We consider a tractable affine stochastic volatility model that generalizes the seminal Heston (1993) model by augmenting it with jumps in the instantaneous variance process. In this framework, we consider options written on the realized variance, and we examine the impact of the distribution of...

An enhanced option pricing framework that makes use of both continuous and discontinuous time paths based on a geometric Brownian motion and Poisson-driven jump processes respectively is performed in order to better fit with real-observed stock price paths while maintaining the analytical...

We price derivatives defined for different asset classes with a full stochastic dependence structure. We consider jointly geometric Brownian motions and mean-reversion processes with a a stochastic variance-covariance matrix driven by a Wishart process. These models cannot be treated within the...

We consider the joint SPX-VIX calibration within a general class of Gaussian polynomial volatility models in which the volatility of the SPX is assumed to be a polynomial function of a Gaussian Volterra process defined as a stochastic convolution between a kernel and a Brownian motion. By...

A family of Exponentially Fitted Block Backward Differentiation Formulas (EFBBDFs) whose coefficients depend on a parameter and step-size is developed and implemented on the Black-Scholes partial differential equation (PDE) for the valuation of options on a non-dividend-paying stock. Specific...

In this thesis, problems in the realm of high frequency trading and optimal market making are established and solved in both single asset and multiple asset economies. For an agent that is averse to holding large inventories for long periods of time, optimal high frequency trading strategies are...

The quintic Ornstein-Uhlenbeck volatility model is a stochastic volatility model where the volatility process is a polynomial function of degree five of a single Ornstein-Uhlenbeck process with fast mean reversion and large vol-of-vol. The model is able to achieve remarkable joint fits of the...

Exponential Lévy processes can be used to model the evolution of various financial variables such as FX rates, stock prices, etc. Considerable efforts have been devoted to pricing derivatives written on underliers governed by such processes, and the corresponding implied volatility surfaces...

A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted to the VIX price history from 1990 to 2022. Using a growing window of training data, the price of the S&P500 is predicted and two trading algorithms are presented, based on the...

This paper develops estimators of the transition density, filters, and parameters of multivariate jump-diffusions with latent components. The drift, volatility, jump intensity, and jump magnitude are allowed to be general functions of the state. Our density and filter estimators converge at the...