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 33
... xtÀ1 À 0:222 xtÀ2 þ 0:004 xtÀ3 þ ^at; ^ 1⁄4 0:417 0:019ðÞ 0:039ðÞ 0:060ðÞ 0:039ðÞ xt 1⁄4 0:034 þ1:091 xtÀ1 À 0:129 xtÀ2 þ ^at þ 0:092 ^atÀ1; ^ 1⁄4 0:419 0:021ðÞ 0:178ðÞ 0:174ðÞ 0:179ðÞ In both models, the additional parameter is ...
... xtÀ1 À 0:222 xtÀ2 þ 0:004 xtÀ3 þ ^at; ^ 1⁄4 0:417 0:019ðÞ 0:039ðÞ 0:060ðÞ 0:039ðÞ xt 1⁄4 0:034 þ1:091 xtÀ1 À 0:129 xtÀ2 þ ^at þ 0:092 ^atÀ1; ^ 1⁄4 0:419 0:021ðÞ 0:178ðÞ 0:174ðÞ 0:179ðÞ In both models, the additional parameter is ...
Página 35
... xtÀ1 À 0:738 xtÀ2 ð0:74Þ ð0:119Þ ð0:096Þ þ at þ 1:083 atÀ1 þ 0:742 atÀ2; ^ 1⁄4 5:96 ð0:120Þ ð0:103Þ and xt 1⁄4 1:21 þat þ 0:130 atÀ1 À 0:107 atÀ2; ^ 1⁄4 5:99 0:28ðÞ 0:045ðÞ 0:045ðÞ Although these models appear quite different, they are ...
... xtÀ1 À 0:738 xtÀ2 ð0:74Þ ð0:119Þ ð0:096Þ þ at þ 1:083 atÀ1 þ 0:742 atÀ2; ^ 1⁄4 5:96 ð0:120Þ ð0:103Þ and xt 1⁄4 1:21 þat þ 0:130 atÀ1 À 0:107 atÀ2; ^ 1⁄4 5:99 0:28ðÞ 0:045ðÞ 0:045ðÞ Although these models appear quite different, they are ...
Página 39
... a t ð2:13Þ Lagging (2.13) one period and subtracting this from (2.13) yields xt À xtÀ1 1⁄4 1 þ at À atÀ1 ð2:14Þ The result is a difference equation following an ARMA(1,1) process. 39 Univariate linear stochastic models: basic concepts.
... a t ð2:13Þ Lagging (2.13) one period and subtracting this from (2.13) yields xt À xtÀ1 1⁄4 1 þ at À atÀ1 ð2:14Þ The result is a difference equation following an ARMA(1,1) process. 39 Univariate linear stochastic models: basic concepts.
Página 40
... xtÀ1 1⁄4 1 À B ð Þxt 1⁄4 Áxt where Á1⁄41ÀB is known as the first difference operator. Equation (2.14) can then be written as wt 1⁄4 Áxt 1⁄4 1 þ Áat and wt is thus generated by a stationary (since Ewtð Þ1⁄4 1 is a constant), but not ...
... xtÀ1 1⁄4 1 À B ð Þxt 1⁄4 Áxt where Á1⁄41ÀB is known as the first difference operator. Equation (2.14) can then be written as wt 1⁄4 Áxt 1⁄4 1 þ Áat and wt is thus generated by a stationary (since Ewtð Þ1⁄4 1 is a constant), but not ...
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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 |