Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Unified And Hybrid Approaches To Identification, Optimization And Control Of Stochastic Financial Processess-Theory, Methods And Applications.
Date
2012-12-31
Author
Weber, Gerhard Wilhelm
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
199
views
0
downloads
Cite This
This research project aims at a new unified view onto both identification and optimal control of Stochastic Differential Equations (SDEs) for purposes of financial mathematics and actuarial sciences. More specific cases such as Stochastic Hybrid Systems are also considered in this framework. A special interests consists in (i) refinement of Parameter Estimation for SDEs and (ii) Portfolio Optimization. Here, the words “unified” or “joint” mean an integrated and simultaneous treatment of (i) and (ii) in theory and algorithms. Alternatively, when following the Martingale Method of Portfolio Optimization, one can also arrive at a stepwise treatment of (i) and (ii), in fact, at a Tri-Level Problem, for which methods of optimization theory and stochastic calculus can be developed. If the parameter estimation is done in a last step, then the martingale method with its two steps is understood in a parametric sense of optimization. Let us remark that a significant contribution to this project was given by the recently finalized BAP project of 2010 “Identification, Optimization and Control of Stochastic Differential Equations in Financial Mathematics”. The use of our GAM & CQP on SDEs was already worked out, now we shall demonstrate the use of our CMARS for SDEs. All of this can also be done for systems of SDEs of various kinds, and with facing the presence of jump processes (i.e., for Lévy processes, incomplete markets), too. Moreover, we are considering the use of other methods, such as Bayesian and Maximum Likelihood Estimation, and of given algorithms / program packages, and the comparison of our techniques with them. When treating parameter estimation and portfolio optimization in a stepwise manner, we discuss and apply different methods from Multi-Level Optimization and Analysis. Finally, as an alternative of varities of the Martingale Method, we also use Stochastic Control, especially, Stochastic Hybrid Control.
URI
https://hdl.handle.net/11511/61677
Collections
Graduate School of Applied Mathematics, Project and Design
Suggestions
OpenMETU
Core
Stochastic Hybrid Systems of Financial and Economical Processess: Identificatied, Optimized and Controlled
Weber, Gerhard Wilhelm; Yolcu Okur, Yeliz; Yerlikaya Özkurt, Fatma; Kuter, Semih; Özmen, Ayşe; Karimov, Azar(2013-12-31)
This research project will scientifically broaden, deepen and apply a scientific unified approach of both identification and optimal control of Stochastic Differential Equations with Jumps (SHSJs), motivated by and foreseen for purposes of financial mathematics and actuarial sciences. SHSJs and further structured and detailed models are in the scope of our framework, and special interests pursued consisted in a. refinement of Parameter Estimation for SDEs and b. Portfolio Optimization and, as a future exten...
Mutual relevance of investor sentiment and finance by modeling coupled stochastic systems with MARS
Kalayci, Betul; Ozmen, Ayse; Weber, Gerhard Wilhelm (Springer Science and Business Media LLC, 2020-08-01)
Stochastic differential equations (SDEs) rapidly become one of the most well-known formats in which to express such diverse mathematical models under uncertainty such as financial models, neural systems, behavioral and neural responses, human reactions and behaviors. They belong to the main methods to describe randomness of a dynamical model today. In a financial system, different kinds of SDEs have been elaborated to model various financial assets. On the other hand, economists have conducted research on s...
Two studies on backward stochastic differential equations
Tunç, Vildan; Sezer, Ali Devin; Department of Financial Mathematics (2012)
Backward stochastic differential equations appear in many areas of research including mathematical finance, nonlinear partial differential equations, financial economics and stochastic control. The first existence and uniqueness result for nonlinear backward stochastic differential equations was given by Pardoux and Peng (Adapted solution of a backward stochastic differential equation. System and Control Letters, 1990). They looked for an adapted pair of processes {x(t); y(t)}; t is in [0; 1]} with values i...
Hybrid wavelet-neural network models for time series data
Kılıç, Deniz Kenan; Uğur, Ömür; Department of Financial Mathematics (2021-3-3)
The thesis aims to combine wavelet theory with nonlinear models, particularly neural networks, to find an appropriate time series model structure. Data like financial time series are nonstationary, noisy, and chaotic. Therefore using wavelet analysis helps better modeling in the sense of both frequency and time. S&P500 (∧GSPC) and NASDAQ (∧ IXIC) data are divided into several components by using multiresolution analysis (MRA). Subsequently, each part is modeled by using a suitable neural network structure. ...
Advanced Mathematical Methods of Financial Risk Management Investigated and Solved by New Methods of Stochastic Calculus, Mathematical Statistics and Optimization
Weber, Gerhard Wilhelm(2010-12-31)
Advanced Mathematical Methods of Financial Risk Management Investigated and Solved by New Methods of Stochastic Calculus, Mathematical Statistics and Optimization
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. W. Weber, “Unified And Hybrid Approaches To Identification, Optimization And Control Of Stochastic Financial Processess-Theory, Methods And Applications.,” 2012. Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/61677.