Simple Quant Investment Strategy Development
This is the official VSCode plugin for QuantConnect. We empower investors with tools and data for easy quant strategy development.
QuantConnect is an open-source, community-driven algorithmic trading platform. More than 220,000 quants and engineers around the world harness QuantConnect to power their investment process. Each month our community writes more than 1M lines of code, and processes $1-2B in live trading volume.
This extension enables seamlessly developing quant strategies on-premise and in the QuantConnect cloud, getting the best of both environments. Harness your local version control, autocomplete, and coding tools with the full power of a scalable cloud at your finger tips.
We intend to keep complete feature parity with our cloud environment, allowing clients to harness cloud or local datasets to power on-premise quantitative research.
The extension requires Docker and the LEAN CLI. On launching the extension, we scan for these projects and prompt you to install them to continue with the extension. We run all algorithms in a Docker container to avoid installing any dependencies on your computer. The LEAN CLI is required to simplify the interactions with the cloud.
In the next few months we'll roll out feature parity with our cloud platform.
The initial release seeks to fully serve the coding and project management needs with the same coding features.
Projects - November 2022
Easily create new algorithms, synchronize code with the cloud, and clone projects with the QuantConnect Extension.
Read more about projects in our documentation.
Research - December 2022
The Research Environment is a Jupyter notebook-based environment where you can access our data through the QuantBook class instead of through the QCAlgorithm class in a backtest. The environment supports both Python and C#. If you use Python, you can import code from the code files in your project into the Research Environment to aid development.
Read more about research in our documentation.
Backtesting - December 2022
Backtesting is the process of simulating a trading algorithm on historical data. By running a backtest, you can measure how the algorithm would have performed in the past. Although past performance doesn't guarantee future results, an algorithm that has a proven track record can provide investors with more confidence when deploying to live trading than an algorithm that hasn't performed favorably in the past. Use the QuantConnect platform to run your backtests because we have institutional-grade datasets, an open-source backtesting engine that's constantly being improved, cloud servers to execute the backtests, and the backtesting hardware is maintained 24/7 by QuantConnect engineers.
Read more about backtesting in our documentation.
Optimization - December 2022
Parameter optimization is the process of finding the optimal algorithm parameters to maximize or minimize an objective function. For instance, you can optimize your indicator parameters to maximize the Sharpe ratio that your algorithm achieves over a backtest. Optimization can help you adjust your strategy to achieve better backtesting performance, but be wary of overfitting. If you select parameter values that model the past too closely, your algorithm may not be robust enough to perform well using out-of-sample data.
Read more about optimization in our documentation.
Live Trading - January 2023
A live algorithm is an algorithm that trades in real-time with real market data. QuantConnect enables you to run your algorithms in live mode with real-time market data. Deploy your algorithms using QuantConnect because our infrastructure is battle-tested. We have successfully hosted more than 200,000 live algorithms and have had more than $15B in volume traded on our servers since 2015. The algorithms that our members create are run on co-located servers and the trading infrastructure is maintained at all times by our team of engineers. It's common for members to achieve 6-months of uptime with no interruptions.
Read more about live trading in our documentation.
Datasets - January 2023
Access data from Our Dataset Market for you to use in your algorithms. Our Dataset Market includes price, fundamental, and alternative datasets. Consider using fundamental and alternative datasets to incorporate more information in your trading decisions. Fundamental and alternative datasets contain information that is not present in the price. Price data is commonly researched for trading ideas, so you may find it easier to discover alpha in other types of datasets.
The Dataset Market enables you to easily load datasets into your trading algorithms for use in the cloud or locally. The datasets come configured ready to integrate into your research and backtesting without any need for cleaning. The datasets in our market are vetted by the QuantConnect team to be high-quality, contain actionable information, and be free of survivorship-bias. Our Dataset Market is growing quickly. New datasets are added frequently.
Read more about datasets in our documentation.
For more support please submit a ticket at https://www.quantconnect.com/support or to firstname.lastname@example.org
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