Technical paper/Model calibration
Neural networks for option pricing and hedging: a literature review
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 quadratic rough Heston model and the joint S&P 500/Vix smile calibration problem
A combination of rough volatility and price-feedback effect allows for SPX-Vix joint calibration
The joint S&P 500/Vix smile calibration puzzle solved
SPX and Vix derivatives are modelled jointly in an arbitrage-free setting
Deep learning calibration of option pricing models: some pitfalls and solutions
Addressing model calibration and the issue of no-arbitrage in a deep learning approach
On probability of default and its relation to observed default frequency and a common factor
This paper considers a definition of through-the-cycle as independent from an economic state that can result in a time-varying TTC probability of default.
Complexity reduction for calibration to American options
In this paper, the authors propose and investigate a new method for the calibration to American option price data.
Validation of the backtesting process under the targeted review of internal models: practical recommendations for probability of default models
This paper provides practical recommendations for the validation of the backtesting process under the targeted review of internal models (TRIM).
The extended SSVI volatility surface
This paper extends Gatheral and Jacquier’s surface stochastic volatility-inspired (SSVI) parameterization by making the correlation maturity dependent and obtaining the necessary and sufficient conditions for no calendar-spread arbitrage.
Equity modelling with local stochastic volatility and stochastic discrete dividends
SocGen quants calibrate local stochastic volatility models with stochastic dividends
The swap market model with local stochastic volatility
An easy to calibrate and accurate swap market model is proposed
American quantized calibration in stochastic volatility
Fiorin, Callegaro and Grasselli show how discretisation methods reduce computing time in high-dimensional problems
A nonparametric local volatility model for swaptions smile
This paper proposes a nonparametric local volatility Cheyette model and applies it to pricing interest rate swaptions.
Local volatility models in commodity markets and online calibration
This paper introduces a local volatility model for the valuation of options on commodity futures by using European vanilla option prices.
Model calibration with neural networks
Andres Hernandez presents a neural network approach to speed up model calibration
Calibration of temperature futures by changing the mean reversion
The authors of this paper study the calibration of futures contracts on temperature indexes.
Calibration of local correlation models to basket smiles
The authors build a whole family of local correlation models by combining the particle method with a new, simple idea.
Path-consistent wrong-way risk: a structural model approach
The author of this paper presents a general and path-consistent wrong-way risk (WWR) model that does not require simulation of credit and market variables simultaneously.
A reduced basis method for parabolic partial differential equations with parameter functions and application to option pricing
The authors introduce an RB space–time variational approach for parametric PPDEs with coefficient parameters and a variable initial condition.
Interest rate models enhanced with local volatility
Lingling Cao and Pierre Henry-Labordère implement Dupire's local volatility in interest rate models
A point-in-time–through-the-cycle approach to rating assignment and probability of default calibration
This paper proposes a methodology for constructing TTC rating grades and assessing the resulting degree of PIT-ness.
Managing temperature-driven volume risks
This paper proposes a stochastic model for coupled natural gas spot prices and temperature.
B-spline techniques for volatility modeling
In this paper the use of B-splines is advocated for volatility modeling within the calibration of stochastic local volatility (SLV) models and for the parameterization of an arbitrage-free implied volatility surface calibrated to sparse option data.
The efficient application of automatic differentiation for computing gradients in financial applications
Automatic differentiation is the theme of this paper. The authors show that many functions in calibration and inverse problems, exhibit a natural substitution structure. A significant speedup is achieved compared with common reverse-mode AD.