经理管理防御会影响公司股价同步性吗?

经理人固守职位衍生的管理防御问题是长期困扰公司发展的重要议题。然而,现有研究多将重点置于管理防御如何影响企业财务决策,而对于其是否会影响资本市场则缺乏足够关注。以2007～2018年中国A股上市公司为样本,依据“防御动机→行为选择→经济后果”的逻辑思路,基于股价同步性的视角,考察经理管理防御影响资本市场的客观表现与内在机理。研究发现,公司股价同步性随着经理管理防御水平的提高而显著上升,该结论在控制内生性问题之后依然稳健;影响路径的检验结果表明：经理管理防御对股价同步性的影响通过：(1)经理管理防御→信息操纵→股价同步性;(2)经理管理防御→内幕交易→股价同步性等两条路径得以实现。异质性检验的结论显示,经理管理防御对公司股价同步性的正影响,在未聘请“四大”审计机构和非国有企业的样本中更为显著。上述研究结论不仅从管理防御这一微观层面拓展了股价同步性影响因素领域的文献研究,而且对于提升资本市场配置效率,实现新阶段下中国金融改革的目标,具有一定的指导意义。     

不同路径下能源价格对碳价格的传导关系研究

针对已有文献大多探讨能源价格与碳价格间的影响程度,本文从建模的角度寻找碳价格与能源价格间的联动关系。首先,使用随机微分方程刻画碳与能源的价格走势,得到碳——能源联动模型解析解。其次,在解析解的基础上,分别讨论能源价格如何通过影响碳市场价格均值、波动率路径从而影响整个碳价格。第三,分析重大能源政策产生的跳跃对碳价格的影响。结果显示,随着能源与碳市场关联程度的增加,相较于能源价格通过均值路径影响碳价格,其通过波动率路径影响碳价格的效果更为明显;且跳跃路径下的碳价格震荡小于波动率路径下能源价格传导引起的碳价格震荡。本文的结果对理清碳——能源价格联动关系具有积极意义,为投资者规避碳市场风险提供必要理论指导。     

Diperfect graphs

Gallai and Milgram have shown that the vertices of a directed graph, with stability number α(G), can be covered by exactly α(G) disjoint paths. However, the various proofs of this result do not imply the existence of a maximum stable setS and of a partition of the vertex-set into paths μ₁, μ₂, ..., μ_k such tht |μ_i ∩S|=1 for alli. Later, Gallai proved that in a directed graph, the maximum number of vertices in a path is at least equal to the chromatic number; here again, we do not know if there exists an optimal coloring (S ₁,S ₂, ...,S _k) and a path μ such that |μ ∩S _i|=1 for alli. In this paper we show that many directed graphs, like the perfect graphs, have stronger properties: for every maximal stable setS there exists a partition of the vertex set into paths which meet the stable set in only one point. Also: for every optimal coloring there exists a path which meets each color class in only one point. This suggests several conjecties similar to the perfect graph conjecture. Dedicated to Tibor Gallai on his seventieth birthday     

MASLOV-TYPE INDEX THEORY FOR SYMPLECTIC PATHS AND SPECTRAL FLOW （II）

1.IntroductionandMainResultsStartingfromthepioneeringworks[5,61ofH.AmannandE.Zehnderin1980,C.ConleyandE.Zehnderestablishedanindextheoryin1984intheircelebratedwork[if]fornondegeneratepathsinSp(Zn)startedfromtheidentitymatrixwithn22.Thisindextheorywasextendedtothenondegeneratecaseofn~1byE.Zehnderandthefirstauthorin[28]of1990.ThisindextheoryforthedegenerateHamiltoniansystemswasestablishedbythefirstauthorin[21]of1990andC.Viterboin[34]of1990viadifferentmethods,andthenextendedtoalldegenerates…     

Continuous learning methods in two-buyer pricing problem

This paper presents continuous learning methods in a monopoly pricing problem where the firm has uncertainty about the buyers’ preferences. The firm designs a menu of quality-price bundles and adjusts them using only local information about the buyers’ preferences. The learning methods define different paths, and we compare how much profit the firm makes on these paths, how long it takes to learn the optimal tariff, and how the buyers’ utilities change during the learning period. We also present a way to compute the optimal path in terms of discounted profit with dynamic programming and complete information. Numerical examples show that the optimal path may involve jumps where the buyer types switch from one bundle to another, and this is a property which is difficult to include in the learning methods. The learning methods have, however, the benefit that they can be generalized to pricing problems with many buyers types and qualities.     

An equivalent subproblem relaxation for improving the solution of a class of transportation scheduling problems

In this paper an algorithm is presented for determining the K best paths that may contain cycles in a directed network.The basic idea behind the algorithm is quite simple. Once the best path has been determined it is excluded from the network in such a way that no new path is formed and no more paths are excluded. This step leads to an enlarged network where all the paths, but the best one, can be determined. The method is repeated until the desired paths have been computed.The proposed algorithm can be used not only for the classical K shortest paths problem but also for ranking paths under a nonlinear objective function, provided that an algorithm to determine the best path exists.Computational results are presented and comparisons with other approaches for the classical problem are made.     

Another explanation for the bias observed in the filter rule test

Substantial bias in profits is observed when we apply Alexander's filter rule to the piecewise linear function formed by the linear interpolation of a past daily (weekly or monthly) stock price sequence. The only explanation for this phenomenon reported up to now is the possible discontinuity of the original price path. This paper demonstrates that the autocorrelation generated by the linear interpolation procedure causes this phenomenon even if the original path is a realization of the Brownian motion. It is also shown that the bias for the TOPIX index in the Tokyo Stock Exchange is substantially explained in our theoretical framework.     

On the Chromaticity of Multi-Bridge Hypergraphs

A multi-bridge hypergraph is an h-uniform linear hypergraph consisting of some linear paths having common extremities. In this paper it is proved that the multisets of path lengths of two chromatically equivalent multi-bridge hypergraphs are equal provided the multiplicities of path lengths are bounded above by 2 ^h-1 − 2. Also, it is shown that h-uniform linear cycles of length m are not chromatically unique for every m, h ≥ 3.     

Computational experiments with a lazy version of a <Emphasis Type="Italic">K</Emphasis> quickest simple path ranking algorithm

The quickest path problem is related to the classical shortest path problem, but its objective function concerns the transmission time of a given amount of data throughout a path, which involves both cost and capacity. The K-quickest simple paths problem generalises the latter, by looking for a given number K of simple paths in non-decreasing order of transmission time. Two categories of algorithms are known for ranking simple paths according to the transmission time. One is the adaptation of deviation algorithms for ranking shortest simple paths (Pascoal et al. in Comput. Oper. Res. 32(3):509–520, 2005; Rosen et al. in Comput. Oper. Res. 18(6):571–584, 1991), and another is based on ranking shortest simple paths in a sequence of networks with fixed capacity lower bounds (Chen in Inf. Process. Lett. 50:89–92, 1994), and afterwards selecting the K quickest ones. After reviewing the quickest path and the K-quickest simple paths problems we describe a recent algorithm for ranking quickest simple paths (Pascoal et al. in Ann. Oper. Res. 147(1):5–21, 2006). This is a lazy version of Chen’s algorithm, able to interchange the calculation of new simple paths and the output of each k-quickest simple path. Finally, the described algorithm is computationally compared to its former version, as well as to deviation algorithms.      

Gaussian quasimartingales

Summary Necessary and sufficient conditions in terms of the mean function and covariance are obtained for a separable Gaussian process to have paths of bounded variation, absolutely continuous or continuous singular. If almost all paths are of bounded variation, the L ² expansion of the Gaussian process is shown to converge in the total variation norm. One then obtains a decomposition of the paths of a Gaussian quasimartingale into a martingale and a predictable process of bounded variation paths such that these components are jointly Gaussian; the martingale component is decomposed into two processes, one consisting of (fixed) jumps and the other a continuous path martingale, and the bounded variation component is decomposed into three processes, one consisting of (fixed) jumps, another with absolutely continuous paths and the third with continuous singular paths. All components are jointly Gaussian. Uniqueness of the decompositions is also established.This work was partially supported by the National Science Foundation.     

Statistical cluster points and turnpike *

In this paper we study an asymptotic behaviour of optimal paths of a difference inclusion. The turnpike property in some wording [5,8, and so on] provided that there is a certain stationary point and optimal paths converge to that point. In this case only a finite number terms of the path (sequence) remain on the outside of every neighbourhood of that point

In the present paper a statistical cluster point introduced in [1] instead of the usual concept of limit point is considered and tue turnpiKe tueorem is proved, Mere it is es-ablished that there exists a stationary point which is a statistical cluster point for the all optimal paths. In this case not only a finite number but also infinite number terms of the path may remain on the outside of every small neighbourhood of the stationary point, but the number of these terms in comparison with the number of terms in the neighbourhood is so small that we can say:the path “almost” remains in this neighbourhood

Note that the main results are obtained under certain assumptions which are essentially weaker than the usual convexity assumption. These assumptions first were introduced for continuous systems in [6]     

Numerical Schemes for Rough Parabolic Equations

This paper is devoted to the study of numerical approximation schemes for a class of parabolic equations on (0,1) perturbed by a non-linear rough signal. It is the continuation of Deya (Electron. J. Probab. 16:1489–1518, 2011) and Deya et al. (Probab. Theory Relat. Fields, to appear), where the existence and uniqueness of a solution has been established. The approach combines rough paths methods with standard considerations on discretizing stochastic PDEs. The results apply to a geometric 2-rough path, which covers the case of the multidimensional fractional Brownian motion with Hurst index H>1/3.     

Optimal Synthesis of the Asymmetric Sinistral/Dextral Markov–Dubins Problem

We consider a variation of the classical Markov–Dubins problem dealing with curvature-constrained, shortest paths in the plane with prescribed initial and terminal positions and tangents, when the lower and upper bounds of the curvature of the path are not necessarily equal. The motivation for this problem stems from vehicle navigation applications, when a vehicle may be biased in taking turns at a particular direction due to hardware failures or environmental conditions. After formulating the shortest path problem as a minimum-time problem, a family of extremals, which is sufficient for optimality, is characterized, and subsequently the complete analytic solution of the optimal synthesis problem is presented. In addition, the synthesis problem, when the terminal tangent is free, is also considered, leading to the characterization of the set of points that can be reached in the plane by curves satisfying asymmetric curvature constraints.     

Underlying paths in interior point methods for the monotone semidefinite linear complementarity problem

An interior point method defines a search direction at each interior point of the feasible region. The search directions at all interior points together form a direction field, which gives rise to a system of ordinary differential equations (ODEs). Given an initial point in the interior of the feasible region, the unique solution of the ODE system is a curve passing through the point, with tangents parallel to the search directions along the curve. We call such curves off-central paths. We study off-central paths for the monotone semidefinite linear complementarity problem (SDLCP). We show that each off-central path is a well-defined analytic curve with parameter μ ranging over (0, ∞) and any accumulation point of the off-central path is a solution to SDLCP. Through a simple example we show that the off-central paths are not analytic as a function of and have first derivatives which are unbounded as a function of μ at μ = 0 in general. On the other hand, for the same example, we can find a subset of off-central paths which are analytic at μ = 0. These “nice” paths are characterized by some algebraic equations. This research was done during the author’s PhD study at the Department of Mathematics, NUS and as a Research Engineer at the NUS Business School.     

A continuous theory of traffic congestion and Wardrop equilibria

In the classical Monge-Kantorovich problem, the transportation cost only depends on the amount of mass sent from sources to destinations and not on the paths followed by each particle forming this mass. Thus, it does not allow for congestion effects, which depend instead on the proportion of mass passing through a same point or following a same path, Usually, the traveling cost (or time) of a path depends on “how crowded” this path is. Starting from a simple network model, we will define equilibria in the presence of congestion. We will then extend this theory to the continuous setting mainly following the recent papers by Brasco, Carlier, and Santambrogio and Carlier, Jimenez, and Santambrogio. After an introduction with almost no mathematical details, we will give a survey of the main features of this theory, Bibliography: 22 titles.     

On Partitioning the Edge Set of a Graph into Internally Disjoint Paths without Exterior Vertices

A collection of nontrivial paths in a graph G is called a path pile of G, if every edge of G is on exactly one path and no two paths have a common internal vertex. The least number that can be the cardinality of a path pile of G is called the path piling number of G. It can be shown that ε ≤ ν + η where ε, ν and η are respectively the size, the order and the path piling number of G. In this note we characterize structurally the class of all graphs for which the equality of this relation holds.     

From Constructive Field Theory to Fractional Stochastic Calculus. (I) An introduction: Rough Path Theory and Perturbative Heuristics

Let B = (B ₁(t), . . . , B _d (t)) be a d-dimensional fractional Brownian motion with Hurst index α ≤ 1/4, or more generally a Gaussian process whose paths have the same local regularity. Defining properly iterated integrals of B is a difficult task because of the low H?lder regularity index of its paths. Yet rough path theory shows it is the key to the construction of a stochastic calculus with respect to B, or to solving differential equations driven by B. We intend to show in a forthcoming series of papers how to desingularize iterated integrals by a weak singular non-Gaussian perturbation of the Gaussian measure defined by a limit in law procedure. Convergence is proved by using “standard” tools of constructive field theory, in particular cluster expansions and renormalization. These powerful tools allow optimal estimates of the moments and call for an extension of the Gaussian tools such as for instance the Malliavin calculus. This first paper aims to be both a presentation of the basics of rough path theory to physicists, and of perturbative field theory to probabilists; it is only heuristic, in particular because the desingularization of iterated integrals is really a non-perturbative effect. It is also meant to be a general motivating introduction to the subject, with some insights into quantum field theory and stochastic calculus. The interested reader should read for a second time the companion article (Magnen and Unterberger in From constructive theory to fractional stochastic calculus. (II) The rough path for \frac16 < a < \frac14{\frac{1}{6} < \alpha < \frac{1}{4}}: constructive proof of convergence, 2011, preprint) for the constructive proofs.     

On the Analyticity of Underlying HKM Paths for Monotone Semidefinite Linear Complementarity Problems

An interior point method (IPM) defines a search direction at an interior point of the feasible region. These search directions form a direction field, which in turn defines a system of ordinary differential equations (ODEs). The solutions of the system of ODEs are called off-central paths, underlying paths lying in the interior of the feasible region. It is known that not all off-central paths are analytic, whether w.r.t. μ or , where μ represents the duality gap, at a solution of a given semidefinite linear complementarity problem, SDLCP (Sim and Zhao, Math. Program. 110:475–499, 2007). In Sim and Zhao (J. Optim. Theory Appl. 137:11–25, 2008), we give a necessary and sufficient condition for when an off-central path is analytic as a function of at a solution of a general SDLCP. It is then natural to ask about the analyticity of a SDLCP off-central path at a solution, as a function of μ. We investigate this in the current paper. Again, we work under the assumption that the given SDLCP satisfies strict complementarity condition.     

Hybrid co-evolutionary particle swarm optimization and noising metaheuristics for the delay constrained least cost path problem

This paper presents a co-evolutionary particle swarm optimization (PSO) algorithm, hybridized with noising metaheuristics, for solving the delay constrained least cost (DCLC) path problem, i.e., shortest-path problem with a delay constraint on the total “cost” of the optimal path. The proposed algorithm uses the principle of Lagrange relaxation based aggregated cost. It essentially consists of two concurrent PSOs for solving the resulting minimization-maximization problem. The main PSO is designed as a hybrid PSO-noising metaheuristics algorithm for efficient global search to solve the minimization part of the DCLC-Lagrangian relaxation by finding multiple shortest paths between a source-destination pair. The auxiliary/second PSO is a co-evolutionary PSO to obtain the optimal Lagrangian multiplier for solving the maximization part of the Lagrangian relaxation problem. For the main PSO, a novel heuristics-based path encoding/decoding scheme has been devised for representation of network paths as particles. The simulation results on several networks with random topologies illustrate the efficiency of the proposed hybrid algorithm for the constrained shortest path computation problems.