def test_simple_ti_crit_strategy(self):
sma2 = technical_indicator.SMA(self.symbol.close, 2)
sma3 = technical_indicator.SMA(self.symbol.close, 3)
self.d.add_technical_indicator(sma2)
self.d.add_technical_indicator(sma3)
enter_crit1 = criteria.Above(sma2, sma3)
enter_crit2 = criteria.Below(sma3, sma2)
enter_crit3 = criteria.InRange(sma2, 25, 26)
enter_crit4 = criteria.CrossingAbove(sma2, sma3)
enter_crit5 = criteria.CrossingBelow(sma2, sma3)
exit_crit1 = criteria.BarsSinceLong(self.symbol, 2)
exit_crit2 = criteria.Equals(sma2, sma3)
enter_crit_group1 = criteria_group.CriteriaGroup(
[enter_crit1, enter_crit2], Long(), self.symbol)
enter_crit_group2 = criteria_group.CriteriaGroup(
[enter_crit1, enter_crit2], Short(), self.symbol)
enter_crit_group3 = criteria_group.CriteriaGroup(
[enter_crit3, enter_crit4, enter_crit5], Long(), self.symbol)
exit_crit_group1 = criteria_group.CriteriaGroup([exit_crit1],
LongExit(),
self.symbol)
exit_crit_group2 = criteria_group.CriteriaGroup([exit_crit2],
LongExit(),
self.symbol)
tp = trading_profile.TradingProfile(10000,
trading_amount.StaticAmount(5000),
trading_fee.StaticFee(0))
strat = strategy.Strategy(self.d, [
enter_crit_group1, enter_crit_group2, enter_crit_group3,
exit_crit_group1, exit_crit_group2
], tp)
strat.simulate()
overview = strat.report.overview()
self.assertEqual(overview['trades'], 0)
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_trailing_stop_long_strategy(self):
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.TrailingStop(self.symbol, -0.2)
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.assertTrue(
np.isnan(strat.realtime_data_frame.iloc[0]['CHANGE_PERCENT_MSFT']))
self.assertEqual(
strat.realtime_data_frame.iloc[-5]['CHANGE_VALUE_MSFT'],
-0.26999999999999957)
self.assertEqual(
strat.realtime_data_frame.iloc[1]['CHANGE_VALUE_MSFT'],
0.40000000000000213)
self.assertEqual(strat.realtime_data_frame.iloc[2]['PL_MSFT'],
153.60000000000014)
self.assertEqual(strat.realtime_data_frame.iloc[0]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[1]['ACTIONS_MSFT'], 1)
self.assertEqual(strat.realtime_data_frame.iloc[2]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[4]['ACTIONS_MSFT'], -1)
self.assertEqual(strat.realtime_data_frame.iloc[5]['ACTIONS_MSFT'], 0)
def test_simple_long_strategy(self):
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.BarsSinceLong(self.symbol, 2)
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)
repr_string = 'Strategy(dataset=Dataset(symbol_list=[MSFT], data_connection=DummyDataConnection(), start_datetime=None, end_datetime=None, periods=0, granularity=None), criteria_groups=[CriteriaGroup(criteria_list=[Above_MSFT_Close_25.88_1, Not_InMarket(symbol=MSFT)], action=long, symbol=MSFT), CriteriaGroup(criteria_list=[BarsSinceLong_MSFT_2_None, IsLong_MSFT], action=longexit, symbol=MSFT)], trading_profile=TradingProfile(capital=10000, trading_amount=StaticAmount(amount=5000, round_up=False), trading_fee=StaticFee(fee=0), slippage=0.0)'
self.assertEquals(strat.__repr__(), repr_string)
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'], 1)
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'], -1)
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'], 0)
self.assertEqual(report_overview['losing_trades'], 1)
self.assertEqual(report_overview['lacking_capital'], 0)
self.assertEqual(report_overview['gross_profit'], 0)
self.assertEqual(report_overview['gross_loss'],
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'], 0)
pretty_overview_string = 'Trades:\nMSFT\nTrade(datetime=2010-06-02 00:00:00, action=LONG, symbol=MSFT, price=26.06, shares=192.0, money=5003.52, fee=0, slippage=0.0)\nTrade(datetime=2010-06-07 00:00:00, action=LONG_EXIT, symbol=MSFT, price=25.82, shares=192.0, money=4957.44, fee=0, slippage=0.0)\nProfitability: 0.0\n# Trades: 1\nNet Profit: -46.08\nGross Profit: 0.0\nGross Loss: -46.08\nWinning Trades: 0\nLosing Trades: 1\nSharpe Ratio: -6.0\nAvg. Trading Amount: 5003.52\nAvg. Fees: 0.0\nAvg. Slippage: 0.0\nAvg. Gains: -0.929512006197\nAvg. Winner: 0.0\nAvg. Loser: -0.929512006197\nAvg. Bars: 3.0\nTotal Fees: 0.0\nTotal Slippage: 0.0\nTrades Lacking Capital: 0\nOngoing Trades: 0'
self.assertEqual(strat.report.pretty_overview(),
pretty_overview_string)
with self.assertRaises(report.InvalidExit):
strat.report.long_exit(None, None, 'MSFT')
with self.assertRaises(report.InvalidExit):
strat.report.short_exit(None, None, 'MSFT')
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_criteria_group(self):
criteria_list = [DummyCriteria(True), DummyCriteria(True)]
with self.assertRaises(criteria_group.InvalidAction):
cg = criteria_group.CriteriaGroup(criteria_list, 'INVALID', 'MSFT')
cg = criteria_group.CriteriaGroup(criteria_list, Long(), 'MSFT')
self.assertEquals(
str(cg),
'CriteriaGroup(criteria_list=[DummyCriteria(), DummyCriteria(), Not_InMarket(symbol=MSFT)], action=long, symbol=MSFT)'
)
self.assertEqual(cg._action, 1)
out = cg.get_result(msft_data)
self.assertEqual(len(cg.criteria_list), 3) # One extra: NotInMarket
self.assertEqual(out, strategy.LONG)
criteria_list = [DummyCriteria(True), DummyCriteria(False)]
cg = criteria_group.CriteriaGroup(criteria_list, Long(), 'MSFT')
out = cg.get_result(msft_data)
self.assertEqual(out, strategy.NO_ACTION)
def test_stop_loss_strategy(self):
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.StopLoss(self.symbol, -0.8)
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(strat.realtime_data_frame.iloc[-2]['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[-1]['CHANGE_VALUE_MSFT']))
self.assertEqual(strat.realtime_data_frame.iloc[0]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[1]['ACTIONS_MSFT'], 1)
self.assertEqual(strat.realtime_data_frame.iloc[-2]['ACTIONS_MSFT'],
-1)
self.assertEqual(strat.realtime_data_frame.iloc[-1]['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[-3]['STATUS_MSFT'], 1)
self.assertEqual(strat.realtime_data_frame.iloc[-2]['STATUS_MSFT'], 0)
self.assertEqual(report_overview['trades'], 1)
self.assertEqual(report_overview['winning_trades'], 0)
self.assertEqual(report_overview['losing_trades'], 1)
self.assertEqual(report_overview['lacking_capital'], 0)
self.assertEqual(report_overview['gross_loss'],
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'], 0.0)
def test_trailing_stop_short_strategy(self):
enter_crit = criteria.Above(self.symbol.close, 25.88)
exit_crit = criteria.TrailingStop(self.symbol, -0.2)
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()
self.assertTrue(
np.isnan(strat.realtime_data_frame.iloc[0]['CHANGE_PERCENT_MSFT']))
self.assertTrue(
np.isnan(strat.realtime_data_frame.iloc[-3]['CHANGE_VALUE_MSFT']))
self.assertEqual(
strat.realtime_data_frame.iloc[-4]['CHANGE_VALUE_MSFT'],
-0.23999999999999844)
self.assertEqual(
strat.realtime_data_frame.iloc[1]['CHANGE_VALUE_MSFT'],
0.40000000000000213)
self.assertEqual(strat.realtime_data_frame.iloc[2]['PL_MSFT'],
153.60000000000014)
self.assertEqual(
strat.realtime_data_frame.iloc[3]['CHANGE_PERCENT_MSFT'],
-0.01036070606293168)
self.assertEqual(strat.realtime_data_frame.iloc[0]['ACTIONS_MSFT'], 0)
self.assertEqual(strat.realtime_data_frame.iloc[1]['ACTIONS_MSFT'], 1)
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'], -1)
# No properly implemented yet
self.assertTrue(np.isnan(strat.report.get_sharpe_ratio(benchmark=5)))
self.assertTrue(
np.isnan(strat.report.get_sharpe_ratio(benchmark=pd.Series())))
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')
d.add_technical_indicator(sma100_previous)
# Criteria
enter_crit_long1 = criteria.Above(rsi28.value, 60)
# SMA100 slope is moving up
enter_crit_long2 = criteria.Above(sma100.value, sma100_previous.value)
enter_crit_short1 = criteria.Below(rsi28.value, 40)
# 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,
import datetime
from nowtrade import symbol_list, data_connection, dataset, technical_indicator, \
criteria, criteria_group, trading_profile, trading_amount, \
trading_fee, strategy, figures
from nowtrade.action import Long, Short, LongExit, ShortExit
dc = data_connection.YahooConnection()
sl = symbol_list.SymbolList(['AAPL'])
symbol = sl.get('AAPL')
start = datetime.datetime(2010, 01, 01)
end = datetime.datetime(2015, 01, 01)
d = dataset.Dataset(sl, dc, start, end)
d.load_data()
adx28 = technical_indicator.ADX(symbol, 28)
d.add_technical_indicator(adx28)
# Enter Long
enter_crit_long1 = criteria.Above(adx28.value, 30)
enter_crit_long2 = criteria.Above(adx28.minus_di, 30)
enter_crit_long3 = criteria.Below(adx28.plus_di, 20)
# Exit Long
exit_crit_long = criteria.BarsSinceLong(symbol, 10) # Exit 10 days later
# Criteria Groups
enter_crit_group = criteria_group.CriteriaGroup([enter_crit_long1, enter_crit_long2, enter_crit_long3], Long(), symbol)
exit_crit_group = criteria_group.CriteriaGroup([exit_crit_long], LongExit(), symbol)
# Strategy
tp = trading_profile.TradingProfile(100000, trading_amount.StaticAmount(20000), trading_fee.StaticFee(10))
strat = strategy.Strategy(d, [enter_crit_group, exit_crit_group], tp)
strat.simulate()
print strat.report.pretty_overview()
import datetime
from nowtrade import symbol_list, data_connection, dataset, technical_indicator, \
criteria, criteria_group, trading_profile, trading_amount, \
trading_fee, strategy, action
dc = data_connection.YahooConnection()
sl = symbol_list.SymbolList(['^gspc']) # S&P 500
snp500 = sl.get('^gspc')
start = datetime.datetime(1980, 01, 01)
end = datetime.datetime(2015, 01, 01)
d = dataset.Dataset(sl, dc, start, end)
d.load_data()
# Go Long in November , Exit in May, every year.
enter_crit = criteria.IsMonth(11)
exit_crit = criteria.IsMonth(5)
enter_crit_group = criteria_group.CriteriaGroup([enter_crit], action.Long(),
snp500)
exit_crit_group = criteria_group.CriteriaGroup([exit_crit], action.LongExit(),
snp500)
tp = trading_profile.TradingProfile(100000,
trading_amount.CapitalPercentage(100),
trading_fee.StaticFee(20))
strat = strategy.Strategy(d, [enter_crit_group, exit_crit_group], tp)
strat.simulate()
print strat.report.pretty_overview()
# 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,
[enter_crit_group1, enter_crit_group2, exit_crit_group1, exit_crit_group2],
tp)
strat.simulate()
from nowtrade import symbol_list, data_connection, dataset, technical_indicator, \
criteria, criteria_group, trading_profile, trading_amount, \
trading_fee, strategy, action
dc = data_connection.YahooConnection()
sl = symbol_list.SymbolList(['GOOGL'])
symbol = sl.get('GOOGL')
print symbol
d = dataset.Dataset(sl, dc, datetime.datetime(2010, 01, 01), datetime.datetime(2015, 01, 01))
d.load_data()
ultosc = technical_indicator.ULTOSC(symbol, 14, 28, 56)
d.add_technical_indicator(ultosc)
# Enter Long
enter_crit_long1 = criteria.Below(ultosc.value, 40)
# Enter Short
enter_crit_short1 = criteria.Above(ultosc.value, 60)
# Exit Long
exit_crit_long1 = criteria.BarsSinceAction(symbol, action.Long(), 10)
# Exit Short
exit_crit_short1 = criteria.BarsSinceAction(symbol, action.Short(), 10)
# Criteria Groups
enter_crit_group1 = criteria_group.CriteriaGroup([enter_crit_long1], action.Long(), symbol)
enter_crit_group2 = criteria_group.CriteriaGroup([enter_crit_short1], action.Short(), symbol)
exit_crit_group1 = criteria_group.CriteriaGroup([exit_crit_long1], action.LongExit(), symbol)
exit_crit_group2 = criteria_group.CriteriaGroup([exit_crit_short1], action.ShortExit(), symbol)
# Strategy
tp = trading_profile.TradingProfile(11000, trading_amount.StaticAmount(10000), trading_fee.StaticFee(0))
strat = strategy.Strategy(d, [enter_crit_group1, enter_crit_group2, exit_crit_group1, exit_crit_group2], tp)
strat.simulate()
print strat.report.pretty_overview()
