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Financial Econometrics and Empirical Market Microstructure

  • Book
  • © 2015

Overview

Editors:
  1. Anil K. Bera

    1. Department of Economics, University of Illinois, Urbana, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Sergey Ivliev

    1. Perm State University, Perm, Russia

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  3. Fabrizio Lillo

    1. Scuola Normale Superiore, Pisa, Italy

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  • Provides recent advances in financial market microstructure modeling
  • Reviews methodology for mortgage portfolio econometrics
  • Introduces novel approaches for stress-testing

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Table of contents (19 chapters)

  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
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Keywords

About this book

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.    ​

Editors and Affiliations

  • 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

About the editors

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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