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Finish experiment 1 and start with Q trader

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This commit is contained in:
Felix Martin
2020-11-05 14:34:48 -05:00
parent 5fbbc26929
commit 889bcf68ca
4 changed files with 139 additions and 9 deletions
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58
strategy_evaluation/experiment1.py
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@@ -10,6 +10,7 @@ from matplotlib.widgets import MultiCursor
from BenchmarkStrategy import BenchmarkStrategy
from ManualStrategy import ManualStrategy
from StrategyLearner import StrategyLearner
from QLearner import QLearner
def plot_indicators(symbol, df):
@@ -92,7 +93,42 @@ def compare_manual_strategies(symbol, sv, sd, ed):
plt.savefig('figure_1.png', dpi=fig.dpi)
def experiment1():
def compare_all_strategies(symbol, sv, sd, ed):
df = util.get_data([symbol], pd.date_range(sd, ed))
df.drop(columns=["SPY"], inplace=True)
normalize = indicators.normalize
bs = BenchmarkStrategy()
orders = bs.testPolicy(symbol, sd, ed, sv)
df["Benchmark"] = normalize(marketsim.compute_portvals(orders, sv))
df["Orders Benchmark"] = orders["Shares"]
ms = ManualStrategy()
orders = ms.testPolicy(symbol, sd, ed, sv)
df["Manual"] = normalize(marketsim.compute_portvals(orders, sv))
df["Orders Manual"] = orders["Shares"]
sl = StrategyLearner(testing=True)
sl.addEvidence(symbol, sd, ed, sv)
orders = sl.testPolicy(symbol, sd, ed, sv)
df["Strategy"] = normalize(marketsim.compute_portvals(orders, sv))
df["Orders Strategy"] = orders["Shares"]
fig, ax = plt.subplots(3, sharex=True)
df[[symbol]].plot(ax=ax[0])
df[["Benchmark", "Manual", "Strategy"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders Manual", "Orders Strategy"]].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_2.png', dpi=fig.dpi)
def experiment1(create_report=False):
symbol = "JPM"
sv = 10000
sd = dt.datetime(2008, 1, 1) # in-sample
@@ -103,25 +139,29 @@ def experiment1():
df = util.get_data([symbol], pd.date_range(sd, ed_out))
df.drop(columns=["SPY"], inplace=True)
if create_report:
compare_manual_strategies(symbol, sv, sd, ed)
compare_all_strategies(symbol, sv, sd, ed)
return
# visualize_correlations(symbol, df)
# plot_indicators(symbol, df)
# compare_manual_strategies(symbol, sv, sd, ed)
bs = BenchmarkStrategy()
orders = bs.testPolicy(symbol, sd_out, ed_out, sv)
df["Benchmark"] = marketsim.compute_portvals(orders, sv)
df["Orders Benchmark"] = orders["Shares"]
sl = StrategyLearner(testing=True)
sl.addEvidence(symbol, sd, ed, sv)
orders = sl.testPolicy(symbol, sd_out, ed_out, sv)
df["SL"] = marketsim.compute_portvals(orders, sv)
df["Orders SL"] = orders["Shares"]
ql = QLearner(testing=True)
ql.addEvidence(symbol, sd, ed, sv)
orders = ql.testPolicy(symbol, sd_out, ed_out, sv)
df["QL"] = marketsim.compute_portvals(orders, sv)
df["Orders QL"] = orders["Shares"]
fig, ax = plt.subplots(3, sharex=True)
df[[symbol]].plot(ax=ax[0])
df[["Benchmark", "SL"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders SL"]].plot(ax=ax[2])
df[["Benchmark", "QL"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders QL"]].plot(ax=ax[2])
for a in ax:
a.grid()