A framework for financial systemic risk valuation and analysis.

Financial research data services for academics.

SOAP - A Tool for Uncovering Filter Bubbles on Very Large Online Platforms

This repository contains the codes for the paper "Machine-Learning-enhanced Systemic Risk Measure: A Two-Step Supervised Learning Approach" (by R. Liu and C.S. Pun)

Official implementation of "Predicting Systemic Risk in Financial Systems Using Deep Graph Learning"

A research-grade lab for stress-testing DeFi protocols using Solidity mini-systems, a Python simulation engine, and a Streamlit dashboard. Simulates price crashes, liquidity shifts, AMM behavior, lending liquidations, and systemic risk dynamics. Designed for DeFi engineers, auditors, and researchers.

A deep exploration of the economic physics governing DeFi crashes, AMM decay, liquidity spirals, and liquidation cascades. This article models decentralized finance as a nonlinear system driven by invariants, thresholds, and feedback loops, revealing why crashes follow predictable laws of motion.

Some codes used for the numerical examples proposed in https://arxiv.org/abs/1803.00445

An open-source platform for modeling systemic climate transition risks in financial systems. Developed by CFA Institute RPC & UK CGFI

Source code, data and plots for our paper "Analysis of Large Market Data Using Neural Networks: A Causal Approach"

Code repository for Restaking research, containing Python scripts, Dune SQL queries, and interactive data visualizations.

Python implementation of advanced financial network analysis toolkit for creating multi-layered Digital Twins of market dynamics. Implements information-theoretic Transfer Entropy and stochastic Kramers-Moyal methods to map non-linear, directed relationships between assets during normal and crisis periods.

Algorithm for reconstructing topology of complex networks from a limited number of links (Bootstrapping method)

This policy report argues that UK higher education should be treated as critical national infrastructure. It highlights systemic risks from market fragility, fiscal exposure, and governance opacity, and sets out reforms for fiduciary openness, resilience planning, and conflict-proofed oversight.

A kernel-based stochastic approximation (KBSA) framework for contextual optimization.

An evidentiary policy paper analysing systemic fragility in UK higher education through the lens of Akerlof’s ‘lemons’ market. Examines opaque rankings and think tanks as conflicted intermediaries, and proposes fiduciary openness, ratings reform, and stress testing to safeguard systemic stability.

End-to-End Python implementation of Markov-Switching VAR framework for detecting endogenous financial fragility. Replicates Delli Gatti et al.'s (2025) methodology using EM algorithm, Hamilton filtering, and HP spectral decomposition to empirically test Minsky's Financial Instability Hypothesis in macroeconomic data.

This repository contains the code and implementation for a master's thesis on using deep learning techniques to model systemic risk in financial systems with non-normal risk factors.

A systemic risk simulation scaffold and ethical blueprint for recursive planning, post collapse governance, and swarm alignment. (v1.0-v5.2)

A quantitative research framework utilizing Linear Algebra (Spectral Decomposition) and Network Theory (PageRank) to decode systemic fragility in global markets.