Metadata-Version: 2.1
Name: nefindata
Version: 0.1.2
Summary: Download data from NEFIN, the Brazilian Center for Research in Financial Economics of the University of São Paulo (http://www.nefin.com.br/)
Home-page: https://github.com/fernandoramacciotti/nefindata
Author: Fernando Ramacciotti
Author-email: fernandoramacciotti@gmail.com
License: MIT
Keywords: NEFIN,financial,time series,financial market,risk factors,fama french,fama factors,Brazilian market
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Requires-Dist: pandas (>=0.24.2)

# nefindata
Python and R packages to download data from NEFIN, the Brazilian Center for Research in Financial Economics of the University of São Paulo (http://www.nefin.com.br/)

# Installation
The python package can be installed via pip. Run the following command:
```sh
pip install nefindata
```

# Risk Factors
Collect data of risk factors such as Market Factor, SMB, WML, HML, IML and Risk Free.

Usage example:
```python
from nefindata.risk_factors import get_risk_factors

factors = ['Mkt', 'SMB'] # for all factors, set it to 'all' or None
df = get_risk_factors(factors)
df_agg = get_risk_factors(factors, agg='month', agg_func='last')
```

# Cost of Capital
Collect data of cost of capital for industrial sectors such as Basic Products, Construction, Consumer, Energy, Finance, Manufacturing and Other.
Data is available for 1, 5, 10 and 20-year projects.

Usage example:
```python
from nefindata.cost_capital import get_sector_cost_of_capital

sector = 'Basic'
df = get_sector_cost_of_capital(sector)
df_agg = get_sector_cost_of_capital(sector, agg='year', agg_func='last')
```

# Other data
Similar functions get other data such as. The syntax is similar as above.
* [Dividend Yield](http://www.nefin.com.br/dividend_yield.html): `get_dividend_yield()`
* [Illiquidity Index](http://www.nefin.com.br/illiquidity_index.html): `get_illiquidity_index()`
* [Loan Fees](http://www.nefin.com.br/loan_fees.html): `get_load_fees()`
* [Short Interest](http://www.nefin.com.br/short_interest.html): `get_short_interest()`

# Next Steps
Include data downloaders from
* [Portfolios](http://www.nefin.com.br/portfolios.html)
* [Spot Rate Curve](http://www.nefin.com.br/spot_rate_curve.html)
* [Volatility Index](http://www.nefin.com.br/volatility_index.html)

