Local Likelihood Density Estimation and Value-at-Risk

high volatility, thick tails and extreme value theory in value at risk estimation: the case of liability insurance in iran insurance company

در این بررسی ابتدا به بررسی ماهیت توزیع خسارات پرداخته میشود و از روش نظریه مقادیر نهایی برای بدست آوردن برآورد ارزش در معرض خطر برای خسارات روزانه بیمه مسئولیت شرکت بیمه ایران استفاده میشود. سپس کارایی نظریه مقدار نهایی در برآورد ارزش در معرض خطر با کارایی سایر روشهای واریانس ، کواریانس و روش شبیه سازی تاریخی مورد مقایسه قرار میگیرد. نتایج این بررسی نشان میدهند که توزیع ،garch شناخته شده مدل...

Value at Risk Estimation

This chapter reviews the recent developments of Value at Risk (VaR) estimation. In this survey, the most available univariate and multivariate methods are presented. The robustness and accuracy of these estimation methods are investigated based on the simulated and real data. In the backtesting procedure, the conditional coverage test (Christoffersen 1998), the dynamic quantile test (Engle and ...

Local likelihood density estimation based on smooth truncation

Two existing density estimators based on local likelihood have properties that are comparable to those of local likelihood regression but they are much less used than their counterparts in regression. We consider truncation as a natural way of localising parametric density estimation. Based on this idea, a third local likelihood density estimator is introduced. Our main result establishes that ...

On Local Likelihood Density Estimation When the Bandwidth Is Large

In this paper, we provide a large bandwidth analysis for a class of local likelihood methods. This work complements the small bandwidth analysis of Park, Kim and Jones (2002). Our treatment is more general than the large bandwidth analysis of Eguchi and Copas (1998). We provide a higher order asymptotic analysis for the risk of the local likelihood density estimator, from which a direct compari...

Penalized Likelihood Density Estimation :