Easy Backtest using Backtrader: Rebalance Edition

# install requirement
%pip install backtrader yfinance matplotlib

# import libs
import datetime
import backtrader as bt
import yfinance as yf
import matplotlib.pyplot as plt

## ticker and ratio
TICKERS = {"VTI": 0.4, "BND": 0.4, "GLD": 0.2}
## start date and end date
FROMDATE = datetime.datetime(2014, 7, 1)
TODATE = datetime.datetime(2024, 7, 1)

# Implement strategy of rebalance
class RebalanceOncePerMonth(bt.Strategy):
    def __init__(self):
        self.last_rebalance = None  # Date last rebalanced
    def next(self):
        dt = self.datetime.date()
        if self.last_rebalance is None or (dt - self.last_rebalance).days >= 30: # If 30 days or more passed
            # self.broker.add_cash(1000) # In case of accumulation, do add_cash every certain period
            self.rebalance_portfolio()
            self.last_rebalance = dt
    def rebalance_portfolio(self):
        total_value = self.broker.getvalue()
        for data in self.datas:
            ticker = data._name
            allocation = data.target
            target_value = total_value * allocation
            current_value = self.getposition(data).size * data.close[0]
            difference = target_value - current_value
            if difference > 0:
                # Buy
                size = difference // data.close[0]
                self.buy(data=data, size=size)
            elif difference < 0:
                # Sell
                size = -difference // data.close[0]
                self.sell(data=data, size=size)

# Initialization of backtrader
cerebro = bt.Cerebro()
cerebro.broker.set_cash(10000)
cerebro.addstrategy(RebalanceOncePerMonth)
# Read data from yahoofinance
for ticker, target in TICKERS.items():
    data = bt.feeds.PandasData(
        dataname=yf.download(ticker, start=FROMDATE, end=TODATE)
    )
    data.target = target
    cerebro.adddata(data, name=ticker)
# Execution of backtest
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

plt.rcParams['figure.figsize'] = [12, 10]
cerebro.plot(iplot=False)