In this paper, the authors present a method for conditional time series forecasting based on an adaptation of the recent deep convolutional WaveNet architecture.
Vibrato and automatic differentiation for high-order derivatives and sensitivities of financial options
This paper deals with the computation of second-order or higher Greeks of financial securities. It combines two methods, vibrato and automatic differentiation (AD), and compares these with other methods.
In this paper, the authors present a new approach to bounding financial derivative prices in regime-switching market models from both above and below.
This paper seeks to contribute a simple and (almost) model-free way of assessing the economic value of the Bermudan exercise right derived from a “minimal” local volatility enhanced interest rate model.
This paper investigates two new strategies for the numerical solution of optimal stopping problems in the regression Monte Carlo (RMC) framework.
This paper develops efficient importance sampling schemes for a class of jump–diffusion processes that are commonly used for modeling stock prices.
In this paper, the authors develop a procedure to reduce the variance when numerically computing the Greeks obtained via Malliavin calculus for jump–diffusion models with stochastic volatility.
In this paper, the authors study factor-based subordinated Lévy processes in their variance gamma (VG) and normal inverse Gaussian (NIG) specifications, and focus on their ability to price multivariate exotic derivatives.
Hybrid finite-difference/pseudospectral methods for the Heston and Heston–Hull–White partial differential equations
In this paper, the authors propose a hybrid spatial finite-difference/pseudospectral discretization for European option-pricing problems under the Heston and Heston–Hull–White models.
Adjoint algorithmic differentiation tool support for typical numerical patterns in computational finance
This paper demonstrates the flexibility and ease in using C++ algorithmic differentiation (AD) tools based on overloading to numerical patterns (kernels) arising in computational finance.
This paper develops a Monte Carlo method to price instruments with discontinuous payoffs and non-smooth trigger functions, which allows a stable computation of Greeks via finite differences.
Pricing multidimensional financial derivatives with stochastic volatilities using the dimensional-adaptive combination technique
In this paper, the authors present a new and general approach to price derivatives based on the Black–Scholes partial differential equation (BS-PDE) in a multidimensional setting.
In this paper, the authors give a decomposition formula to calculate the vega index (sensitivity with respect to changes in volatility) for options with prices that depend on the extrema (maximum or minimum) and terminal value of the underlying stock…
This paper proposes a numerical optimization approach that can be used to solve portfolio selection problems including several assets and involving objective functions from cumulative prospect theory (CPT).
In this paper, the authors study a hybrid tree/finite-difference method, which allows us to obtain efficient and accurate European and American option prices in the Heston–Hull– White and Heston–Hull–White2d models.
This paper considers the problem of European option pricing in the presence of a proportional transaction cost when the price of the underlying follows a jump–diffusion process.
This paper extends and refines the method of option pricing by frame projection of risk-neutral densities to incorporate B-splines.
This paper proposes a generalized risk budgeting approach to portfolio construction.
This paper proposes an efficient algorithm to value two popular crediting formulas found in equity-indexed annuities – APP and MPP – under general Lévy-process-based index returns.
In this paper, the authors propose a new method of constructing volatility surfaces for foreign exchange options.
In this paper, the author considers a special type of nonlinear PDE that arises by applying optimization to some financial problems.
This paper proposes a nonparametric local volatility Cheyette model and applies it to pricing interest rate swaptions.
This paper introduces a local volatility model for the valuation of options on commodity futures by using European vanilla option prices.
Investment opportunities forecasting: a genetic programming-based dynamic portfolio trading system under a directional-change framework
This paper presents an autonomous effective trading system devoted to the support of decision-making processes in the financial market domain.