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QuantStats-0.0.9
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Portfolio analytics for quants
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | QuantStats-0.0.9 |
| نام | QuantStats |
| نسخه کتابخانه | 0.0.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Ran Aroussi |
| ایمیل نویسنده | ran@aroussi.com |
| آدرس صفحه اصلی | https://github.com/ranaroussi/quantstats |
| آدرس اینترنتی | https://pypi.org/project/QuantStats/ |
| مجوز | Apache Software License |
.. image:: https://img.shields.io/badge/python-3.6+-blue.svg?style=flat
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:alt: Python version
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:target: https://pypi.python.org/pypi/quantstats
:alt: PyPi version
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:alt: PyPi status
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\
QuantStats: Portfolio analytics for quants
==========================================
**QuantStats** Python library that performs portfolio profiling, allowing quants and portfolio managers to understand their performance better by providing them with in-depth analytics and risk metrics.
`Changelog » <./CHANGELOG.rst>`__
QuantStats is comprised of 3 main modules:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
1. ``quantstats.stats`` - for calculating various performance metrics, like Sharpe ratio, Win rate, Volatility, etc.
2. ``quantstats.plots`` - for visualizing performance, drawdowns, rolling statistics, monthly returns, etc.
3. ``quantstats.reports`` - for generating metrics reports, batch plotting, and creating tear sheets that can be saved as an HTML file.
Here's an example of a simple tear sheet analyzing a strategy:
Quick Start
===========
.. code:: python
%matplotlib inline
import quantstats as qs
# extend pandas functionality with metrics, etc.
qs.extend_pandas()
# fetch the daily returns for a stock
stock = qs.utils.download_returns('FB')
# show sharpe ratio
qs.stats.sharpe(stock)
# or using extend_pandas() :)
stock.sharpe()
Output:
.. code:: text
0.8135304438803402
Visualize stock performance
~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. code:: python
qs.plots.snapshot(stock, title='Facebook Performance')
# can also be called via:
# stock.plot_snapshot(title='Facebook Performance')
Output:
.. image:: https://github.com/ranaroussi/quantstats/blob/main/docs/snapshot.jpg?raw=true
:alt: Snapshot plot
Creating a report
~~~~~~~~~~~~~~~~~
You can create 7 different report tearsheets:
1. ``qs.reports.metrics(mode='basic|full", ...)`` - shows basic/full metrics
2. ``qs.reports.plots(mode='basic|full", ...)`` - shows basic/full plots
3. ``qs.reports.basic(...)`` - shows basic metrics and plots
4. ``qs.reports.full(...)`` - shows full metrics and plots
5. ``qs.reports.html(...)`` - generates a complete report as html
Let' create an html tearsheet
.. code:: python
(benchmark can be a pandas Series or ticker)
qs.reports.html(stock, "SPY")
Output will generate something like this:
.. image:: https://github.com/ranaroussi/quantstats/blob/main/docs/report.jpg?raw=true
:alt: HTML tearsheet
(`view original html file <https://rawcdn.githack.com/ranaroussi/quantstats/main/docs/tearsheet.html>`_)
To view a complete list of available methods, run
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. code:: python
[f for f in dir(qs.stats) if f[0] != '_']
.. code:: text
['avg_loss',
'avg_return',
'avg_win',
'best',
'cagr',
'calmar',
'common_sense_ratio',
'comp',
'compare',
'compsum',
'conditional_value_at_risk',
'consecutive_losses',
'consecutive_wins',
'cpc_index',
'cvar',
'drawdown_details',
'expected_return',
'expected_shortfall',
'exposure',
'gain_to_pain_ratio',
'geometric_mean',
'ghpr',
'greeks',
'implied_volatility',
'information_ratio',
'kelly_criterion',
'kurtosis',
'max_drawdown',
'monthly_returns',
'outlier_loss_ratio',
'outlier_win_ratio',
'outliers',
'payoff_ratio',
'profit_factor',
'profit_ratio',
'r2',
'r_squared',
'rar',
'recovery_factor',
'remove_outliers',
'risk_of_ruin',
'risk_return_ratio',
'rolling_greeks',
'ror',
'sharpe',
'skew',
'sortino',
'adjusted_sortino',
'tail_ratio',
'to_drawdown_series',
'ulcer_index',
'ulcer_performance_index',
'upi',
'utils',
'value_at_risk',
'var',
'volatility',
'win_loss_ratio',
'win_rate',
'worst']
.. code:: python
[f for f in dir(qs.plots) if f[0] != '_']
.. code:: text
['daily_returns',
'distribution',
'drawdown',
'drawdowns_periods',
'earnings',
'histogram',
'log_returns',
'monthly_heatmap',
'returns',
'rolling_beta',
'rolling_sharpe',
'rolling_sortino',
'rolling_volatility',
'snapshot',
'yearly_returns']
**\*\*\* Full documenttion coming soon \*\*\***
In the meantime, you can get insights as to optional parameters for each method, by using Python's ``help`` method:
.. code:: python
help(qs.stats.conditional_value_at_risk)
.. code:: text
Help on function conditional_value_at_risk in module quantstats.stats:
conditional_value_at_risk(returns, sigma=1, confidence=0.99)
calculats the conditional daily value-at-risk (aka expected shortfall)
quantifies the amount of tail risk an investment
Installation
------------
Install using ``pip``:
.. code:: bash
$ pip install quantstats --upgrade --no-cache-dir
Install using ``conda``:
.. code:: bash
$ conda install -c ranaroussi quantstats
Requirements
------------
* `Python <https://www.python.org>`_ >= 3.5+
* `pandas <https://github.com/pydata/pandas>`_ (tested to work with >=0.24.0)
* `numpy <http://www.numpy.org>`_ >= 1.15.0
* `scipy <https://www.scipy.org>`_ >= 1.2.0
* `matplotlib <https://matplotlib.org>`_ >= 3.0.0
* `seaborn <https://seaborn.pydata.org>`_ >= 0.9.0
* `tabulate <https://bitbucket.org/astanin/python-tabulate>`_ >= 0.8.0
* `yfinance <https://github.com/ranaroussi/yfinance>`_ >= 0.1.38
* `plotly <https://plot.ly/>`_ >= 3.4.1 (optional, for using ``plots.to_plotly()``)
Questions?
----------
This is a new library... If you find a bug, please
`open an issue <https://github.com/ranaroussi/quantstats/issues>`_
in this repository.
If you'd like to contribute, a great place to look is the
`issues marked with help-wanted <https://github.com/ranaroussi/quantstats/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22>`_.
Known Issues
------------
For some reason, I couldn't find a way to tell seaborn not to return the
monthly returns heatmap when instructed to save - so even if you save the plot (by passing ``savefig={...}``) it will still show the plot.
Legal Stuff
------------
**QuantStats** is distributed under the **Apache Software License**. See the `LICENSE.txt <./LICENSE.txt>`_ file in the release for details.
P.S.
------------
Please drop me a note with any feedback you have.
**Ran Aroussi**
نیازمندی
| مقدار | نام |
|---|---|
| >=0.24.0 | pandas |
| >=1.16.5 | numpy |
| >=0.9.0 | seaborn |
| >=3.0.0 | matplotlib |
| >=1.2.0 | scipy |
| >=0.8.0 | tabulate |
| >=0.1.70 | yfinance |
| >=2.0 | python-dateutil |
نحوه نصب
نصب پکیج whl QuantStats-0.0.9:
pip install QuantStats-0.0.9.whl
نصب پکیج tar.gz QuantStats-0.0.9:
pip install QuantStats-0.0.9.tar.gz