mementum

date, open, high, low, close, volume, npy
2001-12-31, 1.0, 1.0, 1.0, 1.0, 0.5, 3.0
2002-01-31, 2.0, 2.5, 1.1, 1.2, 3.0, 5.0
...

mementum

class NetPayOutData(bt.feeds.GenericCSVData):
    lines = ('npy',)  # add a line containing the net payout yield
    params = dict(
        npy=6,  # npy field is in the 6th column (0 based index)
        dtformat='%Y-%m-%d',  # fix date format a yyyy-mm-dd
        timeframe=bt.TimeFrame.Months,  # fixed the timeframe
        openinterest=-1,  # -1 indicates there is no openinterest field
    )

mementum

class St(bt.Strategy):
    params = dict(
        selcperc=0.10,  # percentage of stocks to select from the universe
        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
        reserve=0.05  # 5% reserve capital
    )

mementum

def log(self, arg):
    print('{} {}'.format(self.datetime.date(), arg))

mementum

    def __init__(self):
        # calculate 1st the amount of stocks that will be selected
        self.selnum = int(len(self.datas) * self.p.selcperc)

        # allocation perc per 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 = (1.0 - self.p.reserve) % self.selnum

mementum

        # returns, volatilities and momentums
        rs = [bt.ind.PctChange(d, period=self.p.rperiod) for d in self.datas]
        vs = [bt.ind.StdDev(ret, period=self.p.vperiod) for ret in rs]
        ms = [bt.ind.ROC(d, period=self.p.mperiod) for d in self.datas]

        # simple rank formula: (momentum * net payout) / volatility
        # the highest ranked: low vol, large momentum, large payout
        self.ranks = {d: d.npy * m / v for d, v, m in zip(self.datas, vs, ms)}

mementum

    def next(self):
        # sort data and current rank
        ranks = sorted(
            self.ranks.items(),  # get the (d, rank), pair
            key=lambda x: x[1][0],  # use rank (elem 1) and current time "0"
            reverse=True,  # highest ranked 1st ... please
        )

mementum

        # put top ranked in dict with data as key to test for presence
        rtop = dict(ranks[:self.selnum])

        # For logging purposes of stocks leaving the portfolio
        rbot = dict(ranks[self.selnum:])

mementum

        # prepare quick lookup list of stocks currently holding a position
        posdata = [d for d, pos in self.getpositions().items() if pos]

mementum

        # remove those no longer top ranked
        # do this first to issue sell orders and free cash
        for d in (d for d in posdata if d not in rtop):
            self.log('Exit {} - Rank {:.2f}'.format(d._name, rbot[d][0]))
            self.order_target_percent(d, target=0.0)