Governance structure and Operating Performance of Japanese Major Banks

近年，銀行の経営破綻が相次ぎ，金融システムの不安定性が高まっている。そのため，銀行のガバナンス構造を明らかにし，銀行経営の効率性を高めることは喫緊の課題である。ところで，非金融企業と異なり預金という特殊な負債を保有する銀行の場合，株主によるガバナンスが重要である。本稿では， 1990年から1998年をサンプル期間として，日本の大手銀行18行のパネル・データを用いて，株式所有構造の変化，株式所有構造と経営効率性および労働分配率との関係を分析した。その結果，①銀行の株式所有構造は経営効率性を重視する株主の保有比率が上昇する傾向にあること，②銀行経営に対して株主は経営効率性を高める方向で影響を与えていること，③株式保有比率が高いほど労働分配率が低下すること，すなわち株主への分配が多くなる傾向があること，の3点が明らかになった。従って，少なくとも1990年代において，銀行のガバナンス構造は株主への利益分配を重視する「新古典派型企業」としての性格を示していると言える

A Short Counterexample Property for Safety and Liveness Verification of Fault-tolerant Distributed Algorithms

Distributed algorithms have many mission-critical applications ranging from embedded systems and replicated databases to cloud computing. Due to asynchronous communication, process faults, or network failures, these algorithms are difficult to design and verify. Many algorithms achieve fault tolerance by using threshold guards that, for instance, ensure that a process waits until it has received an acknowledgment from a majority of its peers. Consequently, domain-specific languages for fault-tolerant distributed systems offer language support for threshold guards. We introduce an automated method for model checking of safety and liveness of threshold-guarded distributed algorithms in systems where the number of processes and the fraction of faulty processes are parameters. Our method is based on a short counterexample property: if a distributed algorithm violates a temporal specification (in a fragment of LTL), then there is a counterexample whose length is bounded and independent of the parameters. We prove this property by (i) characterizing executions depending on the structure of the temporal formula, and (ii) using commutativity of transitions to accelerate and shorten executions. We extended the ByMC toolset (Byzantine Model Checker) with our technique, and verified liveness and safety of 10 prominent fault-tolerant distributed algorithms, most of which were out of reach for existing techniques.Comment: 16 pages, 11 pages appendi

Implementation of Fault-tolerant Quantum Logic Gates via Optimal Control

The implementation of fault-tolerant quantum gates on encoded logic qubits is considered. It is shown that transversal implementation of logic gates based on simple geometric control ideas is problematic for realistic physical systems suffering from imperfections such as qubit inhomogeneity or uncontrollable interactions between qubits. However, this problem can be overcome by formulating the task as an optimal control problem and designing efficient algorithms to solve it. In particular, we can find solutions that implement all of the elementary logic gates in a fixed amount of time with limited control resources for the five-qubit stabilizer code. Most importantly, logic gates that are extremely difficult to implement using conventional techniques even for ideal systems, such as the T-gate for the five-qubit stabilizer code, do not appear to pose a problem for optimal control.Comment: 18 pages, ioptex, many figure

A Simple Dual Decomposition Method for Resource Allocation in Telecommunication Networks

© 2016 The Authors, published by EDP Sciences.We consider a problem of optimal resource allocation in a wireless communication network divided into zones (clusters). The network manager aims to distribute some homogeneous resource (bandwidth) among users of several zones in order to maximize the total network profit, which takes into account payments from users and implementation costs. As a result, we obtain a convex optimization problem involving capacity and balance constraints. By using the dual Lagrangian method with respect to the capacity constraint, we reduce the initial problem to a suitable one-dimensional problem, so that calculation of its cost function value leads to independent solution of zonal problems, treated as two-side auction models with one trader. We show that solution of each zonal problem can be found exactly by a simple arrangement type algorithm even in the case where the trader price is not fixed. Besides, we suggest ways to adjust the basic problem to the case of moving nodes. Some results of computational experiments confirm the applicability of the new method

Application of the conditional gradient method to resource allocation in wireless networks

© 2016, Pleiades Publishing, Ltd.We propose a new two-level iterative method for solution of a general problem of optimal allocation of a homogeneous resource (bandwidth) in a wireless communication network. It is divided into service zones (clusters) and the network manager can buy external volumes of this resource. This approach leads to a convex optimization problem, which is solved with a dual Lagrangian method, where calculation of the cost function value decomposes into a system of independent zonal optimization problems. Each of them is treated as a market equilibrium problem. This optimization problem is solved with conditional gradient method for different information exchange schemes for participants. Besides, we suggest several ways to adjust the basic problemto the case of moving nodes. We give some results of numerical experiments on the proposed method which confirm its preference over the previous ones

An extended Gauss-Seidel method for multi-valued mixed complementarity problems

The complementarity problem (CP) is one of the basic topics in nonlinear analysis. Since the constraint set of CP is a convex cone or a cone segment, weak order monotonicity properties can be utilized for its analysis instead of the usual norm monotonicity ones. Such nonlinear CPs with order monotonicity properties have a great number of applications, especially in economics and mathematical physics. Most solution methods were developed for the single-valued case, but this assumption seems too restrictive in many applications. In the paper, we consider extended concepts of multi-valued Z-mappings and examine a class of generalized mixed complementarity problems (MCPs) with box constraints, whose cost mapping is a general composition of multi-valued mappings possessing Z type properties. We develop a Gauss-Seidel algorithm for these MCPs. Some examples of computational experiments are also given

The proximal point method for nonmonotone variational inequalities

We consider an application of the proximal point method to variational inequality problems subject to box constraints, whose cost mappings possess order monotonicity properties instead of the usual monotonicity ones. Usually, convergence results of such methods require the additional boundedness assumption of the solutions set. We suggest another approach to obtaining convergence results for proximal point methods which is based on the assumption that the dual variational inequality is solvable. Then the solutions set may be unbounded. We present classes of economic equilibrium problems which satisfy such assumptions

Partitionable variational inequalities with multi-valued mappings

We consider multi-valued variational inequalities defined on a Cartesian product of finite-dimensional subspaces. We introduce extensions of order monotonicity concepts for set-valued mappings, which are adjusted to the case where the subspaces need not be real lines. These concepts enable us to establish new existence and uniqueness results for the corresponding partitionable multi-valued variational inequalities. Following a parametric coercivity approach, we obtain convergence of the Tikhonov regularization method without monotonicity conditions. © 2006 Springer-Verlag Berlin Heidelberg

Dual methods for optimal allocation of total network resources

© 2016, North Atlantic University Union NAUN. All rights reserved.We consider a general problem of optimal allocation of a homogeneous resource (bandwidth) in a wireless communication network, which is decomposed into several zones (clusters). The network manager must satisfy different users requirements. However, they may vary essentially from time to time. This makes the fixed allocation rules inefficient and requires certain adjustment procedure for each selected time period. Besides, sometimes users requirements may exceed the local network capacity in some zones, hence the network manager can buy additional volumes of this resource. This approach leads to a constrained convex optimization problem. We discuss several ways to find a solution of this problem, which exploit its special features. We suggest the dual Lagrangian method to be applied to selected constraints. This in particular enables us to replace the initial problem with one-dimensional dual one. We consider the case of the affine cost (utility) functions, when each calculation of the value of the dual function requires solution of a special linear programming problem. We can also utilize the zonal resource decomposition approach, which leads to a sequence of onedimensional optimization problems. The results of the numerical experiments confirm the preferences of the first method

Combined methods for dynamic spatial auction market models

An equilibrium model for description of behavior of a system of auction markets joined by transmission lines subject to joint balance and capacity flows constraints for a certain time period is suggested. We treat this model as an extended primal-dual system of variational inequalities or a saddle point problem. Several splitting type methods are proposed to find its solution. © 2011 Springer Science+Business Media, LLC