LESSON 1 7 Tasks   |   Video Included   |   Interactive Learning

Buy and Hold / Equities

Learn how to initialize an algorithm's backtesting date range, and starting portfolio value. You'll be able to request US Equity data and configure the resolution of the data. We'll explore two different normalization techniques; raw and normalized for adjusting the data delivered to your algorithm.

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LESSON 2 6 Tasks   |   Video Included   |   Interactive Learning

Buy and Hold with a Trailing Stop

In this lesson we'll explore how to use a trailing stop to control the risk of an open position, and plot the price of your stops to visualize it triggering. You'll learn how to use the order event system to track when the order is triggered.

LEAN supports trailing stop orders, but your brokerage may not. To check if your brokerage supports these orders, see the Orders section of the documentation for your brokerage model. If your brokerage doesn't support them, you can implement a workaround using just stop market orders.

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LESSON 3 6 Tasks   |   Video Included   |   Interactive Learning

Momentum-Based Tactical Allocation

In this lesson, we'll track the momentum of a portfolio of assets and allocates capital to the best performers, using the SetHoldings method. We'll control the trading frequency to reduce the fees, and learn how to warm up an indicator.

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LESSON 4 5 Tasks   |   Video Included   |   Interactive Learning

Opening Range Breakout

In this lesson, we'll build a strategy searching for price break outs from the first few minutes of trading using consolidators to create custom bars and use a scheduled event to exit the position.

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LESSON 5 6 Tasks   |   Video Included   |   Interactive Learning

Liquid Universe Selection

In this lesson, we'll invest in the most liquid 8 symbols from the collection of 8,000 tickers provided by QuantConnect daily using universe selection. We'll control the resolution of assets added to the algorithm using the universe properties.

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LESSON 6 5 Tasks   |   Video Included   |   Interactive Learning

Fading The Gap

In this lesson, we bet against unusual overnight gaps in price in TSLA assuming the market will mean-reverse. We'll use a standard deviation indicator to remove a parameter from our strategy.

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LESSON 7 5 Tasks   |   Video Included   |   Interactive Learning

200-50 EMA Momentum Universe

In this lesson, we invest in a universe of assets where their 50-day moving average is greater than their 200-day moving average. We combine techniques for universe selection, history, and grouping data with classes.

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LESSON 8 7 Tasks   |   Video Included   |   Interactive Learning

The Algorithm Framework

In this lesson, we introduce the Algorithm Framework, a scaffold for building larger algorithms that separate code in a way its components can be reused. You'll learn about Universe Selection, Alpha Signals, Portfolio Construction, Risk Management, and Execution modules.

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LESSON 9 6 Tasks   |   Video Included   |   Interactive Learning

Pairs Trading with SMA

In this lesson, we'll create a basic pairs trading strategy using an SMA indicator. You'll learn how to create a synthetic asset and investing when the underlying prices diverge.

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LESSON 10 5 Tasks   |   Video Included   |   Interactive Learning

Liquid Value Stocks

In this lesson we harness the Morning Star corporate fundamental data to select companies with high value according to their PE ratio and invest equally in the selected companies.

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LESSON 11 5 Tasks   |   Video Included   |   Interactive Learning

Tiingo Sentiment Analysis on Stocks

In this lesson, we request a news feed from Tiingo and calculate a sentiment score on the companies mentioned, and invest when the signals aggregate above a minimum level for investment.

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LESSON 12 4 Tasks   |   Video Included   |   Interactive Learning

Sector Weighted Portfolio Construction

In this lesson, we use Morning Star fundamental data to group stocks by their industry and assign capital equally to each industry, dividing it among the stocks in the universe. We'll use portfolio targets to rely on the execution models to fulfill the portfolio.

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