Heavy-Tailedness, Dependence and Robustness in Economics, Finance and Econometrics

From whom?

Rustam Ibragimov (Professor of Finance and Econometrics, Imperial College Business School)

Course language

English

Course Description

The seminar will discuss modern approaches to modeling and the analysis of the effects of heavy-tailedness, heterogeneity, dependence and contagion on the properties of key economic, financial and econometric models. We will also discuss modern approaches to statistical and econometric analysis of the above properties of economic and financial markets, including the degree of heavy-tailedness, probability of crises and structures of dependence. The talks at the seminar will further discuss modern methods of robust statistical and econometric analysis of economic and financial models (e.g., predictive regressions for financial returns and foreign exchange rates) that can be used under the problems of heterogeneity, heavy-tailedness, autocorrelation and dependence observed in the dynamics of key indicators of different economies, including those of the countries of the former USSR.

Date: 6 - 7, 9 January, 2023

Schedule

Day 1 (6.01, 12.00 Moscow Time) Introduction. The key statistical properties and stylized facts of financial markets: Crises, heavy-tailed distributions, nonlinear dependence and volatility clustering. The effects of heavy-tailedness and dependence on the properties of economic and financial models and widely used statistical and econometric methods. Modern approaches to modelling and statistical and econometric analysis of heavy-tailedness properties of economic and financial markets. Empirical applications. Probability of crises and heavy-tailedness in economies of the World, including emerging markets and economies of the countries of the former USSR.

Day 2 (7.01, 10.00 Moscow Time) Robust statistical and econometric analysis under the problems of heterogenity, autocorelation and dependence. Consistent standard errors under heterogeneity and autocorrelation (Heteroskedasticity and autocorrelation consistent - HAC - standard errors) and HAC econometric and statistical methods. New and improved approaches to robust econometric and statistical analysis using t-statistics in group estimates of model parameters. Applications: Robust econometric and statistical analysis of income inequality and predictive regressions; empirical analysis of the effects of the COVID-19 pandemics on the World's financial markets.

Day 3 (9.01, 13.30 Moscow Time) New and improved approaches to modelling and inference on key statistical properties of financial markets and their indicators, including nonlinear dependence, volatility clustering, heavy-tailedness and financial contagion. Modern approaches to modelling financial contagion and interdependence of financial markets. Copula models and statistical and econometric analysis of copula dependence structures. Open research problems. Conclusion.

Course materials:

Seminar 2 - video