Keyword

Country risk, company performance, ROE, machine learning algorithms

Abstract

          Managing risk is important. Organizations are starting to see the value of, or asking for strategic solutions to managing the risk. Risk refers to a deviation from what the organization plans or expects. Risk has an upside (opportunity), as well as a downside, the potential negative impact to an asset. This type of risk (loss) can prevent companies from achieving strategic goals. Organizations can turn risks into opportunities through effective risk management.
          For public companies which have subsidiaries in many countries, one of the risks should be managed is country risk. Country risk is defined as the risk a foreign government will default on its bonds or other financial commitments. Country risk also refers to the broader notion of degrees to which political and economic unrest affects the securities of issuers that do businesses in a particular country.
          In this research, we analyze the effect of country risk on company performance. Moreover, we employ linear regression to model the effect and the result shows country risk has a significant negative influence on Return on Equity (ROE). We also build nine models to predict country risk ratings based on country risk reports by utilizing machine learning algorithms. Furthermore, decision tree algorithm has the highest accuracy 31.25% on our dataset. Finally, our results show that, firstly, international companies who have overseas subsidiaries can benefit from using country risk as a tool to measure returns. Secondly, decision tree algorithm should be utilized to help decision makers determine country risks based on country reports; however, the effect of time-series data set into the machine learning algorithms still needs more investigations.


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References
  1. Barber, D. 2012. Bayesian Reasoning and Machine Learning. Cambridge University Press.
  2. Blei, D. M., Ng, A. Y., and Jordan, M. I. 2003. Latent Dirichlet Allocation. The Journal of Machine Learning Research 3: 993-1022.
  3. Brigham, E. F., and Gapenski, L. C. 1993. Intermediate Financial Management 4th Edition. Fort worth Dryden Press.
  4. COSO. 2004. Enterprise Risk Management – Integrated Framework. Executive Summary. www.coso.org. 
  5. Damodaran, A. 2016. Equity Risk Premiums (ERP): Determinants, Estimation and Implications – The 2016 Edition. 
  6. Damodaran, A. 2017. Country Default Spreads and Risk Premiums. 
  7. Erb, C. B., Harvey, C. R., and Viskanta, V. E. 1996. Expected Return and Volatily in 135 Countries. The Journal of Portfolio Management: 46-58.
  8. Fan, W., Wallace, L., Rich, S., and Zhang, Z. 2006. Tapping the Power of Text Mining. Communications of the ACM.
  9. Handayani, D., Korompot, N., and Hadjaat, M. 2011. Analisis Kinerja Keuangan Berdasarkan Rasio Profitabilitas Pada PT.Bhimex di Samarinda. Publikasi Ilmiah Vol 1, No 1. 
  10. Hearst, M. 2003. What Is Text Mining? Retrieved from Marti A. Hearst's Personal Website http://people.ischool.berkeley.edu/~hearst/text-mining.html
  11. Hotho, A., Nurnberger, A., and Paas, G. 2005. A Brief Survey of Text Mining. Ldv Forum: 19-62.
  12. Hoyt, R. E., and Liebenberg, A. P. 2011. The Value of Enterprise Risk Management: Evidence from the U.S. Insurance Industry. The Journal of Risk and Insurance: 795-822.
  13. Husnan, S. 2001. Dasar-dasar Teori Portfolio dan Analisis Sekuritas. Edisi Ketiga. Unit Penerbit dan Percetakan Akademi Manajemen Perusahaan Yayasan Keluarga Pahlawan Negara, Yogyakarta.
  14. Jogiyanto. 2007. Metodologi Penelitian Bisnis: Salah Kaprah dan Pengalaman-Pengalaman. Badan Penerbitan Fakultas Ekonomi - Universitas Gadjah Mada, Yogyakarta.
  15. Kao, A., and Poteet, S. R. 2007. Natural Language Processing and Text Mining. Springer Science and Business Media.
  16. Nafarin, M. 2007. Penganggaran Perusahaan. Salemba Empat, Jakarta.
  17. Martono and Harjito, D. A. 2005. Manajemen Keuangan Perusahaan. Edisi Pertama Cetakan Kelima Ekonisia, Yogyakarta.
  18. Michelle and Megawati. 2005. Tingkat Pengembalian Investasi Dapat Diprediksi Melalui Profitabilitas, Likuiditas dan Leverage. Kumpulan Jurnal Ekonomi.com.
  19. Mihaela, E., and Alina, F. 2011. Country Risk Importance on Investment Decision Making. Romania. http://www.management.ase.ro.
  20. Petrović, E., and Stanković, J. 2009. Contry Risk And Effects Of Foreign Direct Investment. Facta Universitatis Series: Economics and Organization Vol. 6, No 1: 9 – 22.
  21. Sanjaya, C. K., and Linawati, N. 2015. Pengaruh Penerapan Enterprise Risk Management dan Variabel Kontrol Terhadap Nilai Perusahaan di Sektor Keuangan. FINESTA Vol. 3, No. 1: 52-57.
  22. Sartono, R. A. 2008. Manajemen Keuangan. Edisi Keempat Badan Penerbitan Fakultas Ekonomi – Universitas Gadjah Mada, Yogyakarta.
  23. Shenkir, W. G., and Walker, P. L. 2007. Enterprise Risk Management: Tools and Techniques for Effective Implementation. Institute of Management Accountants, New Jersey.
  24. Staines, J. 2015. Mining Text and Time Series Data with Applications in Finance. PhD Thesis UCL (University College London), London.
  25. Sugiyono. 2009. Metode Penelitian Kuantitatif dan Kualitatif. CV. Alfabeta, Bandung.
  26. Sutrisno. 2009. Manajemen Keuangan Teori, Konsep, dan Aplikasi. Ekonisia, Yogyakarta.  
  27. The Economist Group Intellegence Unit. 2016. Country Risk Model - An Interactive Tool for Analysing Country and Sovereign Risk. www.eiu.com.  
  28. http://www.eulerhermes.com.