Research on Mortgage-Backed Securitization Structure

Yang Yue; Yu Bo

doi:doi:10.11648/j.sjams.20160402.11

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Research on Mortgage-Backed Securitization Structure

Yang Yue, Yu Bo

Published in Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 2)

Received: 6 March 2016 Accepted: Published: 6 March 2016

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Abstract

Asset securitization is an important way to improve bank asset liability structure, and can offer investors financial tools with high yields. Owing to the rapid and stable development of the financial market, the large-scale asset securitization age is on the way. To establish a complete and reasonable mortgage-backed securitization structuring model, this paper firstly introduced a method to estimate the repayment default rate based on distributional robust optimization. Then it improved a credit rating system by containing an option on the mortgage market value. Finally it proposed to use the dynamic programming model to structure the mortgage-backed securities. It is supposed to make a contribution to the financial innovation in China and put forward fresh ideals.

Published in	Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 2)
DOI	10.11648/j.sjams.20160402.11
Page(s)	21-28
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Dynamic Programming, Mortgage-Backed Securitization, Distributional Robust Optimization, Default Rate, Credit Rating

References

[1]	W. D. Chen, A. Y. Li, X. X. Liao. The Theory and Practice of Asset Securitization. Beijing, China: Renmin University Press, 2004.
[2]	F. J. Fabozzi. The Handbook of Mortgage-Backed Securities. 5th ed. New York, US: McGraw-Hill, 2001.
[3]	P. Kang, S. A. Zenios. “Complete Prepayment Models for Mortgage-Backed Securities”. Management Science, Focused Issue on Finance Modeling, 1985, vol. 3, pp. 385-408.
[4]	R. Schwartz, W. N. Torous. “Prepayment and the variation of mortgage-backed securities”. Journal of Finance, 1989, vol. 6, pp. 375-392.
[5]	J. Jacobs, R. Koning, E. Sterken. “Modelling Prepayment Risk”. Technical report, University of Groningen, 2005.
[6]	K. Rajaratnam. A Simplified Approach to Modeling the Credit Risk of CMO. arXiv: 0903.1643, 2009, 3. http://www.researchgate.net/publication/24163603.
[7]	W. Bartlett. The Valuation of Mortgage-Backed Securities. New York, US: Irwin Professional Publishing, 1994.
[8]	F. L. Wang. “Empirical research on default risk factors of residential mortgage loan”. Zhejiang, China: Zhejiang University, 2004.
[9]	K. Tian. “Research on credit risk of commercial banks’ personal housing mortgage loans based on the empirical study of logistic model”. Science and Technology Information (academic), 2008, vol. 27, pp. 418-420.
[10]	D. Rosch. “An empirical comparison of default risk forecasts from alternative credit rating philosophies”. International Journal of Forecasting, 2005, vol. 21, pp. 37-51.
[11]	A. Ben-Tal, L. E. Ghaoui, A. Nemirovski. Robust Optimization. Princeton, US: Princeton University Press, 2009.
[12]	S. I. Gass, C. M. Harris. Encyclopedia of Operations Research and Management Science. US: Springer, 2001, pp. 790-790.
[13]	R. C. Merton. “On the pricing of corporate debt: the risk structure of interest rates”. Journal of Finance, 1974, vol. 5, pp. 449-470.
[14]	F. Black, M. Scholes. “The Pricing of Options and Corporate Liabilities”. Journal of Political Economy, 1973, vol. 81(3), pp. 637-654.
[15]	G. Cornuejols, R. Tutuncu. Optimization method in finance. Pittsburgh: Carnegie Mellon University, 2006.
[16]	X. K. DU. “Research on prepayment behavior in China residential mortgage-backed securitization”. Hefei, China: University of Science and Technology of China, 2010.

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APA Style

Yang Yue, Yu Bo. (2016). Research on Mortgage-Backed Securitization Structure. Science Journal of Applied Mathematics and Statistics, 4(2), 21-28. https://doi.org/10.11648/j.sjams.20160402.11

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ACS Style

Yang Yue; Yu Bo. Research on Mortgage-Backed Securitization Structure. Sci. J. Appl. Math. Stat. 2016, 4(2), 21-28. doi: 10.11648/j.sjams.20160402.11

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AMA Style

Yang Yue, Yu Bo. Research on Mortgage-Backed Securitization Structure. Sci J Appl Math Stat. 2016;4(2):21-28. doi: 10.11648/j.sjams.20160402.11

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@article{10.11648/j.sjams.20160402.11,
  author = {Yang Yue and Yu Bo},
  title = {Research on Mortgage-Backed Securitization Structure},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {2},
  pages = {21-28},
  doi = {10.11648/j.sjams.20160402.11},
  url = {https://doi.org/10.11648/j.sjams.20160402.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160402.11},
  abstract = {Asset securitization is an important way to improve bank asset liability structure, and can offer investors financial tools with high yields. Owing to the rapid and stable development of the financial market, the large-scale asset securitization age is on the way. To establish a complete and reasonable mortgage-backed securitization structuring model, this paper firstly introduced a method to estimate the repayment default rate based on distributional robust optimization. Then it improved a credit rating system by containing an option on the mortgage market value. Finally it proposed to use the dynamic programming model to structure the mortgage-backed securities. It is supposed to make a contribution to the financial innovation in China and put forward fresh ideals.},
 year = {2016}
}

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TY  - JOUR
T1  - Research on Mortgage-Backed Securitization Structure
AU  - Yang Yue
AU  - Yu Bo
Y1  - 2016/03/06
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160402.11
DO  - 10.11648/j.sjams.20160402.11
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 21
EP  - 28
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160402.11
AB  - Asset securitization is an important way to improve bank asset liability structure, and can offer investors financial tools with high yields. Owing to the rapid and stable development of the financial market, the large-scale asset securitization age is on the way. To establish a complete and reasonable mortgage-backed securitization structuring model, this paper firstly introduced a method to estimate the repayment default rate based on distributional robust optimization. Then it improved a credit rating system by containing an option on the mortgage market value. Finally it proposed to use the dynamic programming model to structure the mortgage-backed securities. It is supposed to make a contribution to the financial innovation in China and put forward fresh ideals.
VL  - 4
IS  - 2
ER  -

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Author Information

Yang Yue

Department of Mathematics, Dalian Naval Academy, Dalian, China
Yu Bo

Department of Mathematics, Dalian Naval Academy, Dalian, China; Department of Mathematics, Dalian University of Technology, Dalian, China

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APA Style

Yang Yue, Yu Bo. (2016). Research on Mortgage-Backed Securitization Structure. Science Journal of Applied Mathematics and Statistics, 4(2), 21-28. https://doi.org/10.11648/j.sjams.20160402.11

Copy | Download

ACS Style

Yang Yue; Yu Bo. Research on Mortgage-Backed Securitization Structure. Sci. J. Appl. Math. Stat. 2016, 4(2), 21-28. doi: 10.11648/j.sjams.20160402.11

Copy | Download

AMA Style

Yang Yue, Yu Bo. Research on Mortgage-Backed Securitization Structure. Sci J Appl Math Stat. 2016;4(2):21-28. doi: 10.11648/j.sjams.20160402.11

Copy | Download

@article{10.11648/j.sjams.20160402.11,
  author = {Yang Yue and Yu Bo},
  title = {Research on Mortgage-Backed Securitization Structure},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {2},
  pages = {21-28},
  doi = {10.11648/j.sjams.20160402.11},
  url = {https://doi.org/10.11648/j.sjams.20160402.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160402.11},
  abstract = {Asset securitization is an important way to improve bank asset liability structure, and can offer investors financial tools with high yields. Owing to the rapid and stable development of the financial market, the large-scale asset securitization age is on the way. To establish a complete and reasonable mortgage-backed securitization structuring model, this paper firstly introduced a method to estimate the repayment default rate based on distributional robust optimization. Then it improved a credit rating system by containing an option on the mortgage market value. Finally it proposed to use the dynamic programming model to structure the mortgage-backed securities. It is supposed to make a contribution to the financial innovation in China and put forward fresh ideals.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Research on Mortgage-Backed Securitization Structure
AU  - Yang Yue
AU  - Yu Bo
Y1  - 2016/03/06
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160402.11
DO  - 10.11648/j.sjams.20160402.11
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 21
EP  - 28
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160402.11
AB  - Asset securitization is an important way to improve bank asset liability structure, and can offer investors financial tools with high yields. Owing to the rapid and stable development of the financial market, the large-scale asset securitization age is on the way. To establish a complete and reasonable mortgage-backed securitization structuring model, this paper firstly introduced a method to estimate the repayment default rate based on distributional robust optimization. Then it improved a credit rating system by containing an option on the mortgage market value. Finally it proposed to use the dynamic programming model to structure the mortgage-backed securities. It is supposed to make a contribution to the financial innovation in China and put forward fresh ideals.
VL  - 4
IS  - 2
ER  -

Copy | Download