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Finančni primeri uporabe stohastične kontrole : magistrsko delo
ID Kramar, Žan (Author), ID Perman, Mihael (Mentor) More about this mentor... This link opens in a new window

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Abstract
Stohastični procesi so ključni element različnih področij raziskav na različnih področjih. V tem delu predstavimo Itôve procese, njihove lastnosti in Itôvo formulo. Le-ti so eden izmed najbolj razširjenih stohastičnih procesov z jasnimi uporabami v financah. Definiramo parametrični Itôv proces in opišemo načine kako se ocenjuje parametre iz danega vzorca. Opisane metode so Eulerjeva ocena, Fokker-Planckova enačba in povezava do Kolmogorove preme enačbe ter Milsteinova ocena. Nato definiramo problem kontroliranega stohastičnega procesa, opišemo kaj je stohastična kontrola in predstavimo različne primere le-teh. Predstavimo rešitev preko principa dinamičnega programiranja, ki se reši preko Hamilton-Jacobi-Bellmanovih enačb. Nazadnje prikažemo uporabo na dveh primerih. V prvem rešimo primer optimalnega upravljanja portfelja na različnih koristnostnih funkcijah in prikažemo preko simulacije, da je naša izračunana rešitev pravilna. V drugem primeru rešimo znan problem linearnega regulatorja.

Language:Slovenian
Keywords:Stohastična kontrola v zveznem času, linearni regulator, Itôv proces
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FMF - Faculty of Mathematics and Physics
Year:2024
PID:20.500.12556/RUL-154492 This link opens in a new window
UDC:519.2
COBISS.SI-ID:185772035 This link opens in a new window
Publication date in RUL:17.02.2024
Views:439
Downloads:71
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Secondary language

Language:English
Title:Financial applications of stochastic control
Abstract:
Stochastic processes are a key element in various research fields. The thesis presents Itô’s processes, their properties and Itô’s formula. They are one of the most widesrpead stochastic processes with clear applications in finance. We define parametric Itô process and describe methods for parameter estimation from given sample. The described methods include Euler’s approximation, the Fokker-Planck equation and it’s connection to Kolmogorov’s forward equation and finally, Milstein’s method. Next, we define the problem of controlled stochastic processes, explain what stochastic control is and provide various examples of it. We introduce the solution using the dynamic programming principle, which is achieved using Hamilton-Jacobi-Bellman equations. Finally, we present the application to two examples. In the first example we solve the optimal protfolio management problem with different utility functions. In the second example we solve well-known linear regulator problem.

Keywords:Stochastic control in continuous time, the linear regulator, Itô process

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