Python-based portfolio / stock widget which sources data from Yahoo Finance and calculates different types of Value-at-Risk (VaR) metrics and many other (ex-post) risk/return characteristics both on an individual stock and portfolio-basis, stand-alone and vs. a benchmark of choice (constructed with wxPython)

A collection of various computational methods to optimize a user's investment portfolio using Modern Portfolio Theory and optimizing various factors such as Returns, Sharpe Ratio and Risk.

Implementation of a variety of Value-at-Risk backtests

Lasso Quantile Regression

R code for CAViaR model

Projects are developed for implementing the knowledge gained in the courses studied at World Quant University and meeting the requirement of clearing the courses.

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

Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."

Financial modelling, derivatives, investments

Replication and extension of paper on Conditional Value at Risk (CoVaR) by Adrian and Brunnermeier.

Statistical tests for Value at Risk (VaR) Models.

One-week side project to play around stochastic optimization (how to take *good* decisions under uncertainty)

Application to finance

Shows how banks can modernize their risk management practices by back-testing, aggregating and scaling simulations by using a unified approach to data analytics with the Lakehouse.

Python code for rolling Value at Risk(VaR) of fiancial assets and some of economic time series, based on the procedure proposed by Hull & White(1998).

Measure market risk by CAViaR model

Weekly exercises of the course of Stochastic Methods for Finance.

Model and replications scripts for the 2020 IMF Working Paper "Foreign Exchange Interventions Rules for Central Banks: A Risk-Based Framework"

The repo contains the main topics carried out in my master's thesis on operational risk. In particular, it is described how to implement the so called Loss Distribution Approach (LDA), which is considered the state-of-the-art method to compute capital charge among large banks.

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