Internal credit rating framework for real asset investment
Abstract
Real asset investment, which is assumed to be worthier than traditional assets in regards to exposure to income volatility, has become central to investment portfolios in financial institutions. However, the features of illiquidity and uniqueness involved in an individual real asset deal require private investors to review the full dimensions associated with the transaction structure. Banks and global credit rating agencies assess the quality of products by relying heavily on qualitative research executed by human insights and experiences. Such an approach ensures the comprehensiveness of the review process but it requires excessive resources in time and money. This study presents an internal rating system that instantly screens features of a deal proposal and provides a rating compatible with the global rating standard. The result shows that the outcomes created by this model are mostly clustered from BBB to BB. These findings match the average ratings for real assets, as determined by global rating agencies, which strengthens the practicality of the proposed model.
First published online 10 October 2019
Keyword : credit rating, alternative investment, real estate, infrastructure, Bank for International Settlements (BIS)
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Bae, D. S., & Damnjanovic, I. (2018). Credit risk assessment and monitoring of TIF bonds. The Journal of Structured Finance, 23(4), 57-68. https://doi.org/10.3905/jsf.2018.2018.1.062
Bank for International Settlements. (2001). Working paper on the internal ratings-based approach to specialised lending exposures. Retrieved from https://www.bis.org/publ/bcbs_wp9.pdf
Bank for International Settlements. (2017). High-level summary of Basel III reforms. Retrieved from https://www.bis.org/bcbs/publ/d424_hlsummary.pdf
Bank of England. (2019). Internal Ratings Based (IRB) approaches. Retrieved from https://www.bankofengland.co.uk/prudential-regulation/publication/2013/internal-ratingsbased-approaches-ss
Barkham, R., & Luo, W. (2018). Global investment volume rises, driven by robust U.S. market. Retrieved from https://www.cbre.com/research-and-reports/global-marketflash-globalinvestment-volume-rises
Bonsall, S., Koharki, K., & Neamitu, M. (2015). The effectiveness of credit rating agency monitoring: evidence from asset securitization. The Accounting Review, 90(5), 1779-1810. https://doi.org/10.2308/accr-51028
Bonsall, S. B., Koharki, K., & Neamtiu, M. (2017). When do differences in credit rating methodologies matter? Evidence from high information uncertainty borrowers. The Accounting Review, 92(4), 53-79. https://doi.org/10.2308/accr-51641
CBRE. (2017). The global market leader in commercial real estate services. Retrieved from http://phx.corporate-ir.net/External.File?item=UGFyZW50SUQ9Njc5MzI4fENoaWxkSUQ9Mzg 4NDM4fFR5cGU9MQ==&t=1
Choi, S. C. (2018). Expedited infrastructure investment by asset management company. Business Post Korea. Retrieved from http://www.businesspost.co.kr/BP?command=article_view&num=88116
Fracassi, C., Petry, S., & Tate, G. (2013). Are credit ratings subjective? The role of credit analysts in determining ratings. Retrieved from https://www.aeaweb.org/conference/2014/retrieve.php?pdfid=551
Garmaise, M. J., & Moskowitz, T. J. (2003). Confronting information asymmetries: evidence from real estate markets. The Review of Financial Studies, 17(2), 405-437. https://doi.org/10.1093/rfs/hhg037
Griffin, J. M., & Tang, D. Y. (2012). Did subjectivity play a role in CDO credit ratings? The Journal of Finance, 67(4), 1293-1328. https://doi.org/10.1111/j.1540-6261.2012.01748.x
He, Y., Wang, J., & Wei, K. C. J. (2011). Do bond rating changes affect the information asymmetry of stock trading? Journal of Empirical Finance, 18(1), 103-116. https://doi.org/10.1016/j.jempfin.2010.06.001
Heitmann, K., & Davison, A. (2018). Moody᾽s: default and recovery rates for project finance bank loans remain stable. Retrieved from https://www.moodys.com/research/Moodys-Default-andrecovery-rates-for-project-finance-bank-loans--PR_380331
Heitmann, K., Hawken, N., & Davison, A. (2017). Default and recovery rates for project finance bank loans, 1983-2015. Retrieved from https://www.globalinfrafacility.org/sites/gif/files/Moody%27s-Project%20Finance%20Default%20Study%20%281983-2015%29.pdf
Hull, J. C., Predescu, M., & White, A. (2005). Bond prices, default probabilities and risk premiums. SSRN. https://doi.org/10.2139/ssrn.2173148
Korean Ministry of Land Infrastructure and Transport. (2016). Overseas infrastructure development support policy. Retrieved from http://www.molit.go.kr/USR/I0204/m_45/dtl.jsp?gubun=1&search=&search_dept_id=&search_dept_nm=&old_search_dept_nm=&psize=10&search_regdate_s=&search_regdate_e=&srch_usr_nm=&srch_usr_num=&srch_usr_year=&srch_usr_titl=&srch_usr_ctnt=&lcmspage=1&idx=14391
KPMG. (2019). Emerging trends in infrastructure 2019. Retrieved from https://home.kpmg/xx/en/home/industries/infrastructure.html
Longstaff, F. A., Mithal, S., & Eric, N. (2005). Corporate Yield spreads: default risk or liquidity? New evidnece from the credit default swap market. The Journal of Finance, 60(5), 2213-2253. https://doi.org/10.1111/j.1540-6261.2005.00797.x
M&G Institutional. (2017). The opportunity in European commercial real estate debt. Retrieved from http://www.mandg.hk/institutional/articles/the-opportunity-in-european-commercial-real-estate-debt/-/media/68C366BD7CE0436B94AA36482F885AAD.pdf
McKinsey & Company. (2017). Basel “IV”: what᾽s next for banks? Retrieved from https://www.mckinsey.com/~/media/mckinsey/business%20functions/risk/our%20insights/basel%20iv%20whats%20next%20for%20european%20banks/basel-ivwhats-next-for-banks.ashx
Medina, J. (2018). Moody᾽s update its methodology for rating generic project finance issuers. Retrieved from https://www.moodys.com/research/Moodys-updates-its-methodology-forrating-generic-project-finance-issuers--PR_382107
Medina, J., & Marty, D. (2018). Rating methodology: generic project finance. Retrieved from https://www.moodys.com/researchdocumentcontentpage.aspx?docid=PBC_1091596
Meers, W., & Humphrey, T. (2017). Macquarie infrastructure debt investment solutions: an introduction to infrastructure debt. Retrieved from https://www.macquarie.com/dafiles/Internet/mgl/global/shared/sf/pdf/midis-an-introduction-toinfrastructure-debt.pdf?v=2
Morgan Stanley. (2014). Alternative investments: innovative strategies for asset allocation. Retrieved from https://www.morganstanley.com/wealth/investmentsolutions/pdfs/altscapabilitiesbrochure.pdf
Morgenson, G. (2009). When bond ratings get stale. Retrieved from https://www.nytimes.com/2009/10/11/business/economy/11gret.html
Moultrie, J. (2019). FMEA (Failure Modes and Effects Analysis). Retrieved from https://www.ifm.eng.cam.ac.uk/research/dmg/tools-and-techniques/fmea-failure-modes-and-effectsanalysis/
Nikolića, D. M., Jednak, S., Benković, S., & Poznanić, V. (2011). Project finance risk evaluation of the Electric power industry of Serbia. Energy Policy, 39(10), 6168-6177. https://doi.org/10.1016/j.enpol.2011.07.017
Peng, J., & Brucato, P. F. (2004). An empirical analysis of market and institutional mechanisms for alleviating information asymmetry in the municipal bond market. Journal of Economics and Finance, 28(2), 226-238. https://doi.org/10.1007/BF02761613
Piney, C. (2003). Risk identification: combining the tools to deliver the goods. Paper presented at the PMI® Global Congress 2003−EMEA, The Hague, South Holland, The Netherlands.
Raz, T., Shenhar, A. J., & Dvir, D. (2002). Risk management, project success, and technological uncertainty. R&D Management, 32(2), 101-109. https://doi.org/10.1111/1467-9310.00243
Renigier-Biłozor, M., Wisniewski, R., Kaklauskas, A., & Biłozor, A. (2014). Rating methodology for real estate markets – Poland case study. International Journal of Strategic Property Management, 18(2), 198-212. https://doi.org/10.3846/1648715X.2014.927401
Ribeiro, M. I. F., & Ferreira, F. A. F. (2017). A fuzzy knowledgebased framework for risk assessment of residential real estate investments. Technological and Economic Development of Economy, 23(1), 140-156. https://doi.org/10.3846/20294913.2016.1212742
S&P Global Ratings. (2018). S&P Global Ratings definitions. Retrieved from https://www.standardandpoors.com/en_US/web/guest/article/-/view/sourceId/504352
Segismundo, A., & Miguel, P. A. C. (2008). Failure mode and effects analysis (FMEA) in the context of risk management in new product development: a case study in an automotive company. International Journal of Quality & Reliability Management, 25(9), 899-912. https://doi.org/10.1108/02656710810908061
Standard & Poor᾽s. (2014). Project finance ratings criteria reference guide. Retrieved from https://www.spratings.com/documents/20184/86990/SPRS_Project%2BFinance%2BRatings%2BCriteria%2BReference%2BGuide_FINAL/cdfde690-57d1-4ff4-a87f-986527603c22
Tang, T. T. (2009). Information asymmetry and firm᾽s credit market access: evidence from moody᾽s credit rating format refinement. Journal of Financial Economics, 93(2), 325-351. https://doi.org/10.1016/j.jfineco.2008.07.007
The European Group of Valuer᾽s Associations. (2003). European Property and Market Rating: A Valuer᾽s Guide. Retrieved from https://www.tegova.org/data/bin/a56efb621c7ae1_EPMR1.pdf
United Nations Economic Commission for Europe Real Estate Market Advisory Group. (2012). Evaluation of real estate property and market risk for real estate backed financial products. Retrieved from https://www.unece.org/fileadmin/DAM/hlm/sessions/docs2012/real_estate_property_and_market_risk.pdf
Yescombe, E. R. (2002). Principles of project finance. Elsevier. https://doi.org/10.1016/B978-012770851-5.50002-6