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## Statistical uncertainty of minimum spanning tree in market network

P. 157-163.

Koldanov P., Комиссарова А. Э.

The paper deal with uncertainty in market network analysis. The main problem addressed is to investigate statistical uncertainty of Kruskal algorithm for the minimum spanning tree in market network. Uncertainty of Kruskal algorithm is measured by the probability of q incorrectly included edges. Numerical experiments are conducted with the returns of a set of 100 financial instruments traded in the US stock market over a period of 250 days in 2014. Obtained results help to estimate the reliability of minimum spanning tree in market network analysis.

Kalyagin V. A., Koldanov A. P., Koldanov P., Journal of Statistical Planning and Inference 2017 Vol. 181 No. Feb P. 30-40

A class of distribution free multiple decision statistical procedures is proposed for threshold graph identification in correlation networks. The decision procedures are based on simultaneous application of sign statistics. It is proved that single step, step down Holm and step up Hochberg statistical procedures for threshold graph identification are distribution free in sign similarity network in ...

Added: December 14, 2015

Kalyagin V. A., Koldanov A. P., Koldanov P. et al., Springer, 2020

This book studies complex systems with elements represented by random variables. Its main goal is to study and compare uncertainty of algorithms of network structure identification with applications to market network analysis. For this, a mathematical model of random variable network is introduced, uncertainty of identification procedure is defined through a risk function, random variables ...

Added: September 10, 2020

Koldanov P., Kalyagin V. A., Bautin G. A., Annals of Mathematics and Artificial Intelligence 2016 Vol. 76 No. 1 P. 47-57

The problem of stock selection is disscused from different points of view. Three different sequentially rejective statistical procedures for stock selection are described and compared: Holm multiple test procedure, maximin multiple test procedure and multiple decision procedure. Properties of statistical procedures are studied for different loss functions. It is shown that conditional risk for additive loss ...

Added: February 3, 2015

Koldanov P., Advances in Computer Science Research 2019 P. 50-55

The concept of random variables network used to model the complex system of random nature is discussed. The problem of threshold graph identication to network analysis of the complex system is considered as multiple decision statistical procedure. The properties of robustness of dierent tests for testing individual hypotheses for threshold graph identication are investigated by ...

Added: December 7, 2019

Koldanov P., Kalyagin V. A., Koldanov A. P. et al., , in: Optimization oi Science and Engineering (In Honor of the 60th Birthday of Panos M. Pardalos). .: NY: Springer, 2014.. Ch. 15. P. 301-313.

Market graph is known to be a useful tool for market network analysis. Cliques and independent sets of the market graph give an information about con- centrated dependent sets of stocks and distributed independent sets of stocks on the market. In the present paper the connections between market graph and classical Markowitz portfolio theory are ...

Added: October 3, 2014

Kalyagin V. A., Pardalos P. M., Rassias T. undefined., Springer, 2014

Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, ...

Added: July 15, 2014

[б.и.], 2014

Full texts of third international conference on data analytics are presented. ...

Added: October 13, 2014

Kalyagin V. A., Koldanov A. P., Pardalos P., Annals of Mathematics and Artificial Intelligence 2016 Vol. 76 No. 1 P. 83-92

The main goal of the present paper is the development of a general framework of multivariate network analysis of statistical data sets. A general method of multivariate network construction, on the basis of measures of association, is proposed. In this paper we consider Pearson correlation network, sign similarity network, Fechner correlation network, Kruskal correlation network, ...

Added: September 7, 2015

Semenov D., Koldanov P., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics. Vol. 247.: Springer, 2018.. P. 221-234.

Market network analysis attracts a growing attention last decade. Important component of the market network is a model of stock returns distribution. Elliptically contoured distributions are popular as probability model of stock returns. The question of adequacy of this model to real market data is open. There are known results that reject such model and ...

Added: September 24, 2018

Kalyagin V. A., Koldanov P., Zamaraev V. A., Springer Optimization and Its Applications 2014 Vol. 100 P. 181-197

Network model of stock market based on correlation matrix is considered. In the model vector of stock returns is supposed to hve multivariate normal distribution with given correlation matrix. Statistical uncertainty of some popular market network structures is analyzed by numerical simulation for network models of stock makets for different countries. For each market statistical ...

Added: October 13, 2014

Koldanov A. P., Koldanov P., Бизнес-информатика 2012 № 1(19) С. 24-31

Problem of multiple comparisons of several populations on small samples and specificity of the method of it solution are analyzed. It is proposed to extend a classical method for constructing statistical tests by the use of information preprocessing. Examples of the application of the proposed method are given. ...

Added: August 27, 2012

Koldanov A. P., Kalyagin V. A., Pardalos P. M., Lecture Notes in Computer Science 2015 Vol. 9432 P. 26-36

Stock selection by Sharp ratio is considered in the framework of multiple statistical hypotheses testing theory. The main attention is paid to comparison of Holm stepdown and Hochberg step up procedures for different loss functions. Comparison is made on the basis of condittional risk as a function of selection threshold. This approach allows to discover ...

Added: December 13, 2015

Semenov D., Koldanov A. P., Koldanov P. et al., IMA Journal Management Mathematics 2022 Vol. 33 No. 1 P. 123-137

Two market network models are investigated. One of them is based on the classical Pearson correlation
as the measure of association between stocks returns, whereas the second one is based on the
sign similarity measure of association between stocks returns. We study the uncertainty of
identification procedures for the following market network characteristics: distribution of weights
of edges, vertex ...

Added: December 7, 2020

Koldanov A. P., Koldanov P., Springer Optimization and Its Applications 2014 Vol. 87 P. 205-216

Problem of construction of the market graph as a multiple decision statistical problem is considered. Detailed description of a optimal unbiased multiple decision statistical procedure is given. This procedure is constructed using the Lehmann’s theory of multiple decision statistical procedures and the conditional tests of the Neyman structures. The equations for thresholds calculation for the ...

Added: September 13, 2013

Bautin G. A., Koldanov A. P., Pardalos P. M., Springer Optimization and Its Applications 2014 Vol. 100 P. 25-33

Financial market can be modeled as network represented by a complete weighted graph. Differet characteristics of this graph (minimum spanning tree, market graph ad others) give an impotant information on the network. In the pesent paper it is studied how the choice of measure of similarity between stocks influences the statistical errors in the calculation ...

Added: October 13, 2014

Kalyagin V. A., Koldanov A. P., Koldanov P. et al., Annals of Operations Research 2018 Vol. 266 No. 1-2 P. 313-327

Research into the market graph is attracting increasing attention in stock market analysis. One of the important problems connected with the market graph is its identification from observations. The standard way of identifying the market graph is to use a simple procedure based on statistical estimations of Pearson correlations between pairs of stocks. Recently a ...

Added: May 17, 2017

Kalyagin V. A., Koldanov A. P., Pardalos P. M., , in: Learning and Intelligent Optimization.. Vol. 8426: Lectute Notes in Computer Science.: Switzerland: Springer, 2014.. P. 88-97.

The main goal of the present paper is the development of general approach to network analysis of statistical data sets. First a general method of market network construction is proposed on the base of idea of measures of association. It is noted that many existing network models can be obtained as a particular case of ...

Added: August 13, 2014

Kazakov M., Kalyagin V. A., , in: Models, Algorithms and Technologies for Network Analysis, Springer Proceedings in Mathematics & Statistics. Vol. 156.: Switzerland: Springer, 2016.. P. 135-156.

Random matrix theory (RMT) is applied to investigate the cross-correlation matrix of a financial time series in four different stock markets: Russian, American, German, and Chinese. The deviations of distribution of eigenvalues of market correlation matrix from RMT global regime are investigated. Specific properties of each market are observed and discussed. ...

Added: October 14, 2018