def add_strategies(symbols, strategies):
""" 一个组合中的策略
Args:
algos (list): 一个策略组合
Returns:
Profile. 组合结果
"""
simulator = ExecuteUnit(symbols, "1980-1-1", "2100-1-1", None, {})
profiles = list(simulator.add_strategies(strategies))
simulator.run()
return profiles
def run(TheStrategy, code, datasource=_default_datasource):
print 'code: ' + code
pcon = stock(code)
#dt_start = '20130101'
#dt_end = '20150819'
dt_start = None
dt_end = None
simulator = ExecuteUnit([pcon], dt_start, dt_end, datasource=datasource)
algo = TheStrategy(simulator)
simulator.run()
a = {}
b = []
try:
for trans in algo.blotter.transactions:
deals.update_positions(a, b, trans)
except Exception, e:
print e
def run(TheStrategy, code, datasource=_default_datasource):
print 'code: ' + code
pcon = stock(code)
#dt_start = '20130101'
#dt_end = '20150819'
dt_start = None
dt_end = None
simulator = ExecuteUnit([pcon], dt_start, dt_end, datasource=datasource)
algo = TheStrategy(simulator)
simulator.run()
a = {}
b = []
try:
for trans in algo.blotter.transactions:
deals.update_positions(a, b, trans);
except Exception, e:
print e
def set_symbols(pcontracts,
dt_start="1980-1-1",
dt_end="2100-1-1",
n=None,
spec_date={}): # 'symbol':[,]
"""
Args:
pcontracts (list): list of pcontracts(string)
dt_start (datetime/str): start time of all pcontracts
dt_end (datetime/str): end time of all pcontracts
n (int): last n bars
spec_date (dict): time range for specific pcontracts
"""
global _simulator
_simulator = ExecuteUnit(pcontracts, dt_start, dt_end, n, spec_date)
return _simulator
def set_symbols(pcons, window_size=0,
dt_start=datetime.datetime(1980,1,1),
dt_end=datetime.datetime(2100,1,1)):
""" 添加数据
Args:
pcons ([str,]): 周期合约数组
dt_start (str): 开始时间
dt_end (str): 结束
window_size (int): 序列数据的窗口大小
"""
global g_simulator
## @TODO pcon格式验证
g_simulator = ExecuteUnit(pcons, window_size, dt_start, dt_end)
return g_simulator
self.num_cont += 1
#six.print_('buy', self.datetime[0].date(), price, quantity)
elif self.position() > 0 and self.masmall < self.mabig:
price = self.close[0]
self.sell('long', price, self.position())
#six.print_('sel', self.datetime[0].date(), price, self.position())
#six.print_('---')
if price > self.buy_price:
self.num_win += 1
if __name__ == '__main__':
pcon = stock(code)
simulator = ExecuteUnit(
[pcon],
None, #'2015-08-02',
# 使用自定义的数据源
datasource=ds163.CachedStock163Source('163cache'))
algo = DemoStrategy(simulator)
simulator.run()
#six.print_('close: ', algo.close.data)
#six.print_('close length: ', algo.close.length_history)
six.print_('total: %s, win: %s' % (algo.num_cont, algo.num_win))
# 显示回测结果
a = {}
b = []
try:
for trans in algo.blotter.transactions:
deals.update_positions(a, b, trans)
except Exception, e:
self.buy('long', self.open, 1, contract = 'IF000.SHFE')
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
print self.open_(1)[1], self.open
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
if __name__ == '__main__':
try:
pcon = pcontract('IF000.SHFE', '10.Minute')
begin_dt, end_dt = None, None
#begin_dt, end_dt = '2015-05-25', '2015-06-01'
#pcon = stock('600848','10.Minute') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon], begin_dt, end_dt)
algo = DemoStrategy(simulator)
#algo1 = DemoStrategy(simulator)
#algo2 = DemoStrategy(simulator)
simulator.run()
#for deal in algo.blotter.deal_positions:
## code...
#print("----------------")
#print("开仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；") % \
#(deal.open_datetime, deal.open_price, Direction.type_to_str(deal.direction), deal.quantity)
#print("平仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；盈亏: %f；") % \
#(deal.close_datetime, deal.close_price, Direction.type_to_str(deal.direction), deal.quantity, deal.profit())
# 显示回测结果
a = {}
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy('long', self.open, 1, contract = 'IF000.SHFE')
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
#print self.datetime[0]
if __name__ == '__main__':
try:
pcon = pcontract('BB.SHFE', '1.Minute')
#begin_dt, end_dt = '2015-05-25', '2015-06-01'
#pcon = stock('600848','10.Minute') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon])
algo = DemoStrategy(simulator)
#algo1 = DemoStrategy(simulator)
#algo2 = DemoStrategy(simulator)
simulator.run()
# 显示回测结果
from quantdigger.datastruct import TradeSide
ping = 0
kai = 0
for t in algo.blotter.transactions:
if t.side == TradeSide.PING:
ping += t.quantity
elif t.side == TradeSide.KAI:
kai += t.quantity
elif self.position(
) > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
#print self.datetime[0]
if __name__ == '__main__':
try:
pcon = pcontract('BB.SHFE', '1.Minute')
#begin_dt, end_dt = '2015-05-25', '2015-06-01'
#pcon = stock('600848','10.Minute') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon], '2013-12-12', '2013-12-25')
algo = DemoStrategy(simulator)
#algo1 = DemoStrategy(simulator)
#algo2 = DemoStrategy(simulator)
simulator.run()
#for deal in algo.blotter.deal_positions:
## code...
#print("----------------")
#print("开仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；") % \
#(deal.open_datetime, deal.open_price, Direction.type_to_str(deal.direction), deal.quantity)
#print("平仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；盈亏: %f；") % \
#(deal.close_datetime, deal.close_price, Direction.type_to_str(deal.direction), deal.quantity, deal.profit())
# 显示回测结果
positions = {}
) > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
print self.open_(1)[1], self.open
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
if __name__ == '__main__':
try:
pcon = pcontract('IF000.SHFE', '10.Minute')
begin_dt, end_dt = None, None
#begin_dt, end_dt = '2015-05-25', '2015-06-01'
#pcon = stock('600848','10.Minute') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon], begin_dt, end_dt)
algo = DemoStrategy(simulator)
#algo1 = DemoStrategy(simulator)
#algo2 = DemoStrategy(simulator)
simulator.run()
#for deal in algo.blotter.deal_positions:
## code...
#print("----------------")
#print("开仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；") % \
#(deal.open_datetime, deal.open_price, Direction.type_to_str(deal.direction), deal.quantity)
#print("平仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；盈亏: %f；") % \
#(deal.close_datetime, deal.close_price, Direction.type_to_str(deal.direction), deal.quantity, deal.profit())
# 显示回测结果
a = {}
