The Econometric Modelling of Financial Time SeriesCambridge University Press, 2008 M03 20 - 468 páginas Terence Mills' best-selling graduate textbook provides detailed coverage of 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. This third edition, co-authored with Raphael Markellos, contains a wealth of 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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Página 1
... behaviour of financial time series were undertaken by financial professionals and journalists rather than by academics. Indeed, this seems to have become a long-standing tradition, as, even today, much empirical research and development ...
... behaviour of financial time series were undertaken by financial professionals and journalists rather than by academics. Indeed, this seems to have become a long-standing tradition, as, even today, much empirical research and development ...
Página 4
... behaviour of the series at low frequencies or, equivalently, in the very long run. A variety of examples taken from the financial literature are provided throughout these chapters. The random walk model has been the workhorse of ...
... behaviour of the series at low frequencies or, equivalently, in the very long run. A variety of examples taken from the financial literature are provided throughout these chapters. The random walk model has been the workhorse of ...
Página 5
... behaviour of financial prices is neither a sufficient nor a necessary condition for rationally determined financial prices. Moreover, the assumption in (1.1) that price changes are independent was found to be too restrictive to be ...
... behaviour of financial prices is neither a sufficient nor a necessary condition for rationally determined financial prices. Moreover, the assumption in (1.1) that price changes are independent was found to be too restrictive to be ...
Página 6
... behaviour could be modelled by a process in which successive conditional variances of 1ytþ1 (but not successive levels) are positively autocorrelated. Such a specification would be consistent with a martingale, but not with the more ...
... behaviour could be modelled by a process in which successive conditional variances of 1ytþ1 (but not successive levels) are positively autocorrelated. Such a specification would be consistent with a martingale, but not with the more ...
Página 19
... behaviour of the ACF is determined by the difference equation 4(B) pk = 0, fc>0 (2.6) which has the solution Pk = Alft* + A2g\ + • • • + Apgkp Since |g,|<l, the ACF is thus described by a mixture of damped exponentials (for real roots) ...
... behaviour of the ACF is determined by the difference equation 4(B) pk = 0, fc>0 (2.6) which has the solution Pk = Alft* + A2g\ + • • • + Apgkp Since |g,|<l, the ACF is thus described by a mixture of damped exponentials (for real roots) ...
Términos y frases comunes
À Á allow alternative analysis approach approximation ARCH assumed assumption asymptotic autocorrelation average behaviour bilinear cent changes chapter cointegration component computed conditional consider consistent constant contain converges correction correlation critical values ð Þ defined dependence developed discussed distribution effect empirical equation error estimated evidence example expected extension Figure financial first forecast function future GARCH given Granger hypothesis implies important independent integrated interest known limiting linear mean noise non-linear normal Note null observations obtained parameters period positive possible present procedure properties proposed provides random walk ratio regression rejected relationship requires residuals respectively response restrictions returns sample shown shows significant simple squared standard stationary statistic stochastic suggest tail trend unit root values variables variance vector volatility written yields zero
Pasajes populares
Página 12 - A stochastic process is said to be strictly stationary if its properties are unaffected by a change of time origin, that is, if the joint probability distribution associated with m observations...
Referencias a este libro
Probability Theory and Statistical Inference: Econometric Modeling with ... Aris Spanos Vista previa limitada - 1999 |
Extreme Financial Risks: From Dependence to Risk Management Yannick Malevergne,Didier Sornette Sin vista previa disponible - 2006 |