Monte Carlo simulation
Importance sampling for jump–diffusions via cross-entropy
This paper develops efficient importance sampling schemes for a class of jump–diffusion processes that are commonly used for modeling stock prices.
Podcast: Fries on Monte Carlo, Greeks and the future of AAD
Research on AAD is not complete until it becomes easier to implement, says quant
The validation of filtered historical value-at-risk models
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.
Quants needed: how finance can use power of quantum tech
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.
Monte Carlo payoff smoothing for pricing autocallable instruments
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.
Reducing noise is as important as radical change
Quants study ways to reduce noise in XVA Greeks calculations
Pathwise XVA Greeks for early-exercise products
The calculation of XVA Greeks for portfolios with early-exercise products is discussed
A hybrid tree/finite-difference approach for Heston–Hull–White-type models
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.
Calibrating Heston for credit risk
Marco de Innocentis and Sergei Levendorskiĭ describe a faster and more accurate method for market-implied calibration of the Heston model
Portfolio credit risk model with extremal dependence of defaults and random recovery
This paper proposes a portfolio credit risk model with random recovery rates.
TriOptima adds MVA calculations to XVA service
Three firms have signed up to use the tool, which calculates MVA across 100,000 scenarios
On modeling zero-inflated insurance data
The authors of this paper use power series distributions to develop a novel and flexible zero-inflated Bayesian methodology.
An efficient convergent lattice method for Asian option pricing with superlinear complexity
In this paper the authors present an efficient convergent lattice method for Asian option pricing with superlinear complexity.
Valuation of barrier options using sequential Monte Carlo
The authors present Sequential Monte Carlo (SMC) method for pricing barrier options.
Rapidly bounding the exceedance probabilities of high aggregate losses
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.
An exact and efficient method for computing cross-Gammas of Bermudan swaptions and cancelable swaps under the Libor market model
A new simulation algorithm for computing the Hessians of Bermudan swaptions and cancelable swaps is presented.
Paper of the year: PJ de Jongh, Tertius de Wet, Kevin Panman and Helgard Raubenheimer
South African academics pioneer a quick and easy way of estimating op risk capital
Transform-based evaluation of prices and Greeks of lookback options driven by Lévy processes
The authors develop a technique, based on numerical inversion, to compute the prices and Greeks of lookback options driven by Lévy processes.
Faster comparison of stopping times by nested conditional Monte Carlo
The authors propose a novel method for efficiently comparing the performance of different stopping times.