Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 101 for “"Stochastic Volatility"”.
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The Lifted Heston Stochastic Volatility Model
Can we capture the explosive nature of volatility skew observed in the market, without resorting to non-Markovian models? We show that, in terms of skew, the Heston model cannot match the market at both long and short maturities simultaneously. We introduce Abi Jaber (2019)'s Lifted Heston model …
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Pricing stochastic volatility models using random grids
… pricing under the Heston model as well as the stochastic local volatility model. Consistent results are obtained for a call option under the various pricing methods using similar parameters as those used in the random grids paper. More specifically, when using a Heston model, consistent prices …
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Local Stochastic Volatility—The Hyp-Hyp Model
Volatility modelling is used predominantly in order to explain the volatility smile observed in the market. Stochastic volatility models are mainly used to capture the curvature of a volatility smile while local volatility models generally model the skew. Jackel and Kahl ¨ (2008) present a …
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Pricing with Bivariate Unspanned Stochastic Volatility Models
Unspanned stochastic volatility (USV) models have gained popularity in the literature. USV models contain at least one source of volatility-related risk that cannot be hedged with bonds, referred to as the unspanned volatility factor(s). Bivariate USV models are the simplest case, comprising of one …
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Implementation of Bivariate Unspanned Stochastic Volatility Models
Unspanned stochastic volatility term structure models have gained popularity in the literature. This dissertation focuses on the challenges of implementing the simplest case – bivariate unspanned stochastic volatility models, where there is one state variable controlling the term structure, and one …
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Stochastic Volatility with Levy Processes: Calibration and Pricing
In this thesis, stochastic volatility models with Levy processes are treated in parameter calibration by the Carr-Madan fast Fourier transform (FFT) method and pricing through the partial integro-differential equation (PIDE) approach. First, different models where the underlying log stock price or …
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Analytical Solutions of the SABR Stochastic Volatility Model
… to the practice of option trading, in which the volatility parameter of the Black-Scholes-Merton's model has become the market "language'' of quoting option prices. Despite its tremendous success, the Black-Scholes-Merton model has exhibited a few well-known deficiencies, the most important of …
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Fractional stochastic volatility models: approximation, calibration and hedging
The area of modeling stochastic volatility using continuous time models has a long history and is always an interesting and vibrant area in financial mathematics, where the dynamic of the asset is a diffusion driven by Brownian motion and the dynamic of the volatility is associated with a diffusion …
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Option Pricing models with Stochastic Volatility and Jumps
… are able to capture real world behavior (such as stochastic volatility effects and jumps in the price of the underlying). This dissertation tackles the question of which option pricing model to use; it compares diffusion, pure jump and jump-diffusion models. All models are fitted to one-day price …
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Pricing American/Bermudan-style Options under Stochastic Volatility
A method to price American options under a stochastic volatility framework is introduced which is based on Rambharat and Brockwell (2010). We price American options under the Heston and Bates stochastic volatility models where volatility is assumed to be a latent process. The pricing algorithm is …
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Modelling Equities with a Stochastic Volatility Jump Diffusion
… model provides a parsimonious fit to implied volatility surfaces, and its usefulness in developed markets is well documented. However, there is a lack of research assessing its applicability to developing markets. Additionally, research surrounding its usefulness for hedging long term …
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Stochastic Volatility Models for Contingent Claim Pricing and Hedging
… for the discrepancy observed on the implied volatility curve. To achieve this we also propose that market volatility be modeled as random or stochastic as opposed to certain standard option pricing models such as Black-Scholes, in which volatility is assumed to be constant.
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Bayesian analysis of multivariate stochastic volatility and dynamic models
… volatilities in the error term. The time varying volatility for each component of the error is of unknown nature, may be deterministic or stochastic. We propose Bayesian stochastic search as a feasible variable selection technique for the regression and volatility equations. We develop Markov …
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Estimating stochastic volatility models with student-t distributed errors
… with Student-t distributed errors, to estimating Stochastic Volatility (SV) models with Student-t distributed errors. It is unclear whether Gaussian distributed errors sufficiently account for the observed leptokurtosis in financial time series and hence the extension to examine Student-t …
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Asymptotics and numerics in rough and local stochastic volatility models
… in common, that they permit the use of rough volatility processes, meaning that the fluctuations of stock prices are modelled via a very irregular process. Besides this underlying structure, statements about asymptotic behaviour play a major role, both in the description of price developments …
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Long-memory stochastic volatility model calibration using deep neural nets
Widespread use of stochastic volatility models in the financial industry is bottlenecked by the complexity and intractability they present. Since the seminal work in quantitative finance by Black et al. and Merton, the infamous Black-Scholes model has been extensively used in the industry for …
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Term structure models with unspanned factors and unspanned stochastic volatility
… structure of interest rates exhibit unspanned stochastic volatility (USV). A model has this property if it involves a source of stochastic variation — called an unspanned factor — that does not affect the model’s interest rates directly, but does affect the extent to which future interests are …
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Testing adaptive market efficiency under the assumption of stochastic volatility
… Talyor (in progress), which has an underlying stochastic GARCH-M model proposed by Hall (1991). In this dissertation, the stochastic volatility test of evolving efficiency (SV-TEE) is developed using an underlying Stochastic Volatility-in-Mean (SVM) model introduced by Koopman and Uspensky …
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Essays on Fine Structure of Asset Returns, Jumps, and Stochastic Volatility
… of empirical evidences to support redundancy of stochastic volatility for SP500 index returns when stochastic volatility is taken into account with infinite activity pure Lévy jumps models and the importance of stochastic volatility to reduce pricing errors for SP500 index options without regard …
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