UMH - INVESTMENT PORTFOLIO MANAGEMENT

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INVESTMENT PORTFOLIO MANAGEMENT

Course

Code: 1485

Degree: Bachelor's in Business Statistics

Faculty of Social and Legal Sciences of Elche

Year: Year 4 of Bachelor's in Business Statistics

Semester: Fall

Type: Required

Language: Spanish

ECTS credits: 6

Lecture: 3

Laboratory: 3

Hours: 150

Directed: 60

Shared: 25

Autonomous: 65

Subject matter: Financial Analysis

Module: Economics and Business

Department: Statistics, Mathematics and Informatics

Area: STATISTICS AND OPERATIONS RESEARCH

Course instructors are responsible for the course content descriptions in English.

Description

Introduction to risk management: definition, history, fundamentals of credit and operational risk. Models for managing risk and credit risk. Analysis of value at risk from investment portfolios. Liquidity risk management in investment portfolios. Credit risk factors and insolvency estimation.

Faculty

Name	Coordinator	Lecture	Laboratory
SAINZ-PARDO AUÑON, JOSE LUIS	■	■	■

Competencies and learning outcomes

General competencies

Capacity to identify, interpret, formulate, and resolve basic problems within the branch of social and legal sciences.
Capacity for planning, organizing, directing, and controlling systems and processes within a framework that guarantee respect for the values, rights and basic principles of the legal system, business competitiveness, protection and conservation of the environment, and sustainable development in the corresponding field.
Ability to implement efficient tools for troubleshooting within the branch of social and legal sciences.
Capacity to evaluate, optimize, and compare criteria in decision making.
Ability to communicate in formal, graphic, and symbolic styles, as well as with oral and written forms of expression.
Ability to work with multidisciplinary and multicultural teams.
Ability to update knowledge within the branch of social and legal sciences.
Disposition of methodologies and efficient self-learning skills for adapting to and updating new skills and scientific advances, as well as to changing needs in order to adopt an aptitude for innovation and creativity in practicing the profession.

Specific competencies

Skills for analytically and computationally solving mathematical problems that may arise in the statistical analysis of data.
Capacity for formulating hypotheses, critically collecting and assessing information to solve real problems following the scientific method.
Capacity for the development, construction, validation, review, and interpretation of statistical models and operations research to organize, interpret, and communicate information in the decision making process.
Ability to think and reason quantitatively.
Ability to develop and/or simulate forecasts and scenarios in environments of uncertainty.
Acquire the basic training for conducting research activities.
Ability to diagnose the company's financial situation to assess profitability or to design investment plans.

Objectives (Learning outcomes)

01Know the financial vocabulary.
02know the mathematical tools in the Financial Analysis context
03To solve analytically financial problems.
04Solve computationally Financial problems.
05Build mathematical programming models in the optimization portfolio.
06Interpretar y comunicar la información obtenida en el proceso de toma de decisiones, en el problema de optimización de una cartera de inversión.
07Analyze historical series of financial assets.
08Evaluate the performance and the expected revenue of a given portfolio.
09Acquire the basic training for research activities.

Teaching units

Association between objectives and units

Objective/Unit	U1	U2	U3
01
02
03
04
05
06
07
08
09

Schedule

Week	Teaching units	Directed hours	Shared hours	Autonomous hours	Total hours
1	U1	4	1	3	8
2	U1	4	1	3	8
3	U1	4	1	3	8
4	U1	4	1	4	9
5	U1	4	1	4	9
6	U1	4	2	4	10
7	U1	4	2	4	10
8	U1	4	2	5	11
9	U2	4	2	5	11
10	U2	4	2	5	11
11	U3	4	2	5	11
12	U3	4	2	5	11
13	U3	4	2	5	11
14	U3	4	2	5	11
15	U3	4	2	5	11

Basic bibliography

Complementary bibliography

Software

Microsoft Office 2010
R 2.10
R Commander

Methodology and grading

Methodology

Case studies: Learning through the analysis of actual or simulated cases in order to interpret and resolve them by employing various alternative solution procedures.
Cooperative learning: Develop active learning through cooperative working strategies among students and promote shared responsibility to reach group goals.
Lecture: Pass on knowledge and activate cognitive processes in students, encouraging their participation.
Problem-based learning: Develop active learning strategies through problem solving that promote thinking, experimentation, and decision making in the student.
Project-based learning: Realization of a project to solve a problem, applying acquired learning and promoting abilities related to planning, design, performing activities, and reaching conclusions.
Solving exercises and problems: Exercise, test, and apply previous knowledge through routine repetition.

Grading

The final grade is obtained as follows:
0.8 EF +0.2 EC,
where
EF = final exam qualification (0-10);
EC = qualification computer practices (0-10). Those who do not complete the attendance will be assessed against a practical test by computer. The practical exam is valid only for the session in which the examination is performed;

To PASS THE COURSE must be obtained at least 5 points in EF, 4 in EC, and a final score equal to 5 points or above.

Research: INVESTMENT PORTFOLIO MANAGEMENT