semvec/pypi-packages huggingface dataset:
Radium-Tech 0.1.0
Intuitive backtesting for quantitative trading strategies.
License: MIT

# Radium

**Radium-Tech** is a Python package providing an intuitive backtesting and visualisation platform for quantitative trading strategies.

## Main Features

In current version Radium-Tech can:
- Plot price data for multiple equities.
- Regress hedge ratios and price spread for a pair of equities.
- Conduct tests for cointegration on pairs of equities.
- Backtest a Bollinger Band strategy.

Future versions aim to add additonal mean-reversing strategies.

## Where to get it

The latest public version of Radium-Tech is avaliable on [Python Package Index (PyPI)](https://pypi.org/project/Radium-Tech/)

```sh
pip install Radium-Tech
```

## Dependencies

Radium-Tech requires:
- `numpy`
- `pandas`
- `matplotlib`
- `statsmodels`
- `requests`

An [Alpha-Vantage](https://www.alphavantage.co/) free API key is also required for equity data.

## Documentation

Official documentation for Radium-Tech is hosted on readthedocs.io: https://radium-tech.readthedocs.io/en/latest/

They can be downloaded in PDF form: https://radium-tech.readthedocs.io/_/downloads/en/latest/pdf/

## Example 

An example full backtest cycle can be found in `Radium-Tech/Examples/bollinger.py`

```sh
from radium import Equity, Pair
from radium.pair import cadf_test, johansen_test
from radium.strategy import BollingerPair


# Alpha-vantage API Key
API_KEY = ''

# Creates equity, pair objects for visa and mastercard 2015-2021
equity1 = Equity('KO', '2016-01-01', '2021-01-01', API_KEY)
equity2 = Equity('SBUX', '2016-01-01', '2021-01-01', API_KEY)
pair = Pair(equity1, equity2)

# Visualise data
pair.plot_closed()

# Test for cointegration
cadf_test(pair)
johansen_test(pair)

# Hedge the pair
pair.hedge('OLS', 30)

# Backtest Bollinger band strategy on pair
entry_z = 1
exit_z = 0
lookback = 30
bollinger = BollingerPair(pair, entry_z, exit_z, lookback)

# Evaluate strategy
CAGR = bollinger.CAGR
sharpe = bollinger.sharpe

print(f"Compound Annual Growth Rate: {CAGR}")
print(f"Sharpe ratio: {sharpe}")
```

## Authors

Radium-Tech is developed by [Ivan Erlic](https://linkedin.com/in/ivan-e-665420122) and [Callum Rai](https://linkedin.com/in/callumrai) of University College London.

Please submit any bugs/suggestions/questions to the [issues forum](https://github.com/CallumRai/Radium-Tech/issues), or email us at: ivan.erlic.19@ucl.ac.uk, callum.rai.19@ucl.ac.uk
pycewise 0.1.4
Piecewise linear regressions, based on model trees.
License: MIT

# Pycewise

## Installation

```bash
pip install pycewise
```

### Optional installation requirements

The main functionnality of this package (computing a segmented linear regression) can be used without any third-party code.

For additional features, the following packages should be installed (`pip install <package_name>`):

- numpy
- statsmodels
- jupyter
- matplotlib
- graphviz
- coverage
- mock
- palettable


## Usage

Basic example:

```python
from pycewise import *
import pandas

df = pandas.read_csv('test_data/memcpy_small.csv')
reg = compute_regression(df['size'], df['duration'], mode='log')
print(reg)
```

For more advanced usage, see the [notebooks](https://github.com/Ezibenroc/pycewise/tree/master/notebooks).
seirplus-es 1.0.1
Este paquete utiliza un modelo epidemiológico SEIR y redes de contactos (network) para modelar el comportamiento de la pandemia de covid-19. Está basado en el modelo creado por Ryan McGee con modificaciones hechas para ajustarlo a las condiciones específicas de El Salvador.
License: MIT

# Paquete seirsplus_es

## Descripción

Este paquete utiliza un modelo epidemiológico SEIR y redes de contactos (network) para modelar el comportamiento de la pandemia de covid-19.

Está basado en el modelo creado por Ryan McGee con modificaciones hechas para ajustarlo a las condiciones específicas de El Salvador.



## Autores ✒️



* **Ryan McGee** - *Trabajo Base* - [Ryan](https://github.com/ryansmcgee/seirsplus)
* **Víctor Sandoval** - *Correcciones y modificaciones* - [Sandoval](https://github.com/Neik8314/seirsplus_es)



## Licencia

MIT License

Copyright (c) [year] [fullname]

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.