Assessing the financial instability of economic systems: A variety of methods and models

Малкина, Марина; Ovcharov, A. O.

doi:10.24891/ea.18.7.1273

Cited by 4 publications

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“…In modern conditions there are new tools of economic and mathematical modeling-data analysis and machine learning, allowing to solve such problems. The implementation of the principles of machine learning allows not only to build predictive models, but also to effectively adapt them to the rapidly changing conditions of the market environment (Malkina & Ovcharov, 2019).…”

Section: Problem Statementmentioning

confidence: 99%

Machine Learning Models For Predicting Bankruptcy Of Enterprises

Nikitina¹,

Opekunov²,

Kamardina³

2020

European Proceedings of Social and Behavioural Sciences

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Section: Problem Statementmentioning

confidence: 99%

Machine Learning Models For Predicting Bankruptcy Of Enterprises

Nikitina¹,

Opekunov²,

Kamardina³

2020

European Proceedings of Social and Behavioural Sciences

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Dynamic Model of Inter-Industry Balance, the Problem of Its Digitizing and Simulation of Structural Transient Processes

Natalia

Toroptsev

2022

Mathematics and Its Applications in New Computer Systems

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The problem of digitalization of the dynamic input-output model

Toroptsev

Marakhovskii

Duszynski

2020

EATP

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Subject. The article addresses the digitalization of the dynamic model of inter industry balance. Objectives. We focus on developing our own statistical research base for input-output analysis, structural forecasting, sustainability, economic dynamics and economic growth. Mathematically, the study is formalized by the Cauchy problem for ordinary differential equations. Methods. The methodology components include theoretical and practical bases of the systems, statistical, input-output, and structural dynamic analysis. Results. Based on official statistics, we solved the problem of digitalization of the dynamic model of input-output balance, written in the form of a system of differential equations. For the first time, this model was transferred from a set of purely theoretical structures to a class of computable models. We developed a sequence of coordinated actions and calculations, which serve as a methodology for the said transfer. We also devised and presented the elements of our own statistical research base. Conclusions. The quantitative measurement of the dynamic inter-industry model in the form of a system of differential equations opens up broad perspectives on the sustainability of macroeconomics, its structural readiness for expanded reproduction, i.e. economic growth. The model can be used both independently and in combination with equilibrium and other agent-oriented models.

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Assessing the financial instability of economic systems: A variety of methods and models

Cited by 4 publications

References 0 publications

Machine Learning Models For Predicting Bankruptcy Of Enterprises

Machine Learning Models For Predicting Bankruptcy Of Enterprises

Dynamic Model of Inter-Industry Balance, the Problem of Its Digitizing and Simulation of Structural Transient Processes

The problem of digitalization of the dynamic input-output model

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