StockSharp
Lean
StockSharp | Lean | |
---|---|---|
134 | 25 | |
6,638 | 8,714 | |
1.5% | 1.5% | |
9.8 | 9.7 | |
8 days ago | 1 day ago | |
C# | C# | |
Apache License 2.0 | Apache License 2.0 |
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StockSharp
Lean
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What Happened to Quantconnect?
6.) You cant maximize position size of spread options strategies, LEAN always assumes naked margin first and ON THE NEXT DATA FRAME - you get your reg-t margin for spreads. https://github.com/QuantConnect/Lean/issues/5693 We're running into 2 years of this issue being reported.
- Thoughts on QuantConnect?
- IBKR implementation of ALMA indicator
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Backtesting Engines for Testing Intraday Data on Thousands of Symbols Simultaneously
Thanks. I will check it out. Can you point me to the right part of the codebase I should be looking at? I know it must be somewhere here - https://github.com/QuantConnect/Lean
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Quantconnect - Backtest script that accepts multiple dropbox links, creates portfolio, and rebalances on predefined dates, advice?
They have nice documentation on their website for how to download/import external data, though. They even have GitHub examples that pull data from Dropbox.
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Problem with QuantConnect Package on Local IDE
Here is an example https://github.com/QuantConnect/Lean/blob/master/Algorithm.Python/DropboxUniverseSelectionAlgorithm.py
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Exportable quote database for simulations?
There's also the open-source lean.io stuff by QuantConnect which looks decent and comes with data. It's pretty inexpensive too.
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Rant about candles
I can plot OHCL lines, I can plot OHCL scatter points on the chart, why can't I plot candles? It's just those scatter points put together. This thing has been going on for 8 YEARS.
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How has your experience been with QuantConnect? Would you invest in the company?
Here's a link to one of the strategy examples from the QC team that does this -- loading a universe from an external source. https://github.com/QuantConnect/Lean/blob/master/Algorithm.Python/DropboxCoarseFineAlgorithm.py
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What's the best platform to backtest a large amount of 1m data using a simple volume-based strategy ? TradingView provides a minimal amount of candles in the 1m chart to backtest on and I need to test it further.
+1 see https://github.com/QuantConnect/Lean
What are some alternatives?
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
backtrader - Python Backtesting library for trading strategies
Stock.Indicators - Stock Indicators for .NET is a C# NuGet package that transforms raw equity, commodity, forex, or cryptocurrency financial market price quotes into technical indicators and trading insights. You'll need this essential data in the investment tools that you're building for algorithmic trading, technical analysis, machine learning, or visual charting.
finnhub-dotnet - A .NET client for Finnhub API
ibgateway - Docker image for IBGateway
finta - Common financial technical indicators implemented in Pandas.
fastquant - fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
TTM - # TTM Stock squeeze detection based on bollinger + keltner channels. Detects which stocks are out after bollinger is inside keltner channel.
LiteNetLib - Lite reliable UDP library for Mono and .NET
algotrading-example - algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex, binance futures, market making)
ib_api - Interactive Brokers API in TypeScript / Kotlin / Java / Nim
documentation - This repository contains the documentation for the current Quantiacs project. Check it out at: https://quantiacs.com/documentation/en/