mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-28 03:08:01 +00:00
Mark Aron Szulyovszky
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
#%%
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import pandas as pd
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from utils.get_prices import get_crypto_price_crypto_compare, get_stock_price_av
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#%%
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crypto_tickers = ["BTC", "ETH", "BNB", "ADA", "SOL", "XRP", "DOT", "LTC", "UNI", "TRX", "FIL"]
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etf_tickers = ["GLD", "IEF", "TLT", "SPY", "QQQ"]
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tickers = crypto_tickers + etf_tickers
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add_features = True
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#%%
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for ticker in tickers:
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print("Fetching ", ticker)
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if ticker in crypto_tickers:
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df = get_crypto_price_crypto_compare(ticker, "USD", 1500)
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else:
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df = get_stock_price_av(ticker, "2017-11-10")
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df['returns'] = df['close'].pct_change()
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if add_features:
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# volatility (10, 20, 30 days)
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df['vol_10'] = df['returns'].rolling(10).std()*(252**0.5)
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df['vol_20'] = df['returns'].rolling(20).std()*(252**0.5)
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df['vol_30'] = df['returns'].rolling(30).std()*(252**0.5)
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# momentum (10, 20, 30, 60, 90 days)
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df['mom_10'] = df['close'].pct_change(10)
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df['mom_20'] = df['close'].pct_change(20)
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df['mom_30'] = df['close'].pct_change(30)
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df['mom_60'] = df['close'].pct_change(60)
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df['mom_90'] = df['close'].pct_change(90)
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df.to_csv(f"data/{ticker}.csv", index=True)
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# %%
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