Sector Weighted Portfolio Construction

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Boot Camp Lessons

Lesson Overview

In this lesson, we create a sector balanced portfolio by implementing a Sector Weighting Portfolio Construction Model (SWPCM) with a universe of equities from the technology, financial services, and consumer goods sectors.

We'll select equities by sector code and market capitalization, and assign an equal portfolio weight to each sector.

What You'll Learn

Create a custom portfolio construction model
Use a SWPCM to create a sector balanced portfolio
Use inheritance to reduce code required for the SWPCM
Create portfolio targets with insight direction and target percent

Lesson Requirements

We recommend that at a minimum you complete the Liquid Universe Selection, Algorithm Framework, and Liquid Value Stocks lessons before starting this intermediate level Boot Camp.

Lesson Content

	Status

	Status
Selecting Universe By Sector
Sector Weighting Portfolio Construction
Tracking Security Changes
Calculating Target Weight Percentages

About the Author

QuantConnect Team

Selected group of pseudo-humans that can type without looking at the keyboard and use a super advanced neural network to transform coffee and orange juice into code.

Have a Question?

QuantConnect Q&A

What brokerages do you support? Do you have live trading?

We support live trading with Interactive Brokers, Alpaca, GDAX, FXCM, OANDA, and Bitfinex. We also allow you to do paper trading with Equity, Crypto, Forex and CFD data.

What libraries are white-listed for use in QuantConnect?

See a full list of white listed libraries in our Documentation/Supported Libraries section.

If your library is not there and you want it added please let us know.

I can't code, do you have a visual editor to design algorithms?

We do not have any plans to build a visual algorithm designer. We believe the only way to make money in the markets is with the most powerful, flexible tools available. We recently designed the Algorithm Framework which allows relatively easily assembly of coding blocks to design an algorithm but you still need to have a strong foundation in code. Its this belief which has powered many of the design decisions behind QuantConnect. We were algorithmic traders ourselves for 3 years and built hundreds of algorithms. They ranged from the simple, to incredibly complex. The common theme among them was the need for flexibility which can only be achieved through raw code.

How do I get started learning algorithmic trading or quant finance?

Learning quantitative trading is especially difficult as there is so little public information available. We have sought to address this through the educational materials we make available. We provide a Bootcamp for those unfamiliar with programming or trading concepts, a series of tutorials on implementing a quantitative strategy, and our YouTube channel which is intended to guide you on using the QC API. Inside the Algorithm Lab have the QC University which is a collection of 100+ demonstration algorithms to help you get started.

The QuantConnect community and the algorithms they share are also a great way to get started. There are thousands of members just like yourself who share their journey.

How do I know my intellectual property and algorithm source code are secure?

We take protecting your intellectual property very seriously. We limit the access to the database to key team member who need it, and ensure they have no conflict of interest from trading on our personal accounts.

For those especially concerned we have open sourced the LEAN engine, allowing you to do algorithmic trading entirely on your own servers - proving we're truly trying to empower your trading.

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