Valuation of Residential Mortgage-Backed Securities with a Two -Factor Gaussian Model and The Monte Carlo Method: Case Study of The Indonesian Securitization Market
- 주제(키워드) RMBS , Indonesia , Two-Addictive-Factor Gaussian model , Monte Carlo method , MATLAB
- 발행기관 아주대학교
- 지도교수 구형건
- 발행년도 2019
- 학위수여년월 2019. 2
- 학위명 석사
- 학과 및 전공 일반대학원 금융공학과
- 실제URI http://www.dcollection.net/handler/ajou/000000028907
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
The increasing demand for private housing is inseparable from the increasing opportunities to invest in Mortgage-Backed Securities (MBS), especially Residential Mortgage-Backed Securities (RMBS) for investors. Indonesia as the 4th largest population in the world has the prospect for this RMBS market. However, since the global financial crisis happened between 2007 and 2010, the investors have been very careful in investing in RMBS. Valuation is believed to be one of the key efforts which can minimize the problem that might occur in the future. In this thesis, I used Indonesia market data to conduct a valuation of RMBS with Two-Addictive-Factor Gaussian (G2++) model and Monte Carlo method. Results from the MATLAB simulations highlight that the determination of boundary for calibration parameters of the G2++ model is very important. By giving a boundary 0 ~ 0.5 for the estimate parameters (except parameter rho) we can get optimal and consistent parameter calibration results. Further, the results of parameter sensitivity test show that out of the five calibrated parameters (a, b, sigma, eta, rho), the price of RMBS is particularly sensitive to change in eta parameter. Beside the eta parameter, the RMBS price itself is also found to be sensitive to the change in conditional prepayment parameter.
more목차
CHAPTER 1. Introduction 1
1.1 Background and Motivation 1
1.2 Thesis Structure 4
CHAPTER 2. Residential Mortgage-Backed Securities 5
CHAPTER 3. The Prepayment Model 7
3.1 Twelve Year Prepaid Life Model 7
3.2 Federal Home Administration (FHA) Experience Model 8
3.3 Constant Prepayment Rate (CPR) Model 8
3.4 Public Security Association (PSA) Model 9
3.5 Richard and Roll (1989) Model 10
3.5.1 Refinancing Incentive. 11
3.5.2 Seasoning (age of the mortgage). 13
3.5.3 Seasonality (month of the year). 14
3.5.4 Premium burnout. 15
3.5.5 Multiplicative Model. 16
CHAPTER 4. Interest Rate Model 17
4.1 The 2-Factor Gaussian model: G2++ 18
4.2 Pricing of interest rate caps with the G2++ model 20
4.3 Calibrating G2++ to interest rate caps 22
CHAPTER 5. Cash Flow Structure of MBS 23
5.1 MBS Valuation 25
CHAPTER 6. Implementation 26
6.1 Data 27
6.2 Basic Assumption of Pricing a Mortgage Pool 28
6.3 G2++ Parameter Calibration 29
6.4 G2++ Monte Carlo Simulation 31
6.5 Generation of Cash Flow & Pricing of RMBS 32
CHAPTER 7. Conclusion and Future Works 39
REFERENCES 41
