Uncertainty Quantification and Implementation of Local Volatility Surfaces in Bayesian Framework

Animoku, Abdulwahab
Uğur, Ömür
Yolcu Okur, Yeliz


Uncertainty quantification of parameters in local volatility model via frequentist, bayesian and stochastic galerkin methods
Animoku, Abdulwahab; Uğur, Ömür; Department of Financial Mathematics (2018)
In this thesis, we investigate and implement advanced methods to quantify uncertain parameter(s) in Dupire local volatility equation. The advanced methods investigated are Bayesian and stochastic Galerkin methods. These advanced techniques implore different ideas in estimating the unknown parameters in PDEs. The Bayesian approach assumes the parameter is a random variable to be sampled from its posterior distribution. The posterior distribution of the parameter is constructed via “Bayes theorem of inverse p...
Uncertainty models for vector based functional curves and assessing the reliability of G-Band
Kurtar, Ahmet Kürşat; Düzgün, H. Şebnem; Department of Geodetic and Geographical Information Technologies (2006)
This study is about uncertainty medelling for vector features in geographic information systems (GIS). It has mainly two objectives which are about the band models used for uncertainty modelling . The first one is the assessment of accuracy of GBand model, which is the latest and the most complex uncertainty handling model for vector features. Some simulations and tests are applied to test the reliability of accuracy of G-Band with comparing Chrisman’s epsilon band model, which is the most frequently used b...
Uncertainty modelling and stability analysis for 2-way fuzzy adaptive systems
Gürkan, Evren; Erkmen, Aydan Müşerref; Banks, Stephen P.; Department of Electrical and Electronics Engineering (2003)
Uncertainty analysis of a snowmelt runoff model using Markov Chain Monte Carlo (MCMC) approach
Akyürek, Sevda Zuhal (null; 2018-04-13)
Mountainous watersheds have always remained a challenge for the modelers due to ample variations taking place in those watersheds. The key reason could be the lack of ground observations and model parameter uncertainty. Generalized Likelihood Uncertainty Estimation (GLUE) approach is used widely to account for the parameter uncertainty only. However, appraisal of other sources of uncertainty is likewise important such as, forcing data uncertainty, model structural errors etc. This study employs Markov Chain...
Uncertainty quantification by using stochastic approach in pore volume calculation for geothermal reservoir
Gürel, Emrah; Akın, Serhat; Department of Petroleum and Natural Gas Engineering (2015)
This study will present the application of a stochastic approach and experimental design techniques to a geologic system in order to quantify the uncertainty of pore volume estimations for a liquid dominated high temperature geothermal reservoir. The pore volume is a key element when defining the total resource available in the field. Alasehir geothermal reservoir pore volume uncertainty has been assessed. The uncertainties being addressed include geometry (top of reservoir and base of reservoir), reservoir...
Citation Formats
A. Animoku, Ö. Uğur, and Y. Yolcu Okur, “Uncertainty Quantification and Implementation of Local Volatility Surfaces in Bayesian Framework,” 2015, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/81987.