Bayesian Non-Parametric Risk Metric
by Kiwan Hyun Abstract This thesis constructs completely non-parametric Risk Metric models through Dirichlet process in order to account for both the parametric uncertainty and model uncertainty that a Risk Metric may bring. Value at Risk (VaR), along with its integrated form Continuous Value at Risk (CVaR) / Expected Shortfall (ES), is one of the […]
Dealing with Data: An Empirical Analysis of Bayesian Black-Litterman Model Extensions
By Daniel Roeder Portfolio Optimization is a common financial econometric application that draws on various types of statistical methods. The goal of portfolio optimization is to determine the ideal allocation of assets to a given set of possible investments. Many optimization models use classical statistical methods, which do not fully account for estimation risk in […]
