Prediksi Waktu Paling Optimal Untuk Mengambil Restrukturisasi Kredit Dengan Model Cox-Ingersoll Ross dan Simulasi Monte Carlo = Optimal mortgage refinancing with cox-ingersoll ross model and monte carlo simulation

Agatha, Josephine Teresa (2021) Prediksi Waktu Paling Optimal Untuk Mengambil Restrukturisasi Kredit Dengan Model Cox-Ingersoll Ross dan Simulasi Monte Carlo = Optimal mortgage refinancing with cox-ingersoll ross model and monte carlo simulation. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Penurunan pertumbuhan ekonomi di Indonesia memberikan dampak pada banyak sektor, salah satunya adalah pemutusan hubungan kerja. Pemutusan hubungan kerja dapat berdampak pada kredit macet atau Non Performing Loan. Salah satu kebijakan yang diberikan oleh pihak bank untuk menghindari kredit macet adalah dengan memberikan program restrukturisasi kredit yang berupa penurunan suku bunga. Metode yang digunakan dalam penelitian ini adalah model Cox-Ingersoll Ross dan simulasi Monte Carlo. Simulasi Monte Carlo merupakan suatu metode simulasi yang melibatkan penggunaan angka acak untuk memodelkan suatu sistem dari data historis yang bertujuan untuk menemukan nilai yang mendekati nilai sesungguhnya. Angka acak yang dihasilkan dari simulasi Monte Carlo akan digunakan untuk memprediksi suku bunga pada model Cox-Ingersol Ross. Model Cox-Ingersoll Ross merupakan model persamaan diferensial stokastik yang digunakan untuk memprediksi suku bunga berdasarkan data historis. Hasil prediksi suku bunga akan disimulasikan ke dalam dua skema pembayaran dan menentukan batas waktu terakhir mengambil restrukturisasi kredit. Hasil dari penelitian ini menunjukkan bahwa akan lebih baik jika nasabah mengambil restrukturisasi kredit pada awal tenor dikarenakan total pembayaran yang lebih rendah./The decline in economic growth in Indonesia has had an impact on many sectors, one of which is termination of employment. Termination of employment can have an impact on bad debts or Non Performing Loan. One of the policies provided by the bank to avoid bad debts is to provide a credit refinancing program. The method that will be used in this research project is Cox-Ingersoll Ross model and Monte Carlo simulation. Monte Carlo simulation is a simulation method that involves the use of random numbers to model a system from historical data that aims to find values that are close to the real value. Random numbers generated from the Monte Carlo simulation will be used to predict the interest rate in the Cox-Ingersol Ross model. Cox-Ingersoll Ross model is a stochastic differential equation model used to predict interest rates based on historical data. The results predicted interest rates will be simulated into two payment schemes and determine the deadline for taking credit refinancing. The results of this study indicate that it would be better if customers take credit refinancing at the beginning of the contract due to lower total payments.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Agatha, Josephine TeresaNIM01112170018josephineteresaagatha@gmail.com
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorMargaretha, HelenaNIDN0312057504UNSPECIFIED
Thesis advisorFerdinand, Ferry VincenttiusNIDN0323059001UNSPECIFIED
Uncontrolled Keywords: mortgage refinancing; stochastic interest rate model; xox-ingersoll ross; monte carlo simulation; maximum likelihood estimation
Subjects: Q Science > QA Mathematics
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Depositing User: Users 5991 not found.
Date Deposited: 04 Aug 2021 12:23
Last Modified: 04 Aug 2021 12:23
URI: http://repository.uph.edu/id/eprint/41106

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