外国為替 API を使用してプロのようにバックテストを行う

import tradermade as tm
import pandas as pd
def fetch_forex_data(api_key, currency, start_date, end_date,    interval="hourly", fields=["open", "high", "low", "close"]):

   # Set API key
   tm.set_rest_api_key(api_key)
   # Fetch the data
   data = tm.timeseries(currency=currency, start=start_date, end=end_date, interval=interval, fields=fields)

   # Convert data directly to DataFrame
   df = pd.DataFrame(data)

   # Convert 'date' column to datetime
   df["date"] = pd.to_datetime(df["date"])

   # Set 'date' as the index
   df.set_index("date", inplace=True)

   return df

# Adjust as needed
api_key = "YOUR TRADERMADE API KEY"
currency = "EURUSD"
start_date = "2024-11-01-00:00"
end_date = "2024-11-27-05:12"

# Fetch the data and display the first few rows
forex_data = fetch_forex_data(api_key, currency, start_date, end_date)
forex_data = forex_data.rename(columns={"open": "Open", "high": "High", "low": "Low", "close": "Close"})
forex_data.head()

import numpy as np
from backtesting import Backtest, Strategy
from backtesting.lib import crossover
from backtesting.test import SMA

# Define the SMA crossover trading strategy
class SMACrossoverStrategy(Strategy):
       def init(self):
           # Calculate shorter-period SMAs for limited data
           price = self.data.Close
           self.short_sma = self.I(SMA, price, 20)  # Short window
           self.long_sma = self.I(SMA, price, 60)  # Long window

       def next(self):
           # Check for crossover signals
           if crossover(self.short_sma, self.long_sma):
               self.buy()
           elif crossover(self.long_sma, self.short_sma):
               self.sell()

   # Initialize and run the backtest
bt = Backtest(forex_data, SMACrossoverStrategy, cash=10000, commission=.002)
result = bt.run()

   # Display the backtest results
print("Backtest Results:")
print(result)