End-to-End Python implementation of the Mesoscopic Structural Risk-Navigation System from Shao, Yang & Zhang (2026). Estimates rolling QVAR models, extracts multiscale network backbones via Disparity Filter, enumerates 13 directed triadic motifs (30 node orbits), and optimizes a Minimum Structural Similarity Portfolio.
python topology jupyter-notebook network-science portfolio-optimization time-series-analysis computational-finance graph-isomorphism variance-decomposition systemic-risk financial-networks disparity-filter risk-spillovers triadic-motifs connectedness-analysis quantile-var quantile-econometrics mesoscopic-analysis backbone-extraction node-orbits
-
Updated
May 2, 2026 - Jupyter Notebook