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 46 for “"volatility model"”.
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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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Analytical Solutions of the SABR Stochastic Volatility Model
… studies a mathematical problem that arises in modeling the prices of option contracts in an important part of global financial markets, the fixed income option market. Option contracts, among other derivatives, serve an important function of transferring and managing financial risks in today's …
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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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Volatility Model Pricing and Calibration with Neural Networks using Bayesian Optimisation
Stochastic Alpha, Beta, Rho (SABR) and Heston Volatility models have been used in the financial industry due to their ability to price options as a function of time to maturity and moneyness. Implied volatilities for these models are accurately estimated using a numerical integration approach, …
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Optimal choices: mean field games with controlled jumps and optimality in a stochastic volatility model
… applied to a simple illiquid inter-bank market model, where the banks can adjust their reserves only at the jump times of some given Poisson processes with a common constant intensity, and some numerical results are provided. In the second part a stochastic optimization problem is presented. …
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Nonparametric and Parametric Analyses on the Forward Rate Volatilities and Their Implications on Interest Rate Options Pricing
… analysis, this paper proposes an HJM volatility model and estimates it in the GARCH-family models. The proposed volatility model is compared with four alternative HJM models and shown to perform well both in capturing the volatility movement and in American options pricing.
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Finite activity jump models for option pricing
… and Barrier options under the Heston stochastic volatility model and the Bates model. Bates model combines Merton's jump diffusion model and Heston's stochastic volatility model. We look at the calibration problem and use Matlab functions to model the DAX options volatility surface. Finally, …
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Pricing stochastic volatility models using random grids
… others. If one method is used to calibrate the model to market conditions, but another method is used to price the asset, the results obtained may be inconsistent. This dissertation addresses the fundamental problem of this bias that is introduced when calibrating and pricing options using …
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Essays on corporate bonds
… first chapter, I test the ability of structural models of default to price corporate bonds in the cross-section. I find that the Black-Cox model can explain 45% of the cross-sectional variation in yield spreads. The unexplained portion is correlated with proxies for credit risk and thus, cannot …
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Volatility derivatives in the Heston framework
A volatility derivative is a financial contract where the payoff depends on the realized variance of a specified asset's returns. As volatility is in reality a stochastic variable, not deterministic as assumed in the Black-Scholes model, market participants may surely find volatility derivatives to …
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Forward and inverse American option pricing via a complementarity approach
… the pricing of American options under a local volatility model and two jump diffusion models: Kou's jump diffusion model and the Dupire system. In Chapter 2, we establish partial differential complementarity systems for pricing American options under the aforementioned three models. We also …
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Density Estimation for Robust Financial Econometrics
… smoothed density estimates: the simulated model density and corresponding observed density. This approach generalizes work of Beran (1977) and Basu and Lindsay (1994) so that dependent data and simulated model densities are allowed, enabling the estimation without simple analytical …
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Estimating Long Term Equity Implied Volatility
… case, practitioners have to estimate the implied volatility surface across a range of expiries and moneyness levels. A detailed evaluation is performed for different estimation techniques to assess the strengths and weaknesses of each of the models. The estimation techniques considered include …
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Three Essays on Empirical Asset Pricing
… of daily stock returns using an extended GARCH model with event-related dummy variables to capture the predictable components of volatility change, such as earnings announcements, macroeconomic announcements, day-of-the-week effects, etc. We examine the out-of-sample forecasting ability and find …
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Two dimensional COS method for pricing early-exercise and discrete barrier options under the Heston Model
… under the dynamics of the Heston stochastic volatility model. The two-dimensional nature of the Heston model makes the pricing of these options problematic, as the risk-neutral expectations need to be calculated at each exercise/observation date along a continuum of the two state spaces. We …
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Forecasting volatilities in option pricing: An application of Bayesian inference
… forecasting volatilities used in option pricing models for live cattle and live hog futures. The forecast problem is cast in the framework of Bayesian inference. Six types of individual forecast models are used--GARCH models, ARIMA models, systems of simultaneous equations, systems of seemingly …
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Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering
Particle filtering in stochastic volatility/jump models has gained significant attention in the last decade, with many distinguished researchers adding their contributions to this new field. Golightly (2009), Carvalho et al. (2010), Johannes et al. (2009) and Aihara et al. (2008) all attempt to …
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Water Level Modeling around German Bight
… spatial. We apply first stochastic time series models to the data on temporal level. The model has four patterns: trend, seasonality, autoregressive components and the heteroscedastic residuals captured by a dynamics conditional volatility model. Two different procedures are applied in this work …
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Hedging volatility: different perspectives compared
… compared to a benchmark set by the Heston (1993) model in a stochastic volatility environment. The Black-Scholes portfolio was implemented using a fixed volatility and by implying volatility from the market. Additionally, a portfolio based on the Dupire (1994) local volatility model was also …
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Option pricing with physics-informed neutral networks (PINNS)
… is also extended by incorporating a local volatility model. Here, we derive the PDE of a vanilla European option under the constant elasticity of variance (CEV) model. We then construct and train a PINN to solve the PDE and compare it to the true analytical solution of a special case of the …
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