scholarly journals On capital allocation for stochastic arrangement increasing actuarial risks

2017 ◽  
Vol 5 (1) ◽  
pp. 145-153 ◽  
Author(s):  
Xiaoqing Pan ◽  
Xiaohu Li
Keyword(s):  
Optimal Allocation ◽  
Capital Allocation ◽  
Convex Ordering ◽  
Increasing Convex Ordering ◽  
Arrangement Increasing ◽  
Occurrence Times

AbstractThis paper studies the increasing convex ordering of the optimal discounted capital allocations for stochastic arrangement increasing risks with stochastic arrangement decreasing occurrence times. The application to optimal allocation of policy limits is presented as an illustration as well.

On an elementary characterization of the increasing convex ordering, by an application

1994 ◽  
Vol 31 (3) ◽  
pp. 834-840 ◽  
Author(s):  
Armand M. Makowski
Keyword(s):  
Short Proof ◽  
Probability Distributions ◽  
Short Note ◽  
Comparison Result ◽  
Convex Ordering ◽  
Simple Characterization ◽  
Increasing Convex Ordering ◽  
Elementary Characterization

In this short note, we present a simple characterization of the increasing convex ordering on the set of probability distributions on ℝ. We show its usefulness by providing a very short proof of a comparison result for M/GI/1 queues due to Daley and Rolski, and obtained by completely different means.

Stochastic comparisons for queueing models via random sums and intervals

1992 ◽  
Vol 24 (4) ◽  
pp. 960-985 ◽  
Author(s):  
Alain Jean-Marie ◽  
Zhen Liu
Keyword(s):  
Point Process ◽  
Response Times ◽  
Waiting Times ◽  
Random Variables ◽  
Stochastic Ordering ◽  
Partial Sums ◽  
Polling Systems ◽  
Convex Ordering ◽  
Random Intervals ◽  
Increasing Convex Ordering

We consider the relationships among the stochastic ordering of random variables, of their random partial sums, and of the number of events of a point process in random intervals. Two types of result are obtained. Firstly, conditions are given under which a stochastic ordering between sequences of random variables is inherited by (vectors of) random partial sums of these variables. These results extend and generalize theorems known in the literature. Secondly, for the strong, (increasing) convex and (increasing) concave stochastic orderings, conditions are provided under which the numbers of events of a given point process in two ordered random intervals are also ordered.These results are applied to some comparison problems in queueing systems. It is shown that if the service times in two M/GI/1 systems are compared in the sense of the strong stochastic ordering, or the (increasing) convex or (increasing) concave ordering, then the busy periods are compared for the same ordering. Stochastic bounds in the sense of increasing convex ordering on waiting times and on response times are provided for queues with bulk arrivals. The cyclic and Bernoulli policies for customer allocation to parallel queues are compared in the transient regime using the increasing convex ordering. Comparisons for the five above orderings are established for the cycle times in polling systems.

On an elementary characterization of the increasing convex ordering, by an application

1994 ◽  
Vol 31 (03) ◽  
pp. 834-840
Author(s):  
Armand M. Makowski
Keyword(s):  
Short Proof ◽  
Probability Distributions ◽  
Short Note ◽  
Comparison Result ◽  
Convex Ordering ◽  
Simple Characterization ◽  
Increasing Convex Ordering ◽  
Elementary Characterization

In this short note, we present a simple characterization of the increasing convex ordering on the set of probability distributions on ℝ. We show its usefulness by providing a very short proof of a comparison result for M/GI/1 queues due to Daley and Rolski, and obtained by completely different means.

Stochastic comparisons for queueing models via random sums and intervals

1992 ◽  
Vol 24 (04) ◽  
pp. 960-985 ◽  
Author(s):  
Alain Jean-Marie ◽  
Zhen Liu
Keyword(s):  
Point Process ◽  
Response Times ◽  
Waiting Times ◽  
Random Variables ◽  
Stochastic Ordering ◽  
Partial Sums ◽  
Polling Systems ◽  
Convex Ordering ◽  
Random Intervals ◽  
Increasing Convex Ordering

We consider the relationships among the stochastic ordering of random variables, of their random partial sums, and of the number of events of a point process in random intervals. Two types of result are obtained. Firstly, conditions are given under which a stochastic ordering between sequences of random variables is inherited by (vectors of) random partial sums of these variables. These results extend and generalize theorems known in the literature. Secondly, for the strong, (increasing) convex and (increasing) concave stochastic orderings, conditions are provided under which the numbers of events of a given point process in two ordered random intervals are also ordered. These results are applied to some comparison problems in queueing systems. It is shown that if the service times in two M/GI/1 systems are compared in the sense of the strong stochastic ordering, or the (increasing) convex or (increasing) concave ordering, then the busy periods are compared for the same ordering. Stochastic bounds in the sense of increasing convex ordering on waiting times and on response times are provided for queues with bulk arrivals. The cyclic and Bernoulli policies for customer allocation to parallel queues are compared in the transient regime using the increasing convex ordering. Comparisons for the five above orderings are established for the cycle times in polling systems.

A new aging concept derived from the increasing convex ordering

2018 ◽  
Vol 48 (12) ◽  
pp. 2904-2916
Author(s):  
T. H. M. Abouelmagd ◽  
A. A. E. Ahmed ◽  
Enayat M. Abd Elrazik ◽  
Mahmoud M. Mansour ◽  
A-Hadi N. Ahmed ◽  
...  
Keyword(s):  
Convex Ordering ◽  
Increasing Convex Ordering

Optimal allocation under partial ordering of lifetimes of components

1993 ◽  
Vol 25 (04) ◽  
pp. 914-925 ◽  
Author(s):  
Emad El-Neweihi ◽  
Jayaram Sethuraman
Keyword(s):  
Optimal Allocation ◽  
Reliability Theory ◽  
Partial Ordering ◽  
Threshold Models ◽  
Minimal Repair ◽  
Stochastic Orderings ◽  
Redundancy Allocation ◽  
Arrangement Increasing ◽  
Increasing Functions

Assembly of systems to maximize reliability when certain components of the systems can be bolstered in different ways is an important theme in reliability theory. This is done under assumptions of various stochastic orderings among the lifetimes of the components and the spares used to bolster them. The powerful techniques of Schur and arrangement increasing functions are used in this paper to pinpoint optimal allocation results in different settings involving active and standby redundancy allocation, minimal repair and shock-threshold models.

An aging notion derived from the increasing convex ordering: the NBUCA class

2006 ◽  
Vol 136 (3) ◽  
pp. 555-569 ◽  
Author(s):  
I.A. Ahmad ◽  
A. Ahmed ◽  
I. Elbatal ◽  
M. Kayid
Keyword(s):  
Convex Ordering ◽  
Increasing Convex Ordering

Optimality of the round-robin routing policy

1994 ◽  
Vol 31 (2) ◽  
pp. 466-475 ◽  
Author(s):  
Zhen Liu ◽  
Don Towsley
Keyword(s):  
Failure Rate ◽  
Response Times ◽  
Random Variables ◽  
Round Robin ◽  
State Information ◽  
Convex Ordering ◽  
Increasing Failure Rate ◽  
Rate Distribution ◽  
Routing Policy ◽  
Increasing Convex Ordering

In this paper we consider the problem of routing customers to identical servers, each with its own infinite-capacity queue. Under the assumptions that (i) the service times form a sequence of independent and identically distributed random variables with increasing failure rate distribution and (ii) state information is not available, we establish that the round-robin policy minimizes, in the sense of a separable increasing convex ordering, the customer response times and the numbers of customers in the queues.

Economic policy uncertainty and firms' labor investment decision

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jian Chu ◽  
Junxiong Fang
Keyword(s):  
Economic Policy ◽  
Human Capital ◽  
Optimal Allocation ◽  
Investment Decision ◽  
Capital Allocation ◽  
Investment Efficiency ◽  
Policy Uncertainty ◽  
Content Type ◽  
Economic Policy Uncertainty ◽  
The Impact

PurposeThe purpose of this paper is to empirically investigate the impact of economic policy uncertainty on firms' labor investment decision, which includes labor investment level and efficiency, especially human capital allocation.Design/methodology/approachThis paper uses Economic Policy Uncertainty Index for China and Chinese A-share listed firms in the period 2002–2016 to constructs a sample of 20,779 firm-year observations and applies the methods of pooled OLS regressions to do an empirical study.FindingsThis paper finds that firms' labor investment is negatively correlated with economic policy uncertainty. And firms' labor investment efficiency (and overinvestment in labor) is positively (negatively) correlated with economic policy uncertainty, which is more significant for non-SOEs and firms with less government intervention. Further, the positive relation between economic policy uncertainty and labor investment efficiency is more significant for labor-intensive firms, firms in competitive industry, firms in developed labor market and firms under strong labor law protection. In addition, economic policy uncertainty induces firms to make adjustment on human capital structure and allocate more employees with high human capital, which eventually helps firms achieve higher total factor productivity.Social implicationsThe study of this paper indicates that the government needs to consider economic policies' impact on firms when introducing and changing policies and guide firms to improve human capital allocation under different internal and external conditions to finally realize the optimal allocation of social resources.Originality/valueThis paper studies the influence of external economic policy environment on firms' labor investment decision, which lacks adequate attention in the literature and indicates that under economic policy uncertainty, firms actively decrease labor demand and increase labor investment efficiency by optimizing human capital allocation.

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