In this project you need to demonstrates the future price prediction for different stocks using Recurrent Neural Networks.
Acknowledgements
This dataset for this project was obtained from the New York Stock Exchange dataset in Kaggle. You can find more about it from their competition page. You can find out more about the dataset from it's Kaggle page.
You can find the data in the following path:
/cxldata/datasets/project/ny_stock_prediction
The dataset consists of 2 files, prices-split-adjusted.csv and fundamentals.csv. Here is a brief description of the content of the files:
prices-split-adjusted.csv: This file contains daily stock prices with added adjustments for splits. Most of data spans from 2010 to the end 2016, for companies new on stock market date range is shorter. There have been approx. 140 stock splits in that time, this set doesn't account for that.
fundamentals.csv: This file contains the metrics extracted from annual SEC 10K fillings (2012-2016), should be enough to derive most of popular fundamental indicators.
You can follow these steps to complete this project, however, you are free to test your own models:
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