zipline
backtrader
zipline | backtrader | |
---|---|---|
14 | 32 | |
17,471 | 13,953 | |
0.8% | - | |
0.0 | 0.0 | |
7 months ago | 21 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 only |
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zipline
- Ask HN: How to Get into Quantitative Trading?
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Open source backtesting software
https://github.com/quantopian/zipline (event-driven)
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10 FinTech APIs every Indian developer should bookmark
Zipline by Quantopian: An Open-Source tool for algorithmic trading. It is a platform for developing and testing quantitative trading strategies using Python.
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Backtesting Engine Design Primers
For personal use only. I'm currently looking at QuantConnect's LEAN and Quantopian's Zipline (which hasn't seen any updates since 2020, presumably because Quantopian was dissolved).
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[D] Doing my (bachelor) thesis on RL. Which topic do you like best?
(1) I remember there were decent libraries for this setting a while back. Maybe take a look at Quantopian/Zipline.
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Best Backtesting Libraries (Python)
zipline – Zipline is a Pythonic algorithmic trading library. It is an event-driven system that supports both backtesting and live trading.
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How to statistically compare the performance of two strategies?
I found two opensource tools 1. .https://github.com/quantopian/zipline Quantopian 2. https://analyzingalpha.com/backtrader-backtesting-trading-strategies backtrader
- Formula for slippage?
- Online Portfolio Selection - Research paper implementation and backtest
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Best Backtesting software?
Some of the notable libraries in Python are backtesting.py, bt and zipline. Personally I like bt the most, as its tree model makes the most intuitive sense.
backtrader
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[HIRING] Develop template code for crypto backtesting using backtrader
You need to create a template code using https://github.com/mementum/backtrader. 1. Get the 1m candlestick data from binance for a period of 1 month for two symbols and store it in a data folder with data for each day and symbol in a different csv file. Read data for the symbols BTC & ETH. 2. Read the data for 1 month in python and put it in a dataframe for each symbol. 3. Import backtrader and feed data for these two symbols. 4. Create a basic strategy to check the ratio of prices and take trades accordingly. 5. Get the results using library. I am not much interested in the trading logic, just want to get the system to backtest up. It's a straightforward task for someone who has used backtrader before or 30-min job to read the documentation and do it. Project compensation : 5$ Can transfer directly to your binance account.
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What backtest data would you say is more accurate.
For this reason I think it's important to have a deep understanding of exactly how the backtesting engine that you are using works. Building your own backtesting engine is the absolute best way to gain this understanding. That is the path I personally chose and I don't regret it! However, that is also a very difficult and time consuming undertaking. So the next best thing is using something that is open source and has a good reputation like backtrader (https://www.backtrader.com/).
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Backtesting Engines for Testing Intraday Data on Thousands of Symbols Simultaneously
However, if you decide to go down the more well-trodden path of using open source backtesting frameworks then I personally would recommend backtrader (https://www.backtrader.com/). As far as I can tell, it has pretty much all the same features as my own system. The only difference is speed. My backtester is an order of magnitude faster and scales much better to testing thousands of symbols simultaneously. However, for 99% of retail algo traders this will be completely irrelevant.
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Algo Trading for SQQQ/TQQQ
You are welcome to go to discord or any other place. Your question wasn't very clear and thus I made that comment. Now, you still haven't made it clear so I am going to assume that you are looking for someone to "share a bot" that can trade your strategy. It doesn't work that way with algo trading. You code your "bot" to do things for you - The easiest way to start would be to look at backtrader but you will still have to code your own strategy in.
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Quantconnect Rant
I mean, some random dude managed to pull a platform with more basic functionalities than that. Sadly that repo is dead and the live trading implementation no longer works
- Do you use automated trading software or nah?
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Python library to retrieve data from TradingView
I've been working on a Python library which lets the user retrieve data from TradingView.com so it could be used in backtesting a strategy. The project is called TvDatafeedLive and is available on GitHub. To be fair, the project is actually an extension of a project called TvDatafeed, which is a really good project, but only supports retrieving historic data (so far). So, I've taken the liberty to fork it and implement retrieving data continously and "real-time". The data is retrieved in Pandas DataFrames and can easily be plugged into backtrader. There is instructions included in the GitHub page. If this sounds interesting then please check it out and leave feedback if there are any thoughts.
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Historical Trading to Prove/Disprove Plan
If you are a python programmer there is backtrader.
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Backtesting tools
For stocks and crypto: QuantConnect and Backtrader For options: MesoSim and OptionNetExplorer
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Algo Trading Environments
Backtrader can also do live trading afaik.
What are some alternatives?
pyfolio - Portfolio and risk analytics in Python
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
backtrader - Python Backtesting library for trading strategies [Moved to: https://github.com/mementum/backtrader]
vectorbt - Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
PyThalesians - Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)
ccxt - A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
quantstats - Portfolio analytics for quants, written in Python
fastquant - fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
pyfolio-reloaded - Portfolio and risk analytics in Python
qlib - Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
zipline-reloaded - Zipline, a Pythonic Algorithmic Trading Library