Computational study of the US stock market evolution: a rank correlation-based network model

Shirokikh, Oleg; Pastukhov, Grigory; Boginski, Vladimir; Butenko, Sergiy

doi:10.1007/s10287-012-0160-4

Cited by 33 publications

(22 citation statements)

References 19 publications

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“…In [1], Shirokikh, Pastukhov et al make use of graph theory and statistics to compute the relationship between stocks. The Spearman Rank correlation coefficient, denoted ρ, is defined in the following way:…”

Section: Methods From the Papermentioning

confidence: 99%

“…Correlations take on any value in the interval [−1, 1], where a correlation of 1 is a direct correlation, a correlation of −1 is an inverse correlation, and a correlation of 0 represents no correlation. The authors of [1] recorded the correlations between every pair of stocks in a weighted adjacency matrix.…”

Section: Methods From the Papermentioning

confidence: 99%

“…While we should note that the authors of [1] used an undirected graph, they were still able to obtain a set of stocks with the highest correlations. However, these have no relation to sectors.…”

Section: Methods From the Papermentioning

confidence: 99%

“…We remedy this problem by proposing a novel approach to modeling correlation between equities. While this field uses varying degrees of statistics, [1] took a more visual approach with graph theory. This methodology provides a more global view of how the different sectors of the market are interacting, improving the accuracy of short term analysis.…”

Section: Methods From the Papermentioning

confidence: 99%

“…We explore the most efficient ways to maximize the possible return on equities while at the same time reducing exposure to the inherit volatility of the market. The work by Shirokikh, Pastukhov et al, which uses the techniques of graph theory and employs autoregressive models to accomplish this goal is the starting point of this study [1].…”

Section: Introductionmentioning

confidence: 99%

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Section: Methods From the Papermentioning

confidence: 99%

Section: Methods From the Papermentioning

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Section: Methods From the Papermentioning

confidence: 99%

Section: Methods From the Papermentioning

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Section: Introductionmentioning

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Networks in economics and finance in Networks and beyond: A half century retrospective

Nagurney

2019

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This paper presents a panoramic view of research on economic and financial networks in the journal Networks, since its inception half a century ago. This paper focuses on both the breadth and depth of the journal articles, and within the context of earlier contributions, as well as more recent related ones in other scientific publications. From network optimization to game theory and a plethora of equilibrium concepts, along with novel dynamical systems frameworks, the journal has led the way in advancing economic and financial network models, algorithms, and applications. Moreover, Networks has helped to attract researchers in a variety of disciplines to the science of networks and the formulation and solution of associated problems drawn from the real world. KEYWORDS economic networks, financial equilibrium, financial networks, game theory, projected dynamical systems, spatial price equilibrium, variational inequalities 1 INTRODUCTION Networks, from transportation and logistical ones, to communications and energy, have provided the foundation and connectivity for the flow of people, and the exchange of goods, information, and services across space and time. Intimately related to such physical networks, in which the identification of nodes, links, and associated flows with physical entities is well-understood, are economic and financial networks. The importance of all such network systems to the functioning of our societies and economies, coupled with the need to understand their interrelationships, has spurred numerous advances in methodologies for their modeling, analysis, and solution, under different behavioral concepts associated with usage and management. The origins of network theory can be traced back to the 1700s, to the classical paper of Euler [64], the earliest paper on graph theory. By a graph in this context is meant, mathematically, a means of abstractly representing a system by its representation in terms of vertices (or nodes) and edges (arcs or, equivalently, links) joining pairs of vertices. Euler sought to determine whether it was possible to walk around Königsberg (later renamed Kaliningrad) by crossing the seven bridges over the River Pregel exactly once. The problem was depicted as a graph with the vertices representing land masses and the edges-bridges. Interestingly, one of the first network models was for a financial system. Specifically, Quesnay [188], in his Tableau Economique, conceptualized the circular flow of financial funds in an economy as a network. His fundamental idea has been utilized in the construction of financial flow of funds accounts, which provide a statistical description of the flows of money and credit in an economy [37]. This work also inspired the first paper on financial networks in Networks, by Nagurney and Hughes [144]. The network model, with an accompanying decomposition algorithm, can be applied to calculate reconciled values of outstanding financial instruments, tangible assets, and net worth. The reconciled dataset can then be utilized as a base line for ...

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Market Graph and Markowitz Model

Kalyagin

Koldanov

et al. 2014

Optimization in Science and Engineering

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Computational study of the US stock market evolution: a rank correlation-based network model

Cited by 33 publications

References 19 publications

Analysis of Equity Markets: A Graph Theory Approach

Analysis of Equity Markets: A Graph Theory Approach

Networks in economics and finance in Networks and beyond: A half century retrospective

Market Graph and Markowitz Model

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