# stock-market-prediction-using-deep-learning

**Repository Path**: xsongx/stock-market-prediction-using-deep-learning

## Basic Information

- **Project Name**: stock-market-prediction-using-deep-learning
- **Description**: Stock market and Twitter data
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-11-05
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

![ucl-logo](http://static.ucl.ac.uk/img/ucl-logo.svg)
## What is this project about?
This is a research project at the Department of Electronic & Electrical Engineering at University College London (UCL), supervised by Dr Miguel Rodrigues, named "Stock Market Prediction Using Deep Learning Techniques".

* Output data: next-day stock price trend (1 for rise, 0 for not rise)
* Input data
	* past price series (this can only generate about 50% predicting accuracy, because it carries little statistically-significant information)
	* characteristics of Twitter data related to stock (this can boost predicting accuracy because it carries more statistically-significant information)
		* daily volume of tweet messages
		* daily average sentiment score of tweet messages
* [My website about the correlation between stock market and Twitter](https://zhedongzheng.github.io)
<br><br>
![benchmark](https://github.com/zhedongzheng/stock-market-prediction-using-deep-learning/blob/master/util/benchmark.png)

## How to read the code?
![project-folder](https://github.com/zhedongzheng/stock-market-prediction-using-deep-learning/blob/master/util/project_folder.png)

## How to run the code?
* To run all the code, you need to pre-install the following libraries in Python 3:
  * numpy, pandas, matplotlib, scikit-learn (basic suite, most people already have)
  * [pandas-datareader](https://github.com/pydata/pandas-datareader) (for obtaining stock prices)
  * [opencv](http://opencv.org/) (for images)
  * [python-twitter](https://github.com/bear/python-twitter) (for visiting Twitter api)
  * [tensorflow r0.12](https://www.tensorflow.org/) (for advanced neural networks)
  * these libraries can all be easily installed through either `pip` or `conda`
* To run any code, you just need to download the folder "src", and change directory into the folder in the command line, then run the code by type "python xx.py"