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Terence C. Mills
Loughborough University
Raphael N. Markellos
Athens University of Economics and Business
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.
Contents
List of figures; List of tables; Preface to the third edition; 1. Introduction; 2. Univariate linear stochastic models: basic concepts; 3. Univariate linear stochastic models: testing for unit roots and alternative trend specifications; 4. Univariate linear stochastic models: further topics; 5. Univariate non-linear stochastic models: Martingales, random walks and modelling volatility; 6. Univariate non-linear stochastic models: Further models and testing procedures; 7. Modelling return distributions; 8. Regression techniques for non-integrated financial time series; 9. Regression techniques for integrated financial time series; 10. Further topics in the analysis of integrated financial time series; Data appendix; References.
Preface to the third edition
In the nine years since the manuscript for the second edition of The
Econometric Modelling of Financial Time Series was completed there have
continued to be many advances in time series econometrics, some of which
have been in direct response to features found in the data coming from
financial markets, while others have found ready application in financial
fields. Incorporating these developments was too much for a single author,
particularly one whose interests have diverged from financial econometrics
quite significantly in the intervening years! Raphael Markellos has thus
become joint author, and his interests and expertise in finance now
permeate throughout this new edition, which has had to be lengthened
somewhat to accommodate many new developments in the area.
Chapters 1 and 2 remain essentially the same as in the second edition,
although examples have been updated. The material on unit roots and
associated techniques has continued to expand, so much so that it now has
an entire chapter, 3, devoted to it. The remaining material on univariate
linear stochastic models now comprises chapter 4, with much more on
fractionally differenced processes being included in response to developments
in recent years. Evidence of non-linearity in financial time series has
continued to accumulate, and stochastic variance models and the many
extensions of the ARCH process continue to be very popular, along with the
related area of modelling volatility. This material now forms chapter 5, with
further non-linear models and tests of non-linearity providing the material
for chapter 6. Chapter 7 now contains the material on modelling return
distributions and transformations of returns. Much of the material of
chapters 8, 9 and 10 (previously chapters 6, 7 and 8) remains as before, but
with expanded sections on, for example, non-linear generalisations of
cointegration.
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