加州大学－时间序列计量经济学与证券组合 讲义+习题

不错的很

thanks a lot

特棒！

不错！

真是好人啊！

谢谢！[em01][em01]

【书名】 Time Series Econometrics and Portfolio Theory
【作者】 L. Phillips
【出版社】加州大学经济学系
【版本】Econ 240C
【出版日期】2000-4
【文件格式】Word
【文件大小】1.82MB
【页数】
【ISBN出版号】
【资料类别】计量经济学
【扫描版还是影印版】电子档
【是否缺页】否
【关键词】计量经济学,证券组合,时间序列,预测,Eview
【内容简介】本资料为加州大学经济学系L. Phillips于2000年秋季班的上课讲义。该课程的目的是运用经济学上的时间序列模型来做预测。课程一开始便引入稳定性及演进性的时间序列等概念，并且介绍时序上的AR,MA,ARIMA等模型。随着模型的愈趋复杂，作者逐渐用模拟的方式取代分析。
【目录】
Lecture One, 12 p.
          I. Time Series Econometrics and Portfolio Theory
Lecture Two, 13 p.
          I. Inertial Versus Causal Models
          II. Structural(Inertial) Models of Time Series
          III. Deterministic and Stochastic Time Series
          IV. Stationary Stochastic Processes
Lecture Three, 13 p.
          I. Time Averages of Stationary Stochastic Processes
          II. Evolutionary Stochastic Processes
          III. Autocovariance and Autocorrelation Functions
          IV. The Normal Random Variable
          V. White Noise
Lecture Four, 13 p.
          I. Random Walk
Lecture Five, 8 p.
          I. First Order Autoregressive Processes
Lecture Six, 8 p.
          I. Moving Average Processes of Order One
          II. Autoregressive Processes of Order Two
 Lecture Seven, 9 p.
          I. Summary: AR & MA Processes to Date
          II. Summary: Empirical Methods
          III. Autoregressive Processes of Order Two, Continued
Lecture Eight, 5 p.
          I. Forecasting
          II. Partial Autocorrelation Function For an MA(1)
          III. Moving Average Processes of Order Two, MA(2)
Lecture Nine, 7 p.
          I. Diagnostics
          II. Autoregressive Moving Average Processes, ARMA(1,1)
          III. Forecasting and Model Selection
Lecture Ten, 6 p.
          I. Economic Applications of Univariate time Series Analysis
Lecture Eleven, 5 p.
          I. Dynamic causal Models
          II. Econometric Considerations
          III. Box-Jenkins Estimation of Dynamic Distributed lag Models
Lecture Twelve, 13 p.
          I. 1994 Take-home Project Assignment
          II. The Granfield Study
          III. A Simple Univariate Model of General Fund Expenditure on U.C.
          IV. A Dynamic Model Relating the UC Budget to California Personal Income, both nominal
          V. A Combined Distributed Lag and Intervention Model
Lecture Thirteen, 5 p.
          I. Exponential Smoothing
          II. Simple Exponential Smoothing
          III. Forecasting Formula as a Geometric Distributed Lag of the Observations
          IV. Simple Exponential Smoothing as an ARIMA Process
          V. Double Exponential Smoothing
          VI. Holt-Winters with an Additive Seasonal Term
Lecture Fourteen, 6 p.
          I. Intervention Models
          II. Modeling the Event
          III. An Intervention Model of Telephone Directory Assistance
Lecture Fifteen, 14 p.
          I. Accidents, Disasters, Loss in Wealth, and the Impact on Consumer Demand
          II. The Continental Oil Company Takeover
Lecture Sixteen, 16 p.
          I. Autoregressive Conditional Heteroskedastic(ARCH) Models
          II. Simulation of an ARCH(1) Time Series
          III. Generalized Autoregressive Conditional Heteroskedastic(GARCH) Model
          IV. Maximum Likelihood Estimation of GARCH models
          V. ARCH-M models
Lecture Seventeen, 12 p.
          I. Structural Time Series Models
          II. Estimation of Harvey Structural Time Series Models
Lecture Eighteen, 16 p.
          I. Simultaneity, Systems of Equations, and Vector Autoregression Models
          II. Simulation of Impulse Response functions
          III. Decomposition of the Forecast Errors
          IV. Appendix: VAR models in matrix notation
Lecture Nineteen, Review and Introduction to Cointegration, 35 p.
          I. Introduction
          II. Integrated and Cointegrated Time Series
          III. Harvey Structural Models and Cointegration
          IV. Simulation Examples
          V. Error Correction Models and Cointegration
          VI. Vector Autoregression and Cointegration
          VII. Simulation of Impulse Response Functions
          VIII. Johansen Cointegration Test
          IX. Appendix: Cointegration in Matrix Notation
【原创书评】我觉得这是相当棒的教学文件！！作者用很浅显的文字，很直截了当的说明了诸如stationarity、evolutionary,random walk等专业术语。计量经济学少不了得用到许多数学公式，作者除了推导以外，还用数据代入，帮助读者更了解其抽像的概念。且该份讲义不单单只是涉及计量经济学一个领域，还谈及时间序列和投资组合理论，算是把经济和金融二个分流给整合了起来。并且除了理论基础的扎根，还讲求实务的应用。档案中，亦有教人如何使用Eview的资料。从这份文件,让我们也了解，西方名校作学问的态度真的很严谨！

[此贴子已经被pine888于2008-2-7 11:50:34编辑过]

谢谢

想看看题目~

谢谢哈  呵呵