Financial Econometrics and Empirical Market Microstructure

1. Front Matter

   Pages i-viii

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2. Mathematical Models of Price Impact and Optimal Portfolio Management in Illiquid Markets

   • Nikolay Andreev

   Pages 1-11

3. Evidence of Microstructure Variables’ Nonlinear Dynamics from Noised High-Frequency Data

   • Nikolay Andreev, Victor Lapshin

   Pages 13-23

4. Revisiting of Empirical Zero Intelligence Models

   • Vyacheslav Arbuzov

   Pages 25-36

5. Construction and Backtesting of a Multi-Factor Stress-Scenario for the Stock Market

   • Kirill Boldyrev, Dmitry Andrianov, Sergey Ivliev

   Pages 37-45

6. Modeling Financial Market Using Percolation Theory

   • Anastasiya Byachkova, Artem Simonov

   Pages 47-53

7. How Tick Size Affects the High Frequency Scaling of Stock Return Distributions

   • Gianbiagio Curato, Fabrizio Lillo

   Pages 55-76

8. Market Shocks: Review of Studies

   • Mariya Frolova

   Pages 77-92

9. The Synergy of Rating Agencies’ Efforts: Russian Experience

   • Alexander Karminsky

   Pages 93-109

10. Spread Modelling Under Asymmetric Information

    • Sergey Kazachenko

    Pages 111-129

11. On the Modeling of Financial Time Series

    • Aleksey Kutergin, Vladimir Filimonov

    Pages 131-151

12. Adaptive Stress Testing: Amplifying Network Intelligence by Integrating Outlier Information (Draft 16)

    • Alan Laubsch

    Pages 153-193

13. On Some Approaches to Managing Market Risk Using VaR Limits: A Note

    • Alexey Lobanov

    Pages 195-206

14. Simulating the Synchronizing Behavior of High-Frequency Trading in Multiple Markets

    • Benjamin Myers, Austin Gerig

    Pages 207-213

15. Raising Issues About Impact of High Frequency Trading on Market Liquidity

    • Vladimir Naumenko

    Pages 215-223

16. Application of Copula Models for Modeling One-Dimensional Time Series

    • Vadim Onishchenko, Henry Penikas

    Pages 225-239

17. Modeling Demand for Mortgage Loans Using Loan-Level Data

    • Evgeniy Ozhegov

    Pages 241-248

18. Sample Selection Bias in Mortgage Market Credit Risk Modeling

    • Agatha Lozinskaia

    Pages 249-262

19. Global Risk Factor Theory and Risk Scenario Generation Based on the Rogov-Causality Test of Time Series Time-Warped Longest Common Subsequence

    • Mikhail Rogov

    Pages 263-278

20. Stress-Testing Model for Corporate Borrower Portfolios

    • Vladimir Seleznev, Denis Surzhko, Nikolay Khovanskiy

    Pages 279-284

In the era of Big Data our society is given the unique opportunity to understand the inner dynamics and behavior of complex socio-economic systems. Advances in the availability of very large databases, in capabilities for massive data mining, as well as progress in complex systems theory, multi-agent simulation and computational social science open the possibility of modeling phenomena never before successfully achieved. This contributed volume from the Perm Winter School address the problems of the mechanisms and statistics of the socio-economics system evolution with a focus on financial markets powered by the high-frequency data analysis.    ​

• Big data analytics
• Market microstructure
• Mortgage portfolios
• Perm winter school
• Risk management
• Stress testing
• quantitative finance

• Department of Economics, University of Illinois, Urbana, USA

  Anil K. Bera

• Perm State University, Perm, Russia

  Sergey Ivliev

• Scuola Normale Superiore, Pisa, Italy

  Fabrizio Lillo

Anil K. Bera, Ph.D., Professor of Economics at University of Illinois. Since 1989, Dr. Bera has been awarded eight degrees from Calcutta University, the Indian Statistical Institute, and the Australian National University for his excellence in teaching as well as professional and postgraduate training. He is the author of the popular Jarque–Bera goodness-of-fit test, as well as numerous publications in econometrics and economic statistics.

Sergey Ivliev, Ph.D. in economics, Associate Professor at Perm State University, Chief Research Officer at PROGNOZ, Member of Steering committee of PRMIA Russia. He is a Principal coordinator of Perm Winter School and editor of the Market Risk and Financial Markets Modeling book published by Springer.

Fabrizio Lillo, Professor of Quantitative Finance at the Scuola Normale Superiore di Pisa (Italy), Assistant Professor of Physics at Palermo University (Italy) and External Professor at the Santa Fe Institute (USA). He is author of more than 60 referred scientific papers. The ISI papers have received more than 800 citations and his h-index is 16. His research is focused on the application of methods and tools of statistical physics to economic, financial, and biological complex systems.

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