Technical paper/Hedging
AI as pricing law
A neural network tailored to financial asset pricing principles is introduced
CVA sensitivities, hedging and risk
A probabilistic machine learning approach to CVA calculations is proposed
Joint S&P 500/VIX smile calibration in discrete and continuous time
An arbitrage-free model for exotic options that captures smiles and futures is presented
Exchange rate risk management for contractors within a hybrid payment scheme: a case study in Punta del Este, Uruguay
The author proposes methods for how contractors may attempt to mitigate exchange rate risks in hybrid payment systems and validates these with empirical data from a hypothetical project.
Hedging of financial derivative contracts via Monte Carlo tree search
This paper applies the Monte Carlo tree search as a method for replication in the presence of risk and market friction
Information geometry of risks and returns
An innovative product design framework and its geometric interpretation is introduced
Dealing with multi-currency inventory risk in FX cash markets
A market-making model that considers correlation, transaction costs and market impact is presented
Pricing in the gap risk of mini-futures
Mini-futures need to be priced and hedged taking sudden jumps into account
Interpolating commodity futures prices with Kriging
A futures price’s term structure is built to account for trends and seasonality effects
Market-making by a foreign exchange dealer
An optimal liquidity model for pricing and hedging decisions is presented
A three-factor hazard rate model for single-name credit default swap pricing
The authors propose a reduced-form model in which the evolution of the risk-neutral hazard rate is driven by three risk factors.
Semi-analytic conditional expectations
A data-driven approach to computing expectations for the pricing and hedging of exotics
The future of skew
Forward start volatility swaps and their pricing and hedging models are introduced
Pricing barrier options with deep backward stochastic differential equation methods
This paper presents a novel and direct approach to solving boundary- and final-value problems, corresponding to barrier options, using forward pathwise deep learning and forward–backward stochastic differential equations.
Deep hedging: learning to remove the drift
Removing arbitrage opportunities from simulated data used for training makes deep hedging more robust
Dynamically controlled kernel estimation
An accurate data-driven and model-agnostic method to compute conditional expectations is presented
A Darwinian theory of model risk
An ex ante methodology is proposed to analyse the model risk pattern for a broad class of structures
The cost of hedging XVA
HVA is framed consistently with other valuation adjustments
Impact of hedging strategies on variable annuities
Put options may reduce the cost of hedging strategies for insurers
Optimal foreign exchange hedge tenor with liquidity risk
The authors develop an optimal currency hedging strategy that allows fund managers who own foreign assets to choose the hedge tenors that will maximize their foreign exchange carry returns within a liquidity risk constraint.
A verification model to capture option risk and hedging based on a modified underlying beta
This paper analyzes the relationship between option risk and expected return from the perspective of the underlying beta, and estimates the degree of correlation.