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The Econometric Modelling of Financi...

Mills, Terence C.

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The Econometric Modelling of Financial Time Series.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The Econometric Modelling of Financial Time Series./
作者:	Mills, Terence C.
出版者:	Cambridge :Cambridge University Press, : 1999.,
面頁冊數:	380 p.
內容註:	Contents; Preface to the second edition; 1 Introduction; 2 Univariate linear stochastic models: basic concepts; 2.1 Stochastic processes, ergodicity and stationarity; 2.2 Stochastic difference equations; 2.3 ARMA processes; 2.4 Linear stochastic processes; 2.5 ARMA model building; 2.6 Non-stationary processes and ARIMA models; 2.7 ARIMA modelling; 2.8 Forecasting using ARIMA models; 3 Univariate linear stochastic models: further topics; 3.1 Determining the order of integration of a time series; 3.2 Decomposing time series: unobserved component models and signal extraction
內容註:	3.3 Measures of persistence and trend reversion3.4 Fractional integration and long memory processes; 4 Univariate non-linear stochastic models; 4.1 Martingales, random walks and non-linearity; 4.2 Testing the random walk hypothesis; 4.3 Stochastic volatility; 4.4 ARCH processes; 4.5 Other non-linear univariate models; 4.6 Testing for non-linearity; 5 Modelling return distributions; 5.1 Descriptive analysis of three returns series; 5.2 Two
標題:	Finance.; Stochastic processes. -
電子資源:	http://dx.doi.org/10.1017/CBO9780511754128Click here to view book
ISBN:	9780511754128 (electronic bk.)

The Econometric Modelling of Financial Time Series.
Mills, Terence C.

The Econometric Modelling of Financial Time Series.[electronic resource]. - Cambridge :Cambridge University Press,1999. - 380 p.

Contents; Preface to the second edition; 1 Introduction; 2 Univariate linear stochastic models: basic concepts; 2.1 Stochastic processes, ergodicity and stationarity; 2.2 Stochastic difference equations; 2.3 ARMA processes; 2.4 Linear stochastic processes; 2.5 ARMA model building; 2.6 Non-stationary processes and ARIMA models; 2.7 ARIMA modelling; 2.8 Forecasting using ARIMA models; 3 Univariate linear stochastic models: further topics; 3.1 Determining the order of integration of a time series; 3.2 Decomposing time series: unobserved component models and signal extraction

Fully revised and updated, the second edition of the best-selling The Econometric Modelling of Financial Time Series provides comprehensive coverage of the variety of models currently used in the empirical analysis of financial markets. Data appendix available online at www.lboro.ac.uk/departments/ec/cup

Electronic reproduction.

Available via World Wide Web.

Mode of access: World Wide Web.

ISBN: 9780511754128 (electronic bk.)Subjects--Topical Terms:

1898148
Finance.; Stochastic processes.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HG174 .M55 1999eb

Dewey Class. No.: 332.015195

The Econometric Modelling of Financial Time Series.
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505 8 $a 3.3 Measures of persistence and trend reversion3.4 Fractional integration and long memory processes; 4 Univariate non-linear stochastic models; 4.1 Martingales, random walks and non-linearity; 4.2 Testing the random walk hypothesis; 4.3 Stochastic volatility; 4.4 ARCH processes; 4.5 Other non-linear univariate models; 4.6 Testing for non-linearity; 5 Modelling return distributions; 5.1 Descriptive analysis of three returns series; 5.2 Two
520 $a Fully revised and updated, the second edition of the best-selling The Econometric Modelling of Financial Time Series provides comprehensive coverage of the variety of models currently used in the empirical analysis of financial markets. Data appendix available online at www.lboro.ac.uk/departments/ec/cup
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