QuantConnect Boot Camp in Python

In the Buy and Hold Equities tutorial, we’ll practice all the fundamentals to get your algorithm started; executing a simple market order, accessing Portfolio properties, and working with data settings.

In the Buy and Hold Forex tutorial, we’ll practice trading Forex market securities with specific brokerages. You’ll be able to add and request forex data, work with lot size rounding, and place trades with forex assets to your brokerage.

In the Buy and Hold with a Trailing Stop tutorial, we’ll practice managing order risk by identifying a stop loss hit. You’ll be able to place and update a stop market order, access the price data from your algorithm, and observe order level prices in a plot.

In the Momentum-Based Tactical Allocation tutorial, we’ll practice balancing our portfolio and making trades with SetHoldings(). You’ll be able to move your portfolio buying power among different assets depending on market conditions and use indicators to control trading frequency.

In the Opening Range Breakout tutorial, we’ll practice a technical trading strategy which uses the range of prices set during a certain period of time, and trades when the price leaves that range. You’ll be able to create a time period consolidator, take a position, and schedule events to trigger functions that close out that position.

In the Fading The Gap tutorial, we’ll practice a strategy that monitors the market for gaps that occur overnight and bets in the opposite direction, assuming that the market will mean revert. You’ll learn how data moves through rolling windows, use scheduled events to calculate prices changes, and reduce your model’s parameters to avoid overfitting.

In the Liquid Universe Selection tutorial, we’ll practice Universe Selection, which allows you to select stocks based on rules to avoid selection bias. You’ll learn what selection bias is, dynamically filter for a universe of assets based on price and volume, and trade when the universe changes.

In the 200-50 EMA Momentum Universe tutorial, we’ll define a custom class holding fast and slow indicators. You’ll prepare the indicators for immediate use with QC’s History API.

In the Algorithm Framework tutorial, we’ll introduce a system that connects the inputs and outputs of five models to ultimately deliver filled orders based on your strategy. You can reuse this architecture to build robust and flexible investment strategies.