Universities fret over drop in international students and demands of online learning
This paper provides a comprehensive review of the field of neural networks, comparing articles in terms of input features, output variables, benchmark models, performance measures, data partition methods and underlying assets. Related work and…
The author considers a classical term structure model framework, ie, a Heath–Jarrow–Morton framework, on a time-discrete tenor, such as the London Interbank Offered Rate market model, using a sequence of tenor discretizations, where the tenors are valid…
Gaussian process regression for derivative portfolio modeling and application to credit valuation adjustment computations
The authors present a multi-Gaussian process regression approach, which is well suited for the over-the-counter derivative portfolio valuation involved in credit valuation adjustment (CVA) computation.
In the present paper, a decomposition formula for the call price due to Alòs is transformed into a Taylor-type formula containing an infinite series with stochastic terms. The new decomposition may be considered as an alternative to the decomposition of…
Unis are adding machine learning and data science courses, but need instructors to teach them
In this paper, we refer to the axiomatic theory of risk and investigate the problem of formal verification of the expected shortfall (ES) model based on a sample ES. Recognizing the infeasibility of parametric methods, they explore the bootstrap…
In this paper, a novel quasi-multiperiod model for optimal position liquidation in the presence of both temporary and permanent market impact is proposed. Two main features distinguish the proposed approach from its alternatives.
In this paper, the authors investigate a nonlinear generalization of the Black–Scholes equation for pricing American-style call options, where the volatility term may depend on both the underlying asset price and the Gamma of the option.
In this paper, the author uses the mean–variance hedging criterion to value contracts in incomplete markets.
This paper derives an alternative fast Fourier transform-based computational approach for calculating the target capital of the SST that is more than 600 times faster than a Monte Carlo simulation.
In this paper, the authors propose and investigate a new method for the calibration to American option price data.
There is a lot to learn before quantum computers can be applied to specific financial problems
In this paper, the authors construct a Heath-Platen-type Monte Carlo estimator that performs extraordinarily well compared with the crude Monte Carlo estimation.
This paper's aim is twofold: to introduce a mathematical framework that is sufficiently general and sound to cover the main areas of model risk, and to illustrate how a practitioner can identify the relevant abstract concepts and put them to work.
In this paper, the author describes a simple adaptive Filon method that performs better and more accurately than various popular alternatives for pricing options under the Heston model.
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 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.