def cross(self, ticker, signal_a, signal_b):
if self.current_date == self.portfolio.start_day:
return 'no_cross'
prev_day = self.portfolio.get_prev_day()
today = self.current_date
signal_a_0 = dm.get_value(
ticker, signal_a, prev_day,
self.portfolio.trader.confirmation_indicators_table, 1)
signal_a_1 = dm.get_value(
ticker, signal_a, today,
self.portfolio.trader.confirmation_indicators_table, 1)
# signal_a_0 = self.portfolio.get_value(ticker, signal_a, date = prev_day)
# signal_a_1 = self.portfolio.get_value(ticker, signal_a, date = today)
# if signal_b != 0:
# signal_b_0 = self.portfolio.get_value(ticker, signal_b, date=prev_day)
# signal_b_1 = self.portfolio.get_value(ticker, signal_b, date = today)
# else:
signal_b_0 = 0
signal_b_1 = 0
if (signal_a_1 >= signal_b_1) and (signal_a_0 < signal_b_0):
return 'up'
elif (signal_a_0 > signal_b_0) and (signal_a_1 <= signal_b_1):
return 'down'
else:
return 'no_cross'
def buy_signal(stock_ticker):
confirmation_value = dm.get_value(
stock_ticker, 'total_score', self.current_date,
self.portfolio.trader.confirmation_indicators_table, 1)
if confirmation_value >= confirmation_total_buy_limit:
return True
else:
return False
def calc_net_worth(self):
cash = self.current_cash
current_stocks = self.get_current_stocks()
total_net_worth = 0 + cash
for stock in current_stocks:
price = dm.get_value(stock, self.price_field, self.current_day, self.dataset, 1)
stock_total_cost = price * self.get_num_shares(stock)
total_net_worth = total_net_worth + stock_total_cost
return total_net_worth
def modular_strategy(self, params):
# entry_indicator_name = params['entry_indicator'] + str(int(params['entry_indicator_period']))
# volume_total_buy_limit = params['volume_total_buy_limit']
confirmation_total_buy_limit = params['confirmation_total_buy_limit']
close = self.price_field
order = None
def buy_signal(stock_ticker):
confirmation_value = dm.get_value(
stock_ticker, 'total_score', self.current_date,
self.portfolio.trader.confirmation_indicators_table, 1)
if confirmation_value >= confirmation_total_buy_limit:
return True
else:
return False
def sell_signal(price, ticker, order):
sell_dict = {'flag': False, 'exit_type': None}
stop_loss = self.stop_loss(price, order)
trailing_stop = self.trailing_stop_loss(ticker, params)
if stop_loss or trailing_stop:
if stop_loss:
sell_dict['exit_type'] = 'stop_loss'
elif trailing_stop:
sell_dict['exit_type'] = 'trailing_stop'
sell_dict['flag'] = True
return sell_dict
else:
return sell_dict
def scale_out_signal(price, order):
if order.state() == 'open':
take_profit = self.take_profit(price, order)
if take_profit:
return True
else:
return False
for ticker in self.tradeable_tickers:
price = dm.get_value(ticker, close, self.current_date,
self.dataset, 1)
if not self.is_stock_in_portfolio(ticker):
if buy_signal(ticker):
self.add_buy_order(ticker)
else:
order = self.portfolio.get_open_order(ticker)
sell_dict = sell_signal(price, ticker, order)
if sell_dict['flag']:
self.add_sell_order(ticker, sell_dict['exit_type'])
elif scale_out_signal(price, order):
self.add_scale_out_order(ticker)
def trailing_stop_loss(self, ticker, params):
open_orders = self.portfolio.open_orders
value = params['trailing_stop_parameter']
stop_type = params['trailing_stop_type']
if stop_type == 'percentage':
for order in open_orders:
if order.stock == ticker:
max_price = order.max_price
price = dm.get_value(ticker, self.price_field,
self.current_date, self.dataset, 1)
loss = (max_price - price) / max_price
if loss >= value:
return True
else:
return False
raise Exception(
'trailing_stop_loss() - Ticker is not in open_orders!! Ticker['
+ str(ticker) + '] not available!!')
elif stop_type.startswith('atr'):
for order in open_orders:
if order.stock == ticker:
atr = dm.get_value(ticker, stop_type, self.current_date,
self.dataset, 1)
max_price = order.max_price
price = dm.get_value(ticker, self.price_field,
self.current_date, self.dataset, 1)
loss = (max_price - price)
if loss >= atr * value:
return True
else:
return False
raise Exception(
'trailing_stop_loss() - Ticker is not in open_orders!! Ticker['
+ str(ticker) + '] not available!!')
else:
raise Exception('Trailing stop type: ' +
str(params['trailing_stop_type']) +
' doesnt exit!')
def initial_stop_loss(self, ticker, value):
#value = 0.2 means 20% stop loss
open_orders = self.portfolio.open_orders
for order in open_orders:
if order['stock'] == ticker:
buy_price = order['price']
price = dm.get_value(ticker, self.price_field,
self.current_date, self.dataset, 1)
loss = (buy_price - price) / buy_price
if loss >= value:
return True
else:
return False
raise Exception(
'Initial_stop_loss - Ticker is not in open_orders!! Ticker[' +
str(ticker) + '] not available!!')
def get_value(self, ticker,field, date = None):
if date is None:
date = self.current_day
value = dm.get_value(ticker, field, date, self.dataset, 1)
return value
def get_current_price(self, ticker):
price = dm.get_value(ticker, self.price_field, self.current_day, self.dataset, 1)
return price