This repository implements the Stock Forecasting Model based on research reports of Huatai Securities.
run the following command to install dependencies before running the code: pip install -r requirements.txt
The document/ folder contains more detail about research reports.
We have downloaded some data from Wind, and others will be calculated by ourselves. The data could be access from data_download/. This is a whole dataset.
For those which have previous records but do not have current records, we use forward fill and backward fill together.
For those which do not contain any value throughout our time range, we use the average of values of our stock pool.
We take two methods to label the data, the one is label the data by sorting the earning rate per month; and the other is mark the stock which has (earning rate > 1.1) as 1, and others as 0.
The all .py I have saved in stock_model, this is a temp folder which will be deleted later. And two trained model is in data and code is "5f2n" data_download -> data_prepare -> data_preprocess -> data_price -> data_label -> trainmodel