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DOCUMENTATION
QuantConnect allows you to request historical data in many different formats. In this section, we'll cover each of these formats and how you can use them in your algorithm. Broadly, there are two ways to use these data requests: direct historical data requests and indirect algorithm warm up. ADOCUMENTATION
The Slice event handler combines all of the data into a single method. It represents the data at a point in time. The Slice object contains many helpers for accessing your data. The Slice objects arrive to the OnData(Slice data)def OnData(self, slice) event handler. The Slice object gives you three two ways to access your data: . Dynamic string/symbol indexer, which returns a dynamic object ofDOCUMENTATION
You can use two methods to prime technical indicators and get them ready to be used. Algorithm Warm-Up. When we set an algorithm warm-up period, the engine pumps data in and automatically update all the indicators from before the start date (see Setting Warm Up Period).To ensure that all the indicators are ready after the algorithm warm-up period, you need to choose a lookback period thatDOCUMENTATION
Universe selection is the process of screening or filtering the assets you'd like to trade by some predetermined formula. This helps to avoid selection bias in your algorithm. The following section introduces how to use the QuantConnect Universe Selection API. QuantConnect providestwo universes;
DOCUMENTATION
Algorithms have a Securities property that stores a Security object for each asset in your algorithm. Security objects hold the models (backtesting behaviors) and properties of an asset. Each security can be completely customized to behave as you'd like. Securities is aDOCUMENTATION
The Train feature allows you to get an increase in computation time to perform your model training for your machine learning strategies. Normally algorithms must perform all necessary work within 10 minutes before returning from the OnData method. With the training features, these limits have been increased to more than 30 minutes to give you time to run your models. TUTORIALS - STRATEGY LIBRARY - BOOK-TO-MARKET VALUE Book-to-market ratio is used to find the value of a company by comparing the book value of a firm to its market value. The definition of the book-to-market ratio is \ Book value represents a company's assets minus its liabilities and sometimes is PLACING ORDERS WITH A STOPLOSS AND LIMIT BY CHRISTOFER Hi everyone, I'm trying to understand how to define a stopp-loss and limit placing orders. I'm currently working on if statements that liquidate my positions at pre-defined price levels. This w DESIGN AND TRADE ALGORITHMIC TRADING STRATEGIES IN A WEBSIGN IN WITH FACEBOOKCOMPETITIONMARKETDATACOMMUNITYLAB QuantConnect provides a free algorithm backtesting tool and financial data so engineers can design algorithmic trading strategies. We are democratizing algorithm trading technology to empower investors. TUTORIALS - HOME - QUANTCONNECT.COMSIGN INTUTORIAL SERIESINTRODUCTION TO FINANCIAL PYTHONUSING OPTIONS IN QUANTCONNECT Learn to use QuantConnect with guided tutorialsDOCUMENTATION
QuantConnect allows you to request historical data in many different formats. In this section, we'll cover each of these formats and how you can use them in your algorithm. Broadly, there are two ways to use these data requests: direct historical data requests and indirect algorithm warm up. ADOCUMENTATION
The Slice event handler combines all of the data into a single method. It represents the data at a point in time. The Slice object contains many helpers for accessing your data. The Slice objects arrive to the OnData(Slice data)def OnData(self, slice) event handler. The Slice object gives you three two ways to access your data: . Dynamic string/symbol indexer, which returns a dynamic object ofDOCUMENTATION
You can use two methods to prime technical indicators and get them ready to be used. Algorithm Warm-Up. When we set an algorithm warm-up period, the engine pumps data in and automatically update all the indicators from before the start date (see Setting Warm Up Period).To ensure that all the indicators are ready after the algorithm warm-up period, you need to choose a lookback period thatDOCUMENTATION
Universe selection is the process of screening or filtering the assets you'd like to trade by some predetermined formula. This helps to avoid selection bias in your algorithm. The following section introduces how to use the QuantConnect Universe Selection API. QuantConnect providestwo universes;
DOCUMENTATION
Algorithms have a Securities property that stores a Security object for each asset in your algorithm. Security objects hold the models (backtesting behaviors) and properties of an asset. Each security can be completely customized to behave as you'd like. Securities is aDOCUMENTATION
The Train feature allows you to get an increase in computation time to perform your model training for your machine learning strategies. Normally algorithms must perform all necessary work within 10 minutes before returning from the OnData method. With the training features, these limits have been increased to more than 30 minutes to give you time to run your models. TUTORIALS - STRATEGY LIBRARY - BOOK-TO-MARKET VALUE Book-to-market ratio is used to find the value of a company by comparing the book value of a firm to its market value. The definition of the book-to-market ratio is \ Book value represents a company's assets minus its liabilities and sometimes is PLACING ORDERS WITH A STOPLOSS AND LIMIT BY CHRISTOFER Hi everyone, I'm trying to understand how to define a stopp-loss and limit placing orders. I'm currently working on if statements that liquidate my positions at pre-defined price levels. This wDOCUMENTATION
QuantConnect provides a rich data library of alternative data you can import into your algorithm. This data covers corporate fundamentals, macro economics, news and events, price data, and sentiment data. All data is free for all backtesting, Alpha Streams, and use in Alpha Streams Competitions.DOCUMENTATION
You can use two methods to prime technical indicators and get them ready to be used. Algorithm Warm-Up. When we set an algorithm warm-up period, the engine pumps data in and automatically update all the indicators from before the start date (see Setting Warm Up Period).To ensure that all the indicators are ready after the algorithm warm-up period, you need to choose a lookback period thatDOCUMENTATION
QuantConnect provides dozens of methods to create, update, and cancel orders. These orders can be placed automatically with helper methods, or manually through methods on the algorithm API. Manual orders can be fetched, updated, and canceled with Order Tickets. As orders are filled and updated, they generate events that notify your algorithm about their execution.DOCUMENTATION
The Train feature allows you to get an increase in computation time to perform your model training for your machine learning strategies. Normally algorithms must perform all necessary work within 10 minutes before returning from the OnData method. With the training features, these limits have been increased to more than 30 minutes to give you time to run your models. BTCUSD, HOUR THE ISSUE STARTS FROM MAY 1ST, 2021; AND There is no data on the days 5/14, 5/17, 5/18, 5/20, 5/29, and 5/31 on the hourly resolution for BTCUSD. This was also true for ETHUSD. TUTORIALS - STRATEGY LIBRARY - BOOK-TO-MARKET VALUE Book-to-market ratio is used to find the value of a company by comparing the book value of a firm to its market value. The definition of the book-to-market ratio is \ Book value represents a company's assets minus its liabilities and sometimes isDOCUMENTATION
Scheduled events allow you to trigger code to run at specific times of day. This happens regardless of your data events. The schedule API requires a date and time rule to specify when the event is fired. Scheduled events need a DateRules and TimeRules pair to set a specific time. When the event is ALL, HOUR THE ISSUE STARTS AT THE START OF THE DATA; AND Unable to see "Purchase" Link I can browse and preview but no purchase option avaialble. I have purchased few of them in the few days ago. but Can't figure out how to do it today. HOW TO PLOT BENCHMARK IN STRATEGY EQUITY TO COMPARE CHARTS Hey Shih, Unfortunately, it's not currently possible to plot on the strategy equity graph. However you can using self.Plot to create a chart with both the benchmark and portfolio values. Since we want to measure performance rather than absolute value. IS THERE A WAY TO PASS INDICATORS FROM UNIVERSE SELECTION Hi,In my Universe Selection Model, I used EMA as a criteria to select stocks. In my Alpha Model, I wanted to use the same EMA on the stocks I selected to set insight weight.I was wondering if thereToggle navigation
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In addition; we have Morning Star Fundamental data for the most popular 8,000 symbols for 900+ indicators since 1998.CRYPTO, FOREX & CFD
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Find new friends in the community and collaborate together with our team-coding feature! Share projects and see their code instantly as they type. You can even grant live access and control the live algorithm together. Use our internal instant messaging to find prospective team members to join forces! SECURE INTELLECTUAL PROPERTY Our focus is to give you the best possible algorithmic trading platform and protect your valuable intellectual property. We will always be an infrastructure and technology provider first. When you're ready for live trading we'll happily help you execute through yourbroker of choice.
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class MyFirstAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(1998, 1, 1) self.SetEndDate(2020, 04, 23) self.SetCash(100000) self.AddEquity("SPY", Resolution.Minute) //Data event - Every minute, second or tick def OnData(self, data): //Your strategy here! if not self.Portfolio.Invested: self.SetHoldings("SPY", 1) LEVERAGE YOUR POTENTIAL Through Alpha Streams™ , QuantConnect enables you to license your algorithms to world-leading funds. Your algorithms are hosted in our secure, cloud platform and the signals are distributed for fundsto license.
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