Kernel estimation of quantile sensitivities
نویسندگان
چکیده
منابع مشابه
Kernel Estimation of Quantile Sensitivities
Quantiles, also known as value-at-risks in the financial industry, are important measures of random performances. Quantile sensitivities provide information on how changes in input parameters affect output quantiles. They are very useful in risk management. In this article, we study the estimation of quantile sensitivities using stochastic simulation. We propose a kernel estimator and prove tha...
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E quantile sensitivities is important in many optimization applications, from hedging in financial engineering to service-level constraints in inventory control to more general chance constraints in stochastic programming. Recently, Hong (Hong, L. J. 2009. Estimating quantile sensitivities. Oper. Res. 57 118–130) derived a batched infinitesimal perturbation analysis estimator for quantile sensi...
متن کاملDouble Kernel estimation of sensitivities
This paper adresses the general issue of estimating the sensitivity of the expectation of a random variable with respect to a parameter characterizing its evolution. In finance for example, the sensitivities of the price of a contingent claim are called the Greeks. A new way of estimating the Greeks has been recently introduced by Elie, Fermanian and Touzi [6] through a randomization of the par...
متن کاملEstimating Quantile Sensitivities
Quantiles of a random performance serve as important alternatives to the usual expected value. They are used in the financial industry as measures of risk and in the service industry as measures of service quality. To manage the quantile of a performance, we need to know how changes in the input parameters affect the output quantiles, which are called quantile sensitivities. In this paper, we s...
متن کاملKernel and Nearest Neighbor Estimation of a Conditional Quantile
Let (Xl'Z1)' (X2,Z2),· .. ,(Xn,Zn) be LLd. as (X,Z), Z taking values in Rl, and for o < p < 1, let ep(x) denote the conditional p-quantile of Z given X=x, i.e., P(Z ~ ep(x) IX=x) = p. In this paper, kernel and nearest neighbor estimators of ep(x) are proposed. As a first step in studying the asymptotics of these estimates, Bahadur type ~ representations of the sample conditional quantile functi...
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ژورنال
عنوان ژورنال: Naval Research Logistics
سال: 2009
ISSN: 0894-069X,1520-6750
DOI: 10.1002/nav.20358