| The Econometric Modelling of Financial Time Series | 
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Avg. Customer Rating:   (based on 2 reviews) Sales Rank: 466616 Category: Book
Authors: Terence C. Mills, Raphael N. Markellos Publisher: Cambridge University Press Studio: Cambridge University Press Manufacturer: Cambridge University Press Label: Cambridge University Press Languages: English (Original Language), English (Unknown), English (Published) Media: Paperback Edition: 3 Number Of Items: 1 Pages: 470 Shipping Weight (lbs): 2 Dimensions (in): 9.7 x 6.9 x 1.2
ISBN: 052171009X Dewey Decimal Number: 332.015195 EAN: 9780521710091 ASIN: 052171009X
Publication Date: April 21, 2008 Availability: Usually ships in 1-2 business days
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| Editorial Reviews:
Product Description Terence Mills' best-selling graduate textbook provides detailed coverage of the latest research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. The third edition, co-authored with Raphael Markellos, contains a wealth of new material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing.
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| Customer Reviews:
  Poorly Written and Unclear January 10, 2001 10 out of 11 found this review helpful
Obviously patched together from topics written over a period of time, this book is not cohesive nor understandable. Mills doesn't spend any words developing his topics nor explaning the development. Spend your resources on Hamilton's classic and great definative bible, Time Series Analysis instead.
  it's a terrific book for non-linear time series analysis April 6, 2000 15 out of 20 found this review helpful
This is a very compact, practical book. It edits in a very readable way. What I like it most is that it contributes to non-linear time series analysis a lot, whereas not too many other time series related books do. The real data in the appendix can be downloaded and played around by the readers. You will really have a great time to read it.
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