Copulas with Applications in Finance
The financial and other industries currently have a shortage of people with the necessary data science skills to address problems relating to large and/or complex data sets. Nowadays financial institutions are confronted with an abundance of data, and so in order to maintain a competitive advantage it is imperative to have analysts with these necessary data science skills. This short course will address one of the topics needed to become a skilful data scientist.
This short course aims to equip participants with knowledge of the necessary underlying theoretical concepts relating to copulas required to effectively address real-world problems that arise in the financial sector. As a result, the participant will be able to model the dependence structures between financial variables and thereby negating the need to use the naïve assumption of independence that is often used.
NQF level 7 majoring in either Mathematics/Statistics/Engineering/Computer Science
Learning assumed to be in place:
NQF level 7
Course outcomes and the associated assessment criteria:
|After completion of this course, participants will:||Participant will be assessed on the following criteria:|
Assignments and participation
Method of assessment:
Learning objectives will be accomplished through the successful completion of assignments and participation in short course activities, proving insight into the topics at hand.
Mode of delivery:
Graduates and/or industry professionals working in fields that require data science and analytical skills.