Financial econometrics and empirical market microstructure
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書誌事項
Financial econometrics and empirical market microstructure
Springer, c2015
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注記
Includes bibliographical references
内容説明・目次
内容説明
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.
目次
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.
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