Graduate Curriculum Committee Course Proposal Form
for Courses Numbered 6000 and Higher
Note: Before completing this form, please carefully read the accompanying instructions.
Submission guidelines are posted to the GCC Web site: http://www.ecu.edu/cs-acad/gcc/index.cfm
1. Course prefix and number:
ECON 8242
2. Date:
09/13/2011
3. Requested action:
X New Course
Revision of Active Course
Revision & Unbanking of a Banked Course
Renumbering of an Existing Course from
from
to
#
Required
X
#
Elective
4. Method(s) of delivery (check all boxes that apply for both current/proposed and expected
future delivery methods within the next three years):
Current or
Proposed Delivery
Method(s):
X
On-campus (face to face)
Expected
Future Delivery
Method(s):
X
Distance Course (face to face off campus)
Online (delivery of 50% or more of the instruction is offered online)
5. Justification (must cite accreditation and/or assessment by the graduate faculty) for new course
or course revision or course renumbering:
The graduate faculty of the Department of Economics identified a societal need for PhD
graduates with advanced analytic and technical skills necessary for analysis, mitigation,
management and regulation of risk—both environmental and financial. This requires an
understanding of the underlying individual decision maker and firm behavior and their
interaction within market and nonmarket settings. Theoretical modeling and empirical
analysis complete the picture and allow for the identification of effective public policy
and regulation. This doctoral program is unique within the state of North Carolina
because it emphasizes risk modeling and analysis over a broad scope of applications that
range from financial markets to natural hazards. Students with training from this
program will be well equipped to qualify for high level positions within Federal and State
Agencies that deal with natural hazards and regulation of risk, as well as businesses for
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management and mitigation of risk.
The assessment process of the Economics Graduate Faculty has determined that this
course should be the second in a two-course PhD field sequence in applied
macroeconomics.
6. Course description exactly as it should appear in the next catalog:
8242. Applied Macro II (3) P: ECON 8241. Development of the econometric tools
necessary for advanced research in financial risk analysis.
7. If this is a course revision, briefly describe the requested change:
N/A
8. Course credit:
Lecture Hours
3
3
Weekly
OR
Per Term
Credit Hours
s.h.
Lab
Weekly
OR
Per Term
Credit Hours
s.h.
Studio
Weekly
OR
Per Term
Credit Hours
s.h.
Practicum
Weekly
OR
Per Term
Credit Hours
s.h.
Internship
Weekly
OR
Per Term
Credit Hours
s.h.
Other (e.g., independent study) Please explain.
s.h.
3
Total Credit Hours
s.h.
6
9. Anticipated annual student enrollment:
10. Changes in degree hours of your programs:
Degree(s)/Program(s)
Changes in Degree Hours
PhD/ Economics
N/A
11. Affected degrees or academic programs, other than your programs:
Degree(s)/Program(s)
Changes in Degree Hours
12. Overlapping or duplication with affected units or programs:
X Not applicable
Documentation of notification to the affected academic degree programs is
attached.
13. Council for Teacher Education (CTE) approval (for courses affecting teacher education):
X Not applicable
Applicable and CTE has given their approval.
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14. University Service-Learning Committee (USLC) approval:
X Not applicable
Applicable and USLC has given their approval.
15. Statements of support:
a. Staff
Current staff is adequate
X
Additional staff is needed (describe needs in the box below):
b. Facilities
X Current facilities are adequate
Additional facilities are needed (describe needs in the box below):
c. Library
X
Initial library resources are adequate
Initial resources are needed (in the box below, give a brief explanation and an
estimate for the cost of acquisition of required initial resources):
d. Unit computer resources
X
Unit computer resources are adequate
Additional unit computer resources are needed (in the box below, give a brief
explanation and an estimate for the cost of acquisition):
e. ITCS resources
X
ITCS resources are not needed
The following ITCS resources are needed (put a check beside each need):
Mainframe computer system
Statistical services
Network connections
Computer lab for students
Software MATLAB
Approval from the Director of ITCS attached
16. Course information (see: Graduate Curriculum and Program Development Manual for
instructions):
a. Textbook(s) and/or readings: author(s), name, publication date, publisher, and
city/state/country. Include ISBN (when applicable).
Textbooks:
Gourieroux, C. & J. Jasiak. (2001). Financial Econometrics. Princeton, NJ: Princeton
University Press.
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Tsay, R. S. (2002). Analysis of Financial Time Series. Hoboken, NJ: Wiley Series in
Probability and Statistics.
O'Hara, M. (1995). Market Microstructure Theory. Cambridge, MA: Blackwell
Publishers.
Campbell, Lo, & MacKinlay. (1997). The Econometrics of Financial Markets.
Princeton, NJ: Princeton University Press.
.
Hamilton, J. (1994). Time Series Analysis. Princeton, NJ: Princeton University Press.
Readings:
Amin & Ng. (1993). Option Valuation with Systematic Stochastic Volatility. Journal
of Finance (48, pp. 881-910).
Bollerslev, Engle & Nelson. (1994). ARCH Models. Handbook of Econometrics (49).
4, North Holland.
Burns, P. E. & Mezrich. (1998). Volatilities and Correlations for Asynchronous Data.
Journal of Derivatives.
Capiello, E. & Sheppard. (2002). Asymmetric Dynamic Correlations of Global Equity
and Bond Returns. European Central Bank Discussion Paper.
Diebold, F., & Mariano, (1995). Comparing Predictive Accuracy. Journal of Business
and Economic Statistics (13, pp. 253-263).
Duan, J.C. (1995). The GARCH Option Pricing Model. Mathematical Finance (5, pp.
13-32).
Dufour & Engle. (2000). Time and the Price Impact of a Trade. Journal of Finance (
55, pp. 2467-2498)
Engle. (2001). GARCH101: The Use of ARCH/GARCH Models in Applied
Econometrics. Journal of Economic Perspectives (15, pp.157-168).
Engle. (2000). The Econometrics of Ultra-High Frequency Data. Econometrica.
Engle. (2001). Financial Econometrics - A New Discipline With New Methods.
Journal of Econometrics (100, pp.53-56).
Engle. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate
GARCH Models. Journal of Business and Economic Statistics (20, pp. 339-350).
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Engle, R.F. & Mezrich, J. (1995). Grappling with GARCH. Risk. September
Engle, R.F. & Mezrich, J. (1996). GARCH for Groups. Risk (9, pp. 36-40).
Engle & Rosenberg. (1995). GARCH Gamma. Journal of Derivatives (2, pp. 47-59).
Engle, R.F. & Russell J. (1998). Autoregressive Conditional Duration: A New Model
for Irregularly Spaced Transaction Data. Econometrica.
Engle & Kroner. (1995). Multivariate Simultaneous Generalized ARCH. Econometric
Theory (11, pp.122-150).
Engle & Lange. (2001). Measuring, Forecasting and Explaining Time Varying
Liquidity in the Stock Market. Journal of Financial Markets (4, pp. 113-142).
Engle & Susmel. (1993). Common Volatility in International Equity Markets. Journal
of Business and Economic Statistics (11, pp.167 – 176).
Lo, A.W. & C.A. MacKinlay. (1990). An Econometric Analysis of Nonsynchronous
Trading. Journal of Econometrics (45, pp.181-211).
Rosenberg & Engle. (1998). Empirical Pricing Kernels. Journal of Financial
Economics. (64).
Sullivan, R., Timmermann A., & White H. (1999). Data Snooping, Technical Trading
Rule Performance, and the Bootstrap. Journal of Finance (pp.1647-1692).
White, H. (1999). Bootstrap Snooper Reality Check. Econometrica.
b. Course objectives for the course (student – centered, behavioral focus)
Upon completion of this course, students will be able to:
Use financial data in their PhD research with the tools they need for state-of-the-art
empirical research; apply the econometric theory of financial time series analysis, with
an emphasis on recent developments; analyze selected recent works in financial
modeling with an emphasis on their empirical implications and analysis.
c. Course topic outline
I.
Forecasting Returns
II. Forecasting Volatility
III. Pricing and Hedging Options
IV. Extreme Values and Value-at-Risk
V. Asset Allocation
VI. Market Microstructure
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d. List of course assignments, weighting of each assignment, and grading/evaluation system
for determining a grade
5 Problem sets:
Midterm Exam:
Course Paper:
Final Exam:
25%
25%
25%
25%
Evaluation system is A for outstanding performance, B for acceptable performance, C
for inadequate performance, and F for failure.
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