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COMMON PART

Project Number20-18-00365

Project titleRobust methods and models for resilient markets and efficient production lines

Project LeadGadasina Lyudmila

AffiliationFederal State Budgetary Educational Institution of Higher Education "Saint-Petersburg State University",

PROJECT EXTENSION CARD

Research area 08 - HUMANITIES AND SOCIAL SCIENCES, 08-154 - Finance, credit, money circulation, market infrastructure

KeywordsFinancial and economic markets; insurance markets; robust statistical and econometric inference; dependent and heterogeneous data; heavy-tailed distributions; copula dependence models; econometric and mathematical modeling in finance, economics and actuarial science; multivariate statistical methods for economic analysis; stochastic frontier models; nonparametric estimators of production function; endogenous factors of production; stochastic frontier models with environmental factors

PROJECT CONTENT

Annotation
Fundamentally this project targets the development and application of mathematical methods suitable for modelling complex financial markets and production processes, affected by a large number of dependent and extreme random shocks. Examples of such markets and processes include the market for financial derivatives, including mortgage-backed, actuarial markets including reinsurance, and a large class of production processes where technical efficiency is determined by the so called environmental variables, e.g. in agriculture and oil/gas production. The data available to modern markets and firms -- financial, economic, actuarial -- exhibit highly complex dependence patterns, including extreme dependence at times of stress. This proposal presents novel, robust and reliable alternatives to the existing models and methods to analyse such data, expanding the knowledge base in the field of econometrics and, more generally, in the field of statistical inference as it applies to modern business and economic data. Importantly, the project will relax the unrealistic assumptions made in the traditional models of production and market behavior. The proposed research program is situated in the intersection of at least four disciplines: economics, finance and actuarial science, mathematics, and statistics. As an outcome, the project will produce a system of econometric models and estimation methods, accompanied by a freely available toolbox of prototype software. A related task is to create a world-class research laboratory in theoretical and applied econometrics at St.Petersburg State University. The most profound impact will likely take place in the field of econometrics, that is in the intersection of economics and mathematics, where the proposed research will generate a new generation of models and methods that reflect the realities of today's manufacturing and the sophistication of today's financial and actuarial products. To this end, the project will establish a productive international research network consisting of leading scientists who will consistently produce world-class research in the field of statistical and mathematical analysis and modeling of market's and firm's dynamic using a wide range of available statistical resources, including massive data sets. In this way, the proposal will meet the objectives of the Russian Science Foundation by enhancing international collaboration and expanding Russia's research capability.

Expected results
A key scientific outcome of this research project will be a series of papers published in leading Scopus-cited journals in the field, targeting those journals that have a 5-year impact factor of 2 and above, such as Journal of Econometrics. One practical benefit of this work for the Russian economy is that the novel methods will be used to achieve a better understanding and a smoother operation of Russian economic and financial markets, a higher productivity of Russian firms and industries. Unanticipated extreme movements in economic and financial markets have profound detrimental effects on real economy. The increased uncertainty usually slows down growth and reduces productivity. Similar effects follow when production decisions do not account for important dependencies of productivity on other factors than inputs. The new robust models and estimation methods this proposal develops provide means by which market participants can better assess such risks and minimize their effects. Correspondingly, the project will inform Russia's policy by building capacity in the analysis, management and prevention of extreme market behavior, ensuring smooth economic development, crucial for the long term prosperity of the Russian economy. The methodology developed in the project will have direct implications for statistical inference by providing robust and reliable alternatives to the existing methods. One of the main planned outcomes of the study is to provide a toolbox of statistical methodologies to be used in many areas of knowledge, beyond economics, finance and insurance. An appealing property of some of the inference procedures to be developed, especially in robust copula inference, is that they are easily accessible, among others, to graduate and undergraduate students and practitioners. It is planned that some of the results of the study will be included in the courses the research team members are currently teaching at respective universities. In addition, the project will involve collaborations with Ph.D. students, and open problems related to the project will be suggested to them as possible thesis topics. The research network of mid-career researchers that will emerge as a result of this research project will provide spill-over effects outside the outlined proposal and will have long term benefits. Overall, the project will encourage research and research training in a high-quality research environment and enhance international collaboration in research.

REPORTS