Pricing spread and basket options under markov-modulated models

Download
2018
Kozpınar, Sinem
This thesis first aims to study the evaluation of spread and basket options under the classical Markov-modulated framework, for which a transition in the Markov process leads to a switch in the model parameters. In this regard, we provide approximations to the exact option prices based on ideas from the literature without regime switching. We start with pricing spread options when risky assets follow Markov-modulated geometric Brownian motions (MMGBMs). In this context, we focus on the regime-switching version of Kirk's formula. For that reason, a change of numeraire technique is introduced which allows to associate the spread option price with the value of a European call option. Since the underlying asset of this European call follows a MMGBM for relatively small strikes, we evaluate the spread option by using Markov-modulated Black-Scholes formula. Then, we discuss the valuation of spread options when the underlying asset prices are driven by Markov-modulated Lévy processes (MMLPs). Under this modeling set-up, we approximate the spread option price by means of an accurate lower bound, which is obtained via a univariate Fourier inversion. For this method, we only require the joint characteristic function; and therefore, our approximation becomes valid for many regime-switching models. Afterwards, we concentrate on the valuation of basket options for which we provide lower and upper bounds considering the MMLP framework. We first obtain an accurate lower bound by using a univariate Fourier inversion combined with an optimization procedure. However, this optimization procedure increases the computational cost. Therefore, we then derive faster analogous bounds by using the arithmetic-geometric mean inequality and univariate Fourier inversion without an optimization. As in the case of spread options, the approaches we followed for basket options are applicable to several MMLPs under which the joint characteristic functions of the underlying assets are known analytically. Furthermore in this thesis we aim to price spread and basket options under a more generalized framework, in which a transition in the Markov process may induce a switch in the parameters as well as synchronous jumps in the asset prices. For this purpose, we extend the results obtained under the classical MMLP framework, which does not take the synchronous jumps into account, to this generalized framework. Finally, in order to verify the accuracy of proposed approximations presented in this thesis, we include several numerical experiments.

Suggestions

Improved state estimation for jump Markov linear systems
Orguner, Umut; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2005)
This thesis presents a comprehensive example framework on how current multiple model state estimation algorithms for jump Markov linear systems can be improved. The possible improvements are categorized as: -Design of multiple model state estimation algorithms using new criteria. -Improvements obtained using existing multiple model state estimation algorithms. In the first category, risk-sensitive estimation is proposed for jump Markov linear systems. Two types of cost functions namely, the instantaneous an...
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. ...
Spread and basket option pricing in a Markov-modulated Levy framework with synchronous jumps
Deelstra, Griselda; Kozpınar, Sinem; Simon, Matthieu (2018-11-01)
This paper considers the evaluation of spread and basket options when the underlying asset prices are driven by Markov-modulated Levy processes with synchronous jumps. In particular, the asset prices may jump whenever there is a change of phase of the underlying Markov process. We further allow for dependence between the different price dynamics. In this general regime-switching framework, we provide lower and upper bounds to the exact option prices based upon ideas from the literature without regime switch...
Output-feedback control of linear time-varying and nonlinear systems using the forward propagating Riccati equation
Prach, Anna; Tekinalp, Ozan; Bernstein, Dennis S. (2018-04-01)
For output-feedback control of linear time-varying (LTV) and nonlinear systems, this paper focuses on control based on the forward propagating Riccati equation (FPRE). FPRE control uses dual difference (or differential) Riccati equations that are solved forward in time. Unlike the standard regulator Riccati equation, which propagates backward in time, forward propagation facilitates output-feedback control of both LTV and nonlinear systems expressed in terms of a state-dependent coefficient (SDC). To invest...
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...
Citation Formats
S. Kozpınar, “Pricing spread and basket options under markov-modulated models,” Ph.D. - Doctoral Program, Middle East Technical University, 2018.