Rotation Strategy¶
[1]:
# If you would like to refresh your data, please execute the bellow codes.
import pandas as pd
import numpy as np
from datetime import datetime
from tqdm import tqdm
import matplotlib.pyplot as plt
from mypo import Loader
DOWNLOAD = False
if DOWNLOAD:
tickers = pd.read_csv("/app/docs/tutorial/tickers.csv")
loader = Loader()
for row in tqdm(tickers.to_dict('record')):
loader.get(row['Ticker'], expense_ratio=row['ExpenseRatio'] * 0.01)
loader.save('/app/docs/tutorial/all.bin')
[2]:
loader = Loader.load('/app/docs/tutorial/all.bin')
loader = loader.since(datetime(2007, 1, 1))
market = loader.get_market()
selected_tickers = ['SPY', 'EFA', 'GLD']
[3]:
from mypo import split_k_folds
from mypo.optimizer import NoOptimizer, RotationStrategy
from mypo.rebalancer import MonthlyRebalancer
from mypo.evacuator import MovingAverageEvacuator
from mypo import Runner
folds = split_k_folds(market, 1, 200)
fold = folds[0].filter(selected_tickers)
Reference Performance (SPY)¶
[4]:
optimizer = NoOptimizer([1, 0, 0])
runner = Runner(
rebalancer=MonthlyRebalancer(optimizer=optimizer),
)
runner.run(
fold=fold,
verbose=True
)
report = runner.report()
display(report.summary())
display(report.annual_summary())
ax = report.history().plot()
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_weights().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
100%|██████████| 3416/3416 [00:48<00:00, 71.08it/s]
tickers yearly total return sharpe ratio max draw down \
0 [SPY, EFA, GLD] 1.081402 0.313455 0.452535
max draw down span
0 1318
return std sharpe ratio draw down
2007-12-31 -0.070048 0.203789 -0.441871 0.900611
2008-12-31 -0.342729 0.404963 -0.895710 0.495878
2009-12-31 0.230129 0.257868 0.814872 0.452535
2010-12-31 0.130888 0.171868 0.645192 0.685786
2011-12-31 0.017959 0.217142 -0.009400 0.749985
2012-12-31 0.153834 0.121414 1.102295 0.866846
2013-12-31 0.250756 0.101235 2.279415 0.947054
2014-12-31 0.129200 0.104288 1.047103 0.931672
2015-12-31 -0.005435 0.144072 -0.176542 0.889826
2016-12-31 0.125102 0.118920 0.883803 0.878241
2017-12-31 0.189369 0.062425 2.713175 0.975451
2018-12-31 -0.049852 0.153296 -0.455667 0.823208
2019-12-31 0.279925 0.112742 2.305479 0.853734
2020-12-31 0.133233 0.295515 0.383173 0.694815
2021-12-31 0.116567 0.129461 0.745912 0.963183
RotationStrategy¶
[5]:
optimizer = RotationStrategy(risk_free_rate=0.02, do_re_optimize=True)
runner = Runner(
rebalancer=MonthlyRebalancer(optimizer=optimizer),
)
runner.run(
fold=fold,
verbose=True
)
report = runner.report()
display(report.summary())
display(report.annual_summary())
ax = report.history_assets().plot()
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_weights().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_cost().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_cash_vs_assets().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
100%|██████████| 3416/3416 [00:52<00:00, 65.51it/s]
tickers yearly total return sharpe ratio max draw down \
0 [SPY, EFA, GLD] 0.909788 -0.505314 0.187728
max draw down span
0 3415
return std sharpe ratio draw down
2007-12-31 -0.100559 0.229040 -0.526365 0.881695
2008-12-31 -0.491544 0.458861 -1.114814 0.372462
2009-12-31 0.170962 0.238494 0.632978 0.360543
2010-12-31 -0.130924 0.198401 -0.760702 0.397391
2011-12-31 -0.225155 0.256480 -0.955844 0.347718
2012-12-31 0.057298 0.152106 0.245209 0.338550
2013-12-31 0.002860 0.140972 -0.121586 0.370729
2014-12-31 -0.078172 0.134595 -0.729385 0.338084
2015-12-31 -0.179232 0.155981 -1.277277 0.276602
2016-12-31 -0.203691 0.187351 -1.193968 0.223883
2017-12-31 0.118931 0.088167 1.122084 0.231182
2018-12-31 -0.051896 0.135136 -0.532028 0.229060
2019-12-31 0.133415 0.129695 0.874473 0.244140
2020-12-31 0.000367 0.298016 -0.065880 0.187728
2021-12-31 0.001788 0.154273 -0.118049 0.254660
RotationStrategy with cash filter¶
[ ]:
optimizer = RotationStrategy(risk_free_rate=0.02, do_re_optimize=True)
runner = Runner(
rebalancer=MonthlyRebalancer(optimizer=optimizer, evacuator=MovingAverageEvacuator(span=150)),
)
runner.run(
fold=fold,
verbose=True
)
report = runner.report()
display(report.summary())
display(report.annual_summary())
ax = report.history_assets().plot()
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_weights().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_cost().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_cash_vs_assets().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
3%|▎ | 106/3416 [00:02<01:32, 35.61it/s]
If it is no fee.¶
[ ]:
from mypo import Settings
from mypo.trigger import MonthlyTrigger
optimizer = RotationStrategy(risk_free_rate=0.02, do_re_optimize=True)
runner = Runner(
rebalancer=MonthlyRebalancer(optimizer=optimizer, evacuator=MovingAverageEvacuator(span=150)),
settings=Settings(tax_rate=np.float64(0.20), fee_rate=np.float64(0.00))
)
runner.run(
fold=fold,
verbose=True
)
report = runner.report()
display(report.summary())
display(report.annual_summary())
ax = report.history_assets().plot()
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_weights().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_cost().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()
ax = report.history_cash_vs_assets().plot.area(stacked=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0)
plt.show()