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Participants gain hands-on experience with the portfolio credit risk engine, the Algorithmics component that calculates portfolio credit risk and bottom-up measures of integrated market and credit risks.
The course is aimed at quantitative analysts or capital managers with a credit risk focus; however, the significant hands-on emphasis may also make it of interest to non-quantitative business analysts.
DAY 1: PORTFOLIO CREDIT RISK ENGINE BASICS
The Portfolio Credit Risk Engine within Algo One
In this section we discuss the fundamental model upon which the engine is based and the location of the engine (PCRE) within the Mark-to-Future framework.
Inputs and Data
The inputs and data required to drive the portfolio credit risk model are varied. They are also dependent on the sophistication of the model to be adopted. Accordingly, we begin by examining the basic inputs, and address possible additional inputs and data second. Typical input categories include counterparty/obligor/name, exposure, credit quality, recovery rates, historical series and aggregation keys.
Hands-on Experience: Setup
This section familiarizes participants with the Setup Manager tool within PCRE. The objectives revolve around locating data and making associations within the data set.
Outputs and Measures
The contrast between the different classes of measures - absolute, additive, marginal, incremental, cumulative - and the details of the more complex calculations are the primary focus. Interpretation and application of the measures to business purposes is also discussed.
DAY 2: STRESS TESTING AND INTEGRATED RISK MEASUREMENT
Hands-on Experience: Results
This section familiarizes participants with the Results Viewer and Report Definitions Editor tools within PCRE. The objectives revolve around running the engine and effectively viewing results. A demonstration of the ARA reporting infrastructure will be provided upon prior request.
A look at the math behind - and hands-on usage of - an analytic approximation to PCR measures.
An interactive demonstration of the various methods of scenario analysis available within PCRE is followed by a short hands-on case study.
Integrated Market and Credit Risk
Exposure modelling is a key feature of portfolio credit risk measurement within Algo One. We explore the generation of exposures within MtF for use in PCRE calculations of integrated market and credit risks.