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Stock price prediction using ensemble MLP in PyTorch.

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# mlp_stock
Stock price prediction using ensemble MLP in PyTorch.

Predict the index changes by the fluctuation of index and volume in the last 5 days.  
Train data is the daily CISSM (Compositional Index of Shenzhen Stock Market) from 2005/01 to 2015/06, the test data is from 2015/07 to 2017/05.

## Requirements
* Pytorch
* Numpy
* Pandas
* Matplotlib

## Usage
1. Run `train_net.py` to train a group of MLPs with `sz_train.csv`, saved in `/MLPs`.
2. Run `test_net.py` to predict stock market trend (in `sz_test.csv`) using ensemble MLP.

## Result
The train error rate (black) and test error rate (red) of a single MLP, changing with epoches.
![](https://github.com/melissa135/mlp_stock/blob/master/error_rate.png)

The red line is asset sequence if we buy/sell CISSM-ETF according to our ensemble MLP, comparing with CISSM (black).
![](https://github.com/melissa135/mlp_stock/blob/master/asset.png)

## Tips
* Train samples are limited, using drop-out and early-stop to prevent overfitting.  
* Simulated trading using this strategy, see https://xueqiu.com/P/ZH931230 .

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