RETRACTED: Sensitivity Analysis Based on Markovian Integration by Parts Formula

Abstract

Sensitivity analysis is widely applied in financial risk management and engineering; it describes the variations brought by the changes of parameters. Since the integration by parts technique for Markov chains is well developed in recent years, in this paper we apply it for computation of sensitivity and show the closed-form expressions for two commonly-used time-continuous Markovian models. By comparison, we conclude that our approach outperforms the existing technique of computing sensitivity on Markovian models.

Variable Order Mittag–Leffler Fractional Operators on Isolated Time Scales and Application to the Calculus of Variations

“…Summation/integration by parts has a very important role in mathematics: see, e.g., [21,24,33]. This is particularly true in the calculus of variations and optimal control, to prove necessary optimality conditions of Euler-Lagrange type (cf.…”

A Novel Global Sensitivity Measure Based on Probability Weighted Moments

“…Variance-based global sensitivity measures, which are usually called Sobol' indices, were proposed and developed by Sobol' [2], Iman [3], Homma [4], and Saltelli [5]. Besides, there are several mature techniques available to solve the above indices, for instance, Monte Carlo simulation, quasi-Monte Carlo simulation, high-dimensional model representation (HDMR), Markovian integration [6], and the surrogate-assisted method [7,8]. Variance-based global sensitivity measures have been widely applied in various fields such as the spray-drying process [9], heap leaching [10], the rainfall-runoff model [11], and polymeric material [12].…”

RETRACTED: Hang et al. Sensitivity Analysis Based on Markovian Integration by Parts Formula. Math. Comput. Appl. 2017, 22, 40

“…We, the authors, have requested that the title paper [1] is retracted. The results are not reliable due to the technique we applied.…”