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Welcome to FinQuant’s documentation

FinQuant is a program for financial portfolio management, analysis and optimisation. It is designed to generate an object that holds your data, e.g. stock prices of different stocks, which automatically computes the most common quantities, such as Expected annual Return, Volatility and Sharpe Ratio. Moreover, it provides a library for computing different kinds of Returns and visualising Moving Averages and Bollinger Bands. Finally, given a set of stocks, it also allows for finding optimised portfolios.

FinQuant is made to be easily extended. I hope it proves itself useful for hobby investors, students, geeks, and the intellectual curious.

Caution

While FinQuant has tests in place that are run automatically by Travis CI, it cannot guarantee to be bug free, nor that the analysis or optimised portfolio yield to wealth. Please use at your own discretion and refer to the License.

Installation

As it is common for open-source projects, there are several ways to get hold of the code. Choose whichever suits you and your purposes best.

Dependencies

FinQuant depends on the following Python packages:

  • python>=3.5.0
  • numpy>=1.15
  • pandas>=0.24
  • matplotlib>=1.5.1
  • quandl>=3.4.5
  • yfinance>=0.1.43
  • scipy>=1.2.0
  • pytest>=2.8.7

From PyPI

FinQuant can be obtained from PyPI:

pip install FinQuant

From GitHub

Get the code from GitHub:

git clone https://github.com/fmilthaler/FinQuant.git

Then inside FinQuant run:

python setup.py install

Alternatively, if you do not wish to install FinQuant, you can also download/clone it as stated above, and then make sure to add it to your PYTHONPATH.

Indices and tables