Determinants of commercial mortgage-backed securities credit ratings: Australian evidence

International Journal of Strategic Property Management

Volumn 12, Issue 2, 2008, Pages 69-94

  Chikolwa, Bwembya ^a   Chan, Felix ^b  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b CURTIN UNIVERSITY   (Australia)

Author keywords

Artificial neural networks; Commercial mortgage backed securities; Credit rating prediction; Ordinal regression

Indexed keywords

EID: 45749097813     PISSN: 1648715X     EISSN: None     Source Type: Journal    
DOI: 10.3846/1648-715X.2008.12.69-94     Document Type: Review

References (61)

1. Alles, L. (2000) Asset securitisation in Australia: how and why it works. Curtin Business School, Perth.
2. Alyuda Research Inc. (2001) Forecaster XL. Fremont, CA.
3. An, X., Deng, Y. and Sanders, A.B. (2006) Subordination level as a predictor of credit risk. Cambridge-UNC Charlotte Symposium 12-14 June, Madingley Hall, University of Cambridge.
4. Belkaoui, A. (1980) Industrial bond ratings: A new look, Financial Management, 9(3), pp. 44-51.
5. Carroll, S.M. and Dickinson, B.W. (1989) Construction of neural nets using the radon transform. Proceedings of the IEEE Conference on Neural Networks, Washington DC, pp. 607-611.
6. Chaveesuk, R., Srivaree-Ratana, C. and Smith, A.E. (1999) Alternative neural network approaches to corporate bond rating, Journal of Engineering Valuation and Cost Analysis, 2(2), pp. 117-131.
7. Coakley, J.R. and Brown, C.E. (2000) Artificial neural networks in accounting and finance: Modelling issues, Intelligent Systems in Accounting, Finance and Management, 9(2), pp. 119-144.
8. Connellan, O. and James, H. (1998a) Estimated realisation price (ERP) by neural networks: Forecasting commercial property values, Journal of Property Valuation and Investment, 16(1), pp. 71-86.
9. Connellan, O. and James, H. (1998b) Forecasting commercial property values in the short term. RICS Cutting Edge Conference 1998, RICS Research, Leicester.
10. Cybenko, G. (1989) Approximation by superpositions of a sigmoidal function, Mathematics of Control Signals and Systems, 2, pp. 303-314.
11. Daniels, H. and Kamp, B. (1999) Application of MLP networks to bond rating and house pricing, Neural Computing & Applications, 8(8), pp. 226-234.
12. Deng, Y., Quigley, J.M. and Sanders, A.B. (2005) Commercial terminations: Evidence from CMBS', Annual American Real Estate and Urban Economics Association (AREUEA) Meetings.
13. Do, A.Q. and Grudnitski, G. (1992) A neural network approach to residential property appraisal, Real Estate Appraiser, 58(3), pp. 38-45.
14. Dutta, S. and Shekhar, S. (1988) Bond rating: a non-conservative application of neural networks. Proceedings of the IEEE International Conference on Neural Networks, San Diego, vol. 2, pp. 443-450.
15. Ederington, L.H. (1985) Classification models and bond ratings, The Financial Review, 20(4), pp. 237-262.
16. Evans, A.H.J. and Collins, A. (1992) Artificial neural networks: An application to residential valuation in the UK, Journal of Property Valuation and Investment, 11(2), pp. 195-203.
17. Fabozzi, F.J. and Jacob, D.P. (1997) The Handbook of Commercial Mortgage-backed Securities, Frank Fabozzi Associates, New Hope.
18. Fadlalla, A. and Lin, C. (2001) An analysis of the applications of neural networks in finance, Interfaces, 31(4), pp. 112-122.
19. Fischer, D. (2004) Income Property Analysis. D. Fischer, Perth.
20. Fitch Ratings (2005) Rating Single-Borrower Commercial Mortgage Transactions. Fitch Ratings, New York.
21. Funahashi, K. (1989) On the approximate realization of continuous mappings by neural networks, Neural Networks, 2(3), pp. 183-192.
22. Geltner, D. and Miller, N.G. (2001) Commercial Real Estate Analysis and Investments. South-Western, Mason, Ohio.
23. Grovenstein, R.A., Harding, J.P., Sirmans, C.F., Thebpanya, S. and Turnbull, G.K. (2004) Commercial Mortgage Underwriting: How Well Do Lenders Manage Risks? School of Business, University of Connecticut, Storrs.
24. th Pacific Rim Real Estate Society (PPRES) Conference, Melbourne 23-27 January.
25. Hornik, K., Stinchcombe, M. and White, H. (1989) Multilayer feedforward networks are universal approximators, Neural Networks, 2(5), pp. 359-366.
26. Hornik, K., Stinchcombe, M. and White, H. (1990) Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks, Neural Networks, 3(5), pp. 551-576.
27. Huang, Z., Chen, H., Hsu, C., Chen, W. and Wu, S. (2004) Credit rating analysis with support vector machines and neural networks: A market comparative study, Decision Support Systems, 37(4), pp. 543-558.
28. InTech (2003) Institutional Listed Property Exposure. JB Were Investment Series.
29. Jacob, D.P. and Fabozzi, F.J. (2003) The impact of structuring on CMBS class performance, Journal of Portfolio Management, Special Real Estate Issue, pp. 76-86.
30. Jones Lang LaSalle (2001) Commercial Mortgage Backed Securities: The New Kid on the Block. Sydney.
31. Kamstra, M., Kennedy, P. and Suan, T.-K. (2001) Combining bond rating forecasts using logit, The Financial Review, 36(2), pp. 75-96.
32. Kauko, T. (2003) Residential property value and locational externalities, Journal of Property Investment & Finance, 21(3), pp. 250-270.
33. Kauko, T. (2004) Towards the 4th generation - an essay on innovations in residential property value modelling expertise, Journal of Property Research, 21(1), pp. 75-97.
34. Kim, K.S. (2005) Predicting bond ratings using publicly available information, Expert Systems with Applications, 29(1), pp. 75-81.
35. Kose, J., Lynch, A.W. and Puri, M. (2003) Credit ratings, collateral, and loan characteristics: Implications for yield, The Journal of Business, 76(3), pp. 371-409.
36. Krishnaswamy, C.R., Gilbert, E.W. and Pashley, M.M. (2000) Neural network applications in finance: A practical innovation, Journal of Financial Practice and Education, 10(1), pp. 75-84.
37. Kwon, Y.S., Han, I. and Lee, K.C. (1997) Ordinal pairwise partitioning (OPP) approach to neural networks training in bond rating, Intelligent Systems in Accounting, Finance and Management, 6(1), pp. 23-40.
38. th Asian Real Estate Society Annual Conference, Sydney, 18-21 July.
39. Lenk, M.M., Worzala, E.M. and Silva, A. (1997) High-tech valuation: Should artificial neural networks bypass the human valuer, Journal of Property Valuation and Investment, 15(1), pp. 8-26.
40. Maher, J.J. and Sen, T.K. (1997) Predicting bond ratings using neural networks: A comparison with logistic regression, Intelligent Systems in Accounting, Finance and Management, 6(1), pp. 59-72.
41. McGreal, S., Adair, A., McBurney, D. and Patterson, D. (1998) Neural networks: The prediction of residential values, Journal of Property Valuation and Investment, 16(1), pp. 57-70.
42. Moody's Investor Service (2003) CMBS: Moody's Approach to Rating Australian CMBS. Moody's Investors Service, Sydney.
43. Newell, G. (2005) The changing dynamics of Australian commercial property portfolios, Australian Property Journal, 38(7), pp. 553-558.
44. th Annual Conference of the Pacific Rim Real Estate Society, January 22 to 25, 2006, Auckland, New Zealand.
45. Nguyen, N. and Cripps, A. (2001) Predicting housing value: a comparison of multiple regression analysis and artificial neural networks, Journal of Real Estate Research, 22(3), pp. 313-336.
46. Ovnerud-Potter, P. (2003) CMBS: Moody's Approach to Rating Australian CMBS. Moody's Investors Service, Sydney.
47. Roche, T. (2002) Commercial mortgage-backed securities: A homogeneous asset class? Australian Property Journal, August, pp. 170-174.
48. Rowland, P.J. (1993) Property Investments and Their Financing. The Law Book Company Limited, Sydney.
49. Salchenberger, L.M., Cinar, E.M. and Lash, N.A. (1992) Neural networks: A new tool for predicting thrift failures, Decision Sciences, 23(4), pp. 899-915.
50. Shin, K. and Han, I. (2001) A case-based approach using inductive indexing for corporate bond rating, Decision Support Systems, 32(1), pp. 41-52.
51. SPSS Inc. (1968) SPSS 13.0. Chicago, IL.
52. Standard & Poor's (2001) Australian Commercial Mortgage-Backed Securitization - The Rating Process. Standard & Poor's, Melbourne.
53. Standard & Poor's (2004) CMBS Property Evaluation Criteria. Standard & Poor's, New York.
54. Standard & Poor's (2007) Fourth-Quarter and Year-End 2006 Australia and New Zealand Structured Finance Performance Trends. Standard & Poor's, Melbourne.
55. Surkan, A.J. and Singleton, J.C. (1990) Neural networks for bond rating improved by multiple hidden layers. Proceedings of the IEEE International Conference on Neural Networks, Revised edn, San Diego, pp. 163-168.
56. Tam, K.Y. and Kiang, M.Y. (1992) Managerial applications of neural networks: The case of bank failure predictions, Management Science, 38(7), pp. 926-947.
57. Tay, D.P.H. and Ho, D.K.H. (1991) Artificial intelligence and the mass appraisal of residential apartments, Journal of Property Valuation and Investment, 10(2), pp. 525-540.
58. Weeraprajak, I. (2007) Faster Adaptive Network Based on Fuzzy Inference System. University of Canterbury, New Zealand.
59. Worzala, E.M., Lenk, M.M. and Silva, A. (1995) An exploration of neural networks and its application to real estate valuation, Journal of Real Estate Research, 10(2), pp. 185-202.
60. Yesilyaprak, A. (2004) Bond ratings with artificial neural networks and econometric models, American Business Review, 22(1), pp. 113-123.
61. Zhang, G.B., Patuwo, E. and Hu, M.Y. (1998) Forecasting with artificial neural networks: The state of the art, International Journal of Forecasting, 14(1), pp. 35-62.