Information Spillover Effect and Autoregressive Conditional Duration Models
Information Spillover Effect and Autoregressive Conditional Duration Models

Author: Xiangli Liu

Publisher: Routledge

Published: 2014-07-11

Total Pages: 216

ISBN-13: 1317667654

DOWNLOAD EBOOK

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 comovements 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 comovements among different financial markets and financial market microstructure and to investors and regulation departments looking to improve their risk management.

The Lognormal Autoregressive Conditional Duration (LNACD) Model and a Comparison with an Alternative ACD Models
The Lognormal Autoregressive Conditional Duration (LNACD) Model and a Comparison with an Alternative ACD Models

Author: Yongdeng Xu

Publisher:

Published: 2014

Total Pages: 28

ISBN-13:

DOWNLOAD EBOOK

Engle and Russell (1998) introduce the autoregressive conditional duration (ACD) model to model the dynamics of financial duration. It is recognized that the ACD model can be specified in ARMA form. We show that as long as the innovations of the ACD model follows a lognormal distribution, the equivalent ARMA model will be Gaussian distributed. Motivated by this fact, we develop a lognormal autoregressive conditional duration (LNACD) model. The LNACD model permits a humped-shaped hazard function with one free shape parameter, which has a computational advantage compared to the existing ACD specification in the literature. We compare the performance of the LNACD model with alternative specification of ACD model. The empirical results show that the LNACD model is always superior to Exponential and Weibull ACD models and its performance is similar to the Burr and Generalized Gamma ACD models.

Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models
Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models

Author: Giampiero M. Gallo

Publisher:

Published: 2006

Total Pages: 29

ISBN-13:

DOWNLOAD EBOOK

Financial market price formation and exchange activity can be investigated by means of ultra-high frequency data. In this paper we investigate an extension of the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998) by adopting a mixture of distribution approach with time varying weights. Empirical estimation of the Mixture ACD model shows that the limitations of the standard base model and its inadequacy of modelling the behavior in the tail of the distribution are suitably solved by our model.When the weights are made dependent on some market activity data, the model lends itself to some structural interpretation related to price formation and information diffusion in the market.

An Alternative Nonparametric Specification Test in Autoregressive Conditional Duration Models
An Alternative Nonparametric Specification Test in Autoregressive Conditional Duration Models

Author: Patrick Saart

Publisher:

Published: 2012

Total Pages: 0

ISBN-13:

DOWNLOAD EBOOK

This paper introduces an alternative testing procedure to test the distribution of the error term in the Autoregressive Conditional Duration (ACD) class of models. In these models, the error term is normally interpreted as the standardized duration by which its probability distribution may have an important impact on the shape of the conditional intensity process of the financial duration in question.This paper illustrates that the testing procedure developed is applicable to various ACD types of models in the literature. Furthermore, when applied to parametric models, such as the Exponential ACD (EACD) and the weibull ACD (WACD), the test can be used as a diagnostic test of the accuracy of the required distributional assumption. Moreover, the hypothetical structure of the test is useful to the specification testing of a number of financial market microstructure hypotheses, especially those related to the information asymmetry in finance. Finally, the testing procedure introduced in this paper differs in many ways from those discussed in existing literatures. This paper shows theoretically and experimentally the statistical validity of the testing procedure, while demonstrating its usefulness and practicality using datasets from New York and Australia Stock Exchange.

Autoregressive Conditional Duration
Autoregressive Conditional Duration

Author: Jeffrey R. Russell

Publisher:

Published: 2008

Total Pages:

ISBN-13:

DOWNLOAD EBOOK

This paper proposes a new statistical model for the analysis of data that do not arrive in equal time intervals, such as financial transactions data, telephone calls, or sales data on commodities that are tracked electronically. In contrast to fixed interval analysis, the model treats the time between events as a stochastic time varying process. We propose a new model for point processes with intertemporal correlation. Because the model focuses on the time interval between events it is called the Autoregressive Conditional Duration (ACD) model. Strong evidence is provided for transaction clustering for the financial transactions dataanalyzed, even after time-of-day effects are removed. Although the model is most naturally applied to the arrival of transactions, we suggest a thinning algorithm to model characteristics associated with the arrival times, allowing the investigator to model processes that are observed in irregular time intervals, not just the arrival times of the data. Models for transaction events, the flow of volume, and the rate of change for prices are estimated.

Forecasting Transaction Rates
Forecasting Transaction Rates

Author: Robert F. Engle

Publisher:

Published: 1994

Total Pages: 64

ISBN-13:

DOWNLOAD EBOOK

This paper will propose a new statistical model for the analysis of data that does not arrive in equal time intervals such as financial transactions data, telephone calls, or sales data on commodities that are tracked electronically. In contrast to fixed interval analysis, the model treats the time between observation arrivals as a stochastic time varying process and therefore is in the spirit of the models of time deformation initially proposed by Tauchen and Pitts (1983), Clark (1973) and more recently discussed by Stock (1988), Lamoureux and Lastrapes (1992), Muller et al. (1990) and Ghysels and Jasiak (1994) but does not require auxiliary data or assumptions on the causes of time flow. Strong evidence is provided for duration clustering beyond a deterministic component for the financial transactions data analyzed. We will show that a very simple version of the model can successfully account for the significant autocorrelations in the observed durations between trades of IBM stock on the consolidated market. A simple transformation of the duration data allows us to include volume in the model.

Palgrave Handbook of Econometrics
Palgrave Handbook of Econometrics

Author: Terence C. Mills

Publisher: Palgrave Handbook of Econometr

Published: 2009-06-25

Total Pages: 1432

ISBN-13:

DOWNLOAD EBOOK

Palgrave Handbooks of Econometrics comprises 'landmark' essays by the world's leading scholars and provides authoritative guidance in key areas of econometrics. With definitive contributions on the subject, the Handbook is an essential source for reference for professional econometricians, economists, researchers and students. Following the successful Palgrave Handbook of Econometrics: Volume 1, this second volume brings together leading academics working in econometrics today and explores applied econometrics. Volume 2 contains contributions on subjects including growth/development econometrics, computing, microeconomics, macroeconomics, finance, spatial and urban economics and international economics.