Credit Ratings and Liquidity Risk for the Optimization of Debt Maturity Structure

Abstract

The purpose of this study is to examine the relationship between credit rating scales and debt maturity choices. A liquidity hypothesis is used to formulate the testable proposition and conceptual framework. Generalized linear model (GLM) and pooled ordinary least square (OLS) are utilized by SAS programming to test the proposed hypothesis. Other different estimation techniques are also used for robust evidence. Results suggest that companies with high and low ratings have a shorter debt maturity. Companies with medium ratings have longer debt maturity structure. Liquidity shows a negative association with longer debt maturity structure. It is evident that at high rating scale with high liquidity, and at lower rating scales with lower liquidity firms have a shorter debt maturity. Mid rated firms with a low probability of refinancing risk show longer debt maturity structure. Considering refinancing risk by Asian companies make the nonlinear relationship between credit ratings and debt maturity choices. Results suggest the importance of credit ratings for the optimization of debt maturity structure of Asian firms, which was totally overlooked by the past studies. The findings of this study are consistent with the liquidity hypothesis. The findings also motivating financial managers and investors to consider credit ratings as a measure of financial constraints.

Multiagent Decision-Making of Enterprise Debt Restructuring Based on Fuzzy-Set Qualitative Comparative Analysis

“…Shortterm borrowings have relatively short terms, while longterm investments have longer terms to generate returns, putting companies under enormous cash fow pressure. Relevant studies have found that the higher the proportion of short-term borrowings in the total assets of the company, the greater the risk of the enterprise's stock price crash and the greater the liquidity risk when the enterprise's borrowings are repaid [16]. Te short-term loans of enterprises will signifcantly afect the asset quality and proftability of enterprises, resulting in an imbalance in the fnancing structure of enterprises and increasing the risk of enterprises falling into a fnancial crisis [17,18].…”

Assessing the Scholarly Landscape: A Bibliometric Journey through Credit Rating Agency Research

“…Credit Rating Agencies (CRAs) play a crucial role in the financial markets by providing independent assessments of borrowers' creditworthiness (Rowe, 2020), (Xiaodie & Cai, 2020). Investors, lenders, and other market participants use these assessments to measure the risk associated with investing or lending to a particular entity (Sajjad & Zakaria, 2018), (Xiaodie & Cai, 2020). Rating agencies give useful and credible information about performance and creditworthiness of companies, which aids in reducing information asymmetry between lenders and borrowers (Machek & Hnilica, 2013).…”

“…Their influence is derived from the rating they produce is utilized by investors and market participants to make informed decisions (Machek & Hnilica, 2013), (Xiaodie & Cai, 2020). These agencies not only assess the creditworthiness of entities but also have an impact on financial market regulation (Sajjad & Zakaria, 2018). With the rise of international credit markets, the importance of credit rating agencies has increased dramatically (Machek & Hnilica, 2013).…”

“…A notable factor is the conflict of interest arising from the business model of credit rating agencies (Weitzner & Peridis, 2011), (Xiaodie & Cai, 2020). The issuer-pays model of income creates potential influence to assign more favourable ratings in order to attract business from the rated firms (Sajjad & Zakaria, 2018), (Xiaodie & Cai, 2020). This conflict of interest has the potential to compromise the objectivity and independence of the ratings provided by these agencies (Rowe, 2020).…”

Risk Analysis and Portfolio Modelling

“…They suggest that older apartments with just one room are more likely to experience risk reduction benefits in the context of a housing portfolio. Sajjad and Zakaria (2018) examine the relationship between credit rating scales and debt maturity choices using a sample of non-financial listed Asian companies rated by Standard and Poor's rating agency. The non-financial companies are chosen from eight selected Asian regions: Japan, South Korea, Singapore, China, Hong Kong, Indonesia, Malaysia, and India.…”