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Information Spillover Effect and Autoregressive Conditional Duration Models: Routledge Advances in Risk Management

Autor Xiangli Liu, Yanhui Liu, Yongmiao Hong, Shouyang Wang
en Limba Engleză Paperback – 28 iun 2018
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. It explores this new method by testing the information spillover between the Chinese stock market and the international market, futures market and spot market. Using the high frequency data, this book investigates the intraday effect and examines which type of ACD model is particularly suited in capturing financial duration dynamics.
The book will be of invaluable use to scholars and graduate students interested in co-movements among different financial markets and financial market microstructure and to investors and regulation departments looking to improve their risk management.
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Specificații

ISBN-13: 9781138316874
ISBN-10: 1138316873
Pagini: 210
Ilustrații: 52
Dimensiuni: 156 x 234 x 25 mm
Greutate: 0.42 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Seria Routledge Advances in Risk Management

Locul publicării:Oxford, United Kingdom

Public țintă

Postgraduate and Undergraduate

Cuprins

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

Descriere

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.