政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/124743
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113393/144380 (79%)
Visitors : 51241745      Online Users : 890
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/124743


    Title: 擔保房貸憑證(CMOs)之評價：應用機器學習方法預測提前還款率
    Pricing Collateralized Mortgage Obligations: Using Machine Learning to Predict Prepayment Rate
    Authors: 吳海棠
    Wu, Hai-Tang
    Contributors: 林士貴
    莊明哲
    Lin, Shih-Kuei
    Chuang, Ming-Che
    吳海棠
    Wu, Hai-Tang
    Keywords: 擔保房貸憑證
    提前還款模型
    機器學習
    Hull & White 利率模型
    Collateralized mortgage obligations
    Prepayment model
    Machine learning
    Hull & White Interest Rate Model
    Date: 2019
    Issue Date: 2019-08-07 16:13:31 (UTC+8)
    Abstract: 本研究使用機器學習模型預測擔保房貸憑證(Collateral Mortgage Obligation, CMOs)之提前還款率並評價，且和两种傳统的提前還款率的模型進行比較。第一種是靜態的提前還款模型，使用聯邦住宅管理局經驗法(Federal Home Administration, FHA)、條件提前還款率(Conditional Prepayment Rate, CPR)或以美國公共證券協會(The Public Securities Association, PSA)提前還款基準作為提前還款預測的模型。第二種是動態的提前還款，由美國儲蓄機構管理局(Office Thrift Supervision, OTS)提出的30年期固定利率房屋抵押貸款動態提前還款模型。由於評價CMOs時會將現金流進行折現，且票面利息的計算會使用到倫敦銀行同業隔夜拆款利率(London Interbank Offered Rate, Libor)。因此，本研究使用Hull & White利率模型模擬即期利率路徑，再通過遠期利率協定(Forward Rate Agreement, FRA)轉換成遠期Libor的路徑計算現金流。通過Fannie Mae發行的一檔CMOs商品的公開資料用於實證，實證結果證實機器學習預測提前還款優於傳统模型。
    In this paper we predict the prepayment rate and price the Collateral Mortgage Obligation by using Machine Learning, and compare the results with two traditional prepayment models. The first one is static prepayment model, which uses Federal Housing Administration (FHA) Model, Conditional Prepayment Rate (CPR) Model or the Public Securities Association (PSA) prepayment benchmark for the prepayment model. The second one is the dynamic prepayment model from Office Thrift Supervision (OTS), which uses 30 years fixed mortgage rate. Because the high relationship between coupon rate of CMO trench and Libor rate, this paper uses Hull & White interest rate model to simulate the spot interest rate as the discount rate, and converts it to the Libor rate with the help of Forward Rate Agreement (FRA). The empirical analysis based on a CMOs issued by Fannie Mae illustrated that for Machine Learning, the efficiency in predicting the prepayment rate is better than traditional models.
    Reference: 中文文獻
    1. 王立偉，2008，「提前還款對住房抵押貸款支持證券定價影響的效果」，大連理工大學金融工程系碩士班碩士論文。
    2高心怡，2000，「結合HULL-WHITE利率模型與PHM提前清償模型評價CMO利率衍生性商品」，國立台灣大學財務金融系碩士班碩士論文。
    3.張繼文，2010，「擔保房貸憑證（CMOs）評價-以BGM利率模型為例」，國立政治大學金融系碩士班碩士論文。
    4.張憲明，2018，「擔保房貸憑證（CMOs）之評價：應用類神經網路預測提前還款率」，國立政治大學金融系碩士班碩士論文。
    5.廖伯媛，2001，「不動產抵押貸款證券化之分析與評價」，國立政治大學金融系碩士班碩士論文。
    6.劉展宏、張金鶚，2001，「購屋貸款提前清償行為之研究」，住宅學報，10 卷 1 期：29~49。

    英文文獻
    1. Andreas, K, and Rudi, Z, 2008,”A Hybrid-Form Model for the Prepayment-Risk-Neutral Valuation of Mortgage-Backed Securities”, The International Journal of Theoretical and Applied Finance, 11, pp.635-656
    2. Clauretie and Sirmans, 1999, “Real Estate Finance Theory Practice”, Longman Higher Education Division ; 3rd edition
    3. Deng Y., 1977, ”Mortgage Termination: An Empirical Hazard Model with Stochastic Term Structure ”, Journal of Real Estate Finance and Economics,Vol.14,pp.309-331
    4. Dunn, K. B. and McConnell, J. J. (1981), “Valuation of GINNIE MAE Mortgage-Backed Securities,” Journal of Finance, Vol.36, pp.599-616
    5. Dunn, K. B. and McConnell, J. J. (1981), “A Compare of Alternative Models for Pricing GINNIE MAE Mortgage-Back Securities,” Journal of Finance Vol.36, pp.471-484.
    6. Green ,J , and J. B. Shoven ,1983,”The Effect of Interest Rates on Mortgage Prepayments”, Journal of Money, Credit and Banking 18,41-59
    7. Gurrieri , M. Nakabayashi & T. Wong (2009), “Calibration methods of Hull–White model”, Working paper.
    8. Jone, J. Mcconnell and Manoj Singh,1993,”Valuation and Analysis of Collateralized Mortgage Obligations”, Management Science, Vol.39, No. 6,pp.692-709
    9. Jone J. Mcconnell and Manoj Singh, 1994,”Rational Prepayments and the Valuation of Collateralized Mortgage Obligations”, The Journal of Finance, Vol. 49, No. 3,pp.891-921
    10. Ronald w. Spahr and Mark A. Sunderman,”The Effect of Prepayment Modeling in Pricing Mortgage-Backed Securities”, Journal of Housing Research, Vol. 3,pp.381-400
    11. R Riksen , 2017,”Using Articial Neural Networks in the Calculation of Mortgage Prepayment Risk”, University of Amsterdam, Korteweg-de Vries Institute for Mathematics
    12. Scott F. Richard Roll, 1989,”Prepayments on Fixed-Rate Mortgage-Backed Securities”, Journal of Portfolio Management 15,pp.73-82
    13. Schwartz, Eduardo S., and Walter N. Torous, 1989, "Prepayment and the Valuation of Mortgage-Backed Securities," Journal of Finance, 44, 375-39
    14. Waller B. and Aiken M.,1998, “Predicting Prepayment of Residential Mortgages: A Neural Network Approach ”, Information and Management Sciences, 9, pp.37-44
    Description: 碩士
    國立政治大學
    金融學系
    106352046
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106352046
    Data Type: thesis
    DOI: 10.6814/NCCU201900177
    Appears in Collections:[Department of Money and Banking] Theses

    Files in This Item:

    File SizeFormat
    204601.pdf2040KbAdobe PDF20View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback