Strategy based on constituent lists

[jondej123]

When I try to make a portfolio strategy based on yearly constituent lists, my code works. But when I try it for monthly constituent lists, it does not work. You can find my code for the yearly strategy below:

class EquallyWeighted(bt.Strategy):
params = (
('constituent_companies', {}), # a dictionary mapping year to list of consistent companies
)

def __init__(self):
    self.current_year = self.datas[0].datetime.date().year
    self.constituent_companies = self.params.constituent_companies.get(self.current_year, [])
    self.weights = {}  # Dictionary to store the weights for each company

def next(self):
    if self.datas[0].datetime.date().year != self.current_year:
        self.current_year = self.datas[0].datetime.date().year
        self.close_all_positions()  # close all positions

        self.constituent_companies = self.params.constituent_companies.get(self.current_year, [])
        self.calculate_weights()  # calculate new weights for the constituent companies

    for i, d in enumerate(self.datas):
        if not self.getposition(d).size:
            if d._name in self.constituent_companies:
                size = self.broker.get_cash() * self.weights[d._name]  # calculate position size based on weight
                self.buy(data=d, size=size)

def close_all_positions(self):
    for i, d in enumerate(self.datas):
        position = self.getposition(d).size
        if position > 0:
            self.close(data=d)

def calculate_weights(self):
    num_companies = len(self.constituent_companies)
    if num_companies > 0:
        weight = 1.0 / num_companies
        for company in self.constituent_companies:
            self.weights[company] = weight

if name == 'main':
# Create a cerebro entity
cerebro = bt.Cerebro()

# Define the path to the CSV file
base_path = '/Users/jonat/Documents/Documenten/data/Test/Constituents/'

# Read constituent companies for each year
constituent_companies = {}
years = [2000, 2001, 2002, 2003, 2004]  # Update with your desired years
for year in years:
    csv_path = base_path + f'constituent_companies_{year}.csv'
    with open(csv_path, 'r', encoding='utf-8-sig') as csvfile:
        reader = csv.reader(csvfile)
        next(reader)  # Skip the header row
        companies = [row[0] for row in reader if row[0]]  # Read company names from column A
        constituent_companies[year] = companies

cerebro.addstrategy(EquallyWeighted, constituent_companies=constituent_companies)

datalist = ['AAPL.csv', 'DIS.csv', 'IBM.csv', 'BA.csv', 'F.csv', 'GE.csv', 'KO.csv', 'MMM.csv', 'PG.csv', 'XOM.csv']
datapath= "/Users/jonat/Documents/Documenten/data/Test/"

for i in range(len(datalist)):
    data= bt.feeds.YahooFinanceCSVData(
        dataname=datapath+datalist[i],
        # Do not pass values before this date
        fromdate=datetime(2000, 1, 1),
        # Do not pass values after this date
        todate=datetime(2004, 12, 31),
        reverse=False)
    cerebro.adddata(data, name=datalist[i])
    
# Set our desired cash start
cerebro.broker.setcash(1000.0)

# Add a FixedSize sizer according to the stake
cerebro.addsizer(bt.sizers.PercentSizer, percents=10)

# Set the commission
cerebro.broker.setcommission(commission=0.0)

# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

# Run over everything
cerebro.run()

# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

You can find my code for the monthly strategy below:

class EquallyWeightedM(bt.Strategy):
params = (
('constituent_companies', {}), # a dictionary mapping year to list of consistent companies
)

def __init__(self):
    self.constituent_companies = constituent_companies
    self.weights = {}  # Dictionary to store the weights for each company

def start(self):
    self.calculate_weights()

def next(self):
    for i, d in enumerate(self.datas):
        if not self.getposition(d).size:
            if d._name in self.weights:
                size = self.broker.get_cash() * self.weights[d._name]  # calculate position size based on weight
                self.buy(data=d, size=size)

def calculate_weights(self):
    num_companies = len(self.constituent_companies)
    if num_companies > 0:
        weight = 1.0 / num_companies
        for company in self.constituent_companies:
            self.weights[company] = weight

if name == 'main':
cerebro = bt.Cerebro()
cerebro.addstrategy(EquallyWeightedM, constituent_companies=constituent_companies)

base_path = '/Users/jonat/Documents/Documenten/data/Test/Constituents/'
dates = [datetime(2000, 1, 1), datetime(2000, 2, 1), datetime(2000, 3, 1), datetime(2000, 4, 1), datetime(2000, 5, 1)]

for date in dates:
    csv_path = base_path + f'constituent_companies_{date.strftime("%Y-%m-%d")}.csv'
    with open(csv_path, 'r', encoding='utf-8-sig') as csvfile:
        reader = csv.reader(csvfile)
        next(reader)  # Skip the header row
        companies = [row[0] for row in reader if row[0]]  # Read company names from column A

datalist = ['AAPL.csv', 'DIS.csv', 'IBM.csv', 'BA.csv', 'F.csv', 'GE.csv', 'KO.csv', 'MMM.csv', 'PG.csv', 'XOM.csv']
datapath= "/Users/jonat/Documents/Documenten/data/Test/"

for i in range(len(datalist)):
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath+datalist[i],
        fromdate=datetime(2000, 1, 1),
        todate=datetime(2004, 12, 31),
        reverse=False
    )
    cerebro.adddata(data, name=datalist[i])

cerebro.broker.setcash(1000.0)
cerebro.addsizer(bt.sizers.PercentSizer, percents=10)
cerebro.broker.setcommission(commission=0.0)

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

Can someone help me out?