Hi I have problem. There is no graph in implementing the momentum strategy.

[황윤태]

My code is as follows. I wonder how we can get the graph to print out.
And look at the code and point out if there's a problem.
Thank you in advance for all the people who will reply.

import pandas as pd
import numpy as np
import backtrader as bt
from scipy.stats import linregress
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
import backtrader.plot
from matplotlib.pyplot import figure
from datetime import datetime
import yfinance as yf

# Date range
start = '2010-01-01'
end = '2020-03-25'

ETF_TICKERS = ['XLB', 'XLE', 'XLF', 'XLI', 'XLK', 'XLP', 'XLU', 'XLV', 'XLY',"SPY"]

prices = yf.download(ETF_TICKERS, start = start, end = end)
prices = prices.dropna()

def momentum_func(self, price_array):
    r = np.log(price_array)
    slope, _, rvalue, _, _ = linregress(np.arange(len(r)), r)
    annualized = (1 + slope) ** 252
    return (annualized * (rvalue ** 2))


class Momentum(bt.ind.OperationN):
    lines = ('trend',)
    params = dict(period=90)
    func = momentum_func


class Strategy(bt.Strategy):
    params = dict(
        momentum=Momentum,
        momentum_period=180,
        num_positions=2,
        when=bt.timer.SESSION_START,
        timer=True,
        monthdays=[1],
        monthcarry=True,
        printlog=True
    )

    def log(self, txt, dt=None, doprint=False):
        ''' Logging function fot this strategy'''
        if self.params.printlog or doprint:
            dt = dt or self.datas[0].datetime.date(0)
            print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.i = 0
        self.securities = self.datas[1:]
        self.inds = {}

        self.add_timer(
            when=self.p.when,
            monthdays=self.p.monthdays,
            monthcarry=self.p.monthcarry
        )

        for security in self.securities:
            self.inds[security] = self.p.momentum(security,
                                                  period=self.p.momentum_period)

    def notify_timer(self, timer, when, *args, **kwargs):
        if self._getminperstatus() < 0:
            self.rebalance()

    def rebalance(self):
        rankings = list(self.securities)
        rankings.sort(key=lambda s: self.inds[s][0], reverse=True)
        pos_size = 1 / self.p.num_positions

        # Sell stocks no longer meeting ranking filter.
        for i, d in enumerate(rankings):
            if self.getposition(d).size:
                if i > self.p.num_positions:
                    self.close(d)

        # Buy and rebalance stocks with remaining cash
        for i, d in enumerate(rankings[:self.p.num_positions]):
            self.order_target_percent(d, target=pos_size)

    def next(self):
        self.notify_timer(self, self.p.timer, self.p.when)

    def stop(self):
        self.log('| %2d | %2d |  %.2f |' %
                 (self.p.momentum_period,
                  self.p.num_positions,
                  self.broker.getvalue()),
                 doprint=True)


if __name__ == '__main__':
    assets_prices = []

    for i in ETF_TICKERS[1:len(ETF_TICKERS) - 1]:
        prices_ = prices.drop(columns='Adj Close').loc[:, (slice(None), i)].dropna()
        prices_.columns = ['Close', 'High', 'Low', 'Open', 'Volume']
        assets_prices.append(bt.feeds.PandasData(dataname=prices_, plot=True))

    # Creating Benchmark bt.feeds
    benchdata = prices.drop(columns='Adj Close').loc[:, (slice(None), 'SPY')].dropna()
    benchdata.columns = ['Close', 'High', 'Low', 'Open', 'Volume']
    benchdata = bt.feeds.PandasData(dataname=benchdata, plot=True)

    cerebro = bt.Cerebro(optreturn=False)

    for data in benchdata:
        cerebro.adddata(benchdata)

    for data in assets_prices:
        data.plotinfo.plotmaster = benchdata
        cerebro.adddata(data)

    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Add Strategy
    stop = len(ETF_TICKERS) + 1
    cerebro.optstrategy(Strategy,
                        momentum_period=range(50, 300, 50),
                        num_positions=range(1, len(ETF_TICKERS) + 1))

    # Run the strategy. Results will be output from stop.
    cerebro.run(stdstats=False, tradehistory=False)

    cerebro.plot()

[vladisld]

I'm not sure plotting works well with optstrategy (if at all). See: https://community.backtrader.com/topic/409/optstrategy-and-plotting

[황윤태]

@vladisld said in Hi I have problem. There is no graph in implementing the momentum strategy.:

optstrategy

Thank you for your Reply .
I tried, but it didn't work out. ...................