def test_upcoming_action(self):
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.Equals(self.symbol.close, 25.00)
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()
next_action = strat.get_next_action()[self.symbol]
self.assertTrue(self.symbol in strat.upcoming_actions)
self.assertEqual(strat.upcoming_actions[self.symbol], SHORT_EXIT)
self.assertEqual(next_action['estimated_money_required'],
5000.8699999999999)
self.assertEqual(next_action['estimated_enter_value'],
25.129999999999999)
self.assertEqual(next_action['action_name'], 'SHORT_EXIT')
self.assertEqual(next_action['estimated_shares'], 199.0)
self.assertEqual(next_action['action'], SHORT_EXIT)
self.assertEqual(next_action['enter_on'], 'OPEN')
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 __init__(self, criteria_list, action, symbol):
self.criteria_list = criteria_list
self.action = action
self._action = 0
self.symbol = str(symbol)
# Add Actions Criteria Automatically
if self.action == Long():
self.criteria_list.append(Not(InMarket(self.symbol)))
self._action = LONG
elif self.action == LongExit():
self.criteria_list.append(IsLong(self.symbol))
self._action = LONG_EXIT
elif self.action == Short():
self.criteria_list.append(Not(InMarket(self.symbol)))
self._action = SHORT
elif self.action == ShortExit():
self.criteria_list.append(IsShort(self.symbol))
self._action = SHORT_EXIT
else:
raise InvalidAction()
self.logger = logger.Logger(self.__class__.__name__)
self.logger.info('New Criteria Group - %s for %s (%s)' \
%(str(action).upper(), symbol, criteria_list))
# SMA100 slope is moving down
enter_crit_short2 = criteria.Below(sma100.value, sma100_previous.value)
# Stop loss and take profit exit criteria
exit_crit_long1 = criteria.StopLoss(symbol, 0.01, percent=True) # 1%
exit_crit_long2 = criteria.TakeProfit(symbol, 50) # $100
exit_crit_short1 = criteria.StopLoss(symbol, 0.01, short=True,
percent=True) # 1%
exit_crit_short2 = criteria.TakeProfit(symbol, 50, short=True) # $100
# Criteria Groups
enter_crit_group1 = criteria_group.CriteriaGroup(
[enter_crit_long1, enter_crit_long2], Long(), symbol)
enter_crit_group2 = criteria_group.CriteriaGroup(
[enter_crit_short1, enter_crit_short2], Short(), symbol)
exit_crit_group1 = criteria_group.CriteriaGroup([exit_crit_long1], LongExit(),
symbol)
exit_crit_group2 = criteria_group.CriteriaGroup([exit_crit_long2], LongExit(),
symbol)
exit_crit_group3 = criteria_group.CriteriaGroup([exit_crit_short1],
ShortExit(), symbol)
exit_crit_group4 = criteria_group.CriteriaGroup([exit_crit_short2],
ShortExit(), symbol)
# Strategy
tp = trading_profile.TradingProfile(20000, trading_amount.StaticAmount(10000),
trading_fee.StaticFee(5))
strat = strategy.Strategy(d, [
enter_crit_group1, enter_crit_group2, exit_crit_group1, exit_crit_group2,
exit_crit_group3, exit_crit_group4
], tp)
strat.simulate()
print strat.report.pretty_overview()
# 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,
[enter_crit_group1, enter_crit_group2, exit_crit_group1, exit_crit_group2],
tp)
strat.simulate()
print strat.report.pretty_overview()
def __init__(self, symbol, periods, condition=None):
BarsSinceAction.__init__(self, symbol, ShortExit(), periods, condition)
self.label = 'BarsSinceShortExit_%s_%s_%s' % (symbol, periods,
condition)