mirror of
https://github.com/wassname/options_backtester.git
synced 2026-06-28 00:59:37 +08:00
Juan Pablo Amoroso
89 lines
2.6 KiB
Python
89 lines
2.6 KiB
Python
import os
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from datetime import date, timedelta
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import pandas as pd
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import pandas_datareader.data as web
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from backtester.utils import get_data_dir
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def create_test_data(data_dir, filename="SPX_2008-2018.csv"):
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"""Create test data set with 10 years of SPX"""
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spx_dir = os.path.join(data_dir, "allspx")
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test_file = os.path.join(data_dir, filename)
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with open(test_file, "w+") as f:
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f.write("date,price\n")
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for year in range(2008, 2019):
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filename = "SPX_{}.csv".format(year)
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year_df = pd.read_csv(os.path.join(spx_dir, filename))
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grouped = year_df.groupby("quotedate").first()
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grouped.to_csv(
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test_file, mode="a", columns=["underlying_last"], header=False)
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def create_synthetic_data(data_dir, filename="synthetic_data.csv"):
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"""Create an synthetic data set with known statistics.
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Price goes from 1 to 2000.
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Mean = 1000.5
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% Price = 1999"""
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synth_file = os.path.join(data_dir, filename)
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day = date(1970, 1, 1)
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with open(synth_file, "w+") as f:
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f.write("date,price\n")
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for i in range(1, 2001):
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line = "{},{}\n".format(day.strftime("%m/%d/%Y"), i)
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f.write(line)
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day += timedelta(days=1)
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def fetch_balanced_data(data_dir,
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filename="balanced_2015.csv",
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start=None,
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end=None):
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"""Downloads daily data from `start` til `end` from IEX.
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Symbols
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-------
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VOO: VANGUARD IX FUN/S&P 500 ETF
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GLD: SPDR Gold Trust
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VNQ: VANGUARD IX FUN/RL EST IX FD ETF
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VNQI: VANGUARD INTL E/GLB EX-US RL EST IX
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TLT: iShares Barclays 20+ Yr Treas.Bond
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TIP: iShares TIPS Bond ETF
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BNDX: VANGUARD CHARLO/TOTAL INTL BD ETF
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EEM: iShares MSCI Emerging Markets Indx
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RJI: Rogers International Commodity Index
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"""
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if not start or not end:
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start = date(2015, 1, 1)
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end = date(2015, 12, 31)
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symbols = ["VOO", "GLD", "VNQ", "VNQI", "TLT", "TIP", "BNDX", "EEM", "RJI"]
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# Write headers
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full_path = os.path.join(data_dir, filename)
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with open(full_path, "w+") as f:
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f.write("date,symbol,open,high,low,close,volume\n")
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columns = ["symbol", "open", "high", "low", "close", "volume"]
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for symbol in symbols:
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data = web.DataReader(symbol, "iex", start, end)
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data["symbol"] = symbol
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data.to_csv(
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full_path,
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mode="a",
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index_label="date",
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columns=columns,
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header=False)
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if __name__ == "__main__":
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data_dir = get_data_dir()
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create_test_data(data_dir)
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create_synthetic_data(data_dir)
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fetch_balanced_data(data_dir)
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