awesome-quant
bt
awesome-quant | bt | |
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18 | 5 | |
16,056 | 2,031 | |
- | - | |
8.8 | 5.7 | |
1 day ago | about 22 hours ago | |
Python | Python | |
- | MIT License |
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awesome-quant
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RustQuant: A Library for Quantitative Finance
No, it looks more like a Rust equivalent of libraries like ffn (financial functions for python) or many of the other ones listed here https://github.com/wilsonfreitas/awesome-quant
Using rust to do exploratory analysis in python seems like a misguided idea. But using rust to productize models that have performance and accuracy sensitivities, the things that C/C++ is still used for, indeed sounds like a good idea.
Most of the python libraries used in finance, like numpy/pandas, call out to C for performance reasons; the libraries are essentially python bindings + syntax to C functions. It would be interesting to think about replacing that backend with rust.
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Open Source Projects
This is a good list https://github.com/wilsonfreitas/awesome-quant
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Iām not a Quant, but a Headhunter - ask me anything
also, what are the best quanty python packages that you like to see an applicant use? there are so many. https://github.com/wilsonfreitas/awesome-quant
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Why building profitable trading bot is hard?
If the financial analyst does not have a (possibly piecewise) software function to at least test with backtesting and paper trading, do they even have an objective relative performance statistic? Your notebook or better should also model fees and have a parametrizable initial balance.
Here's the awesome-quant link directory: https://github.com/wilsonfreitas/awesome-quant
- For Traders Who Want To Be Quants
- A curated list of libraries, packages and resources for Quants
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Hacker News top posts: Feb 22, 2022
A curated list of libraries, packages and resources for Quants\ (0 comments)
bt
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Best Backtesting Libraries (Python)
bt ā bt is a flexible backtesting framework for Python used to test quantitative trading strategies.
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Are there any ready solutions for backtesting portfolio with daily or more frequent rebalancing?
Here is link number 1 - Previous text "Bt"
- What open source frameworks should i be considering for hobby algo trading?
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How do I run 100 algos live?
A better way would be to create a master strategy that manages 100 other strategies, each with $10 a pop. The bt backtesting framework was designed to support this. That way you can manage your portfolio from one account, but also use multiple strategies. The master strategy just handles fund allocation, and rebalancing if necessary.
What are some alternatives?
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.
PyPortfolioOpt - Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
backtrader - Python Backtesting library for trading strategies
backtrader - Python Backtesting library for trading strategies [Moved to: https://github.com/mementum/backtrader]
uniswap-sushiswap-arbitrage-bot - Two bots written in JS that uses flashswaps and normal swaps to arbitrage Uniswap. Includes an automated demostration.
pyalgotrade - Python Algorithmic Trading Library
CUDA.jl - CUDA programming in Julia.
zipline - Zipline, a Pythonic Algorithmic Trading Library
awesome-discord-communities - A curated list of awesome Discord communities for programmers
PyThalesians - Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)
Gekko-Strategies - Strategies to Gekko trading bot with backtests results and some useful tools.
pybacktest - Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier ā compact, simple and fast