Evaluating macroeconomic models of credit risk: The Czech construction sector

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F14%3A86090356" target="_blank" >RIV/61989100:27510/14:86090356 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.ekf.vsb.cz/export/sites/ekf/rmfr/cs/sbornik/Sbornik_parts/Sbornik_II.dil.pdf" target="_blank" >http://www.ekf.vsb.cz/export/sites/ekf/rmfr/cs/sbornik/Sbornik_parts/Sbornik_II.dil.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Evaluating macroeconomic models of credit risk: The Czech construction sector

Popis výsledku v původním jazyce

The global financial crisis hit the Czech Republic in 2008 and caused significant drop in output with damaging impact to the Czech construction sector. Weakening macroeconomic fundamentals led to increase in credit risk in the Czech banking system. Thispaper investigates the credit risk of construction sector measured by non-performing loans ratio. The author employs three different approaches: moving-average (ARMA) model, autoregressive distributed lag (ARDL) model and unrestricted vector autoregressive (VAR) model. Data span covers period from 2002 to 2013 and includes non-performing loans and its macroeconomic determinants: real economic growth, inflation, real effective exchange rate growth and companies´ lending rates. The last part of the paperevaluates forecasting performance of the models. The results suggest that VAR model performs well in data fit but is rather poor in the forecasting exercise.

Název v anglickém jazyce

Evaluating macroeconomic models of credit risk: The Czech construction sector

Popis výsledku anglicky

The global financial crisis hit the Czech Republic in 2008 and caused significant drop in output with damaging impact to the Czech construction sector. Weakening macroeconomic fundamentals led to increase in credit risk in the Czech banking system. Thispaper investigates the credit risk of construction sector measured by non-performing loans ratio. The author employs three different approaches: moving-average (ARMA) model, autoregressive distributed lag (ARDL) model and unrestricted vector autoregressive (VAR) model. Data span covers period from 2002 to 2013 and includes non-performing loans and its macroeconomic determinants: real economic growth, inflation, real effective exchange rate growth and companies´ lending rates. The last part of the paperevaluates forecasting performance of the models. The results suggest that VAR model performs well in data fit but is rather poor in the forecasting exercise.

Druh

D - Stať ve sborníku

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Managing and Modeling of Financial Risks : 7th international scientific conference : proceedings : 8th-9th September 2014, Ostrava, Czech Republic. [Part I-III]

ISBN

978-80-248-3631-7

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

497-503

Název nakladatele

VŠB-Technical University of Ostrava

Místo vydání

Ostrava

Místo konání akce

Ostrava

Datum konání akce

8. 9. 2014

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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