backtrader
caffeinated-pandas | backtrader | |
---|---|---|
2 | 32 | |
45 | 13,081 | |
- | - | |
0.0 | 0.0 | |
about 2 years ago | 11 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 only |
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.
caffeinated-pandas
-
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!
The real "gotcha" though is as you start to progress, bring in more data, more experiments, more complexity, longer runs, having some Python basics in place is key. I spent more time on "infrastructure" than on actual modeling and backtesting, and I decided to publish some of these challenges around memory, disk, processing speed, and iteration. https://github.com/scollay/caffeinated-pandas
-
Programming Language for Quantitative Finance
I just published some articles and code that I developed after a lot of trial and error optimizing RAM, disk, processing, and development with Python around stock quotes data. Perhaps it will be useful if you decide on Python. https://github.com/scollay/caffeinated-pandas
backtrader
-
[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.
-
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/).
-
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.
-
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.
-
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?
-
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.
-
Historical Trading to Prove/Disprove Plan
If you are a python programmer there is backtrader.
-
Backtesting tools
For stocks and crypto: QuantConnect and Backtrader For options: MesoSim and OptionNetExplorer
-
Algo Trading Environments
Backtrader can also do live trading afaik.
What are some alternatives?
zipline-reloaded - Zipline, a Pythonic Algorithmic Trading Library
backtesting.py - :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
pyfolio-reloaded - Portfolio and risk analytics in Python
zipline - Zipline, a Pythonic Algorithmic Trading Library
vectorbt - Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
ccxt - A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
fastquant - fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
interactive-broker-python-api - A python packaged used to interact with the Interactive Brokers REST API.
freqtrade - Free, open source crypto trading bot
Lean - Lean Algorithmic Trading Engine by QuantConnect (Python, C#)