Stohastično modeliranje obrestnih mer

Štampar, Ines

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Title:	Stohastično modeliranje obrestnih mer
Authors:	ID Štampar, Ines (Author) ID Jakovac, Marko (Mentor) More about this mentor... ID Pisanec, Mihael (Comentor)
Files:	MAG_Stampar_Ines_2020.pdf (736,59 KB) MD5: 030938CEA104C343EA9C893E92CFD051 PID: 20.500.12556/dkum/a67e10fc-8b66-4427-a02e-e3d1f3ff0842
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FNM - Faculty of Natural Sciences and Mathematics
Abstract:	Magistrsko delo obravnava napoved obrestnih mer in vpliv gibanja obrestnih mer na anuiteto dolgoročnega kredita. V prvem delu je na kratko povzeta teorija stohastičnih procesov, Brownovega gibanja in Itôvega procesa. Za napoved obrestnih mer so bili uporabljeni Vasickov, CIR in Hull-Whiteov model. V drugem delu so opisane lastnosti modelov ter izpeljava pričakovane vrednosti in variance. V tretjem delu sledi modeliranje 3-mesečnega Euribor-ja. Uporabljena je metoda največje verjetnosti za Vasickov in CIR model, za Hull-Whiteov model pa metoda najmanjšega verjetja. Vključene so napovedi posameznega modela in pregled gibanja naslednjih 20 let. V četrtem delu so analizirani možni načini najema dolgoročnega kredita, predvsem odločitev o fiksni ali spremenljivi obrestni meri. Glede na dobljene rezultate napovedi obrestnih mer je sestavljen amortizacijski načrt in potek dolgoročnega kredita. Delo je zaključeno s poglavjem, kjer so podani odgovori na vprašanje, ali se splača najeti nov kredit in poplačati starega (glede na nizke vrednosti trenutnih obrestnih mer).
Keywords:	Stohastični model, obrestne mere, Vasicek, CIR, Hull-White, napoved, kredit, amortizacija
Place of publishing:	Maribor
Publisher:	[I. Štampar]
Year of publishing:	2020
PID:	20.500.12556/DKUM-77840
UDC:	519.856:336.781.5(043.2)
COBISS.SI-ID:	47801859
NUK URN:	URN:SI:UM:DK:G8BBSCJ6
Publication date in DKUM:	20.01.2021
Views:	1334
Downloads:	134
Metadata:
Categories:	FNM
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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	16.09.2020

Secondary language

Language:	English
Title:	Stohastic modeling of interest rates
Abstract:	The thesis discusses the topic of forecasting interest rates and the impact interest rate movements have on long-term loans. The first part briefly summarizes the theory of stochastic processes, Brownian motion and Itô process. Vasicek, CIR and Hull-White models were used to forecast interest rates. The second part presents features of the three models and the derivation of expected value and variance. The third part details the modeling of a 3 month Euribor. For forecasting with Vasicek and CIR models the maximum likelihood estimation method was used, and for Hull-White model the least squares method was used. Forecasts of interest rates and movements for the next 20 years are presented using the three models. The fourth part includes the analysis of possible ways to get a long-term loan, especially with consideration to the choice between getting a fixed or variable rate loan. Based on the forecasting an amortization schedule for a long-term loan was drawn up. The thesis ends with an evaluation whether it is more reasonable to apply for a new loan and pay off the old one (considering currently low interest rates).
Keywords:	Stochastic model, Vasicek, CIR, Hull-White, prediction, loan, amortization

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