Overall Statistics
Total Trades
128
Average Win
0.32%
Average Loss
-0.50%
Compounding Annual Return
-0.024%
Drawdown
11.400%
Expectancy
-0.002
Net Profit
-0.158%
Sharpe Ratio
0.013
Probabilistic Sharpe Ratio
0.266%
Loss Rate
39%
Win Rate
61%
Profit-Loss Ratio
0.64
Alpha
0.001
Beta
-0.002
Annual Standard Deviation
0.036
Annual Variance
0.001
Information Ratio
-0.782
Tracking Error
0.167
Treynor Ratio
-0.212
Total Fees
$281.27
Estimated Strategy Capacity
$11000.00
Lowest Capacity Asset
QAT VQ6KGBSR66AT
 
# https://quantpedia.com/strategies/ramadan-effect/
#
# The investment universe consists of countries for which stock market index data are available and in which the proportion of population the professing Muslim faith
# exceeded 50%. Most of the countries could be easily tracked via index ETFs. The research paper we use as an example uses 14 Muslim countries.
# Ramadan is the ninth month in the Islamic calendar, which is based on the motion of the moon. The Ramadan month could be calculated by using information on the
# lunar phases and sunset times from astronomical calendar or information about Ramadan dates from various public sources.
# The trading strategy is simple. The investor holds an equally weighted portfolio of ETFs during Ramadan month. He/she is otherwise invested in cash.

class RamadanEffect(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2015, 1, 1)
        self.SetCash(100000)
        
        self.symbols = ['TUR', 'GULF', 'GAF', 'PAK', 'UAE', 'QAT', 'EGPT', 'EWM', 'EIDO', 'KSA']
        for symbol in self.symbols:
            self.AddEquity(symbol, Resolution.Daily)

        csv_string_file = self.Download('data.quantpedia.com/backtesting_data/economic/ramadan_dates.csv')
        date_pairs_str = csv_string_file.split('\r\n')
        date_pairs = []
        for pair in date_pairs_str:
            split = pair.split(';')
            date_pairs.append([datetime.strptime(split[0], "%d.%m.%Y"), datetime.strptime(split[1], "%d.%m.%Y")])
            
        start_dates = [pair[0] for pair in date_pairs]
        end_dates = [pair[1] for pair in date_pairs]
        
        self.Schedule.On(self.DateRules.On(start_dates), self.TimeRules.AfterMarketOpen(self.symbols[0]), self.Open)
        self.Schedule.On(self.DateRules.On(end_dates), self.TimeRules.AfterMarketOpen(self.symbols[0]), self.Close)

    def Open(self):
        if not self.Portfolio.Invested:
            count = len(self.symbols)
            for symbol in self.symbols:
                self.SetHoldings(symbol, 1 / count)

    def Close(self):
        self.Liquidate()