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.
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.
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.
FinQuant depends on the following Python packages:
Table of Contents¶
- Quick Start
- Portfolio Management
- Expected Return, Volatility, Sharpe Ratio
- Daily and Historical Returns
- Moving Average
- Efficient Frontier
- Monte Carlo