Docs/Cloud Platform/Organizations/Training - Introduction
Onboard new team members to your organization through the content in the Learning Center. The Learning Center enables you to systematically track and monitor the progress of your team members on the courses you purchase or create. If you purchase or create a course, you can access it from the Organization > Resources page in the Algorithm Lab.
Docs/Writing Algorithms/Securities/Asset Classes/Futures/Market Hours/CME/6A - Introduction
This page shows the trading hours, holidays, and time zone of the Australian Dollar Futures contract in the CME Future market.
Docs/Writing Algorithms/Reality Modeling/Brokerages/Supported Models/Kraken - Introduction
This page explains the KrakenBrokerageModel, including the asset classes it supports, its default security-level models, and its default markets. SetBrokerageModel(BrokerageName.Kraken, AccountType.Cash); SetBrokerageModel(BrokerageName.Kraken, AccountType.Margin); self.set_brokerage_model(BrokerageName.KRAKEN, AccountType.CASH) self.set_brokerage_model(BrokerageName.KRAKEN, AccountType.MARGIN) To view the implementation of this model, see the LEAN GitHub repository.
Docs/Writing Algorithms/Securities/Asset Classes/Index Options/Market Hours/USA/RUT - Introduction
This page shows the trading hours, holidays, and time zone of the Russell 2000 Index Option contracts market.
Docs/Writing Algorithms/Consolidating Data/Getting Started - Introduction
Consolidating data allows you to create bars of any length from smaller bars. Consolidation is commonly used to combine one-minute price bars into longer bars such as 10-20 minute bars. Consolidated bars are helpful because price movement over a longer period can sometimes contain less noise and bars of exotic length are less researched than standard bars, so they may present more opportunities to capture alpha. To consolidate data, create a Consolidator object and register it for data. The built-in consolidators make it easy to create consolidated bars without introducing bugs. In the following sections, we will introduce the different types of consolidators and show you how to shape data into any form.
Docs/Writing Algorithms/Datasets/QuantConnect/US Equities Short Availability - Introduction
The US Equity Short Availability dataset provides the available shares for open short positions and their borrowing cost in the US Equity market. The data covers 10,500 US Equities, starts in January 2018, and is delivered on a daily frequency. This dataset is created using information from the exchanges. This dataset depends on the US Equity Security Master dataset because the US Equity Security Master dataset contains information on splits, dividends, and symbol changes. For more information about the US Equities Short Availability dataset, including CLI commands and pricing, see the dataset listing.
Docs/Writing Algorithms/Indicators/Supported Indicators/Swiss Army Knife - Introduction
Swiss Army Knife indicator by John Ehlers To view the implementation of this indicator, see the LEAN GitHub repository.
Docs/Writing Algorithms/Historical Data/Alternative Data - Introduction
Alternative datasets provide signals to inform trading decisions. To view all the alternative datasets available on QuantConnect, see the Dataset Market. This page explains how to get historical data for alternative datasets.
