def run(self, prices, timestamp, cash, **kwargs):
symbol = "AAPL"
orders = Orders()
if (prices.loc[timestamp, symbol] * 100) < cash:
orders.add_order(symbol, 100)
return orders
def run(self, prices, timestamp, cash, **kwargs):
symbol = "AAPL"
orders = Orders()
if (prices.loc[timestamp, symbol] * 100) < cash:
orders.add_order(symbol, 100)
return orders
def run(self, prices, timestamp, cash, data, **kwargs):
""" Takes bollinger event data and generates orders """
events = data['events']
if not hasattr(self, 'sell_orders'):
self.setup(events)
orders = Orders()
# Find buy events for this timestamp
timestamps = prices.index
daily_data = events.loc[timestamp]
order_series = daily_data[daily_data > 0]
# Sell 5 market days after bought
index = timestamps.get_loc(timestamp)
if index + 5 >= len(timestamps):
sell_datetime = timestamps[-1]
else:
sell_datetime = timestamps[index + 5]
symbols = order_series.index
self.sell_orders.loc[sell_datetime, symbols] -= 100
daily_sell_data = self.sell_orders.loc[timestamp]
daily_sell_orders = daily_sell_data[daily_sell_data != 0]
# Buy and sell in increments of 100
for symbol in daily_sell_orders.index:
orders.add_order(symbol, -100)
daily_event_data = events.loc[timestamp]
daily_buy_orders = daily_event_data[daily_event_data != 0]
# Buy and sell in increments of 100
for symbol in daily_buy_orders.index:
orders.add_order(symbol, 100)
return orders
def run(self, prices, timestamp, cash, data, **kwargs):
""" Takes bollinger event data and generates orders """
events = data['events']
if not hasattr(self, 'sell_orders'):
self.setup(events)
orders = Orders()
# Find buy events for this timestamp
timestamps = prices.index
daily_data = events.loc[timestamp]
order_series = daily_data[daily_data > 0]
# Sell 5 market days after bought
index = timestamps.get_loc(timestamp)
if index + 5 >= len(timestamps):
sell_datetime = timestamps[-1]
else:
sell_datetime = timestamps[index + 5]
symbols = order_series.index
self.sell_orders.loc[sell_datetime, symbols] -= 100
daily_sell_data = self.sell_orders.loc[timestamp]
daily_sell_orders = daily_sell_data[daily_sell_data != 0]
# Buy and sell in increments of 100
for symbol in daily_sell_orders.index:
orders.add_order(symbol, -100)
daily_event_data = events.loc[timestamp]
daily_buy_orders = daily_event_data[daily_event_data != 0]
# Buy and sell in increments of 100
for symbol in daily_buy_orders.index:
orders.add_order(symbol, 100)
return orders
def test_quickstart():
prophet = Prophet()
prophet.set_universe(['AAPL', 'XOM'])
prophet.register_data_generators(YahooCloseData(cache_path=CACHE_PATH))
prophet.set_order_generator(OrderGenerator())
backtest = prophet.run_backtest(start=datetime(2010, 1, 1),
end=datetime(2014, 11, 21))
prophet.register_portfolio_analyzers(default_analyzers)
analysis = prophet.analyze_backtest(backtest)
assert round(analysis['sharpe'], 10) == 1.1083876014
assert round(analysis['average_return'], 10) == 0.0010655311
assert round(analysis['cumulative_return'], 10) == 2.2140809296
assert round(analysis['volatility'], 10) == 0.0152607097
today = datetime(2014, 11, 10)
expected_orders = Orders(Order(symbol='AAPL', shares=100))
assert prophet.generate_orders(today) == expected_orders
def test_quickstart():
prophet = Prophet()
prophet.set_universe(['AAPL', 'XOM'])
price_generator = YahooData('Adj Close', 'prices', cache_path=CACHE_PATH)
prophet.register_data_generators(price_generator)
prophet.set_order_generator(OrderGenerator())
backtest = prophet.run_backtest(start=datetime(2010, 1, 1),
end=datetime(2014, 11, 21))
prophet.register_portfolio_analyzers(default_analyzers)
analysis = prophet.analyze_backtest(backtest)
assert round(analysis['sharpe'], 10) == 1.0967430073
assert round(analysis['average_return'], 10) == 0.0010501702
assert round(analysis['cumulative_return'], 10) == 2.1604345132
assert round(analysis['volatility'], 10) == 0.0152004028
today = datetime(2014, 11, 10)
expected_orders = Orders(Order(symbol='AAPL', shares=100))
assert prophet.generate_orders(today) == expected_orders
