PPT-Time Series Econometrics:

Some Basic Concepts Reference Gujarati Chapters 21 Course Incharge Prof Dr Himayatullah Khan Time Series Data One of the important and frequent types of data used in empirical . Session 1 – Introduction. Amine Ouazad,. Asst. Prof. of Economics. Preliminaries. Session 1 - Introduction. Introduction. Who I am. Arbitrage. Textbook. Grading. Homework. Implementation. Session 1. An econometric model consists of a set of equations describing the behaviour. These equations are derived from the economic model and have two parts DESDynI. :. Lessons from ALOS PALSAR. Piyush . Agram. a. , Mark . Simons. a. and Howard . Zebker. b. a. Seismological. Laboratory, California Institute of Technology. b. Depts. of EE and Geophysics, Stanford University. 1. An Introduction to Econometrics. Prepared by Vera Tabakova, East Carolina University. Chapter 1: . An Introduction to Econometrics. 1.1 Why Study Econometrics. 1.2 What is Econometrics About. 1.3 The Econometric Model. 12. Nonstationary Time Series Data and Cointegration. Prepared by Vera Tabakova, East Carolina University. Chapter 12: . Nonstationary Time Series Data and Cointegration. 12.1 Stationary and Nonstationary Variables. Authors. Jessica Lin. Eamonn. Keogh. Li Wei. Stefano . Lonardi. Presenter. Arif. Bin . Hossain. Slides incorporate materials kindly provided by Prof. . Eamonn. Keogh. Time Series.  A . time series. Introduction to Time Series Analysis. A . time-series. is a set of observations on a quantitative variable collected over time.. Examples. Dow Jones Industrial Averages. Historical data on sales, inventory, customer counts, interest rates, costs, etc. From: ICDE2009. Author: Bin Jiang, Jian Pei. Speaker: . Zhifeng. . Lin. Date: Nov 28. th. ,2008. Outline. What’s online Interval Skyline Query. ?. Definition and Notation. On-the-fly Solution. Conclusion.  . Eamonn Keogh . With. Yan Zhu, Chin-. Chia. Michael . Yeh. , Abdullah Mueen. . with contributions from Zachary Zimmerman, Nader . Shakibay. . Senobari. ,, Gareth Funning, Philip Brisk, Liudmila Ulanova, Nurjahan Begum, . . Didar . Erdinc, Ph.D.. Associate Professor of Economics. American University in Bulgaria. . Vector . Autoregression. (VAR). Introduction. VAR resembles a SEM modeling – we consider several endogenous variables together. Each endogenous variables is explained by its lagged values and the lagged values of all other endogenous variables in the model.. Hyun . Duk. . Kim (now at Twitter) , . Danila. . Nikitin. (now at Google), . ChengXiang. . Zhai. University of Illinois at Urbana-Champaign. Malu. Castellanos, . Meichun. Hsu. HP Laboratories. …. Data . Mining Algorithm. Peter Myers. Bitwise Solutions Pty Ltd. DBI-B326. Presenter Introduction. Peter Myers. BI Expert, Bitwise Solutions Pty Ltd. BBus. , SQL Server MCSE, MCT, SQL Server MVP (since 2007).  . Eamonn Keogh . With. Yan Zhu, Chin-. Chia. Michael . Yeh. , Abdullah Mueen. . with contributions from Zachary Zimmerman, Nader . Shakibay. . Senobari. ,, Gareth Funning, Philip Brisk, Liudmila Ulanova, Nurjahan Begum, . Danny Hendler . hendlerd@post.bgu.ac.il. Amir Rubin . amirrub@post.bgu.ac.il. Agenda. Introduction to time series analysis. Euclidean distance. Dynamic time wrapping. Mini project TSA. Agenda. Introduction to time series analysis.