Financial econometrics and empirical market microstructure
Author(s)
Bibliographic Information
Financial econometrics and empirical market microstructure
Springer, c2015
Available at 10 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references
Description and Table of Contents
Description
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.
Table of Contents
Mathematical Models of Price Impact and Optimal Portfolio Management in Illiquid Markets.- Evidence of Microstructure Variables' Nonlinear Dynamics from Noised High-Frequency Data.- Revisiting of Empirical Zero Intelligence Models.- Construction and Backtesting of a Multi-Factor Stress-Scenario for the Stock Market.- Modeling Financial Market Using Percolation Theory.- How Tick Size Affects the High Frequency Scaling of Stock Return Distributions.- Market Shocks: Review of Studies.- The Synergy of Rating Agencies' Efforts: Russian Experience.- Spread Modelling Under Asymmetric Information.- On the Modeling of Financial Time Series.- Adaptive Stress Testing: Amplifying Network Intelligence by Integrating Outlier Information.- On Some Approaches to Managing Market Risk Using Var Limits: A Note.- Simulating the Synchronizing Behavior of High-Frequency Trading in Multiple Markets.- Raising Issues About Impact of High Frequency Trading on Market Liquidity.- Application of Copula Models for Modeling One-Dimensional Time Series.- Modeling Demand for Mortgage Loans Using Loan-Level Data.- Sample Selection Bias in Mortgage Market Credit Risk Modeling.- Global Risk Factor Theory and Risk Scenario Generation Based on the Rogov-Causality Test of Time Series Time-Warped Longest Common Subsequence.- Stress-Testing Model for Corporate Borrower Portfolios.
by "Nielsen BookData"