Aggregation of log-linear risks
نویسندگان
چکیده
In this paper we work in the framework of a k-dimensional vector of log-linear risks. Under weak conditions on the marginal tails and the dependence structure of a vector of positive risks we derive the asymptotic tail behaviour of the aggregated risk and present an application concerning log-normal risks with stochastic volatility.
منابع مشابه
ارزیابی و رتبه‌بندی ریسک در پروژه‌های تونل‌سازی با استفاده از روش تخصیص خطی
Ranking of a project's risks is considered an essential part of risk management process, especially when the number of risk factors increases. In the present study, a comprehensive structure of main risks existing in tunneling projects was initially prepared composed of 17 major levels and 196 sub-level, and these risks were subsequently ranked in tunneling project of Seymareh dam in South-We...
متن کاملCelebrating 50 Years of the Applied Probability Trust
In this paper we work in the framework of a k-dimensional vector of log-linear risks. Under weak conditions on the marginal tails and the dependence structure of a vector of positive risks, we derive the asymptotic tail behaviour of the aggregated risk and present an application concerning log-normal risks with stochastic volatility.
متن کاملSome New Results on Policy Limit Allocations
Suppose that a policyholder faces $n$ risks X1, ..., Xn which are insured under the policy limit with the total limit of l. Usually, the policyholder is asked to protect each Xi with an arbitrary limit of li such that ∑ni=1li=l. If the risks are independent and identically distributed with log-concave cumulative distribution function, using the notions of majorization and stochastic orderings, ...
متن کاملLog-mean linear regression models for binary responses with an application to multimorbidity
In regression models for categorical data a linear model is typically related to the response variables via a transformation of probabilities called the link function. We introduce an approach based on two link functions for binary data named log-mean (LM) and log-mean linear (LML), respectively. The choice of the link function plays a key role for the interpretation of the model, and our appro...
متن کاملOn the Estimation of Relative Risks via Log Binomial Regression
Given the well known convergence difficulties in fitting log binomial regression with standard GLM software, we implement a direct solution via constrained optimization which avoids the circumventions found in the literature. The use of a log binomial model is motivated by our interest in directly estimating relative risks adjusted for confounders. A Bayesian log binomial regression model is al...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Applied Probability
دوره 51 شماره
صفحات -
تاریخ انتشار 2014