> pip install -r requirements.txt> export API_TOKEN=[Your Tiingo API token here]
> python ./script/download_data.py --helpusage: download_data.py [-h] [--tickers TICKERS] [--year YEAR] --token TOKEN
[--path PATH] [--freq FREQ]
Download & save stock price data
optional arguments:
-h, --help show this help message and exit
--tickers TICKERS Tickers (comma separated values). Eg. AAPL,MSFT,WMT,GS.
Default S&P500 (Will download all stock data)
--year YEAR Year (to download data). Default: 2019
--token TOKEN API token
--path PATH Path to store data. Default: ./data
--freq FREQ Frequency ([min], [hour]) in which you want data
resampled. Eg. 1min 5min 1hour. Default: 1min
Example:
> python ./script/download_data.py \
--tickers=AAPL,MSFT,WMT,AMZN,GOOG,BLK,JPM,GS,NFLX,KO \
--year=2019 \
--token=$API_TOKEN \
--path=./data \
--freq=1min-
Arévalo, A., Niño, J., Hernández, G. and Sandoval, J., 2020. High-Frequency Trading Strategy Based On Deep Neural Networks.
-
Zhou, X., Pan, Z., Hu, G., Tang, S. and Zhao, C., 2018. Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets. Mathematical Problems in Engineering, 2018, pp.1-11.
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