Information Spillover Effect and Autoregressive Conditional Duration - Model

Informationen zum Autor Xiangli Liu received her PhD in Management Sciences and Engineering from the School of Management! Graduate University of the Chinese Academy of Sciences in 2008. She is currently Associate Professor of the School of Finance! Central University of Finance and Economics. She has published over 20 papers in domestic and international journals. Her research interests include econometrics! financial market microstructure and financial risk management.Yanhui Liu received her PhD in Management Sciences and Engineering from the Institute of Systems Science! Academy of Mathematics and Systems Science! Chinese Academy of Sciences in 2005.She has worked in theDevelopment Bank of Singapore since 2005. Now she is the Chief Executive. She has published several papers in domestic and international journals. Her research interests include econometrics! financial econometrics and financial instruments.Yongmiao Hong received his PhD in Economics! University of California! San Diego in 1993. He joined as Assistant Professor! Economics Department! at Cornell University in 1993! and became tenured Associate Professor in 1998 and tenured Full Professor in 2001. Now he serves as a tenured Professor of Economics and Statistics at Cornell University anda Cheung Kong Lecture Professor of Wang Yanan Institute for Studies in Economics (WISE) at Xiamen University. He has been selected as a member of the Thousand Talents Program to promote the recruitment of first-class international talents for the development of national key disciplines.His current research interests include econometrics! time series analysis and application! financial econometrics! Chinese economics and empirical research in financial markets in China.?Shouyang Wang received his PhD in Operations Research from theInstitute of Systems Science! Academy of Mathematics and Systems Science! Chinese Academy of Sciences in 1986. He is currently a Bairen distinguished Professor of Management Science at Academy of Mathematics and Systems Science! Chinese Academy of Sciences. He is also an adjunct professor of over 30 universities in the world. He is the editor-in-chief! an area editor or a co-editor of 12 journals. He has published 30 monographs and over 250 papers in leading journals. His current research interests include financial engineering! economic forecasting and financial risk management. Zusammenfassung This book studies the information spillover among financial markets and explores the intraday effect and ACD models with high frequency data. This book also contributes theoretically by providing a new statistical methodology with comparative advantages for analyzing co-movements between two time series. Inhaltsverzeichnis 1. Introduction 2. Methodology to Detect Extreme Risk Spillover 3. VaR Estimation 4. Extreme Risk Spillover Between Chinese Stock Markets and International Stock Markets 5. Information Spillover Effects Between Chinese Futures Market and Spot Market 6. How Well Can Autoregressive Duration Models Capture the Price Durations Dynamics of Foreign Exchanges 7. Intraday Effect 8. Conclusions and Perspective Studies ...

Product details

• Authors: Yongmiao Hong, Yongmiao (Cornell University Hong, Hong Yongmiao, Liu, Xiangli Liu, Xiangli (Central University of Finance and Ec Liu, Xiangli (Central University of Finance and Economics Liu, Xiangli Liu Liu, Yanhui Liu, Liu Xiangli, Liu Yanhui, Shouyang Wang, Shouyang (Chinese Academy of Sciences Wang, Wang Shouyang
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 30.06.2018
• EAN: 9781138316874
• ISBN: 978-1-138-31687-4
• No. of pages: 210
• Series: Routledge Advances in Risk Management
• Subjects: Social sciences, law, business > Business > General, dictionaries; Business & Economics / General, Asia, Banking, Regional Studies, business strategy, Regional / International studies, Investment & securities, Econometrics, Investment and securities, Econometrics and economic statistics