from backtrader.feeds import PandasData
class PycaishenData(PandasData):
# Add a 'pe' line to the inherited ones from the base class
lines = ('turnover','mkt_cap')
# openinterest in GenericCSVData has index 7 ... add 1
# add the parameter to the parameters inherited from the base class
params = (('turnover', -1),('mkt_cap',-1))
class StAmine(bt.Strategy):
params = dict(
rperiod=1, # period for the returns calculation, default 1 period
vperiod=36, # lookback period for volatility - default 36 periods
mperiod=12, # lookback period for momentum - default 12 periods
torank=10, # number of stocks to rank as top
reserve=0.05 # 5% reserve capital
)
def __init__(self):
# The highest ranked: mkt_cap
self.ranks = [bt.ind.movav(d.mkt_cap,period = 1) for d in self.datas]
# allocation perc pro stock
# reserve kept to make sure orders are not rejected due to
# margin. Prices are calculated when known (close), but orders can only
# be executed next day (opening price). Price can gap upwards
self.perctarget = (100.0 - self.p.reserve) % self.p.torank
def next(self):
# get the ranks sorted for each iteration in a list
ranks = sorted(
((self.datas[i], rank[0]) for i, rank in enumerate(self.ranks)),
key=lambda x: x[1], # use rank (elem 1 in the tuple) to sort
reverse=True, # highest ranked 1st ... please
)
# Put top 100 in ordereddict with data as key to test for presence
r100 = collections.OrderedDict(ranks[:self.p.torank])
# Remove those no longer Top 100, prepare quick lookup dict
positions = {pos: pos.data for pos in self.getpositions().values() if pos}
for pos, data in positions.items():
if data not in r100: # open and no rank100 ... close
self.order_target_percent(data, target=0.0)
# Add the newcomers to the Top 100, prepare easy reverse lookup
revpositions = {data: pos for pos, data in positions.items()}
for data in (d for d in r100 if d not in revpositions):
self.order_target_percent(data, target=self.perctarget)
def run(tickers, datas,strategy = StAmine,plotdetails= True,writedetail = False):
cerebro = bt.Cerebro()
print ('Starting Portfolio Value: %.2f ' % cerebro.broker.getvalue())
cerebro.addstrategy(strategy)
for ticker, data in zip(tickers , datas):
dt = PycaishenData(dataname=data)
if plotdetails == False:
dt.plotinfo.plot = False
cerebro.adddata(dt,ticker)
cerebro.broker.set_fundmode(True)
cerebro.broker.set_fundstartval(10.0) # the default is 100
cerebro.broker.setcommission(commission=0.0025)
# Add the Analyzers
cerebro.addanalyzer(btanalyser.SQN)
cerebro.addanalyzer(btanalyser.AnnualReturn)
cerebro.addanalyzer(btanalyser.SharpeRatio)
cerebro.broker.setcash(100000.0)
cerebro.addanalyzer(btanalyser.TradeAnalyzer)
if writedetail:
cerebro.addwriter(bt.WriterFile, csv=True, rounding=4)
cerebro.run()
cerebro.plot()
print ('Final portfolio value: %.2f' % cerebro.broker.getvalue())
run(tickers, datas,strategy = StAmine,plotdetails= False,writedetail = False)
the code seems to do nothing!!