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Show both MACD and indicator strat on figure

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Prepare for strategy learner.
This commit is contained in:
Felix Martin
2020-11-04 09:23:42 -05:00
parent 0519ae9336
commit c40ffcf84b
4 changed files with 61 additions and 28 deletions
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58
strategy_evaluation/experiment1.py
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@@ -9,6 +9,7 @@ import matplotlib.pyplot as plt
from matplotlib.widgets import MultiCursor
from BenchmarkStrategy import BenchmarkStrategy
from ManualStrategy import ManualStrategy
from StrategyLearner import StrategyLearner
def plot_indicators(symbol, df):
@@ -16,7 +17,6 @@ def plot_indicators(symbol, df):
price_sma = indicators.price_sma(df, symbol, [8])
bb = indicators.bollinger_band(df, symbol)
sma = indicators.sma(df, symbol, [8])
rsi = indicators.rsi(df, symbol)
macd = indicators.macd(df, symbol).copy()
@@ -57,6 +57,40 @@ def visualize_correlations(symbol, df):
sys.exit(0)
def compare_manual_strategies(symbol, sv, sd, ed):
df = util.get_data([symbol], pd.date_range(sd, ed))
df.drop(columns=["SPY"], inplace=True)
bs = BenchmarkStrategy()
orders = bs.testPolicy(symbol, sd, ed, sv)
df["Benchmark"] = marketsim.compute_portvals(orders, sv)
df["Orders Benchmark"] = orders["Shares"]
ms = ManualStrategy()
orders = ms.testPolicy(symbol, sd, ed, sv, macd_strat=True)
df["MACD Strat"] = marketsim.compute_portvals(orders, sv)
df["Orders MACD"] = orders["Shares"]
# df["Holding Manual"] = orders["Shares"].cumsum()
orders = ms.testPolicy(symbol, sd, ed, sv)
df["Three Strat"] = marketsim.compute_portvals(orders, sv)
df["Orders Three"] = orders["Shares"]
fig, ax = plt.subplots(3, sharex=True)
df[[symbol]].plot(ax=ax[0])
df[["Benchmark", "MACD Strat", "Three Strat"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders MACD", "Orders Three"]].plot(ax=ax[2])
for a in ax:
a.grid()
MultiCursor(fig.canvas, ax, color='r', lw=0.5)
# plt.show()
fig.set_size_inches(10, 8, forward=True)
plt.savefig('figure_1.png', dpi=fig.dpi)
def experiment1():
symbol = "JPM"
start_value = 10000
@@ -65,33 +99,33 @@ def experiment1():
# sd = dt.datetime(2010, 1, 1) # out-sample
# ed = dt.datetime(2011, 12, 31) # out-sample
df = util.get_data([symbol], pd.date_range(sd, ed))
df.drop(columns=["SPY"], inplace=True)
# visualize_correlations(symbol, df)
# plot_indicators(symbol, df)
# compare_manual_strategies(symbol, start_value, sd, ed)
df = util.get_data([symbol], pd.date_range(sd, ed))
df.drop(columns=["SPY"], inplace=True)
bs = BenchmarkStrategy()
orders = bs.testPolicy(symbol, sd, ed, start_value)
df["Benchmark"] = marketsim.compute_portvals(orders, start_value)
df["Orders Benchmark"] = orders["Shares"]
ms = ManualStrategy()
sl = StrategyLearner()
orders = ms.testPolicy(symbol, sd, ed, start_value)
df["Manual"] = marketsim.compute_portvals(orders, start_value)
df["Orders Manual"] = orders["Shares"]
df["Holding Manual"] = orders["Shares"].cumsum()
df["SL"] = marketsim.compute_portvals(orders, start_value)
df["Orders SL"] = orders["Shares"]
# df["Holding Manual"] = orders["Shares"].cumsum()
fig, ax = plt.subplots(3, sharex=True)
df[[symbol]].plot(ax=ax[0])
df[["Benchmark", "Manual"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders Manual"]].plot(ax=ax[2])
df[["Benchmark", "SL"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders SL"]].plot(ax=ax[2])
for a in ax:
a.grid()
multi = MultiCursor(fig.canvas, ax, color='r', lw=0.5)
MultiCursor(fig.canvas, ax, color='r', lw=0.5)
plt.show()
# plt.savefig('figure_1.png')
if __name__ == "__main__":