Feel free to use my code. 

If you're interested in my GitHub, then here's the link.

R Packages

An improved and simplified package for MF-DFA analysis, including significance testing, surrogate algorithms (IAAFT, IAAWT) and simulation of multifractal series. 

Spectral Projected Gradient method with Inexact Restoration: An algorithm for large-scale nonlinear optimization problems with nonconvex constraints. We apply the algorithm here to solve the "nearest option-implied correlation matrix problem".


Iterated Amplitude Adjusted Wavelet Transform for Python. We're using it in this paper to transform the heavy-tailed distribution of daily returns  to a normal distribution while keeping the structure of volatility clustering.

Direct least-squares method for fitting the implied volatility smile with the SVI (Stochastic Volatility Inspired) equation. The method linearizes the SVI equation to then solve it via Eigenvalue decomposition. Details can be found in my working paper.