Universidad Nacional de Colombia
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escudo colombia
Departamento de Matemáticas
First International Congress on
Actuarial Science and Quantitative Finance
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Mapa del sitio

Programme

PROGRAMME:

TUESDAY, JUNE 17

WEDNESDAY, JUNE 18

THURSDAY, JUNE 19

FRIDAY, JUNE 20

Short Courses

Prof. Monique Jeanblanc

Modelling Credit Risk events

Abstract:

The course will present the basic model of credit risk event.

In a first lecture, we  study various models of one default event.  We   explain the main differences between structural approach and  the intensity approach. We present  the seminal Cox model, based on a given intensity. Then, we extend the model to a general default time, and we show how to  obtain closed form formula for prices of defaultable zero-coupon and credit default swap.

The second lecture is devoted to multidefault models. If time permits, we  shall present  counterparty risk models, and explain the need of Counterparty Value Adjustment.

The course will be mainly based on the lecture available on

http://www.maths.univ-evry.fr/pages_perso/jeanblanc/cours/Credit_Risk_Modeling_Notes.pdf

Schedule:

Tu Jun 17, Wed Jun 18: 10:10 a.m.—12:45p.m.

 

 

Prof. Richard A. Davis

Heavy-tailed Time Series: Theory and Applications

Abstract:

Many time series, especially those that occur in finance and insurance, exhibit heavy-tails.  The analysis of such time series often require new tools.  The notion of multivariate regular variation is fundamental to modeling joint power-law behavior of  random vectors.  In this course we show that multivariate regular variation arises naturally in some common linear and non-linear time series models.  After introducing the basic concepts of heavy-tails in time series, we will focus on the extremogram, a flexible quantitative tool that measures various types of extremal dependence in a stationary time series.  In many respects, the extremogram can be viewed as an extreme-value analogue of the autocorrelation function (ACF) for a time series, which can be used in various phases of modeling fitting and confirmation.

Schedule:

Tu Jun 17, Wed Jun 18, Fri jun 20: 8:00a.m.—9:50 a.m.

 

 

Prof. Stephane Loisel

Enterprise Risk Management for insurance companies

Abstract:

Enterprise Risk Management (ERM) arose in the 1990’s and has quickly evolved to become a requirement for financial services firms and a common set of practices for non-financial firms. An enterprise wide internal model is a fundamental part of an enterprise risk management program for insurers and has also become the core of the forthcoming EU insurance Solvency II regulatory platform. Regulators are now expecting that insurance management not only have the capability to measure and manage their risks, but that they are relying upon these tools and processes as a major part of the decision making regime for the firm.

This course will look at both the management and risk evaluation aspects of ERM as they are found in the best ERM programs. These will be addressed from both a theoretical and practical point of view. The discussion of management of an ERM program will include ERM Objectives, risk preferences and the practices found in a good ERM program. The risk evaluation discussion includes nested simulations issues, as well as accelerated and simplified economic capital computation methods. It also features correlation aspects, contagion and correlation crises (sudden increase of correlation during exceptional events), customer behavior and competition issues. We will describe and analyze three types of model risk.

The course will also address the two elements of Solvency II that bring together the management and risk evaluation aspects of ERM: the Use Test and the ORSA.

Schedule:

Tu 17 Jun, Wed Jun 18 : 10:10am—12:45pm.

 

 

 

 

 

Prof. Edward W. (Jed) Frees

Regression Modelling with Actuarial Applications

Abstract:

Statistical techniques can be used to address new situations. This is important in a rapidly evolving risk management world. Analysts with a strong statistical background understand that a large data set can represent a treasure trove of information to be mined and can yield a strong competitive advantage. This course provides attendees with a foundation in multiple regression. Although no specific knowledge of risk management is presumed, the approach introduces applications where statistical techniques can be used to analyze real data of interest. In addition to the fundamentals, this course describes selected advanced statistical topics that are particularly relevant to actuarial and financial practice, including the analysis of longitudinal and two-part (frequency/severity) data.

Course Contents:

* Review of linear regression methods

* Logistic, Poisson, and Generalized linear modeling

* Two-part (frequency/severity) regression modeling

* Survey of longitudinal and panel models

* Regression methods in credibility and loss reserves

* Tips on communicating by making effective graphs

Target Audience: Practicing actuaries as well as researchers with a general knowledge of probability and statistics.

https://courses.moodle.wisc.ed<wbr>u/prod/course/view.php?id=2506 (Hit "Login as a guest")

Schedule:

Tu 17 Jun, Wed  Jun 18 , Fri Jun 20 Jun: 8:00—9:50 am

Universidad Nacional de Colombia
Av. Carrera 30 No. 45-03 Ciudad Universitaria - Edificio 404
Bogotá D.C. - Colombia