quant-risk

Keywords: quantitative finance, mean-variance optimization, financial ratios, VaR, statistical tests, Hurst exponent, ARIMA

This Python package is available on PyPi and can be installed using pip. The source code is available on GitHub. It is intended to serve as a toolkit for common quantitative finance functions, and was developed as a member of the NTU Quantitative Asset Management Club.

My contributions mainly included implementing different statistical functions: Hurst exponent, ACF & PACF, Augmented Dickey-Fuller test for stationarity of a time series, and Granger Causality test.

I also implemented the Mean-Variance portfolio optimization and ARIMA models.

One unrelated lesson I learnt while working on this package was to improve my documenting skills: I got into the habit of type hinting in Python, and for properly documenting all my functions with docstrings and also naming variables with the right convention.