gkeng / Listening-to-Chaotic-Whishpers--Code
☆59Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for Listening-to-Chaotic-Whishpers--Code
- TensorFlow implementation of Z. Hu et al. "Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Predict…☆29Updated 2 months ago
- Code for stock movement prediction from tweets and historical stock prices.☆204Updated 5 years ago
- A deep learning method for event driven stock market prediction. Deep learning is useful for event-driven stock price movement predictio…☆204Updated 5 years ago
- Deep Time Series Code (Stock Sentiment Prediction)☆81Updated 6 years ago
- Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019☆167Updated 5 years ago
- ☆71Updated 4 years ago
- HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction☆151Updated 4 years ago
- Implementation of "Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading." In Findings of ACL2021☆101Updated 3 years ago
- Try to implement Hybrid Attention Net mentioned in 'Listening to Chaotic Whispers'☆11Updated 3 years ago
- In this project, my team and I use Google's new BERT model to predict the S&P 500 using SEC 8-K filings☆48Updated 5 years ago
- ☆49Updated 2 years ago
- ☆53Updated 4 years ago
- Applying Deep Learning and NLP in Quantitative Trading☆102Updated 5 years ago
- Stock Price prediction using news data. The datasets used consists news and stock price data from 2008 to 2016. The polarity(Subjectivity…☆47Updated 6 years ago
- ☆61Updated 3 years ago
- Using past price data and sentiment analysis from news and other documents to predict the S&P500 index using a LSTM RNN. Idea replicated …☆32Updated 6 months ago
- Replication of Time Series Momentum strategy by Moskowtiz, Ooi, Pedersen, 2011.☆61Updated last year
- The code and datasets of "Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction"☆52Updated 3 years ago
- Improve S&P 500 stock price prediction (random forest and gradient boosting trees) with time series similarity measurements: DTW, SAX, co…☆94Updated 3 years ago
- Code for WWW-20 Paper: HTML: Hierarchical Transformer-based Multi-task Learning for Volatility Prediction☆56Updated 10 months ago
- The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using t…☆58Updated 3 years ago
- RNN - Stock Prediction Model using Attention Multilayer Recurrent Neural Networks with LSTM Cells☆39Updated 7 years ago
- Model news data in short, medium and long term for stock price trend prediction☆20Updated 6 years ago
- Embedding stocks to vectors based on the price history☆63Updated 8 years ago
- Stock prediction from news with deep learning☆8Updated 6 years ago
- predict the price trend of individual stocks using deep learning and natural language processing☆74Updated 6 years ago
- ☆98Updated 3 years ago
- A genetic programming algorithm used for generating alpha factors in the multi-factor investment strategy☆56Updated 3 years ago
- Implementation of Events Embedding Network by Ding et a 2015 https://www.ijcai.org/Proceedings/15/Papers/329.pdf☆21Updated 7 years ago
- ☆131Updated last year