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. |
Dentro del libro
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Página 1
... analysis, in both its theoretical and empirical aspects, has been for many years an integral part of the study of financial markets. The first attempts to study the behaviour of financial time series were undertaken by financial ...
... analysis, in both its theoretical and empirical aspects, has been for many years an integral part of the study of financial markets. The first attempts to study the behaviour of financial time series were undertaken by financial ...
Página 2
... analysis, including stationarity, market efficiency, correlation between asset returns and indices, diversification and unpredictability, they made no serious effort to adopt formal statistical methods. Most of the empirical analysis ...
... analysis, including stationarity, market efficiency, correlation between asset returns and indices, diversification and unpredictability, they made no serious effort to adopt formal statistical methods. Most of the empirical analysis ...
Página 7
... analysis have allowed a much deeper investigation of the tail shapes of empirical distributions, and methods of estimating tail shape indices are introduced and applied to a variety of returns series. The chapter then looks at the ...
... analysis have allowed a much deeper investigation of the tail shapes of empirical distributions, and methods of estimating tail shape indices are introduced and applied to a variety of returns series. The chapter then looks at the ...
Página 9
... analysis of linear stochastic processes. As already stated in chapter 1, our treatment is purposely non-rigorous. For detailed theoretical treatments, but which do not, however, focus on the analysis of financial series, see, for ...
... analysis of linear stochastic processes. As already stated in chapter 1, our treatment is purposely non-rigorous. For detailed theoretical treatments, but which do not, however, focus on the analysis of financial series, see, for ...
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 |