class DualEMATaLib(TradingAlgorithm): """ Dual Moving Average Crossover algorithm. This algorithm buys apple once its short moving average crosses its long moving average (indicating upwards momentum) and sells its shares once the averages cross again (indicating downwards momentum). """ def __init__(self, dbhandler, *args, **kwargs): super(DualEMATaLib, self).__init__(*args, **kwargs) self.dbhandler = dbhandler self.mstockid = self.dbhandler.stock.ids[0] def initialize(self, short_window=20, long_window=40): # Add 2 mavg transforms, one with a long window, one # with a short window. self.short_ema_trans = EMA(timeperiod=short_window) self.long_ema_trans = EMA(timeperiod=long_window) self.real_obv_trans = OBV() # To keep track of whether we invested in the stock or not self.invested = False def handle_data(self, data): self.short_ema = self.short_ema_trans.handle_data(data) self.long_ema = self.long_ema_trans.handle_data(data) self.real_obv = self.real_obv_trans.handle_data(data) if self.short_ema is None or self.long_ema is None or self.real_obv is None: return self.buy = False self.sell = False # buy/sell rule if (self.short_ema > self.long_ema).all() and not self.invested: self.order(self.mstockid, 1000) self.invested = True self.buy = True elif (self.short_ema < self.long_ema).all() and self.invested: self.order(self.mstockid, -1000) self.invested = False self.sell = True # save to recorder signals = { 'open': data[self.mstockid].open, 'high': data[self.mstockid].high, 'low': data[self.mstockid].low, 'close': data[self.mstockid].close, 'volume': data[self.mstockid].volume, 'short_ema': self.short_ema[self.mstockid], 'long_ema': self.long_ema[self.mstockid], 'buy': self.buy, 'sell': self.sell } self.record(**signals)
def initialize(self, short_window=20, long_window=40): # Add 2 mavg transforms, one with a long window, one # with a short window. self.short_ema_trans = EMA(timeperiod=short_window) self.long_ema_trans = EMA(timeperiod=long_window) # To keep track of whether we invested in the stock or not self.invested = False
def initialize(context): context.asset = symbol('AAPL') # Add 2 mavg transforms, one with a long window, one with a short window. context.short_ema_trans = EMA(timeperiod=20) context.long_ema_trans = EMA(timeperiod=40) # To keep track of whether we invested in the stock or not context.invested = False
def initialize(self): self.asset = self.symbol('AAPL') # Add 2 mavg transforms, one with a long window, one with a short window. self.short_ema_trans = ta.EMA(timeperiod=20) self.long_ema_trans = EMA(timeperiod=40) # To keep track of whether we invested in the stock or not self.invested = False
class DualEMATaLib(TradingAlgorithm): """Dual Moving Average Crossover algorithm. This algorithm buys apple once its short moving average crosses its long moving average (indicating upwards momentum) and sells its shares once the averages cross again (indicating downwards momentum). """ def initialize(self, short_window=20, long_window=40): # Add 2 mavg transforms, one with a long window, one # with a short window. self.short_ema_trans = EMA(timeperiod=short_window) self.long_ema_trans = EMA(timeperiod=long_window) # To keep track of whether we invested in the stock or not self.invested = False def handle_data(self, data): self.short_ema = self.short_ema_trans.handle_data(data) self.long_ema = self.long_ema_trans.handle_data(data) if self.short_ema is None or self.long_ema is None: return self.buy = False self.sell = False if (self.short_ema > self.long_ema).all() and not self.invested: self.order('AAPL', 100) self.invested = True self.buy = True elif (self.short_ema < self.long_ema).all() and self.invested: self.order('AAPL', -100) self.invested = False self.sell = True self.record(AAPL=data['AAPL'].price, short_ema=self.short_ema['AAPL'], long_ema=self.long_ema['AAPL'], buy=self.buy, sell=self.sell)
class DualEMATaLib(TradingAlgorithm): """Dual Moving Average Crossover algorithm. This algorithm buys apple once its short moving average crosses its long moving average (indicating upwards momentum) and sells its shares once the averages cross again (indicating downwards momentum). """ def initialize(self, short_window=20, long_window=40): # Add 2 mavg transforms, one with a long window, one # with a short window. self.short_ema_trans = EMA(timeperiod=short_window) self.long_ema_trans = EMA(timeperiod=long_window) # To keep track of whether we invested in the stock or not self.invested = False def handle_data(self, data): self.short_ema = self.short_ema_trans.handle_data(data) self.long_ema = self.long_ema_trans.handle_data(data) if self.short_ema is None or self.long_ema is None: return self.buy = False self.sell = False if self.short_ema > self.long_ema and not self.invested: self.order('AAPL', 100) self.invested = True self.buy = True elif self.short_ema < self.long_ema and self.invested: self.order('AAPL', -100) self.invested = False self.sell = True self.record(AAPL=data['AAPL'].price, short_ema=self.short_ema['AAPL'], long_ema=self.long_ema['AAPL'], buy=self.buy, sell=self.sell)
class DualEmaTalib(zp.TradingAlgorithm): def __init__(self, *args, **kwargs): super(DualEmaTalib, self).__init__( *args, **kwargs) #mid 采用super(child,self).method()格式调用某个类的父类的方法。 def initialize(self): self.asset = self.symbol('AAPL') # Add 2 mavg transforms, one with a long window, one with a short window. self.short_ema_trans = ta.EMA(timeperiod=20) self.long_ema_trans = EMA(timeperiod=40) # To keep track of whether we invested in the stock or not self.invested = False def handle_data(self, data): #mid only long short_ema = self.short_ema_trans.handle_data(data) long_ema = self.long_ema_trans.handle_data(data) if short_ema is None or long_ema is None: return buy = False sell = False if (short_ema > long_ema).all() and not self.invested: self.order(self.asset, 100) self.invested = True buy = True elif (short_ema < long_ema).all() and self.invested: self.order(self.asset, -100) self.invested = False sell = True self.record(AAPL=data[self.asset].price, short_ema=short_ema[self.asset], long_ema=long_ema[self.asset], buy=buy, sell=sell)