pyfolio-reloaded
Lean
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| pyfolio-reloaded | Lean | |
|---|---|---|
| 2 | 25 | |
| 278 | 8,655 | |
| - | 1.8% | |
| 2.9 | 9.7 | |
| about 1 month ago | 6 days ago | |
| Jupyter Notebook | C# | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pyfolio-reloaded
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Backtesting Engine Design Primers
Stephen Jansen has resurrected both Zipline and Pyfolio following Quantopian's belly-up.
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That’s it, I’m done with Zipline. I can’t take it anymore. Does anyone have any other good backtesting libraries in Python where I can use my own personal data? Thanks in advance!
If that's because Quantopian went belly-up and Zipline is not maintained anymore, check Stefan Jansen on Github, he's actively maintaining zipline-reloaded and pyfolio-reloaded.
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?
backtrader - Python Backtesting library for trading strategies
StockSharp - Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
zipline-reloaded - Zipline, a Pythonic Algorithmic Trading Library
caffeinated-pandas
finnhub-dotnet - A .NET client for Finnhub API
zipline - Zipline, a Pythonic Algorithmic Trading Library
finta - Common financial technical indicators implemented in Pandas.
TTM - # TTM Stock squeeze detection based on bollinger + keltner channels. Detects which stocks are out after bollinger is inside keltner channel.
algotrading-example - algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex, binance futures, market making)
documentation - This repository contains the documentation for the current Quantiacs project. Check it out at: https://quantiacs.com/documentation/en/
rl-trading - Using Reinforcement Learning agents as Algorithmic Traders