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76 lines
2.5 KiB
76 lines
2.5 KiB
import datetime
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import lib
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from matplotlib import pyplot as plt
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import strategies as st
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import pandas as pd
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if __name__ == "__main__":
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stockList = ["^GSPC"]
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monthly_params = dict(sum=100000, coef=1, t_rate=1 + 0.02 / 12)
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# startDate = datetime.datetime.fromisoformat("2000-01-01")
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# endDate = datetime.datetime.fromisoformat("2022-01-01")
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print(stockList[0])
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stockData = lib.get_data(stockList[0])
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start_date = stockData.index[0]
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year_step = 1
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label_string = "Investing to {} monthly over {} years, increasing {:.2f}%, starting from ${}".format(
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stockList[0],
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year_step,
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(monthly_params["coef"] * 100) - 100,
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monthly_params["sum"],
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)
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print(label_string)
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plot_param = "annual%"
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_strategies = (
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st.QDCA,
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st.EDCA,
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st.SmaCross,
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)
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strategies = (st.DCA,) + _strategies
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df_comp = pd.DataFrame(index=list(st.__name__ for st in strategies))
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df_vwr = pd.DataFrame(index=list(st.__name__ for st in strategies))
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df_rel_to_dca = pd.DataFrame(index=list(st.__name__ for st in _strategies))
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for start_year in range(
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start_date.year, datetime.datetime.today().year - year_step + 1, year_step
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):
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start_date = datetime.date(start_year, 1, 1)
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end_date = datetime.date(start_year + year_step - 1, 12, 31)
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if (today := datetime.date.today()) < end_date:
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end_date = today
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stockData = lib.get_data(stockList[0], start_date, end_date)
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start, end = lib.get_data_borders(stockData)
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print(
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"{} to {}, {:.1f} years".format(
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start,
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end,
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(end - start).days / 365,
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)
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)
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newdf = pd.concat(
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[
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lib.test_strategy(stockData, strategy, monthly_params)
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for strategy in strategies
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]
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)
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print(newdf.to_string())
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df_rel_to_dca[start_year] = list(
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newdf.loc[s.__name__][plot_param] - newdf.loc[st.DCA.__name__][plot_param]
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for s in _strategies
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)
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df_comp[start_year] = newdf[plot_param].values
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# print(df[["annual%", "froi%", "cost", "total_value", "max_dd%", "max_md"]])
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# print(newdf["annual%"])
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print(df_rel_to_dca.to_string())
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df_comp.T.plot()
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for index, s in df_rel_to_dca.iterrows():
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print("{}: avg {:.3f} dev {:.3f}".format(index, s.mean(), s.std()))
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df_rel_to_dca.T.hist(bins=20)
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plt.grid()
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plt.title(label_string)
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plt.ylabel(plot_param)
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plt.xlabel("year")
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plt.show()
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