[See Description] Paper Trading a Strategy on Quantopian - Python for Finance 12

TL;DR

Learn how to transition from backtesting to live trading using Quantopian's platform, including strategies based on moving averages and the importance of adapting to different market conditions.

Transcript

what is going on everybody welcome to the 12th python for finance tutorial with quanto peon slash zipline in this tutorial we're talking about taking the next steps with our algorithm so we're going to be moving off the sent decks kind of stuff simply because the rather cruel of me I think to do an entire series based on data that people may not ha... Read More

Key Insights

• 🏮 Quantopian offers more than just backtesting capabilities, including the ability to trade strategies using paper trading.
• 🥳 Using a rebalance function can help ensure that a strategy only trades once a day, even when using minute data.
• 🥳 Live trading on Quantopian comes with limitations, such as the need to update CSV files by midnight EST and the running of initialize once a day.

Questions & Answers

Q: How can we use Quantopian's fundamental data for our strategy?

Quantopian provides access to free fundamental data, which can be used to reference price history and perform functions such as calculating moving averages.

Q: Why should we use rebalance to ensure our strategy trades once a day?

By using the rebalance function, we can schedule our strategy to execute at a specific time, such as market open, and prevent multiple trades throughout the day.

Q: What should we keep in mind when using live data for paper trading?

Live initialize is run once a day, so any data tracked within the context may be emptied out daily. Additionally, the CSV fetcher doesn't allow changes to prior data, so appending changes to the end of the file is necessary.

Q: How can we transition from backtesting to live trading on Quantopian?

After running a minute backtest, users can deploy their strategy for live trading by clicking the "Live Trading" button and selecting Quantopian as the deployment platform.

Summary & Key Takeaways

• The tutorial discusses the need to move away from data that may not be accessible to everyone and instead create our own strategy using Quantopian's fundamental data.

• It explains how to schedule functions and use rebalance to run a minute backtest and ensure that a strategy only trades once a day.

• The tutorial explores the limitations of live paper trading, such as data availability and the need to update CSV files by midnight EST.