Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/sangyx/deep-finance

Datasets, papers and books on AI & Finance.
https://github.com/sangyx/deep-finance

List: deep-finance

artificial-intelligence awesome-list deep-learning finance fintech paper-list

Last synced: about 1 month ago
JSON representation

Datasets, papers and books on AI & Finance.

Awesome Lists containing this project

README 

        
# `deep-finance`: Deep Learning for Finance



> This repository is no longer updated since the interesting works in this field are rare. If you are really interested in Deep Learning & Finance, it's better to read high quality papers on **Time Series Forecasting**, **Natural Language Processing**, **Graph Neural Networks**, **Recommendation System** and **Finance**, whose ideas and models may be more helpful.



## [Content](#content)



1. Dataset 

2. Paper



     2.1 Stock Prediction

     2.2 Portfolio Selection



     2.3 Risk Management

     2.4 Finance NLP



     2.5 Blockchain

     2.6 Market Maker



     2.7 Others

    



3. Book

4. Disscussion Group



## [Dataset](#content)

| Dataset                                                                                              | Task                                  | Describe                                                                                                                                                                   |

| ---------------------------------------------------------------------------------------------------- | ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |

| [StockNet](https://github.com/yumoxu/stocknet-dataset)                                               | Stock Movement Prediction             | A comprehensive dataset for stock movement prediction from tweets and historical stock prices.                                                                             |

| [EarningsCall](https://github.com/GeminiLn/EarningsCall_Dataset)                                     | Stock Risk Prediction                 | The earnings conference call dataset of S&P 500 companies.                                                                                                                 |

| [FinSBD-2019](https://sites.google.com/nlg.csie.ntu.edu.tw/finnlp/)                                  | Financial Sentence Boundary Detection | The FinSBD-2019 dataset contains financial text that had been pre-segmented automatically, which can be used for Financial Sentence Boundary Detection.                    |

| [Financial Phrasebank]( https://www.researchgate.net/publication/251231364_FinancialPhraseBank-v10/) | Financial Sentence Boundary Detection | Financial Phrasebank dataset consists of 4845 English sentences selected randomly from financial news found on LexisNexis database.                                        |

| [FiQA ](https://sites.google.com/view/fiqa/home/)                                                    | Financial Question Answering          | Financial QA dataset is built by crawling Stack exchange posts under the Investment topic in the period between 2009 and 2017.                                             |

| [FiQA SA](https://sites.google.com/view/fiqa/home/)                                                  | Financial Sentiment Analysis          | FiQA SA dataset includes two types of discourse: financial news headlines and financial microblogs, with manually annotated target entities, sentiment scores and aspects. |



## [Paper](#content)

### [Stock Prediction](#content)



1. **Applications of deep learning in stock market prediction: recent progress**. arxiv 2020. [paper](https://arxiv.org/abs/2003.01859)

   

   *Weiwei Jiang*



2. **Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding**. KDD 2019. [paper](https://www.kdd.org/kdd2019/accepted-papers/view/individualized-indicator-for-all-stock-wise-technical-indicator-optimizatio)



    *Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin and Tie-Yan Liu*



3. **Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction**. KDD 2019. [paper](https://www.kdd.org/kdd2019/accepted-papers/view/investment-behaviors-can-tell-what-inside-exploring-stock-intrinsic-propert)



    *Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing and Tie-Yan Liu*



4. **Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis**. CoRR 2019. [paper](https://arxiv.org/abs/1909.10660)



    *Daiki Matsunaga, Toyotaro Suzumura, Toshihiro Takahashi*



5. **Temporal Relational Ranking for Stock Prediction**. TOIS 2019 . [paper](https://arxiv.org/abs/1809.09441)



    *Fuli Feng, Xiangnan He, Xiang Wang, Cheng Luo, Yiqun Liu, Tat-Seng Chua*



6. **Incorporating Corporation Relationship via Graph Convolutional Neural Networks for Stock Price Prediction**. CIKM 2018 . [paper](https://dl.acm.org/doi/pdf/10.1145/3269206.3269269)



    *Yingmei Chen, Zhongyu Wei, Xuanjing Huang*



7. **Knowledge-Driven Event Embedding for Stock Prediction**. COLING 2016 . [paper](https://www.aclweb.org/anthology/C16-1201)



    *Xiao Ding, Yue Zhang, Ting Liu, Junwen Duan*



8. **HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction**. arxiv 2019 . [paper](https://arxiv.org/abs/1908.07999) 



    *Raehyun Kim, Chan Ho So, Minbyul Jeong, Sanghoon Lee, Jinkyu Kim, Jaewoo Kang*



9. **Hierarchical Complementary Attention Network for Predicting Stock Price Movements with News** . CIKM 18 . [paper](https://dl.acm.org/doi/pdf/10.1145/3269206.3269286)



    *Qikai Liu, Xiang Cheng, Sen Su, Shuguang Zhu*



10. **Stock Movement Prediction from Tweets and Historical Prices** . ACL 2018 . [paper](https://www.aclweb.org/anthology/P18-1183) 



    *Yumo Xu, Shay B. Cohen*



 more 



11. **What You Say and How You Say It Matters: Predicting Financial Risk Using Verbal and Vocal Cues** . ACL 2019 . [paper](https://www.aclweb.org/anthology/P19-1038)



    *Yu Qin, Yi Yang*



12. **Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction** . WSDM 2018 . [paper](https://arxiv.org/abs/1712.02136)



    *Ziniu Hu, Weiqing Liu, Jiang Bian, Xuanzhe Liu*



13. **Enhancing Stock Movement Prediction with Adversarial Training** . IJCAI 2019 . [paper](https://www.ijcai.org/Proceedings/2019/0810.pdf) 



    *Fuli Feng, Huimin Chen, Xiangnan He, Ji Ding, Maosong Sun, Tat-Seng Chua*



14. **Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction** . KDD 2019 . [paper](https://www.kdd.org/kdd2019/accepted-papers/view/multi-task-recurrent-neural-network-and-higher-order-markov-random-fields-f)



    *Chang Li (School of Computer Science University of Sydney);Dongjin Song ( Capital Market CRC);Dacheng Tao (NEC);*



15. **Stock Price Prediction via Discovering Multi-Frequency Trading Patterns** . KDD 2017 . [paper](http://www.eecs.ucf.edu/~gqi/publications/kdd2017_stock.pdf) 



    *Liheng Zhang, Charu C. Aggarwal, Guojun Qi*



16. **A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction** . IJCAI 2017 . [paper](https://arxiv.org/abs/1704.02971) 



    *Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Guofei Jiang, Garrison Cottrell*



17. **Modeling the Stock Relation with Graph Network for Overnight Stock Movement Prediction**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0626.pdf)



    *Wei Li, Ruihan Bao, Keiko Harimoto, Deli Chen, Jingjing Xu, Qi Su*



18. **A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0614.pdf)



    *Lu Bai, Lixin Cui, Yue Wang, Yuhang Jiao, Edwin R. Hancock*



19. **Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0640.pdf)

 

    *Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Jian Guo*



20. **Multi-scale Two-way Deep Neural Network for Stock Trend Prediction**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0628.pdf)



    *Guang Liu, Yuzhao Mao, Qi Sun, Hailong Huang, Weiguo Gao, Xuan Li, Jianping Shen, Ruifan Li, Xiaojie Wang*



### [Portfolio Selection](#content)

1. **A Two-level Reinforcement Learning Algorithm for Ambiguous Mean-variance Portfolio Selection Problem**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0624.pdf)



    *Xin Huang, Duan Li*



2. **Financial Thought Experiment: A GAN-based Approach to Vast Robust Portfolio Selection**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0637.pdf)



    *Chi Seng Pun, Lei Wang, Hoi Ying Wong*



3. **MAPS: Multi-Agent reinforcement learning-based Portfolio management System.**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0623.pdf)



    *Jinho Lee, Raehyun Kim, Seok-Won Yi, Jaewoo Kang*



4. **Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0646.pdf)



    *Mengying Zhu, Xiaolin Zheng, Yan Wang, Qianqiao Liang, Wenfang Zhang*



5. **RM-CVaR: Regularized Multiple β-CVaR Portfolio**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0629.pdf)



    *Kei Nakagawa, Shuhei Noma, Masaya Abe*



6. **Relation-Aware Transformer for Portfolio Policy Learning**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0641.pdf)

   

    *Ke Xu, Yifan Zhang, Deheng Ye, Peilin Zhao, Mingkui Tan*



7. **Vector Autoregressive Weighting Reversion Strategy for Online Portfolio Selection**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0616.pdf)

    

    *Xia Cai*



8. **An End-to-End Optimal Trade Execution Framework based on Proximal Policy Optimization**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0627.pdf)

    

    *Siyu Lin, Peter A. Beling*



### [Risk Management](#content)

1. **Financial Risk Analysis for SMEs with Graph-based Supply Chain Mining**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0643.pdf)



    *Shuo Yang, Zhiqiang Zhang, Jun Zhou, Yang Wang, Wang Sun, Xingyu Zhong, Yanming Fang, Quan Yu, Yuan Qi*



2. **Federated Meta-Learning for Fraudulent Credit Card Detection**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0642.pdf)

    

    *Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang*



3. **The Behavioral Sign of Account Theft: Realizing Online Payment Fraud Alert**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0636.pdf)

    

    *Cheng WANG*



4. **Phishing Scam Detection on Ethereum: Towards Financial Security for Blockchain Ecosystem**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0621.pdf)

    

    *Weili Chen, Xiongfeng Guo, Zhiguang Chen, Zibin Zheng, Yutong Lu*



5. **Interpretable Multimodal Learning for Intelligent Regulation in Online Payment Systems**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0645.pdf)

    

    *Shuoyao Wang, Diwei Zhu*



6. **Risk Guarantee Prediction in Networked-Loans**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0618.pdf)

    

    *Dawei Cheng, Xiaoyang Wang, Ying Zhang, Liqing Zhang*



7.  **Risk-Averse Trust Region Optimization for Reward-Volatility Reduction**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0632.pdf)

    

    *Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori, Matteo Papini, Marcello Restelli*



8. **Spotlighting Anomalies using Frequent Patterns**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/kuchar18a/kuchar18a.pdf)

    

    *Jaroslav Kuchař, Vojtěch Svátek*

    

9. **Collective Fraud Detection Capturing Inter-Transaction Dependency**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/cao18a/cao18a.pdf)

    

    *Bokai Cao, Mia Mao, Siim Viidu, Philip S. Yu*

    

10. **Automated System for Data Attribute Anomaly Detection**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/love18a/love18a.pdf)

    

    *Nalin Aggarwal, Alexander Statnikov, Chao Yuan*



 more 



11. **Sleuthing for adverse outcomes using anomaly detection**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/miller18a/miller18a.pdf)

    

    *Michelle Miller, Robert Cezeaux*

    

12. **Anomaly detection with density estimation trees**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/ram18a/ram18a.pdf)

    

    *Parikshit Ram, Alexander Gray*

    

13. **Binned Kernels for Anomaly Detection in Multi-timescale Data using Gaussian Processes**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/adelsberg18a/adelsberg18a.pdf)

    

    *Matthew van Adelsberg, Christian Schwantes*

    

14. **Ensemble-based Anomaly Detection Using Cooperative Agreement**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/kashef18a/kashef18a.pdf)

    

    *Rasha Kashef*

    

15. **Real-time anomaly detection system for time series at scale**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/toledano18a/toledano18a.pdf)

    

    *Ira Cohen, Meir Toledano, Yonatan Ben Simhon, Inbal Tadeski*

    

16. **PD-FDS: Purchase Density based Online Credit Card Fraud Detection System**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/ki18a/ki18a.pdf)

    

    *Youngjoon Ki, Ji Won Yoon*

    

17. **Deep Learning to Detect Treatment Fraud amongst Healthcare Providers**. KDD 2017: Anomaly Detection in Finance . [paper](http://proceedings.mlr.press/v71/lasaga18a/lasaga18a.pdf)

    

    *Daniel Lasaga, Prakash Santhana*



    



### [Finance NLP](#content)

1. **Deep Semantic Compliance Advisor for Unstructured Document Compliance Checking**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0613.pdf)



    *Honglei Guo, Bang An, Zhili Guo, Zhong Su*



2. **"The Squawk Bot": Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0634.pdf)



    *Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos*



3. **A Unified Model for Financial Event Classification, Detection and Summarization**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0644.pdf)



    *Quanzhi Li, Qiong Zhang*



4. **F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification**. IJCAI 2020: AI in FinTech . paper[](https://www.ijcai.org/Proceedings/2020/0619.pdf)



    *Xin Liang, Dawei Cheng, Fangzhou Yang, Yifeng Luo, Weining Qian, Aoying Zhou*



5. **Financial Risk Prediction with Multi-Round Q&A Attention Network**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0631.pdf)



    *Zhen Ye, Yu Qin, Wei Xu*



6. **FinBERT: A Pre-trained Financial Language Representation Model for Financial Text Mining**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0622.pdf)



    *Zhuang Liu, Degen Huang, Kaiyu Huang, Zhuang Li, Jun Zhao*



7. **Two-stage Behavior Cloning for Spoken Dialogue System in Debt Collection**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0639.pdf)



    *Zihao Wang, Jia Liu, Hengbin Cui, Chunxiang Jin, Minghui Yang, Yafang Wang, Xiaolong Li, Renxin Mao*



### [Blockchain](#content)

1. **BitcoinHeist: Topological Data Analysis for Ransomware Prediction on the Bitcoin Blockchain**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0612.pdf)



    *Cuneyt G. Akcora, Yitao Li, Yulia R. Gel, Murat Kantarcioglu*



2. **SEBF: A Single-Chain based Extension Model of Blockchain for Fintech**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0620.pdf)



    *Yimu Ji, Weiheng Gu, Fei Chen, Xiaoying Xiao, Jing Sun, Shangdong Liu, Jing He, Yunyao Li, Kaixiang Zhang, Fen Mei, Fei Wu*



3. **Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0635.pdf)



    *Naman Goel, Cyril van Schreven, Aris Filos-Ratsikas, Boi Faltings*



### [Market Maker](#content)

1. **Market Manipulation: An Adversarial Learning Framework for Detection and Evasion**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0638.pdf)



    *Xintong Wang, Michael P. Wellman*



2. **Data-Driven Market-Making via Model-Free Learning**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0615.pdf)



    *Yueyang Zhong, YeeMan Bergstrom, Amy Ward*



3. **Robust Market Making via Adversarial Reinforcement Learning**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0633.pdf)



    *Thomas Spooner, Rahul Savani*



### [Others](#content)

1. **IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0625.pdf)



    *Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu*



2. **Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance**. IJCAI 2020: AI in FinTech . [paper](https://arxiv.org/abs/1910.09357)



    *Di Chen, Yada Zhu, Xiaodong Cui, Carla P. Gomes*



3. **WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series**. IJCAI 2020: AI in FinTech . [paper](https://www.ijcai.org/Proceedings/2020/0630.pdf)



    *Michael Poli, Jinkyoo Park, Ilija Ilievski*



## [Book](#content)

1. [The Econometrics of Financial Markets](https://item.jd.com/1107212917.html)



    *John Y. Campbell, Andrew W. Lo, A. Craig Mackinlay*



2. [Advances in Financial Machine Learning](https://item.jd.com/39205783211.html)



    *Marcos Lopez de Prado*



3. [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)



    *J. Campbell*



## [Disscussion Group](#content)

对于AI+Finance方向感兴趣的童鞋，欢迎扫描下面的二维码学习交流：