# deep-stock

**Repository Path**: physer/deep-stock

## Basic Information

- **Project Name**: deep-stock
- **Description**: Deep Learning for Stock Market
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 2
- **Forks**: 4
- **Created**: 2020-09-05
- **Last Updated**: 2023-04-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# `deep-stock`: Deep Learning for Stock Market <!-- omit in toc -->

- [Paper](#paper)
  - [Survey](#survey)
  - [Indicator](#indicator)
  - [Graph Neural Network & Knowledge Graph](#graph-neural-network--knowledge-graph)
  - [Public News & Social Media](#public-news--social-media)
  - [Model](#model)
- [Book](#book)
- [Data Source](#data-source)
- [Website](#website)
- [Others](#others)

## Paper
### Survey
* [Applications of deep learning in stock market prediction: recent progress](https://arxiv.org/abs/2003.01859)

### Indicator
* [Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding](https://www.kdd.org/kdd2019/accepted-papers/view/individualized-indicator-for-all-stock-wise-technical-indicator-optimizatio)
* [Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction](https://www.kdd.org/kdd2019/accepted-papers/view/investment-behaviors-can-tell-what-inside-exploring-stock-intrinsic-propert)

### Graph Neural Network & Knowledge Graph
* [Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis](https://arxiv.org/abs/1909.10660)
* [Temporal Relational Ranking for Stock Prediction](https://arxiv.org/abs/1809.09441) [\[code\]](https://github.com/fulifeng/Temporal_Relational_Stock_Ranking)
* [Incorporating Corporation Relationship via Graph Convolutional Neural Networks for Stock Price Prediction](https://dl.acm.org/doi/pdf/10.1145/3269206.3269269)
* [Knowledge-Driven Event Embedding for Stock Prediction](https://www.aclweb.org/anthology/C16-1201)
* [HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction](https://arxiv.org/abs/1908.07999) [\[code\]](https://github.com/dmis-lab/hats)

### Public News & Social Media
* [Hierarchical Complementary Attention Network for Predicting Stock Price Movements with News](https://dl.acm.org/doi/pdf/10.1145/3269206.3269286)
* [Stock Movement Prediction from Tweets and Historical Prices](https://www.aclweb.org/anthology/P18-1183) [\[code\]](https://github.com/yumoxu/stocknet-\[code\])
* [What You Say and How You Say It Matters: Predicting Financial Risk Using Verbal and Vocal Cues](https://www.aclweb.org/anthology/P19-1038)
* [Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction](https://arxiv.org/abs/1712.02136) [\[code\]](https://github.com/gkeng/Listening-to-Chaotic-Whishpers--\[code\])

### Model
* [Enhancing Stock Movement Prediction with Adversarial Training](https://www.ijcai.org/Proceedings/2019/0810.pdf) [\[code\]](model/adv-alstm.py)
* [Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction](https://www.kdd.org/kdd2019/accepted-papers/view/multi-task-recurrent-neural-network-and-higher-order-markov-random-fields-f)
* [Stock Price Prediction via Discovering Multi-Frequency Trading Patterns](http://www.eecs.ucf.edu/~gqi/publications/kdd2017_stock.pdf) [\[code\]](model/sfm.py)
* [A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction](https://arxiv.org/abs/1704.02971) [\[code\]](model/da-rnn.py)


## Book
* [The Econometrics of Financial Markets](https://link.zhihu.com/?target=https%3A//item.jd.com/1107212917.html)
* [Advances in Financial Machine Learning](https://link.zhihu.com/?target=https%3A//item.jd.com/39205783211.html)
* [Financial Decisions and Markets: A Course in Asset Pricing](https://www.semanticscholar.org/paper/Financial-Decisions-and-Markets%3A-A-Course-in-Asset-Campbell/f413566883c4be4f8e55e275e3f70b2aebf9e8fc)


## Data Source
* [Tushare](http://tushare.org/): 一个免费、开源的python财经数据接口包。
* [stocknet-dataset](https://github.com/yumoxu/stocknet-dataset): A comprehensive dataset for stock movement prediction from tweets and historical stock prices.
* [EarningsCall_Dataset](https://github.com/GeminiLn/EarningsCall_Dataset): The earnings conference call dataset of S&P 500 companies
* [新浪财经A股个股新闻数据](https://opendata.pku.edu.cn/dataset.xhtml?persistentId=doi:10.18170/DVN/NL8XVL): 新浪财经网全部A股的个股新闻数据；时间范围：2015-11-01 至2018-01-12；


## Website
* [雪球](https://xueqiu.com/): 聪明的投资者都在这里
* [Morningstar](https://www.morningstar.com/): Empowering Investor Success
* [Yahoo Finance](http://finance.yahoo.com/): Stock Market Live, Quotes, Business & Finance News
* [Seeking Alpha](https://seekingalpha.com/): Stock Market Insights
* [EarningsCast](https://earningscast.com/): Latest Earnings Calls, EarningsCast - Upcoming Earnings Calls


## Others
* 知乎专栏：[人工智能与量化投资](https://zhuanlan.zhihu.com/intro-to-quant)、[宏观经济算命师的解签](https://zhuanlan.zhihu.com/hgjjsms)、[黄金矿工](https://zhuanlan.zhihu.com/c_1234153682486874112)
* 微信公众号：农药兑水
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* 微信讨论群因为二维码会过期，大家可以加我微信申请进群，请备注一下姓名-机构-方向:
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