Empirical Risk Modeling of Financial Time Series using Value at Risk

The aim of this book is to highlight and illustrate selected quantitative techniques for estimating financial risk. The first module in risk assessment is concerned with the risk measure used, whereas the second module is based on the risk estimation technique. The process of risk assessment involves the Value at Risk, popularly known as VaR with some corresponding risk estimators; Expected Shortfall (ES), the Extreme Value Theory (EVT) and the Generalized Pareto Distribution (GPD). The quality of the risk estimation approach with its corresponding techniques studied shall be tested for with real data. Numerical results and programming code shall be provided for the comparative estimators by the R statistical software.