StockPricePrediction-master.zip_hidentt_python 股票_python 股票分析_分析

# Stock Market Price Predictor using Supervised Learning ### Aim To examine a number of different forecasting techniques to predict future stock returns based on past returns and numerical news indicators to construct a portfolio of multiple stocks in order to diversify the risk. We do this by applying supervised learning methods for stock price forecasting by interpreting the seemingly chaotic market data. ## Setup Instructions ``` $ workon myvirtualenv [Optional] $ pip install -r requirements.txt $ python scripts/Algorithms/regression_models.py <input-dir> <output-dir> ``` Download the Dataset needed for running the code from [here](https://drive.google.com/open?id=0B2lCmt16L_r3SUtrTjBlRHk3d1E). ## Project Concept Video [](https://www.youtube.com/watch?v=z6U0OKGrhy0) ### Methodology 1. Preprocessing and Cleaning 2. Feature Extraction 3. Twitter Sentiment Analysis and Score 4. Data Normalization 5. Analysis of various supervised learning methods 6. Conclusions ### Research Paper - [Machine Learning in Stock Price Trend Forecasting. Yuqing Dai, Yuning Zhang](http://cs229.stanford.edu/proj2013/DaiZhang-MachineLearningInStockPriceTrendForecasting.pdf) - [Stock Market Forecasting Using Machine Learning Algorithms. Shunrong Shen, Haomiao Jiang. Department of Electrical Engineering. Stanford University](http://cs229.stanford.edu/proj2012/ShenJiangZhang-StockMarketForecastingusingMachineLearningAlgorithms.pdf) - [How can machine learning help stock investment?, Xin Guo](http://cs229.stanford.edu/proj2015/009_report.pdf) ### Datasets used 1. http://www.nasdaq.com/ 2. https://in.finance.yahoo.com 3. https://www.google.com/finance ### Useful Links - **Slides**: http://www.slideshare.net/SharvilKatariya/stock-price-trend-forecasting-using-supervised-learning - **Video**: https://www.youtube.com/watch?v=z6U0OKGrhy0 - **Report**: https://github.com/scorpionhiccup/StockPricePrediction/blob/master/Report.pdf ### References - [Scikit-Learn](http://scikit-learn.org/stable/) - [Theano](http://deeplearning.net/software/theano/) - [Recurrent Neural Networks - LSTM Models](http://colah.github.io/posts/2015-08-Understanding-LSTMs/) - [ARIMA Models](http://people.duke.edu/~rnau/411arim.htm) - https://github.com/dv-lebedev/google-quote-downloader - [Book Value](http://www.investopedia.com/terms/b/bookvalue.asp) - http://www.investopedia.com/articles/basics/09/simplified-measuring-interpreting-volatility.asp - [Volatility](http://www.stock-options-made-easy.com/volatility-index.html) - https://github.com/dzitkowskik/StockPredictionRNN