The relationship between sovereign credit rating and trends of macroeconomic indicators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F04274644%3A_____%2F19%3A%230000509" target="_blank" >RIV/04274644:_____/19:#0000509 - isvavai.cz</a>

Výsledek na webu

<a href="https://is.vsfs.cz/auth/repo/7739/Clanek_publikovany.pdf" target="_blank" >https://is.vsfs.cz/auth/repo/7739/Clanek_publikovany.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21511/imfi.16(3).2019.26" target="_blank" >10.21511/imfi.16(3).2019.26</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The relationship between sovereign credit rating and trends of macroeconomic indicators

Popis výsledku v původním jazyce

The sovereign credit rating provides information about the creditworthiness of a given country and thereby serves investors as a tool for deciding which financial assets merit the investment of their funds. Given that the determination of a sovereign credit rating is a highly complex and challenging activity. Specialized agencies are involved in determining the rating. And yet it remains worthwhile to analyze their work and seek out easily accessible tools for generating estimates of such ratings. The objective of this article is to explore whether sovereign credit rating can be reliably estimated using trends of selected macroeconomic indicators, despite the fact that sovereign credit rating is most likely influenced by factors other than economic factors. This can be used for strategic considerations at national and multinational level. The relationships between sovereign credit rating and the trends of macroeconomic indicators were examined using statistical methods, linear multiple regression analysis, cumulative correlation coefficient, and non-traditional multicollinearity. The data source used is comprised of selected World Bank indicators meeting the conditions of completeness and representativeness. The data set showed a cumulative correlation coefficient value greater than 95%, however at a 100% multicollinearity. This is followed by the gradual elimination of indicators, but even this did not achieve acceptable values. From this, it can be concluded that rating levels are not explainable solely by the trends of economic indicators, but that other influences, e.g. political, were applied in their creation. Nonetheless, the fact that the statistical model yielded acceptable results for 5 and fewer indicators allowed a regression equation to be found that gives good estimates of a country’s rating. This allows, for example, relatively easy forecasting of ratings by forecasting the development of selected macroeconomic indicators.

Název v anglickém jazyce

The relationship between sovereign credit rating and trends of macroeconomic indicators

Popis výsledku anglicky

The sovereign credit rating provides information about the creditworthiness of a given country and thereby serves investors as a tool for deciding which financial assets merit the investment of their funds. Given that the determination of a sovereign credit rating is a highly complex and challenging activity. Specialized agencies are involved in determining the rating. And yet it remains worthwhile to analyze their work and seek out easily accessible tools for generating estimates of such ratings. The objective of this article is to explore whether sovereign credit rating can be reliably estimated using trends of selected macroeconomic indicators, despite the fact that sovereign credit rating is most likely influenced by factors other than economic factors. This can be used for strategic considerations at national and multinational level. The relationships between sovereign credit rating and the trends of macroeconomic indicators were examined using statistical methods, linear multiple regression analysis, cumulative correlation coefficient, and non-traditional multicollinearity. The data source used is comprised of selected World Bank indicators meeting the conditions of completeness and representativeness. The data set showed a cumulative correlation coefficient value greater than 95%, however at a 100% multicollinearity. This is followed by the gradual elimination of indicators, but even this did not achieve acceptable values. From this, it can be concluded that rating levels are not explainable solely by the trends of economic indicators, but that other influences, e.g. political, were applied in their creation. Nonetheless, the fact that the statistical model yielded acceptable results for 5 and fewer indicators allowed a regression equation to be found that gives good estimates of a country’s rating. This allows, for example, relatively easy forecasting of ratings by forecasting the development of selected macroeconomic indicators.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50200 - Economics and Business

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Investment Management and Financial Innovations

ISSN

1810-4967

e-ISSN

1812-9358

Svazek periodika

16

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

UA - Ukrajina

Počet stran výsledku

15

Strana od-do

292-306

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85073554634