Hey there, trader! 👋 Looking to supercharge your trading strategy development? You're in the right place!
Backtest Manager is your new best friend for algorithmic trading strategy development - a powerful VSCode extension that makes backtesting as easy as a few clicks. No more juggling complex configurations or switching between different tools!
Developing trading strategies can be complex and time-consuming. With Backtest Manager, you'll:
- Save hours of setup time - everything runs right in your favorite IDE
- Visualize results instantly - see how your strategies perform without extra tools
- Iterate faster - quickly tweak parameters and re-run tests in seconds
- Focus on strategy logic - not on technical setup or configuration hassles
- Make better trading decisions - backed by solid data and performance metrics
- Backtest Strategy Development & Management: Create and manage backtest strategies directly within VSCode.
- Visual Result Analysis: View backtest results through gorgeous graphs and comprehensive statistical data.
- Project Management: Keep everything organized with easy project management tools.
- Environment Variable Configuration: Experiment freely by changing parameters on the fly.
- AI Assistance: Leverage VSCode's AI capabilities to write smarter, more optimized strategy code.
- Backtrader - Python-based backtesting framework
- Visual Studio Code 1.98.0 or higher
- Python 3.7 or higher
- Backtrader library
pip install backtrader- Search for 'Backtest Manager' in the VSCode marketplace
- Install the extension
- Restart VSCode
Just a few clicks and you're ready to start building your trading empire:
- Click on the Backtest Manager icon in the activity bar
- Click the 'Create New Project' button
- Enter a project name (a basic template will be automatically generated)
Backtest Manager provides a basic template, and you can write strategies with AI assistance. Get creative and let your trading ideas flow!
import backtrader as bt
class MyStrategy(bt.Strategy):
params = (
('period', 20), # Moving average period
('riskpercent', 2), # Risk percentage
)
def __init__(self):
self.sma = bt.indicators.SimpleMovingAverage(self.data.close, period=self.params.period)
def next(self):
if not self.position:
if self.data.close[0] > self.sma[0]:
size = self.broker.getcash() * (self.params.riskpercent / 100) / self.data.close[0]
self.buy(size=size)
else:
if self.data.close[0] < self.sma[0]:
self.sell()
# cerebro configuration
def cerebro_init(cerebro: bt.Cerebro):
# data = bt.feeds.YahooFinanceData()
# cerebro.adddata(data)
pass
# The extension automatically handles data and cerebro setup using the cerebro_init functionEach project must include the cerebro_init function, which allows the extension to handle data loading and cerebro configuration. This function is called automatically by the extension before running the backtest.
Testing your brilliant strategy ideas has never been easier:
- Open and edit the strategy file
- Click the backtest run button (or use the right-click menu in the project panel)
- Adjust necessary parameters and settings
- Click the 'Run Backtest' button and watch the magic happen!
Dive deep into your strategy's performance with comprehensive analytics:
- Equity curve graph - see your profits grow
- Performance metrics (total return, Sharpe ratio, maximum drawdown, win rate, etc.)
- Trade history (time, price, size, profit, etc.)
Distributed under the MIT License.
Got ideas to make this even better? Issues and pull requests are always welcome! Contributors should check the issue tracker.
Note: A Korean version of this README is available in the README_ko.md file. 🇰🇷