Update cookies preferences

E-book: Econometric Modelling of Stock Market Intraday Activity

Other books in subject:
  • Format - PDF+DRM
  • Price: 110,53 €*
  • * the price is final i.e. no additional discount will apply
  • Add to basket
  • Add to Wishlist
  • This ebook is for personal use only. E-Books are non-refundable.
Other books in subject:

DRM restrictions

  • Copying (copy/paste):

    not allowed

  • Printing:

    not allowed

  • Usage:

    Digital Rights Management (DRM)
    The publisher has supplied this book in encrypted form, which means that you need to install free software in order to unlock and read it.  To read this e-book you have to create Adobe ID More info here. Ebook can be read and downloaded up to 6 devices (single user with the same Adobe ID).

    Required software
    To read this ebook on a mobile device (phone or tablet) you'll need to install this free app: PocketBook Reader (iOS / Android)

    To download and read this eBook on a PC or Mac you need Adobe Digital Editions (This is a free app specially developed for eBooks. It's not the same as Adobe Reader, which you probably already have on your computer.)

    You can't read this ebook with Amazon Kindle

Over the past 25 years, applied econometrics has undergone tremen­ dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen­ eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro­ duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil­ ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled.
Acknowledgments vii
Introduction ix
Market Microstructure, Trading Mechanisms and Exchanges
1(34)
Introduction
1(1)
Price setting in financial markets
2(9)
The Walrasian auction
2(1)
Price driven and order driven markets
2(4)
Characteristics of trading mechanisms
6(1)
Market Liquidity
7(4)
Exchanges
11(10)
The New York Stock Exchange
11(4)
The NASDAQ
15(2)
The Foreign Exchange market
17(1)
The Paris Bourse
18(3)
Market microstructure
21(14)
Behavior of market makers: theoretical models
21(3)
Empirical research
24(11)
Nyse Taq Database and Financial Durations
35(30)
Introduction
35(1)
The TAQ database
36(5)
The trade database
36(1)
The quote database
37(1)
Best bid-ask quotes
38(2)
Direction of a trade
40(1)
Downstairs or upstairs trade?
40(1)
Recording mistakes
40(1)
Bid-ask bounce
41(1)
Extracting information from the TAQ database
41(3)
Durations
44(4)
Price durations
45(2)
Volume durations
47(1)
Durations: a descriptive analysis
48(17)
Trades and quotes
49(1)
Intraday seasonality
50(2)
Time-of-day adjusted durations
52(13)
Intraday Duration Models
65(42)
Introduction
65(1)
Basic statistical concepts
65(4)
Econometric models
69(22)
ACD models
70(6)
Logarithmic ACD models
76(5)
Estimation
81(2)
Diagnostics
83(8)
Illustration on NYSE data
91(6)
Appendix: probability distributions
97(10)
Empirical Results and Extensions
107(18)
Introduction
107(1)
Market microstructure effects
108(3)
Adding variables in the ACD model
108(1)
Empirical application
109(2)
A joint model of durations and price change indicators
111(11)
The model
113(3)
Empirical application
116(2)
Forecasting and trading rules
118(4)
Appendix
122(3)
Intraday Volatility and Value-at-Risk
125(48)
Introduction
125(1)
A review of ARCH models
126(6)
Asset returns and market efficiency
126(2)
The ARCH model
128(2)
Extensions
130(2)
ARCH models for intraday data
132(15)
Time transformations and intraday seasonality
133(8)
GARCH and EGARCH Models
141(3)
Volume and number of trades
144(3)
Intraday Value-at-Risk
147(26)
Value-at-Risk
147(2)
VaR models for intraday data
149(3)
Empirical application
152(21)
About the Authors 173(2)
Index 175
Luc Bauwens is Professor of Economics at the Université catholique de Louvain, Belgium where he chairs the Department of Economics, and has been co-director of the Center for Operations Research and Econometrics (CORE) from 1992 to 1998. He has published several books and papers in the fields of Bayesian inference, time series methods, simulation and numerical methods in econometrics, as well as empirical finance and international trade.

Pierre Giot is Professor of Econometrics and Quantitative Finance at Maastricht University in The Netherlands, and he is a member of CORE in Belgium. After graduating as a Civil Engineer (Polytechnique) in Electronics, he got his Ph.D. in Economics at the Université catholique de Louvain in 1999. His current research interests focus on quantitative finance, models for intraday data and empirical market microstructure.