'Unit root' diaporamas de présentation

Chapter 12

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Module 3 GARCH Models

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Chapter 12

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Arch-Garch

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Review of Unit Root Testing

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What affects MFP in the long-run? Evidence from Canadian industries

What affects MFP in the long-run? Evidence from Canadian industries. Danny Leung and Yi Zheng Bank of Canada, Research Department Structural Studies May 2008 The views expressed in this presentation are those of the authors. No responsibility should be attributed to the Bank of Canada.

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LECTURE 11 : RATIONAL BUBBLES

LECTURE 11 : RATIONAL BUBBLES. Contents. M arket price of stocks may deviate, possibly substantially , from their fundamental value even when agents are homogeneous and rational and the market is informationally efficient

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Time Series Data

Time Series Data. y t = b 0 + b 1 x t1 + . . .+ b k x tk + u t 1. Basic Analysis. Time Series vs. Cross Sectional. Time series data has a temporal ordering, unlike cross-section data

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temporal and causal relationships among prices of major fish species in Thailand : A trend and cointegration analysis

temporal and causal relationships among prices of major fish species in Thailand : A trend and cointegration analysis. Amporn Laowapong Umesh Bastola Prof. Dr. Madan Dey FAO Value chain project workshop The university of Tokyo 9-11 December 2011. Presentation Outline. Background

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Seasonal ARIMA

Seasonal ARIMA. FPP Chapter 8. Backshift Notation. Backshift Notation. Backshift Notation. Backshift Notation. Seasonal ARIMA Models. Seasonal ARIMA Models. Seasonal ARIMA Models. Seasonal ARIMA Models. Seasonal ARIMA Models. Seasonal ARIMA Models. Seasonal ARIMA Models.

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Econometric Analysis

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The Academy of Economic Studies Doctoral School of Finance and Banking

The Academy of Economic Studies Doctoral School of Finance and Banking. Monetary policy: analysis of a SVAR model for Romania. MSc S tudent: DR?GOI IONU? Supervisor: Professor MOIS? ALT?R. CONTENTS. Literature review The Data The SVAR approach

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Factoring Emerging Markets into the Relationship Between Commodities and Global Liquidity

Factoring Emerging Markets into the Relationship Between Commodities and Global Liquidity. Steven Landgraf WPPI Energy and Marquette University Abdur Chowdhury Marquette University USAEE/IAEE North American Conference Tuesday Oct 11 th , 2011. Background .

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The Properties of Time Series: Lecture 4

The Properties of Time Series: Lecture 4. Previously introduced AR(1) model X t = ?X t-1 + u t (1) (a) White Noise (stationary/no unit root) X t = u t i.e. ? = 0 in AR(1) equation (1) (b) Random Walk (non-stationary/unit root)

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An Empirical Evaluation of Relationship Between Crude Oil and Natural Gas Prices

www.eia.doe.gov. An Empirical Evaluation of Relationship Between Crude Oil and Natural Gas Prices. Meeting with the the American Statistical Association Committee on Energy Statistics With the Energy Information Administration April 7, 2006 Jose Villar jvillar@eia.doe.gov

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Realized Volatility of Won-Dollar Exchange Rate

Realized Volatility of Won-Dollar Exchange Rate. Lee, Seung Moon Economics, Rutgers University 12 / 10 /2006. Motivation. Taking a growing interest in Risk Management. Measuring of realized volatility of won-dollar exchange rate. Data. Data period: 3/2/1999 ~ 4/30/2002.

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Behavior of constant terms and general ARIMA models

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DATA STATIONER AND DATA NON STATIONER

DATA STATIONER AND DATA NON STATIONER. Example- Real GDP (2000 Prices) Seasonally Adjusted. (1) Plot Time Series - Non-Stationary (i.e. time varying mean and correlogram non-zero). GDP. Time. r. k. These are Examples of Non-Stationary Time Series. Unit Root Testing.

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Unit Root Tests

Unit Root Tests. Integrated Process. Integrated Process I(1): Y t = Y (t-1) + ARMA(p, q) t A Key Model (Hypothesis) for Macroeconomic Variables. Behavior of Two Trend Models - Long Run Forecast Implications. For t = h (for h=0, Y 0 = b 0 )

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