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.
StanChart quant proposes new technique to compute MVA quicker
Algorithmic differentiation are used to simulate sensitivities to calculate MVA
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.
Research on AAD is not complete until it becomes easier to implement, says quant
In this paper, the authors examine the problem of validating and calibrating FHS VaR models, focussing in particular on the Hull and White (1998) approach with EWMA volatility estimates, given its extended use in the industry.
New machines have big potential in AI, valuations and VAR, but tech giants like IBM need help from practitioners
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.
Quants study ways to reduce noise in XVA Greeks calculations
The calculation of XVA Greeks for portfolios with early-exercise products is discussed
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.
Marco de Innocentis and Sergei Levendorskiĭ describe a faster and more accurate method for market-implied calibration of the Heston model
This paper proposes a portfolio credit risk model with random recovery rates.
Three firms have signed up to use the tool, which calculates MVA across 100,000 scenarios
The authors of this paper use power series distributions to develop a novel and flexible zero-inflated Bayesian methodology.
In this paper the authors present an efficient convergent lattice method for Asian option pricing with superlinear complexity.
The authors present Sequential Monte Carlo (SMC) method for pricing barrier options.
The authors of this paper assess the right-hand tail of an insurer’s loss distribution for a specified period (a year), presenting and analyzing six different approaches in doing so.
A mixed Monte Carlo and partial differential equation variance reduction method for foreign exchange options under the Heston–Cox–Ingersoll–Ross model
The paper concerns a hybrid pricing method build upon a combination of Monte Carlo and PDE approach for FX options under the four-factor Heston-CIR model.