Muutke küpsiste eelistusi

Financial Econometrics [Kõva köide]

5.00/5 (1 hinnangut Goodreads-ist)
(University of Plymouth, UK)
  • Formaat: Hardback, 320 pages, kõrgus x laius: 234x156 mm, kaal: 780 g, 41 Tables, black and white; 26 Line drawings, black and white; 26 Illustrations, black and white
  • Sari: Routledge Advanced Texts in Economics and Finance
  • Ilmumisaeg: 19-Sep-2008
  • Kirjastus: Routledge
  • ISBN-10: 0415426707
  • ISBN-13: 9780415426701
Teised raamatud teemal:
Financial EconometricsSuurem pilt
  • Formaat: Hardback, 320 pages, kõrgus x laius: 234x156 mm, kaal: 780 g, 41 Tables, black and white; 26 Line drawings, black and white; 26 Illustrations, black and white
  • Sari: Routledge Advanced Texts in Economics and Finance
  • Ilmumisaeg: 19-Sep-2008
  • Kirjastus: Routledge
  • ISBN-10: 0415426707
  • ISBN-13: 9780415426701
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780415426701.html
Märksõnad:

This book provides an essential toolkit for all students wishing to know more about the modelling and analysis of financial data. Applications of econometric techniques are becoming increasingly common in the world of finance and this second edition of an established text covers the following key themes:

- unit roots, cointegration and other developments in the study of time series models

- time varying volatility models of the GARCH type and the stochastic volatility approach

- analysis of shock persistence and impulse responses

- Markov switching and Kalman filtering

- spectral analysis

- present value relations and rationality

- discrete choice models

- analysis of truncated and censored samples

- panel data analysis.

This updated edition includes new chapters which cover limited dependent variables and panel data. It continues to be an essential guide for all graduate and advanced undergraduate students of econometrics and finance.

Arvustused

"The author aimed at bringing together, to a single research-oriented volume, various topics concerning the modelling and analysis of financial data, which were previously scattered in different books. The main difference from the first edition is in the time series modelling, but also this second edition considers discrete choice models, estimation of censored and truncated samples and other topics which developed significantly since the first edition. The unique feature of the book is that each chapter has a section or two of examples and cases, and a section of empirical literature. This will give a potential reader an opportunity both to understand better the theory and to practice in applying this theory to real models. " Yuliya S. Mishura, Zentralblatt MATH 1171

List of figures
ix
List of tables
x
Acknowledgements xii
Preface xiv
Stochastic processes and financial data generating processes
1(14)
Introduction
1(4)
Stochastic processes and their properties
5(3)
The behaviour of financial variables and beyond
8(7)
Commonly applied statistical distributions and their relevance
15(15)
Normal distributions
15(8)
X2-distributions
23(2)
t-distributions
25(3)
F-distributions
28(2)
Overview of estimation methods
30(15)
Basic OLS procedures
30(2)
Basic ML procedures
32(1)
Estimation when iid is violated
33(2)
General residual distributions in time series and cross-section modelling
35(5)
MM and GMM approaches
40(5)
Unit roots, cointegration and other comovements in time series
45(21)
Unit roots and testing for unit roots
45(4)
Cointegration
49(2)
Common trends and common cycles
51(2)
Examples and cases
53(5)
Empirical literature
58(8)
Time-varying volatility models: GARCH and stochastic volatility
66(23)
ARCH and GARCH and their variations
66(4)
Multivariate GARCH
70(4)
Stochastic volatility
74(1)
Examples and cases
75(7)
Empirical literature
82(7)
Shock persistence and impulse response analysis
89(24)
Univariate persistence measures
90(2)
Multivariate persistence measures
92(3)
Impulse response analysis and variance decomposition
95(3)
Non-orthogonal cross-effect impulse response analysis
98(1)
Examples and cases
99(9)
Empirical literature
108(5)
Modelling regime shifts: Markov switching models
113(18)
Markov chains
113(1)
Estimation
114(3)
Smoothing
117(2)
Time-varying transition probabilities
119(1)
Examples and cases
120(6)
Empirical literature
126(5)
Present value models and tests for rationality and market efficiency
131(20)
The basic present value model and its time series characteristics
131(2)
The VAR representation
133(3)
The present value model in logarithms with time-varying discount rates
136(2)
The VAR representation for the present value model in the log-linear form
138(1)
Variance decomposition
139(1)
Examples and cases
140(7)
Empirical literature
147(4)
State space models and the Kalman filter
151(17)
State space expression
151(1)
Kalman filter algorithms
152(1)
Time-varying coefficient models
153(1)
State space models of commonly used time series processes
154(4)
Examples and cases
158(6)
Empirical literature
164(4)
Frequency domain analysis of time series
168(30)
The Fourier transform and spectra
168(4)
Multivariate spectra, phases and coherence
172(1)
Frequency domain representations of commonly used time series processes
173(2)
Frequency domain analysis of the patterns of violation of white noise conditions
175(7)
Examples and cases
182(12)
Empirical literature
194(4)
Limited dependent variables and discrete choice models
198(28)
Probit and logit formulations
199(3)
Multinomial logit models and multinomial logistic regression
202(3)
Ordered probit and logit
205(2)
Marginal effects
207(3)
Examples and cases
210(10)
Empirical literature
220(6)
Limited dependent variables and truncated and censored samples
226(23)
Truncated and censored data analysis
226(4)
The Tobit model
230(3)
Generalisation of the Tobit model: Heckman and Cragg
233(1)
Examples and cases
234(8)
Empirical literature
242(7)
Panel data analysis
249(40)
Structure and organisation of panel data sets
250(2)
Fixed effects vs. random effects models
252(8)
Random parameter models
260(4)
Dynamic panel data analysis
264(5)
Examples and cases
269(9)
Empirical literature
278(11)
Research tools and sources of information
289(24)
Financial economics and econometrics literature on the Internet
289(2)
Econometric software packages for financial and economic data analysis
291(3)
Learned societies and professional associations
294(5)
Organisations and institutions
299(14)
Index 313
Peijie Wang is Professor of Finance at IÉSEG School of Management, Catholic University of Lille. He is author of An Econometric Analysis of the Real Estate Market (Routledge 2001) and The Economics of Foreign Exchange and Global Finance.