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Corporate bonds, exchange rates and business strategy

Author

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  • Konstantina Vartholomatou
  • Konstantina Pendaraki
  • Athanasios Tsagkanos

Abstract

We examine the relationship between corporate bonds and exchange rates in the USA and Greece highlighting asymmetries and volatility among markets. A theoretical framework is constructed to treat the issue of corporate bonds. The employed methodology concerns the QARDL-ECM that is applied to non-stationary regressors. In Greece, our key findings point that changes in corporate bonds are mainly driven by changes in exchange rates. The quantile estimates show that the strength of long-run relationship increases as the risk of default for the country diminishes. In the USA, both long-run and short-run relationships between variables are defined. The changes in exchange rates are mainly driven by changes in corporate bonds. The quantile estimates exhibit a non-symmetrical pattern of the relationship which is a clear evidence of possible financing problems in enterprises. A key contribution concerns the suggestion of a sound policy for the enterprises for attaining stable growth in an environment of financial stress and asymmetry.

Suggested Citation

  • Konstantina Vartholomatou & Konstantina Pendaraki & Athanasios Tsagkanos, 2021. "Corporate bonds, exchange rates and business strategy," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 12(2), pages 97-117.
    • Handle: RePEc:ids:injbaf:v:12:y:2021:i:2:p:97-117
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    Citations

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    Cited by:

    1. Alshubiri, Faris, 2021. "Financial deepening indicators and income inequality of OECD and ASIAN countries," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    2. Mallick, Lingaraj & Behera, Smruti Ranjan & Murthy, R.V. Ramana, 2021. "Does the twin deficit hypothesis exist in India? Empirical evidence from an asymmetric non-linear cointegration approach," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    3. Chyan-Long Jan, 2021. "Detection of Financial Statement Fraud Using Deep Learning for Sustainable Development of Capital Markets under Information Asymmetry," Sustainability, MDPI, vol. 13(17), pages 1-20, September.

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