HOFSTRA UNIVERSITY
Spring 1999FRANK G. ZARB SCHOOL OF BUSINESS
"to provide students with a perspective on the integration of the functional areas of business,
while maximizing the use of analytical skills and knowledge for decision making in a contemporary
global business environment"
DEPARTMENT OF FINANCE
FINANCE 304
ADVANCED RESEARCH SEMINAR IN FINANCE
(graduate course)
INSTRUCTOR’S NAME Dr. Ehsan Nikbakht
OFFICE HOUR
LOCATION OF OFFICE 116A Weller Hall
PHONE EXTENSION ON CAMPUS 463-5679
E-MAIL ADDRESS FINEZN@HOFSTRA.EDU
GENERAL INFORMATION
Location of Department Office 221 Weller Hall
Telephone number of Department 463-5698
Department Chairperson Dr. Edward Zychowicz
DESCRIPTION OF COURSE
Students write an integrative paper on an assigned topic based on secondary research and then formulate a written primary data research design to investigate a specific key issue. They must formulate research questions and hypotheses, construct survey instruments and experimental designs, draft sample plans, outline data handling procedures, and prepare a comprehensive research proposal, furnishing justifications for its theoretical as well as practical significance. An oral presentation of each project is required at the conclusion of the semester.
(NOTE: FIN 306-308 may be offered in place of 304).
PREREQUISITES OF COURSE
Completion of all core competency courses, 21 s.h. of advanced core courses or above (including QM 210, IB 219, and at least 6 s.h. of the required 15 s.h. in the area of concentration, and permission of department chairperson. Full-time students may take IB 219 as a corequisite.
REQUIRED TEXT
Multivariate Data Analysis with Readings, by Joseph Hair, Ralph Anderson and Ronald Tatham, (New York: MacMillan Pub. Co.), Latest Edition. (HAT)
SAS on VAX (free manual)
OUTCOME OBJECTIVES AND METHODS OF ACHIEVING THE OBJECTIVES
This course will focus on all phases of business research in general, and research in the field of finance in particular. Discussions will include hypothesis development, research problems, data generation, data handling, statistical analysis and making conclusions. The objective of the course is to acquaint the M.B.A. student with the practice of research methods as it applies in the business setting and the area of finance. Students will be introduced to the SAS, which is a powerful computer statistical package to solve finance-related inquiries. Articles in the field of finance will be reviewed and their methodologies and contributions will be critically evaluated.
Significant written and oral communication skills (for example, class participation, presentations, team projects, etc.) will be emphasized.
METHODS OF EVALUATING STUDENTS
GRADING SYSTEM
Class preparation and discussion, including
computer assignments 20%
Research Project 50%
Final Exam 30%
TOTAL 100%
SCHOOL OF BUSINESS POLICY ON MAKEUP EXAMINATIONS
To be eligible for a makeup examination, a student must submit to the instructor written documentation of the reason for missing a scheduled examination due to medical problems or death of an immediate family member. The instructor (not the student) determines whether and when a makeup is to be given. If a makeup examination is to be given, the instructor will determine the type of makeup examination. If the student misses (for any reason) the scheduled makeup examination, additional makeups are not permissible.
UNIVERSITY POLICY ON INCOMPLETE GRADES
Incomplete work must be completed and submitted to the instructor for a passing or failing grade before the end of the next regular semester.
COURSE CONTENT AND ACTIVITIES
HAT, Chapter 1 - Introduction
HAT, Chapter 2 - Multiple Regression Analysis (MRA)
SESSION 4 HAT, Chapter 3 - Multiple Discriminant Analysis (MDA)
SESSION 5 Computer Work (SAS Programs)
SESSION 6 Your computer assignments on MRA and MDA are due and will be discussed in class
SESSION 7 HAT, Chapter 4 - Multivariate Analysis of Variance (MAV)
SESSION 8 HAT, Chapter 4 - MAV
SESSION 9 HAT, Chapter 6 - Factor Analysis
SESSION 10 Selected Readings in Finance
SESSION 11 PRESENTATIONS
SESSION 12 Selected Readings in Finance
SESSION 13 PRESENTATIONS
SESSION 14 PRESENTATIONS
SESSION 15 A CUMULATIVE FINAL EXAM
SELECTED BIBLIOGRAPHY
Balsley and Clover, BUSINESS RESEARCH METHODS, Grid Publishing, 1986.
Bateman and Ferris, METHOD AND ANALYSIS IN ORGANIZATION RESEARCH, Reston Publishing, 1984.
Brewer, M. and Crano, William, PRINCIPLES AND METHODS OF SOCIAL RESEARCH, Allyn and Bacon, Inc., 1986.
Dunn, O.J., et.al., APPLIED STATISTICS: ANALYSIS OF VARIANCE AND REGRESSION, John Wiley and Sons, 1987.
SELECTED BIBLIOGRAPHY (cont'd)
Emory, William, BUSINESS RESEARCH METHODS, Richard D Irwin. 1986
Neter, John, etal. APPLIED REGRESSION MODELS, Irwin 1989.
Puri, M.L. and Sen, P.K., NON-PARAMETRI METHOD IN MULTIVARIATE ANALYSIS, Wiley, 1971.
SAS STATISTICAL PROCEDURES, SAS Institute, 1985.
SAGE PUBLICATIONS, The Publications of Professional Social Science:
1 - ANALYSIS OF VARIANCE by Gudmund R. Iversen and Helmut Norpoth
2 - OPERATIONS RESEARCH METHODS by Stuart Nagel with Marian Neef
3 - CAUSAL MODELING by Herbert B. Asher
4 - TESTS OF SIGNIFICANCE by Ramon E. Henkel
5 - COHORT ANALYSIS by Norval D. Glenn
6 - CANONICAL ANALYSIS AND FACTOR COMPARISON by Mark S. Levine
7 - ANALYSIS OF NOMINAL DATA by H.T. Reynolds
8 - ANALYSIS OF ORDINAL DATA by David K. Hildebrand, James D. Laing, and Howard Rosenthal.
9 - TIME SERIES ANALYSIS: Regression Techniques by Charles W. Ostrom, Jr.
10 - ECOLOGICAL INFERENCE by Laura Irwin Langbein and Allan J. Lichtman
11 - MULTIDEMINSION SCALING by Joseph B. Kruskal and Myron Wish
12 - ANALYSIS OF COVARIANCE by Albert R. Wildt and Olli Ahtola
13 - INTRODUCTION TO FACTOR ANALYSIS by Jes-On Kim and Charles W. Mueller
14 - FACTOR ANALYSIS by Jae-On Kim and Charles W. Mueller
15 - MULTIPLE INDICATORS: An Introduction, by John L. Sullivan and Stanley Feldman
16 - EXPLORATORY DATA ANALYSIS by Frederick Hartwig with Brian E. Dearing
17 - RELIABILITY AND VALIDITY ASSESSMENT by Edward G. Carmines and Richard A. Zeller
18 - ANALYZING PANEL DATA by Gregory B. Markus
19 - DISCRIMINANT ANALYSIS by William R. Klecka
20 - LOG-LINEAR MODELS by David Knoke and Peter J. Burke
21 - INTERRUPTED TIME-SERIES by David McDowell, Richard McCleary, Errol E. Meidinger, and Richard A. Hay, Jr.
22 - APPLIED REGRESSION: An Introduction by Michael S. Lewis-Beck
23 - RESEARCH DESIGNS by Paul E. Spector
24 - UNIDIMENSIONAL SCALING by John P. Mciver and Edward G. Carmines
25 - MAGNITUDE SCALING by Milton Lodge
26 - MULTIATTRIBUTE EVALUATION by Ward Edwards and J. Robert Newman
27 - DYNAMIC MODELING: An Introduction by R. Robert Huckfeldt, C.W. Kohfeld and Thomas W. Likens
28 - NETWORK ANALYSIS by David Knoke and James H. Kukinski
29 - INTERPRETING AND USING REGRESSION by Christopher H. Achen
30 - TEST ITEM BIAS by Steven J. Osterind
31 - MOBILITY TABLES by Michael Hout
32 - MEASURES OF ASSOCIATION by Albert M. Liebetrau
Assignment #1
BIVARIATE ANALYSIS (PAIRED T-TEST)
Using the program in the SAS manual, (PG.799) please select two mutual funds, collect their quarterly returns for a period of six years and run the following tests:
In three pages (typed and double-spaced) interpret your results and evaluate the strength of t-test as a methodology for similar inquiries. List all the assumptions and limitations of t-tests (paired and non-paired) in your report.
Assignment #2
MULTIPLE REGRESSION
Using the program in the SAS manual, please develop a hypothetical relationship between a dependent financial variable and several meaningful independent variables including a dummy variable if you wish. Your program file should be made separately from your data file. Include the following "options" on your program: ALL, standardized regression coefficients, Durbin-Watson and plots of residuals.
In three pages (typed and double-spaced) answer the following questions: