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    <link>https://cris.library.msu.ac.zw//handle/11408/6573</link>
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        <rdf:li rdf:resource="https://cris.library.msu.ac.zw//handle/11408/6576" />
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    <dc:date>2026-05-24T23:50:05Z</dc:date>
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  <item rdf:about="https://cris.library.msu.ac.zw//handle/11408/6576">
    <title>Credit risk modelling by commercial banks in Southern Africa in the presence of market friction (1997 - 2020)</title>
    <link>https://cris.library.msu.ac.zw//handle/11408/6576</link>
    <description>Title: Credit risk modelling by commercial banks in Southern Africa in the presence of market friction (1997 - 2020)
Authors: Matanda Ephraim
Abstract: The research proposes and examines new structural equity, risk of default, expected loss, and &#xD;
profitability models for banks in frictional and fuzzy financial markets. It is motivated by the need &#xD;
to fill the shortcomings of structural probability-based asset and credit risk models such as Merton &#xD;
(1974) and Black and Scholes (1973) that are characterised by unrealistic assumptions such as &#xD;
crisply precise and constant risk-free rates of return and asset volatilities. The problem investigated &#xD;
here specifically proposes new Kealhofer-Merton-Vasicek (KMV) and vector auto-regression &#xD;
(VAR) models for the valuation of equities, risks of default, expected losses, and profitability of &#xD;
banks respectively which are extended for both market friction represented by transaction costs &#xD;
and uncertainty modelled by fuzziness. The respective novel valuation models are then validated &#xD;
using cross-sectional financial data of listed banking corporations drawn from several emerging &#xD;
economies in Southern Africa. The results from the proposed equity and credit risk models are &#xD;
fairly stable, reliable, and consistent compared to those from conventional or structural credit risk &#xD;
models currently used for bank valuations in the markets. Therefore these proposed models are &#xD;
relevant in that they fairly capture practical conditions faced by banks in emerging markets that &#xD;
influence their equity, risk metrics, and credit exposures in their quest to improve capitalisation, &#xD;
financial performance, and shareholders' wealth. The study recommends that banks in frictional &#xD;
and fuzzy financial markets, such as those in emerging economies can adopt and implement the &#xD;
proposed models to even out under and overestimation errors caused by unrealistic assumptions &#xD;
underlying the structural models currently used worldwide.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
    <dc:creator>Matanda Ephraim</dc:creator>
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