def experiment1():
ms = mas.MannualStrategy(symbol="JPM", sd=dt.datetime(2008,1,1), ed=dt.datetime(2009,12,31), sv=100000)
portval_ms = ms.manual_portfolio(symbol="JPM", sd=dt.datetime(2008,1,1), ed=dt.datetime(2009,12,31), sv=100000, commission=0.0, impact=0.0)
portval_benchmark = ms.benchmark_portfolio(symbol="JPM", sd=dt.datetime(2008,1,1), ed=dt.datetime(2009,12,31), sv=100000, commission=0.0, impact=0.0)
stl = sl.StrategyLearner()
portval_stl, trades = stl.strategy_learner_result(symbol="JPM", sv=100000, sd=dt.datetime(2008,1,1), ed=dt.datetime(2009,12,31), commission=0.0, impact=0.00)
ax = portval_stl.plot(title="Experiment 1. Manual Strategy vs Benchmark vs Q Learning Strategy", fontsize=12, color="red", label="Q Learning Strategy")
portval_benchmark.plot(ax=ax, color="blue", label="Benchmark")
portval_ms.plot(ax=ax, color="black", label="Manual Strategy")
ax.set_ylabel('Normalized Value')
ax.set_xlabel('Dates')
plt.grid(True)
plt.legend(loc=0)
plt.savefig("Experiment1.png")
plt.show()
def experiment1():
mbs = ms.MannualStrategy(symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000)
portval_mbs = mbs.get_manualrule_portfolio(symbol="JPM",
sv=100000,
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
commission=0.0,
impact=0.00)
portval_benchmark = mbs.get_benchmark_portfolio(symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(
2009, 12, 31),
sv=100000,
commission=0.0,
impact=0.00)
sbl = sl.StrategyLearner(verbose=False, impact=0.0)
trades_sbl, portval_sbl = sbl.get_strategy_learner_portfolio(
symbol="JPM",
sv=100000,
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
commission=0.0,
impact=0.00)
ax = portval_sbl.plot(
title=
"Figure 1. Benchmark vs. QLearning Strategy vs. Manual Rule-based",
fontsize=12,
color="black",
label="QLearner-based")
portval_benchmark.plot(ax=ax, color="blue", label="Benchmark")
portval_mbs.plot(ax=ax, color="red", label="Manual Rule-based")
ax.set_ylabel('Normalized Value')
ax.set_xlabel('Dates')
plt.grid(True)
plt.legend(loc=0)
plt.savefig("Fig1.png")
plt.show()
def experiment2():
mbs = ms.MannualStrategy(symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000)
portval_benchmark = mbs.get_benchmark_portfolio(symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(
2009, 12, 31),
sv=100000,
commission=0.0,
impact=0.005)
sbl = sl.StrategyLearner(verbose=False, impact=0.0)
trades_sbl, portval_sbl = sbl.get_strategy_learner_portfolio(
symbol="JPM",
sv=100000,
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
commission=0.0,
impact=0.005)
ax = portval_sbl.plot(
title="Figure 2. Benchmark vs. QLearning Strategy (impact=0.005)",
fontsize=12,
color="black",
label="QLearner-based")
ymin, ymax = ax.get_ylim()
entries = []
entries2 = []
for i in range(0, len(trades_sbl), 5):
if trades_sbl.ix[i, "Order"] == "SELL":
entries.append(trades_sbl.index[i])
elif trades_sbl.ix[i, "Order"] == "BUY":
entries2.append(trades_sbl.index[i])
for day in entries:
ax.axvline(x=day, color="r")
for day in entries2:
ax.axvline(x=day, color="g")
plt.grid(True)
portval_benchmark.plot(ax=ax, color="blue", label="Benchmark")
ax.set_ylabel('Normalized Value')
ax.set_xlabel('Dates')
plt.legend(loc=0)
plt.savefig("Fig2.png")
plt.show()
portval_benchmark2 = mbs.get_benchmark_portfolio(
symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000,
commission=0.0,
impact=0.02)
trades_sbl2, portval_sbl2 = sbl.get_strategy_learner_portfolio(
symbol="JPM",
sv=100000,
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
commission=0.0,
impact=0.02)
plt.grid(True)
ax2 = portval_sbl2.plot(
title="Figure 3. Benchmark vs. QLearning Strategy (impact=0.02)",
fontsize=12,
color="black",
label="QLearner-based")
portval_benchmark2.plot(ax=ax2, color="blue", label="Benchmark")
ymin, ymax = ax2.get_ylim()
entries = []
entries2 = []
for i in range(0, len(trades_sbl2), 5):
if trades_sbl2.ix[i, "Order"] == "SELL":
entries.append(trades_sbl2.index[i])
elif trades_sbl2.ix[i, "Order"] == "BUY":
entries2.append(trades_sbl2.index[i])
for day in entries:
ax2.axvline(x=day, color="r")
for day in entries2:
ax2.axvline(x=day, color="g")
ax2.set_ylabel('Normalized Value')
ax2.set_xlabel('Dates')
plt.legend(loc=0)
plt.savefig("Fig3.png")
plt.show()
def experiment2():
ms = mas.MannualStrategy(symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000)
portval_benchmark = ms.benchmark_portfolio(symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000,
commission=0.0,
impact=0.005)
stl = sl.StrategyLearner()
portval_stl, trades_sbl = stl.strategy_learner_result(
symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000,
commission=0.0,
impact=0.005)
ax = portval_stl.plot(
title="Experiment 2-1. Benchmark vs Q Learning Strategy (impact=0.005)",
color="black",
label="Q Learning Strategy")
short_entries = []
long_entries = []
for i in range(0, len(trades_sbl)):
if trades_sbl.ix[i, "Order"] == "SELL":
short_entries.append(trades_sbl.index[i])
elif trades_sbl.ix[i, "Order"] == "BUY":
long_entries.append(trades_sbl.index[i])
for day in long_entries:
ax.axvline(x=day, color="g")
plt.grid(True)
portval_benchmark.plot(ax=ax, color="blue", label="Benchmark")
ax.set_ylabel('Normalized Value')
ax.set_xlabel('Dates')
plt.legend(loc=0)
plt.savefig("Experiment 2-1.png")
plt.show()
portval_benchmark = ms.benchmark_portfolio(symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000,
commission=0.0,
impact=0.03)
portval_stl, trades_sbl = stl.strategy_learner_result(
symbol="JPM",
sd=dt.datetime(2008, 1, 1),
ed=dt.datetime(2009, 12, 31),
sv=100000,
commission=0.0,
impact=0.03)
plt.grid(True)
ax = portval_stl.plot(
title="Experiment 2-2. Benchmark vs Q Learning Strategy (impact=0.03)",
color="black",
label="Q Learning Strategy")
portval_benchmark.plot(ax=ax, color="blue", label="Benchmark")
short_entries = []
long_entries = []
for i in range(0, len(trades_sbl)):
if trades_sbl.ix[i, "Order"] == "SELL":
short_entries.append(trades_sbl.index[i])
elif trades_sbl.ix[i, "Order"] == "BUY":
long_entries.append(trades_sbl.index[i])
for day in long_entries:
ax.axvline(x=day, color="g")
ax.set_ylabel('Normalized Value')
ax.set_xlabel('Dates')
plt.legend(loc=0)
plt.savefig("Experiment 2-2.png")
plt.show()