false

Pricing Quanto and Composite Contracts with Local-Correlation Models

Pricing Quanto and Composite Contracts with Local-Correlation Models ArXiv ID: 2501.07200 “View on arXiv” Authors: Unknown Abstract Pricing composite and quanto contracts requires a joint model of both the underlying asset and the exchange rate. In this contribution, we explore the potential of local-correlation models to address the challenges of calibrating synthetic quanto forward contracts and composite options quoted in the market. Specifically, we design on-line calibration procedures for generic local and stochastic volatility models. The paper concludes with a numerical study assessing the calibration performance of these methodologies and comparing them to simpler approximations of the correlation structure. ...

January 13, 2025 · 1 min · Research Team

CVA Hedging by Risk-Averse Stochastic-Horizon Reinforcement Learning

CVA Hedging by Risk-Averse Stochastic-Horizon Reinforcement Learning ArXiv ID: 2312.14044 “View on arXiv” Authors: Unknown Abstract This work studies the dynamic risk management of the risk-neutral value of the potential credit losses on a portfolio of derivatives. Sensitivities-based hedging of such liability is sub-optimal because of bid-ask costs, pricing models which cannot be completely realistic, and a discontinuity at default time. We leverage recent advances on risk-averse Reinforcement Learning developed specifically for option hedging with an ad hoc practice-aligned objective function aware of pathwise volatility, generalizing them to stochastic horizons. We formalize accurately the evolution of the hedger’s portfolio stressing such aspects. We showcase the efficacy of our approach by a numerical study for a portfolio composed of a single FX forward contract. ...

December 21, 2023 · 2 min · Research Team