Multiclass Sentiment Prediction for Stock Trading

2022-09-28 · Marshall R. McCraw

Python was used to download and format NewsAPI article data relating to 400 publicly traded, low cap. Biotech companies. Crowd-sourcing was used to label a subset of this data to then train and evaluate a variety of models to classify the public sentiment of each company. The best performing models were then used to show that trading entirely off public sentiment could provide market beating returns.

📄 PDF Abstract BibTeX arXiv:2210.00870

Code (0)

등록된 구현이 없습니다.

Tasks

Prediction

Trading the Twitter Sentiment with Reinforcement Learning

2018-01-07 · Catherine Xiao, Wanfeng Chen

This paper is to explore the possibility to use alternative data and artificial intelligence techniques to trade stocks. The efficacy of the daily Twitter sentiment on predicting the stock return is examined using machin…

BIG-bench Machine Learning Q-Learning reinforcement-learning Reinforcement Learning+1

Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning

2020-01-26 · Abhishek Nan, Anandh Perumal, Osmar R. Zaiane

Algorithmic trading, due to its inherent nature, is a difficult problem to tackle; there are too many variables involved in the real world which make it almost impossible to have reliable algorithms for automated stock t…

Algorithmic Trading Deep Reinforcement Learning Knowledge Graphs reinforcement-learning+4

Sentiment Analysis

Multiclass Sentiment Prediction for Stock Trading

Code (0)

Tasks

Similar Papers 제목 키워드 기반

Trading the Twitter Sentiment with Reinforcement Learning

Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning

Computing trading strategies based on financial sentiment data using evolutionary optimization

Internet sentiment exacerbates intraday overtrading, evidence from A-Share market

Analyst Reports and Stock Performance: Evidence from the Chinese Market