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)

Implementation of a variety of Value-at-Risk backtests

R code for CAViaR model

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.

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

Lasso Quantile Regression

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.

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

Statistical tests for Value at Risk (VaR) Models.

Financial modelling, derivatives, investments

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).

Rest Api risk management trading tool based on incremental value at risk

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

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

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

Proposed solutions to selected exercises in the book "Value-at-Risk: Theory and Practice" (2nd edition) by Glyn A. Holton.

Backtesting my current US stocks portfolio

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

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."