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Credit and debit value adjustment estimations in the data sparse South African market

Thesis (MCom)--Stellenbosch University, 2017.

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Main Author: De Jager, Louis Porter
Other Authors: Van der Merwe, Carel Johannes
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2017
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access_status_str Open Access
author De Jager, Louis Porter
author2 Van der Merwe, Carel Johannes
author_browse De Jager, Louis Porter
Van der Merwe, Carel Johannes
author_facet Van der Merwe, Carel Johannes
De Jager, Louis Porter
author_sort De Jager, Louis Porter
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MCom)--Stellenbosch University, 2017.
format Thesis
id oai:scholar.sun.ac.za:10019.1/100846
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:44:21.236Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2017
publishDateRange 2017
publishDateSort 2017
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
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source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/100846 Credit and debit value adjustment estimations in the data sparse South African market De Jager, Louis Porter Van der Merwe, Carel Johannes Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Statistics and Actuarial Science. Derivative securities -- South Africa Counterparty risk -- South Africa Financial statements -- Standards Credit value adjustment Debit value adjustment UCTD Thesis (MCom)--Stellenbosch University, 2017. ENGLISH SUMMARY : During 2014, the International Accounting Standards Board (IASB) implemented a new standard for measuring the fair value of assets through the International Financial Reporting Standards (IFRS) 13 guidance. The newly introduced guidelines have probed market participants to adjust their valuation of financial positions for material counterparty credit risk (CCR) in the over-thecounter (OTC) market Five different models are implemented in this research for the purpose of calculating the credit value adjustment (CVA) and debit value adjustment (DVA) of an interest rate swap portfolio between a South African corporate treasurer, Eskom, and a generic South African tier 1 bank. The models differ from simple to complex. The Monte Carlo (MC) simulation model is assumed to be the most accurate, since it involves the simulation of expected exposure and the modelling of the short-rate. Corporate treasurers do not always have the necessary resources to calculate CVA by means of a sophisticated approach. Due to input data and resource challenges, corporate treasurers need to consider creative alternative methods to include CCR in their fair value adjustments. Therefore, semi-analytic methods and input approximation methods were considered in this research. It was found that simpler semi-analytic approximation methods do not possess the complexity needed to deal with the complexity of netting and collateral agreements. They serve as good approximations to quickly estimate a ball-park CVA, but lack the accuracy of the MC based approach. AFRIKAANSE OPSOMMING : Die International Accounting Standards Board (IASB) het gedurende 2014 ‘n nuwe standard geimplementeer ten opsigte van die meting van die billike mark-waarde van bates onder die nuwe International Financial Reporting Standard (IFRS) 13 leiding. Hierdie nuwe leiding het mark belanghebbers gepeil om aanpassings te maak tot hul finansiele posisies ten opsigte van teenparty kredietrisko in die oor-die-toonbank mark. Vyf verskillende modelle word in hierdie studie geimplementeer vir die berekening van kredietwaardeaanpassing en debietwaardeaanpassing, van ‘n portefeulje bestaande uit rentekoers uitruilkontrakte tussen die Suid-Afrikaanse korporatiewe tesourier Eskom en ‘n generiese Suid-Afrikaanse vlak 1 bank. Die modelle wissel van eenvoudig tot kompleks. Die Monte Carlo model word aanvaar as die mees akkuraatste, vanwee sy komplekse onderliggende modellering van die kort-rentekoerse, asook sy onderliggende verwagte krediet blootstelling simulasie. Korporatiewe tesouriers beskik dikwels nie oor die nodige hulpbronne om kredietwaardeaanpassing s te bereken met ‘n gesofistikeerde model nie. As gevolg van data en ander hulpbron uitdagings, berus dit op die korporatiewe tesouriers om met kreatiewe alternatiewe voorendag te kom vir die hantering van kredietwaardeaanpassings tot hul finanisiele posisies. Dus moet semi-analitiese metodes en data beramings ondersoek word. In die studie word gevind dat hierdie eenvoudiger semi-analitiese metodes nie oor die nodige kompleksiteit beskik om komplekse netting en kollateraal kontrakte, wat met baie afgeleide instrumente gepaard gaan, te hanteer nie. Hulle dien egter as goeie metodes om vining ‘n beraming van kredietwaardeaanpassing te bereken, alhoewel hulle nie so akkuraat is soos die meer kompleke Monte Carlo en Swaption modelle nie. Masters 2017-02-13T09:31:22Z 2017-03-29T11:37:47Z 2017-02-13T09:31:22Z 2017-03-29T11:37:47Z 2017-03 Thesis http://hdl.handle.net/10019.1/100846 en_ZA Stellenbosch University xiv, 114 pages ; illustrations, includes annexures application/pdf Stellenbosch : Stellenbosch University
spellingShingle Derivative securities -- South Africa
Counterparty risk -- South Africa
Financial statements -- Standards
Credit value adjustment
Debit value adjustment
UCTD
De Jager, Louis Porter
Credit and debit value adjustment estimations in the data sparse South African market
title Credit and debit value adjustment estimations in the data sparse South African market
title_full Credit and debit value adjustment estimations in the data sparse South African market
title_fullStr Credit and debit value adjustment estimations in the data sparse South African market
title_full_unstemmed Credit and debit value adjustment estimations in the data sparse South African market
title_short Credit and debit value adjustment estimations in the data sparse South African market
title_sort credit and debit value adjustment estimations in the data sparse south african market
topic Derivative securities -- South Africa
Counterparty risk -- South Africa
Financial statements -- Standards
Credit value adjustment
Debit value adjustment
UCTD
url http://hdl.handle.net/10019.1/100846
work_keys_str_mv AT dejagerlouisporter creditanddebitvalueadjustmentestimationsinthedatasparsesouthafricanmarket