PyMC
zipline
PyMC | zipline | |
---|---|---|
3 | 14 | |
8,186 | 17,097 | |
0.8% | 0.6% | |
9.5 | 0.0 | |
about 20 hours ago | 3 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
PyMC
- PYMC Release: v5.0.0
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An Astronomer's Introduction to NumPyro
I believe the pymc versions were resolved into developing version 4 of pymc. Development at https://github.com/pymc-devs/pymc
It still depends on theano now evolved and renamed
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What is Probabilistic Programming?
This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing
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.
What are some alternatives?
statsmodels - Statsmodels: statistical modeling and econometrics in Python
backtrader - Python Backtesting library for trading strategies
Dask - Parallel computing with task scheduling
pyfolio - Portfolio and risk analytics in Python
stan - Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
backtrader - Python Backtesting library for trading strategies [Moved to: https://github.com/mementum/backtrader]
Numba - NumPy aware dynamic Python compiler using LLVM
PyThalesians - Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)
SymPy - A computer algebra system written in pure Python
quantstats - Portfolio analytics for quants, written in Python
pyro - Deep universal probabilistic programming with Python and PyTorch
vectorbt - Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.