Overall Statistics
Total Orders
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Start Equity
1000.00
End Equity
1000
Net Profit
0%
Sharpe Ratio
0
Sortino Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
0
Tracking Error
0
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
Portfolio Turnover
0%
 
# region imports
from AlgorithmImports import *
# endregion

class MinimalTestAlgorithm(QCAlgorithm):

    def initialize(self):
        self.set_start_date(2024, 5, 2)  # Start date for backtest (first trading day of the year)
        self.set_end_date(2024, 5, 10)   # End date for backtest
        self.set_cash(1000)              # Capital for backtest
        self.eurusd = self.add_forex("EURUSD", resolution=Resolution.MINUTE, market=Market.OANDA).Symbol
        
        self.debug(f"Initialization Complete - Start Date: {self.start_date}, End Date: {self.end_date}, Pair: {self.eurusd}")
           # Attempt to retrieve historical data for debugging
        history = self.History(self.eurusd, 10, Resolution.Minute)
        self.debug(f"Retrieved {len(history)} historical data points")


    def on_data(self, data):
        self.debug(f"OnData called at {self.Time}")
        
        if self.Time.date() == self.start_date.date():
            self.debug(f"OnData triggered on Start Date: {self.Time}")
        
        if self.Time.date() == self.end_date.date():
            self.debug(f"OnData triggered on End Date: {self.Time}")

    def on_end_of_algorithm(self):
        self.debug("Algorithm Ended")

# Ensure this script is within a proper Lean Environment and run as expected.