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Finish project 8 and course!

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Felix Martin
2020-11-10 12:33:42 -05:00
parent 6e1f70bcba
commit 063d9a75ae
7 changed files with 147 additions and 19 deletions
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74
strategy_evaluation/experiment1.py
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@@ -128,20 +128,63 @@ def compare_all_strategies(symbol, sv, sd, ed):
plt.savefig('figure_2.png', dpi=fig.dpi)
def compare_number_trades(symbol, sv, sd, ed):
def compare_number_trades():
symbol = "JPM"
sv = 10000
sd = dt.datetime(2008, 1, 1) # in-sample
ed = dt.datetime(2009, 12, 31) # in-sample
df = util.get_data([symbol], pd.date_range(sd, ed))
df.drop(columns=["SPY"], inplace=True)
print(f"| commission | n_orders |")
print(f"-------------------------")
for commission in [0, 9.95, 20, 50, 100]:
ql = QLearner(testing=True, commission=commission, impact=0.005)
ql.addEvidence(symbol, sd, ed, sv)
orders = ql.testPolicy(symbol, sd, ed, sv)
n_orders = orders[orders["Shares"] != 0].shape[0]
print(f"| {commission} | {n_orders} |")
def compare_q_learners():
symbol = "JPM"
sv = 10000
sd = dt.datetime(2008, 1, 1) # in-sample
ed = dt.datetime(2009, 12, 31) # in-sample
sd_out = dt.datetime(2010, 1, 1) # out-sample
ed_out = dt.datetime(2011, 12, 31) # out-sample
df = util.get_data([symbol], pd.date_range(sd_out, ed_out))
df.drop(columns=["SPY"], inplace=True)
bs = BenchmarkStrategy()
orders = bs.testPolicy(symbol, sd_out, ed_out, sv)
df["Benchmark"] = indicators.normalize(marketsim.compute_portvals(orders, sv))
df["Orders Benchmark"] = orders["Shares"]
ql = QLearner(testing=True, verbose=False)
ql.addEvidence(symbol, sd, ed, sv)
orders = ql.testPolicy(symbol, sd, ed, sv)
n_orders_no_commission = orders[orders["Shares"] != 0].shape[0]
orders = ql.testPolicy(symbol, sd_out, ed_out, sv)
df["QL 5"] = indicators.normalize(marketsim.compute_portvals(orders, sv))
df["Orders QL 5"] = orders["Shares"]
ql = QLearner(testing=True, verbose=False, commission=9.95, impact=0.005)
ql = QLearner(testing=True, verbose=False, n_bins=4)
ql.addEvidence(symbol, sd, ed, sv)
orders = ql.testPolicy(symbol, sd, ed, sv)
n_orders_commision = orders[orders["Shares"] != 0].shape[0]
print(f"{n_orders_no_commission=} {n_orders_commision=}")
orders = ql.testPolicy(symbol, sd_out, ed_out, sv)
df["QL 4"] = indicators.normalize(marketsim.compute_portvals(orders, sv))
df["Orders QL 4"] = orders["Shares"]
fig, ax = plt.subplots(3, sharex=True)
df[[symbol]].plot(ax=ax[0])
df[["Benchmark", "QL 5", "QL 4"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders QL 5", "Orders QL 4"]].plot(ax=ax[2])
for a in ax:
a.grid()
m = MultiCursor(fig.canvas, ax, color='r', lw=0.5)
fig.set_size_inches(10, 8, forward=True)
plt.savefig('figure_4.png', dpi=fig.dpi)
sys.exit(0)
def experiment1(create_report=False):
@@ -152,27 +195,28 @@ def experiment1(create_report=False):
sd_out = dt.datetime(2010, 1, 1) # out-sample
ed_out = dt.datetime(2011, 12, 31) # out-sample
df = util.get_data([symbol], pd.date_range(sd, ed))
df = util.get_data([symbol], pd.date_range(sd_out, 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
sys.exit(0)
# visualize_correlations(symbol, df)
# plot_indicators(symbol, df)
# compare_number_trades(symbol, sv, sd, ed)
# compare_q_learners()
bs = BenchmarkStrategy()
orders = bs.testPolicy(symbol, sd, ed, sv)
df["Benchmark"] = marketsim.compute_portvals(orders, sv)
orders = bs.testPolicy(symbol, sd_out, ed_out, sv)
df["Benchmark"] = indicators.normalize(marketsim.compute_portvals(orders, sv))
df["Orders Benchmark"] = orders["Shares"]
ql = QLearner(testing=True, verbose=False, commission=9.95, impact=0.005)
ql = QLearner(testing=True, verbose=False)
ql.addEvidence(symbol, sd, ed, sv)
orders = ql.testPolicy(symbol, sd, ed, sv)
df["QL"] = marketsim.compute_portvals(orders, sv)
orders = ql.testPolicy(symbol, sd_out, ed_out, sv)
df["QL"] = indicators.normalize(marketsim.compute_portvals(orders, sv))
df["Orders QL"] = orders["Shares"]
fig, ax = plt.subplots(3, sharex=True)
@@ -184,6 +228,8 @@ def experiment1(create_report=False):
a.grid()
m = MultiCursor(fig.canvas, ax, color='r', lw=0.5)
plt.show()
# fig.set_size_inches(10, 8, forward=True)
# plt.savefig('figure_4.png', dpi=fig.dpi)
if __name__ == "__main__":