machine learning, has achieved great development recently and has been used in financial market. In this project, we are aiming to use an algotithm to analyze text data from influential financial websites to construct a sentimental factor which represents the daily sentiment of the market.
And papers here: English version and 中文版.

Experiment

Correlation Between Sentimental Factor and Chinese Markets

Time Series of Sentimental Factor and Chinese Markets

  • As for SSE,

  • As for SZSE,

Contribution

Contributors

  • Junfeng Jiang
  • Jiahao Li

Institutions

  • AI&FintechLab of Likelihood Technology
  • Sun Yat-sen University

Acknowledgement

pass

Set up

Python Version

  • 3.6

Modules needed

  • os
  • six
  • codec
  • logging
  • jieba
  • gensim
  • nltk
  • selenium
  • numpy
  • pandas
  • threading
  • datetime
  • time

Contact