Model calibration
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.
Data shortage hits margin models for Asia banks
Thin trade volumes in local derivatives threaten to undermine key tests for initial margin models
How old calibration techniques can be applied to exotics pricing
SocGen quants propose technique to more accurately calibrate exotic options
Equity modelling with local stochastic volatility and stochastic discrete dividends
SocGen quants calibrate local stochastic volatility models with stochastic dividends
Swaptions vol modelling tweak opens up pricing possibilities
Nomura quant proposes local volatility model that can directly calibrate to swaption smiles
The swap market model with local stochastic volatility
An easy to calibrate and accurate swap market model is proposed
Podcast: Callegaro, Fiorin and Grasselli on quantization
High-dimension problems can be solved with discretisation techniques
American quantized calibration in stochastic volatility
Fiorin, Callegaro and Grasselli show how discretisation methods reduce computing time in high-dimensional problems
Quantitative finance still needs mathematicians
Quants develop model that fixes a longstanding problem with pricing American options
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.
Exposing actionable insights in credit risk management
Sponsored webinar: Moody's Analytics and Qlik
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.