quantstats
finta
| quantstats | finta | |
|---|---|---|
| 9 | 5 | |
| 4,293 | 1,728 | |
| - | - | |
| 4.8 | 2.7 | |
| 15 days ago | almost 2 years ago | |
| Python | Python | |
| Apache License 2.0 | GNU Lesser General Public License v3.0 only |
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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
finta
- looking for a python lib
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How It's Made! // Building A Crypto Trading Bot Network - A Tutorial (Part 1) // Whew, this was a tough one guys. It took 10x longer to put this together than I imagined. This is an in-depth review of my Bots and their parent system. Please let me know what you think and if I should continue.
Have you thought about using the FinTA package for trading signals and also ratelimit to help with some of those weird things that can pop up with dealing with external APIs
- Yesterday I came across Awesome-Quant repository and it was great. I went ahead and dig through all the backtesting & AI repos from Python and created a list of repo which are most updated & maintained. Let me know if I missed your favorite.
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Important python libraries?
I'm also going to shamelessly plug fast-trade, which is a backtesting library where you write strategies as objects instead of actual code. It's also built on a couple of pretty wonderful libraries including pandas and FinTa, which has a lot of indicators and it's really simple to use.
- Why use ta_lib when you can use FinTA?
What are some alternatives?
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.
pandas-ta - Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
zipline - Zipline, a Pythonic Algorithmic Trading Library
ta-lib-python - Python wrapper for TA-Lib (http://ta-lib.org/).
fast-trade - low code backtesting library utilizing pandas and technical analysis indicators
qtpylib - QTPyLib, Pythonic Algorithmic Trading
trading-ig - A lightweight Python wrapper for the IG Markets API
Empyrial - AI and data-driven quantitative portfolio management library for portfolio risk and performance analysis 投资组合管理
Lean - Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
alphalens - Performance analysis of predictive (alpha) stock factors
documentation - This repository contains the documentation for the current Quantiacs project. Check it out at: https://quantiacs.com/documentation/en/