Financial Econometrics and Empirical Market Microstructure /
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-agen...
Salvato in:
| Ente Autore: | |
|---|---|
| Altri autori: | , , |
| Natura: | eBook |
| Lingua: | English |
| Pubblicazione: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
|
| Soggetti: | |
| Accesso online: | Click here to view the full text content |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne! !
|
Sommario:
- 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.