def test_report(self):
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.BarsSinceLong(self.symbol, 1)
enter_crit_group = criteria_group.CriteriaGroup([enter_crit], Long(),
self.symbol)
exit_crit_group = criteria_group.CriteriaGroup([exit_crit], LongExit(),
self.symbol)
tp = trading_profile.TradingProfile(10000,
trading_amount.StaticAmount(5000),
trading_fee.StaticFee(0))
strat = strategy.Strategy(self.d, [enter_crit_group, exit_crit_group],
tp)
strat.simulate()
report_overview = strat.report.overview()
self.assertAlmostEqual(report_overview['net_profit'], 7.68)
self.assertAlmostEqual(report_overview['average_gains'],
0.153256704981)
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.BarsSinceShort(self.symbol, 1)
enter_crit_group = criteria_group.CriteriaGroup([enter_crit], Short(),
self.symbol)
exit_crit_group = criteria_group.CriteriaGroup([exit_crit],
ShortExit(),
self.symbol)
tp = trading_profile.TradingProfile(10000,
trading_amount.StaticAmount(5000),
trading_fee.StaticFee(0))
strat = strategy.Strategy(self.d, [enter_crit_group, exit_crit_group],
tp)
strat.simulate()
report_overview = strat.report.overview()
self.assertAlmostEqual(report_overview['net_profit'], -7.68)
self.assertAlmostEqual(report_overview['average_gains'],
-0.15325670498086685)
enter_crit = criteria.Above(self.symbol.close, 50)
exit_crit = criteria.BarsSinceLong(self.symbol, 1)
enter_crit_group = criteria_group.CriteriaGroup([enter_crit], Long(),
self.symbol)
exit_crit_group = criteria_group.CriteriaGroup([exit_crit], LongExit(),
self.symbol)
tp = trading_profile.TradingProfile(10000,
trading_amount.StaticAmount(5000),
trading_fee.StaticFee(0))
strat = strategy.Strategy(self.d, [enter_crit_group, exit_crit_group],
tp)
strat.simulate()
pretty_overview = strat.report.pretty_overview()
no_trades = pretty_overview.split('\n')[0]
self.assertEqual(no_trades, 'No trades')
def test_simple_short_strategy(self):
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.BarsSinceShort(self.symbol, 2)
enter_crit_group = criteria_group.CriteriaGroup([enter_crit], Short(),
self.symbol)
exit_crit_group = criteria_group.CriteriaGroup([exit_crit],
ShortExit(),
self.symbol)
tp = trading_profile.TradingProfile(10000,
trading_amount.StaticAmount(5000),
trading_fee.StaticFee(5))
self.assertEquals(
tp.__repr__(),
'TradingProfile(capital=10000, trading_amount=StaticAmount(amount=5000, round_up=False), trading_fee=StaticFee(fee=5), slippage=0.0'
)
strat = strategy.Strategy(self.d, [enter_crit_group, exit_crit_group],
tp)
strat.simulate()
report_overview = strat.report.overview()
self.assertAlmostEqual(strat.realtime_data_frame.iloc[4]['PL_MSFT'],
report_overview['net_profit'])
self.assertTrue(
np.isnan(strat.realtime_data_frame.iloc[0]['CHANGE_PERCENT_MSFT']))
self.assertTrue(
np.isnan(strat.realtime_data_frame.iloc[5]['CHANGE_VALUE_MSFT']))
self.assertEqual(strat.realtime_data_frame.iloc[0]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[1]['ACTIONS_MSFT'], 2)
self.assertEqual(strat.realtime_data_frame.iloc[2]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[3]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[4]['ACTIONS_MSFT'], -2)
self.assertEqual(strat.realtime_data_frame.iloc[5]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[0]['STATUS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[1]['STATUS_MSFT'], -1)
self.assertEqual(strat.realtime_data_frame.iloc[2]['STATUS_MSFT'], -1)
self.assertEqual(strat.realtime_data_frame.iloc[3]['STATUS_MSFT'], -1)
self.assertEqual(strat.realtime_data_frame.iloc[4]['STATUS_MSFT'], 0)
self.assertEqual(report_overview['trades'], 1)
self.assertEqual(report_overview['winning_trades'], 1)
self.assertEqual(report_overview['losing_trades'], 0)
self.assertEqual(report_overview['lacking_capital'], 0)
self.assertEqual(report_overview['gross_loss'], 0)
self.assertEqual(report_overview['gross_profit'],
report_overview['net_profit'])
self.assertEqual(report_overview['ongoing_trades'], 0)
self.assertEqual(report_overview['average_trading_amount'],
5003.5199999999995)
self.assertEqual(report_overview['profitability'], 100.00)
def test_bars_since_action(self):
crit = criteria.BarsSinceAction(self.one, Long(), 2)
self.assertEquals(str(crit), 'BarsSinceAction(symbol=ONE, action=1, periods=2, condition=NONE)')
crit = criteria.BarsSinceLongExit(self.one, 3)
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 2)
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 1)
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 0)
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 4)
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 5)
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 6)
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 0, 'under')
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 1, 'under')
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 2, 'under')
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 5, 'under')
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 6, 'under')
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 7, 'under')
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 1, 'over')
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceShortExit(self.one, 0, 'over')
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceShort(self.one, 0, 'over')
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 4, 'over')
self.assertTrue(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 5, 'over')
self.assertFalse(crit.apply(self.data))
crit = criteria.BarsSinceLong(self.one, 6, 'over')
self.assertFalse(crit.apply(self.data))
# Our random forest will spit out a prediction price for 5 bars in the future
# We still need a threshold to determine whether or not we want to enter the trade
# Let's define a TI that is $5 higher than the random forest's prediction
threshold_above = technical_indicator.Addition(random_forest.value, 5)
test_dataset.add_technical_indicator(threshold_above)
# And $5 lower than the neural network's prediction
threshold_below = technical_indicator.Subtraction(random_forest.value, 5)
test_dataset.add_technical_indicator(threshold_below)
# Criteria
# Current price is below the threshold of our random forest's prediction price
enter_crit_long = criteria.Below(symbol.close, threshold_below.value)
# Current price is above the threshold of our random forest's prediction price
enter_crit_short = criteria.Above(symbol.close, threshold_above.value)
# Exit after 5 days - as per the random forest's build parameters
exit_crit_long = criteria.BarsSinceLong(symbol, 5)
exit_crit_short = criteria.BarsSinceShort(symbol, 5)
# Criteria Groups
enter_crit_group1 = criteria_group.CriteriaGroup([enter_crit_long], Long(),
symbol)
enter_crit_group2 = criteria_group.CriteriaGroup([enter_crit_short], Short(),
symbol)
exit_crit_group1 = criteria_group.CriteriaGroup([exit_crit_long], LongExit(),
symbol)
exit_crit_group2 = criteria_group.CriteriaGroup([exit_crit_short], ShortExit(),
symbol)
# Trading Profile
tp = trading_profile.TradingProfile(100000, trading_amount.StaticAmount(10000),
trading_fee.StaticFee(5))
# Strategy
strat = strategy.Strategy(
test_dataset,