Banking
Semi-analytic conditional expectations
A data-driven approach to computing expectations for the pricing and hedging of exotics
Singular exotic perturbation
A solution based on local volatility and sensitivities is proposed to calculate exotics' prices
The future of skew
Forward start volatility swaps and their pricing and hedging models are introduced
Chebyshev Greeks: smoothing gamma without bias
A numerical method to obtain stable deltas and gammas for complex payoffs is presented
Mind the gap
A default intensity model reveals the risk carried by a highly leveraged counterparty
A new fast local volatility model
A local volatility model based on the Bass construction and alternative to Dupire-style models is introduced
Valuation and risk management of vanilla Libor swaptions in a fallback
A procedure to price vanilla European Libor swaptions derived from the SABR model is presented
Deep hedging: learning to remove the drift
Removing arbitrage opportunities from simulated data used for training makes deep hedging more robust
Sec-lending haircuts and indemnification pricing
A pricing method for borrowed securities that includes haircut and indemnification is introduced
Efficient simulation of affine forward variance models
Andersen's quadratic-exponential scheme is used for simulations of rough volatility models
Dynamically controlled kernel estimation
An accurate data-driven and model-agnostic method to compute conditional expectations is presented
Optimal transport for model calibration
Volatility models and SPX/VIX joint dynamics are calibrated using optimal transport theory
Sticky varswaps
Bergomi's skew-stickiness ratio is extended to the setting of variance swaps
Multi-horizon forecasting for limit order books
A multi-step path is forecast using deep learning and parallel computing
Approximating lifetime expected credit loss
Credit rating and collateral value's changes have a measurable impact on creditworthiness
Black basket analytics for mid-curves and spread options
A new solution to calibrate derivatives with multiple strikes is proposed
Deep learning profit and loss
The P&L distribution of a complex derivatives portfolio is computed via deep learning
Axes that matter: PCA with a difference
Differential PCA is introduced to reduce the dimensionality in derivative pricing problems
NLP and transformer models for credit risk
News feeds are factored into models to predict credit events
Risky caplet pricing with backward-looking rates
The Hull-White model for short rates is extended to include compounded rates and credit risk
Capturing the effects of climate change on CVA and FVA
A framework to incorporate climate change risk into derivative prices is presented
The curious case of backward short rates
A discretisation approach for both backward- and forward-looking interest rate derivatives is proposed
A Darwinian theory of model risk
An ex ante methodology is proposed to analyse the model risk pattern for a broad class of structures
An approximate solution for options market-making
An algorithm for the market-making of options on different underlyings is proposed