"RWE.TRADES",
"RWE.NEWS",
]
# TODO: SELECT DATE RANGE. Please use format 'YYYY-MM-DD'.
start_date = "2016-01-01"
end_date = "2016-03-31"
# TODO: INSTANTIATE YOUR TRADING AGENT. You may submit multiple agents.
agent = Agent(name="test_agent", )
# TODO: INSTANTIATE YOUR ML MODEL. Only if you need to make predictions.
model = Model(name="test_model", )
# insantiate generator
generator = Generator(
sources=sources,
start_date=start_date,
end_date=end_date,
)
# instantiate backtest
backtest = Backtest(
agent=agent,
generator=generator,
)
# run backtest
results = backtest.run()
start_date = "2016-03-01"
end_date = "2016-03-31"
# TODO: INSTANTIATE YOUR TRADING AGENT. You may submit multiple agents.
agent = Agent(
name="agent_example_2",
default_quantity=100,
model=model,
steps=SEQUENCE_LENGTH,
)
# instantiate generator
generator = Generator(
sources=sources,
start_date=start_date,
end_date=end_date,
)
# instantiate backtest
backtest = Backtest(
agent=agent,
generator=generator,
)
# run backtest
results = backtest.run(
verbose=True,
interval=1_000, # report every 1_000 events
)
if strategy == "regime-filter" or strategy == "new-regime-filter":
trained_hmm_model = pickle.load(open(args.pickle_path, 'rb'))
variances = trained_hmm_model.covars_
flattened_variances = variances.flatten()
high_regime = 0
if numpy.argmax(flattened_variances) == 1:
high_regime = 1
elif numpy.argmax(flattened_variances) == 2:
high_regime = 2
else:
high_regime = 0
backtest = Backtest(daily_prices, daily_returns, strategy,
backtest_start_date, backtest_end_date,
high_regime, trained_hmm_model)
backtested_portfolio = backtest.run()
else:
backtest = Backtest(daily_prices,
daily_returns,
strategy,
backtest_start_date,
backtest_end_date,
high_regime=None,
hmm_model=None)
backtested_portfolio = backtest.run()
# Print dates, portfolio equity, and current state if using regime-filter strategy
DATE = 0
EQUITY = 1
REGIME = 2
for day in backtested_portfolio: