bt_main_optimize.py

import datetime
import backtrader as bt
from strategies import *

# Instantiate Cerebro engine
cerebro = bt.Cerebro(optreturn=False)

# Set data parameters and add to Cerebro
data = bt.feeds.YahooFinanceCSVData(
	dataname='TSLA.csv',
	fromdate=datetime.datetime(2016, 1, 1),
	todate=datetime.datetime(2017, 12, 31),
)

cerebro.adddata(data)

# Add strategy to Cerebro
cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name='sharpe_ratio')
cerebro.optstrategy(
	MAcrossover, pfast=range(5, 20), pslow=range(50, 100)
)  # Add the trading strategy

# Default position size
cerebro.addsizer(bt.sizers.SizerFix, stake=3)

if __name__ == '__main__':
	
	optimized_runs = cerebro.run()

	final_results_list = []
	# Iterate through list of lists
	for run in optimized_runs:
		for strategy in run:
			PnL = round(strategy.broker.get_value() - 10000, 2)
			sharpe = strategy.analyzers.sharpe_ratio.get_analysis()
			final_results_list.append(
				[
					strategy.params.pfast,
					strategy.params.pslow,
					PnL,
					sharpe['sharperatio'],
				]
			)

	sort_by_sharpe = sorted(final_results_list, key=lambda x: x[3], reverse=True)
	# Print top 5 results sorted by Sharpe Ratio
	for line in sort_by_sharpe[:5]:
		print(line)