UEH Standard programs in English (20% English)

Brief Course Description

1. Course Title:

Risk Analysis & Modelling

2. Language of Instruction:

Tiếng Việt

3. Course Code:

FIN505087

4. Credits:

3

5. Course Objectives:

The Risk Analysis and Modelling course provides the learners the in-depth knowledge and practical skills needed to analyse, evaluate, and model risks in the financial sector. Specifically, this course aims to: - Help learners master the concepts related to risk and modelling, including common types of risks such as market risk, credit risk, and operational risk. - Use quantitative methods to analyse and evaluate the level of risk in real-world situations, including collecting, processing, and interpreting risk data. - Learn how to build and apply mathematical, statistical, and computational models to simulate and predict risk scenarios. This includes the use of popular modelling tools and software. - Help learners learn how to forecast risks and analyse different scenarios based on data modelling, thereby making effective risk management decisions. - Learners will learn how to test and evaluate the effectiveness of the models they have built and adjust and improve them to ensure accuracy and practical applicability. - Learners will be introduced to modern risk analysis and modelling software, thereby improving their practical skills and ability to apply knowledge to real-world situations.

6. Brief Description of Course Content:

This course explores quantitative risk measurement and modeling methods. It provides students with an in-depth understanding of market risk analysis from a practical and technical perspective. Topics covered include pricing and return attributes, univariate and multivariate models for risk forecasting, risk metrics, making and evaluating risk forecasts, and simulation.

After completion of this course, students will be able to understand the theoretical and technical concepts used in market risk analysis. In addition, the course will enable students to use programming language tools in quantitative risk management. This will enable students to address practical risk management problems from a quantitative perspective.