Lecture
Quantitative Risk Management: VaR Estimation and Multivariate Distributions
In course
DEMO: tempor tempor occaecat
Duis tempor eu labore ut culpa nostrud sit aliqua duis labore commodo anim. Occaecat esse id ea mollit. Qui pariatur laboris in esse et labore aute dolore deserunt proident qui nostrud nisi mollit.
Description
This lecture covers the estimation of Value at Risk (VaR) using Monte Carlo simulations, constructing confidence intervals, backtesting VaR computations, and evaluating the accuracy of VaR models. It also delves into multivariate distributions, including the multivariate normal distribution and properties such as marginal distributions, linear combinations, and conditional distributions. The lecture concludes with discussions on testing normality through QQ plots and the Jarque-Bera statistic.
Instructor
excepteur elit
Consequat magna ullamco consequat ea ad fugiat Lorem et ad ex ad. Proident duis nisi id fugiat non sint mollit deserunt. Commodo do do eu qui. Est officia consequat ex nisi qui aliquip ea pariatur. Ad ut adipisicing commodo nulla irure anim sit cillum commodo tempor ea sint sint. Exercitation culpa nulla aliqua adipisicing. Veniam minim occaecat et exercitation laboris cupidatat sint dolore cillum labore proident id enim.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related lectures (37)
Gaussian Mixture Models: Data Classification
Explores denoising signals with Gaussian mixture models and EM algorithm, EMG signal analysis, and image segmentation using Markovian models.
Quantum Chemistry
Covers quantum chemistry topics such as tunneling, wave packets, and harmonic oscillators.
Quantum Chemistry: Spin Operators
Explores spin operators in quantum chemistry, focusing on their properties and commutation rules with orbital angular momentum operators.
Interval Estimation: Method of Moments
Covers the method of moments for estimating parameters and constructing confidence intervals based on empirical moments matching distribution moments.
Spatial Analysis: Spatial Statistics and Analysis
Explores spatial statistics, digital elevation models, land cover analysis, and geographically weighted regression in spatial analysis.