Empyrial
quantstats
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| Empyrial | quantstats | |
|---|---|---|
| 7 | 9 | |
| 864 | 4,264 | |
| - | - | |
| 8.1 | 5.4 | |
| 3 months ago | 12 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
Empyrial
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Are there any good tools for Quantitative analysis of stocks ?
I created a python library called Empyrial (https://github.com/ssantoshp/Empyrial) might help for doing that. Tell me what you think about it and don't hesitate to DM me ;)
- Empyrial, Python library for portfolio risk and performance analysis
- Empyrial, portfolio management library for portfolio risk and performance analysis
- Empyrial makes portfolio management and analysis faster and easier
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What are the top Python finance libraries?
I created a python library called Trafalgar which has for goal to help to make quantitative and portfolio analysis. You can check it out here : https://github.com/ssantoshp/trafalgar
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Trafalgar: a python library to make quantitative finance and portfolio analysis faster and easier
Thanks, yes I'm planning it but for the moment I don't think it's my priority on this project you can just download the file and type pip install + the file name. You can find more info about how to download in the article or here: https://github.com/ssantoshp/trafalgar.
quantstats
- Quantstats issue with Google Colab
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Excel (or other) summary stats for algo performance?
IMO can’t do better than QuantStats https://github.com/ranaroussi/quantstats
- QuantStats: Portfolio Analytics for Quants
- Backtesting Results
- Python: which are good modules for strategy evaluation?
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Beyond sample reports
https://github.com/ranaroussi/quantstats Many technical metrics for detailed performance
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successful bots easy
I have a bot that does 100x in 3 years. But it is only 60 % accurate. You don't need high accuracy. In the end what counts is cumulative returns when you include trading costs (even if zero fees you still have slippage). Sharpe, Sortino, daily returns, drawdowns you have to look at all these measures. Use this and it does a pretty in depth report of your trading strategy. https://github.com/ranaroussi/quantstats
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What are the top Python finance libraries?
Quantstats for generating backtest reports: https://github.com/ranaroussi/quantstats
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Important python libraries?
quantstats to analyze the performance of strategies
What are some alternatives?
Riskfolio-Lib - Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
finta - Common financial technical indicators implemented in Pandas.
alphalens - Performance analysis of predictive (alpha) stock factors
Portfolio-Report-Generator - A program which allows the user to enter positions and their allocation to get return metrics and data on the underlying positions.
senate-stock-watcher-data - Data repository of JSON files that are filed by US Senators on efdsearch.senate.gov where they must report their stock trades. This is the same data as on senatestockwatcher.com
zipline - Zipline, a Pythonic Algorithmic Trading Library
goplan-app - An intuitive portfolio mangaer !
fast-trade - low code backtesting library utilizing pandas and technical analysis indicators
The-Oracle - 🤖 Predict the stock market with AI 用AI预测股票市场 [Moved to: https://github.com/ssantoshp/Beibo]
qtpylib - QTPyLib, Pythonic Algorithmic Trading
Finance - Study resources for quantitative finance