Modelling market risk with SAS Risk Dimensions : a step by step implementation
Date
2005-03
Authors
Du Toit, Carl
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : University of Stellenbosch
Abstract
Financial institutions invest in financial securities like equities, options and
government bonds. Two measures, namely return and risk, are associated with
each investment position. Return is a measure of the profit or loss of the
investment, whilst risk is defined as the uncertainty about return.
A financial institution that holds a portfolio of securities is exposed to different
types of risk. The most well-known types are market, credit, liquidity, operational
and legal risk. An institution has the need to quantify for each type of risk, the
extent of its exposure. Currently, standard risk measures that aim to quantify risk
only exist for market and credit risk. Extensive calculations are usually required to
obtain values for risk measures. The investments positions that form the portfolio,
as well as the market information that are used in the risk measure calculations,
change during each trading day. Hence, the financial institution needs a business
tool that has the ability to calculate various standard risk measures for dynamic
market and position data at the end of each trading day.
SAS Risk Dimensions is a software package that provides a solution to the
calculation problem. A risk management system is created with this package and
is used to calculate all the relevant risk measures on a daily basis.
The purpose of this document is to explain and illustrate all the steps that should
be followed to create a suitable risk management system with SAS Risk
Dimensions.
Description
Thesis (MComm (Statistics and Actuarial Science))--University of Stellenbosch, 2005.
Keywords
Risk management -- Statistical methods, Financial institutions -- Risk management -- Statistical methods, SAS Risk dimensions, Dissertations -- Statistics and actuarial science, Theses -- Statistics and actuarial science, Assignments -- Statistics and actuarial science