Backtest Your Dollar Cost Average Strategy easily in Python

dca-backtesting-py.py

# Licensed under the MIT License. See comment below for full licence information.

import pandas as pd
from backtesting import Backtest, Strategy

from backtesting.test import GOOG
import math


class DCA(Strategy):

    amount_to_invest = 10

    def init(self):

        self.day_of_week = self.I(
                            lambda x: x,
                            self.data.Close.s.index.dayofweek,
                            plot = False,
                            )

    def next(self):

        if self.day_of_week[-1] == 1:
            self.buy( size = math.floor(self.amount_to_invest / self.data.Close[-1]))
            try:
                if self.data.Close[-1]/self.data.Close[-30] < 0.95:
                    self.buy( size = math.floor(self.amount_to_invest / self.data.Close[-1]))
            except:
                pass



print(GOOG)

GOOG = GOOG * 10**-6

bt = Backtest(
        GOOG,
        DCA,
        trade_on_close = True,
        finalize_trades = True,
        )

stats = bt.run()

print(stats)

# Size  EntryBar  ExitBar  EntryPrice  ExitPrice 

trades = stats["_trades"]
price_paid = trades["Size"] * trades["EntryPrice"]
total_invested = price_paid.sum()

current_shares = trades["Size"].sum()
current_equity = current_shares * GOOG.Close.iloc[-1]

print("Total investment:",total_invested)
print("Current Shares:",current_shares / (10**6))
print("current Equity:", current_equity)

print("Return:", current_equity / total_invested)

Hi Chad,
I had to insert
finalize_trades = True,
before line 42 in your code, otherwise it just shows 0 trades in the stats and also subsequent calcs fail.
Maybe this is because of a newer version of the backtesting library!?

Cheers, Marc

@marc260870-byte. Hey Mark, yes looks like there was an API change introduced in version 0.6.0 I've updated the script like you suggested. Thanks!