COURSE INFORMATION Course Title: MATHEMATICAL ECONOMICS

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
ECO 405	B	1	3	0	0	3	7.5

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Eglantina Hysa
Second 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:	Elective
Classroom and Meeting Time:
Course Description:	This course aims to focuses on the mathematical methods and models that are required to understand current economics and to investigate economic models. Mathematical models are developed in the context of economics. Their application is done in various fields of economics such as macroeconomics, microeconomics, international economics and so forth.
Course Objectives:	This course will be an overview of general mathematical methods which application in solving finance problems. The course will be focus in some well-known methods as optimization, some statistical e probability methods as Marcov chain, Monte-Carlo theory, game theory, queuing models and some introduction methods of market efficiency and options. International trade and international monetary economics theory and policy. The purpose is to help students understand the basics of mathematical methods and fields of their applications in economy. Topics are selected carefully to comprehensive ones. Specific concepts as arbitrage, delta hedging and Black- Scholes formula and martingales are news and in international programs of mathematical finance.

COURSE OUTLINE

Week	Topics
1	The transportion model and its variants
2	Net models.; Terminology of nets ; Shorterst path problem
3	The network representative of the projects
4	Game theory; the formulationof the two-person game.
5	The analysis of the Decision
6	Markov chains
7	Analysis of absorbing states.
8	Midterm
9	Model of queuing Systems
10	Economic analysis of the queuing.
11	Risk. Market efficiency. The use of opsions.
12	Trees and option princing.
13	Practicalities. Introduction.
14	Black Schols formula.

Prerequisite(s):
Textbook:	Taha, H., Operations research, an introduction, Pearson, Prentice Hall 2007
Other References:	1. Anderson, S.W. Quantitative Methods for Business, 2006 2. Bharucha - Reid, A.T. Elements of the Theory of Markov Processes and their Applications, 1997. 3. Paul Wilmott, Introduces Quantitative Finance, second edition. John Wiley & Sons, Ltd, 2004
Laboratory Work:
Computer Usage:
Others:	No

COURSE LEARNING OUTCOMES

1	Application of methods of mathematics to better understand the quantitative problems in management the economic problems.
2	Knowledge of main methods of mathematics in modern economy management.
3	Knowledge of the role and importance of mathematical methods and its impact in economic problems
4	Knowledge of specific concepts decision, optimization, option, hedging

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

No	Program Competencies	Cont.
Master of Science in Economics Program
1	Students apply advanced knowledge in economics	5
2	Students explain the interaction between related disciplines and economics	5
3	Students apply scientific methods to address economic problems	4
4	Students define existing theory in a specialized branch of economics	3
5	Students critically evaluate knowledge in economics and carry out advanced research independently	3
6	Students develop economic models and formulate policy options	3
7	Students make an original contribution to the discipline	12
8	Students effectively communicate in a variety of professional and academic contexts
9	Students will develop new strategic approaches for unexpected, complicated situations in economics and take responsibility in solving them	3
10	Students uphold and defend ethical values data collection, interpretation and dissemination	4
11	Students use advanced empirical analyses to address social problems
12	Students interact with professional networks in their field of specialization

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	35
Project	1	10
Final Exam	1	45
Attendance		10
	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	3	48
Mid-terms	1	10	10
Assignments			0
Final examination	1	15	15
Other	1	13	13
Total Work Load:			150
Total Work Load/25(h):			6
ECTS Credit of the Course:			7.5