COURSE INFORMATION Course Title: FINANCIAL ECONOMETRICS I

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
BAF 333	B	5	2	0	2	3	5

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	M.Sc. Egla Mansi emansi@epoka.edu.al , Thursday and Friday, write me an email first
Second Course Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Compulsory
Study program: (the study for which this course is offered)	Bachelor in Banking and Finance (3 years)
Classroom and Meeting Time:	check timetable
Code of Ethics:	Code of Ethics of EPOKA University Regulation of EPOKA University "On Student Discipline"
Attendance Requirement:	75%
Course Description:	Description: BAF 333 - Financial Econometrics I: Techniques of Econometrics, estimating the basic linear model and hypothesis testing, empirical illustrations to contemporary economic issues. The objective of this course is to prepare students for basic empirical work in economics and finance. In particular, topics will include basic data analysis, regression analysis, testing, and forecasting. Students will be provided with the opportunity to use actual economic data to test economic theories.
Course Objectives:	The goal of this course is to provide students with knowledge of the elements of statistical inference, namely multivariate statistics and multivariate data analysis methods. Students will understand and be able to perform standard descriptive and inferential data analysis, investigate and test relationship between variables as well as specify, use and interpret multivariate models, including regression-type models. The course will also emphasize empirical analysis and focus on the use of data in practice along with the use of available statistical software. An empirical project is an integral part of the course. If possible, economics, financial, and business applications will be chosen during the course to reflect the interests and backgrounds of students.

BASIC CONCEPTS OF THE COURSE

1	Ordinary least squares
2	Regression
3	Panel data
4	Hypothesis Testing
5	Model Specification
6	Multicollinearity
7	Heteroskedasticity
8	Autocorrelation
9	Time Series
10	Endogeneity

COURSE OUTLINE

Week	Topics
1	Intro; Evaluation Method; Term Project & A brief Lecture on Types of Data
2	Descriptive Summary, Chapter 1 page: 1-30. Data Sources and Graphical Representation of Data 2. Summary Statistics for one Variable 3. Summary Statistics for two (or more) variables
3	Regression Analysis, Chapter 1 page: 1-30 1. What is regression analysis? 2. The Classical Model: Ordinary Least Squares (OLS) 3. Learning and Using Regression Analysis/Running Your Own Project 4. Practical issues: Reading Computer Output 5. The Classical Model: Assumptions and Properties 6. Hypothesis Testing
4	Ordinary Least Squares, Chapter 2 page: 35-63 1. What is regression analysis? 2. The Classical Model: Ordinary Least Squares (OLS) 3. Learning and Using Regression Analysis/Running Your Own Project 4. Practical issues: Reading Computer Output 5. The Classical Model: Assumptions and Properties 6. Hypothesis Testing
5	Assymptotic theory/properties and testing in regression, Chapter 3, page:65-89 1. What is regression analysis? 2. The Classical Model: Ordinary Least Squares (OLS) 3. Learning and Using Regression Analysis/Running Your Own Project 4. Practical issues: Reading Computer Output 5. The Classical Model: Assumptions and Properties 6. Hypothesis Testing
6	Model specification, Chapter 4, page:92-108 1. Choosing the Variables in a Regression 2. Including and Interpreting Categorical Variables 3. Choosing the Functional Form
7	Model specification and closing functional form, Chapter 4, page:92-108 1. Choosing the Variables in a Regression 2. Including and Interpreting Categorical Variables 3. Choosing the Functional Form
8	How to write a research paper and review for midterm, Chapter 11, page:340-358 1. Choosing a Research Project 2. Data Management
9	Midterm
10	Heteroskedasticity, Chapter 8-10, page: 221-337 1. Outliers 2. Multicollinearity 3. Heteroskedasticity and Autocorrelation 4. Lagged Dependent Variables and Time Series
11	Autocorrelation and Lagged dependent variable (Time Series), Chapter 12, page:364-385 1. Outliers 2. Multicollinearity 3. Heteroskedasticity and Autocorrelation 4. Lagged Dependent Variables and Time Series
12	Transformations, Endogeneity and Instrumental Variables, Chapter 16, page 465-484: Miscellaneous (some topics could be replaced/extended base on the class response) 1. Discontinuity design, diff-in-diff 2. Sensitivity issues, using robustness approach in the analysis 3. Introduction to non-parametric methods 4. Collecting data – introduction to survey data
13	Project Presentations
14	Project Presentations + Review

Prerequisite(s):	Statistics I and II
Textbook(s):	Studenmund (2021): Using Econometrics: A Practical Guide, 7th edition, Pearson. The website for the book (www.pearsonhighered.com/studenmund) includes the datasets mentioned in the book formatted for use in Stata (and other programs). It also includes additional interactive regression learning exercises.
Additional Literature:	Wooldridge, J.M. (2003) Introductory Econometrics: A Modern Approach, 2nd ed, Thomson/South-Western. (Good text book, but more technical) Bruce Hansen (2022), Econometrics
Laboratory Work:	yes
Computer Usage:	yes
Others:	No

COURSE LEARNING OUTCOMES

1	The student should be able to focus the nature of Econometrics and apply the basic econometric techniques in different studies.
2	The student should be able to estimate and interpret econometric models.
3	The student should be able to check the robustness and specification of the econometric models.
4	The student should be able to apply fundamental econometric principles to real life and scientific problems as well as test economic theories.
5	Learn how to diagnose and check the key assumptions of regression models, including linearity, independence of errors, homoscedasticity, and normality of residuals.
6	Focus on the challenges and methods associated with making causal inferences from observational data, including issues related to endogeneity, omitted variables, and instrumental variables.
7	Gain hands-on experience with econometric software packages (e.g., R, Python, Stata) to perform data analysis and estimate econometric models.
8	Develop the ability to communicate econometric results effectively through written reports, including clear explanations of methodology, findings, and policy implications.
9	Understand the ethical considerations and potential biases that can arise in econometric analysis, and learn how to address them responsibly.
10	Apply econometric techniques to answer economic research questions, analyze economic policies, and contribute to empirical economic research.

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Bachelor in Banking and Finance (3 years) Program
1	The students gain the ability to look at the problems of daily life from a broader perspective with an increased awareness of the importance of moral/ethical considerations and professional integrity in the workplace.	5
2	They develop their knowledge and understanding of banking and finance including concepts, theories, and analytical tools that serve both in national and international markets.	4
3	They gain an understanding of the role of financial management in business firms and the essentials of corporate finance and further develop their knowledge in the field.	3
4	They are able to apply valuation models to estimate the price of different financial assets, measure risk and describe the risk-return tradeoff.	5
5	They are provided with the knowledge and understanding of the regulatory framework and functioning of banking system and central banking as well as international banking system.	3
6	They are able to understand and use fundamental economic theories and tools to solve economic problems in banking and financial services industry.	4
7	They have the ability to develop and utilize accounting, financial and economic data as well as other information to solve different business problems by making use of basic mathematical and statistical models.	5
8	They are expected to develop their numerical and IT skills as well as knowledge of databases in order to address the significant development in the delivery and use of financial services known as FinTech.	4
9	They develop their ability to think critically, do research, analyze, interpret, draw independent conclusions, and communicate effectively, both individually and as part of a team.	5
10	They are provided with opportunities to acquire the necessary skills and competencies to develop professionalism in the banking and financial services industry or to move on to further study within the discipline.	4

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Homework	4	5
Midterm Exam(s)	1	25
Project	1	25
Final Exam	1	30
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	4	64
Hours for off-the-classroom study (Pre-study, practice)	16	2	32
Mid-terms	1	6	6
Assignments			0
Final examination	1	10	10
Other	1	13	13
Total Work Load:			125
Total Work Load/25(h):			5
ECTS Credit of the Course:			5

CONCLUDING REMARKS BY THE COURSE LECTURER

If a student has a misbehavior report then automatically that student gets zero points for that exam. The same rule goes if the projects they submit have high plagiarism