Portfolio level (un)conditional risk measure estimation for backtesting using Vine Copula and ARMA-GARCH models.

Expected Shortfall Backtesting

R Finance packages not listed in the Empirical Finance Task View

Manuel Touyaa's porfotlio of Python projects/assignments for Finance Market Risk.

R package providing functions for computing Expected shortfall (ES) and Value at risk (VaR)

A package for evaluating tail probabilities and partial moments for random vectors in multivariate generalized hyperbolic random vectors.

Comparisons of financial metrics (e.g. VaR vs CVaR/ES, simple vs log returns, etc.).

[R] Statistical analysis of financial data conducted in R

This repository consits of: projects and homeworks connected with research area such as Risk Management.

A collection of approaches for forecasting VaR and ES, based on both autoregressive approaches and neural networks.

A library for the calculation of tail risk measures

Backtesting my current US stocks portfolio

Code for the case studies and theoretical visualizations for the master thesis 'Estimation and Backtesting of the Expected Shortfall and Value at Risk using Vine Copulas'

Essential techniques to assess financial risks

Market risk analytics dashboard in Python and Streamlit that computes portfolio volatility, drawdowns, VaR/ES, rolling correlations, and stress tests (shocks + COVID‑style crisis window) for equity/ETF portfolios. ​

Repository represents python usability of measuring and managing risks (practice tasks and real cases)

Curso ministrado por mim na Financial Risk Academy (FRA) sobre Introdução ao Risco de Mercado com Python

Provides a concrete Julia implementation for computing the conditional value-at-risk (aka expected shortfall) for discrete probability distributions. Also works as a pseudocode for other languages.

The purpose of investments is to obtain a profit. One type of investments that can be done is stock investment. Investors can diversify the stocks to reduce the risk of an investment. Stock diversification is done by combining several stocks and then forming a portfolio.

The goal of esreg is to simultaneously model the quantile and the expected shortfall of a response variable given a set of covariates.

Production-grade open-source Market Risk Engine 🚀💹 – Full-stack FastAPI (Python) + React 19/TypeScript with a sleek fintech dark-theme dashboard.Compute VaR & CVaR via multiple methods, advanced stress testing (historical crises + custom), VaR backtesting (Kupiec test), and rich portfolio analytics.

Interactive Risk Management Dashboard built with Streamlit. Features visual explanations of Quant Finance concepts like Value at Risk (VaR), modular Python architecture, and automated data processing. 📊 📈

Risk analysis of a stock portfolio using Python metrics like Sharpe Ratio, VaR, etc.

Nonparametric methods concerning to expected shortfall

A collection of tools for filtering daily risk measures starting from the high-frequency observations.

This repository contains a multivariate econometric study that has been applied to the financial risk management of an equally-weighted (EW) portfolio.

Time-series forecasting of IBEX 35 and S&P 500 using econometric models and volatility analysis.

Monte Carlo simulation of credit migration and default risk under a one-factor Merton model, comparing concentrated and diversified bond portfolios.

R package for nonparametric estimation of CES

Financial Risk with Python