def main(data_path: str=None):
'''
Download daily price bars for base US stocks and indexes.
Parameters
----------
data_path:
path to folder in which downloaded data will be stored.
OR ``None`` (downloading path will be as ``daily_bars_data_path`` from
`~/.ml_investment/config.json`
'''
if data_path is None:
config = load_config()
data_path = config['daily_bars_data_path']
global _data_path
_data_path = data_path
tickers = load_tickers()['base_us_stocks']
index_tickers = ['SPY', 'TLT', 'QQQ']
os.makedirs(data_path, exist_ok=True)
p = Pool(8)
for _ in tqdm(p.imap(_single_ticker_download,
tickers + index_tickers)):
None
def main():
'''
Default model training. Resulted model weights directory path
can be changed in `~/.ml_investment/config.json` ``models_path``
'''
pipeline = MarketcapDownStdYahoo(pretrained=False)
tickers = load_tickers()['base_us_stocks']
result = pipeline.fit(tickers, median_absolute_relative_error)
print(result)
path = '{}/{}'.format(config['models_path'], OUT_NAME)
pipeline.export_core(path)
def main(data_path: str = None):
'''
Download quarterly and base data from https://finance.yahoo.com
Parameters
----------
data_path:
path to folder in which downloaded data will be stored.
OR ``None`` (downloading path will be as ``yahoo_data_path`` from
`~/.ml_investment/config.json`
'''
if data_path is None:
config = load_config()
data_path = config['yahoo_data_path']
tickers = load_tickers()['base_us_stocks']
downloader = YahooDownloaderV1()
downloader.download_quarterly_data(data_path, tickers)
downloader.download_base_data(data_path, tickers)
def main(data_path: str = None):
'''
Download quarterly and base data from https://finance.yahoo.com
Parameters
----------
data_path:
path to folder in which downloaded data will be stored.
OR ``None`` (downloading path will be as ``yahoo_data_path`` from
`~/.ml_investment/config.json`
'''
if data_path is None:
config = load_config()
data_path = config['yahoo_data_path']
global _data_path
_data_path = data_path
tickers = load_tickers()['base_us_stocks']
os.makedirs('{}/quarterly'.format(data_path), exist_ok=True)
os.makedirs('{}/base'.format(data_path), exist_ok=True)
p = Pool(12)
for _ in tqdm(p.imap(_single_ticker_download, tickers)):
None