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The Econometric Modelling of Financi...
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Ebooks Corporation.
The Econometric Modelling of Financial Time Series.[electronic resource].
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
杜威分類號:
332.015195
書名/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.
標題:
Finance.; Stochastic processes.
ISBN:
9780511754128 (electronic bk.)
ISBN:
9780521624138 (print)
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
摘要、提要註:
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
電子資源:
Click here to view book
The Econometric Modelling of Financial Time Series.[electronic resource].
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:
566057
Finance.; Stochastic processes.
Index Terms--Genre/Form:
336502
Electronic books.
LC Class. No.: HG174 .M55 1999eb
Dewey Class. No.: 332.015195
The Econometric Modelling of Financial Time Series.[electronic resource].
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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
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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
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