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Econ 240 C. Lecture 15. Outline. Project II Forecasting ARCH-M Models Granger Causality Simultaneity VAR models. I. Work in Groups II. You will be graded based on a PowerPoint presentation and a written report.
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Econ 240 C Lecture 15
Outline • Project II • Forecasting • ARCH-M Models • Granger Causality • Simultaneity • VAR models
I.Work in Groups II.You will be graded based on a PowerPoint presentation and a written report. III.Your report should have an executive summary of one to one and a half pages that summarizes your findings in words for a non-technical reader. It should explain the problem being examined from an economic perspective, i.e. it should motivate interest in the issue on the part of the reader. Your report should explain how you are investigating the issue, in simple language. It should explain why you are approaching the problem in this particular fashion. Your executive report should explain the economic importance of your findings.
The technical details of your findings you can attach as an appendix Technical Appendix 1. Table of Contents 2. Spreadsheet of data used and sources or, if extensive, a subsample of the data 3. Describe the analytical time series techniques you are using 4. Show descriptive statistics and histograms for the variables in the study 5. Use time series data for your project; show a plot of each variable against time
Group A Group B Group C Eirk Skeid Markus Ansmann Xiaoyin Zhang Tor Seim Theresa Firestine Samantha Gardner Bradley Moore Nikolay Laptev Ryan Nabinger Anders Graham Lawrence bboth Brett Hanifin Steven Comstock Birthe Smedsrud Ali Irtturk S. Matthew Scott Lingu Tang Gregory Adams Group D Group E Troy Dewitt Mats Olson Emilia Bragadottir Brandon Briggs Christopher Wilderman Theodore Ehlert Qun Luo Alan Weinberg Dane Louvier David Sheehan
Part I. ARCH-M Modeks • In an ARCH-M model, the conditional variance is introduced into the equation for the mean as an explanatory variable. • ARCH-M is often used in financial models
Net return to an asset model • Net return to an asset: y(t) • y(t) = u(t) + e(t) • where u(t) is is the expected risk premium • e(t) is the asset specific shock • the expected risk premium: u(t) • u(t) = a + b*h(t) • h(t) is the conditional variance • Combining, we obtain: • y(t) = a + b*h(t) +e(t)
Northern Telecom And Toronto Stock Exchange • Nortel and TSE monthly rates of return on the stock and the market, respectively • Keller and Warrack, 6th ed. Xm 18-06 data file • We used a similar file for GE and S_P_Index01 last Fall in Lab 6 of Econ 240A
Try Adding the Conditional Variance to the Returns Model • PROCS: Make GARCH variance series: GARCH01 series