Valuation of Residential Mortgage-Backed Securities with a Two -Factor Gaussian Model and The Monte Carlo Method: Case Study of The Indonesian Securitization Market
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.
