We consider two data-driven approaches to hedging, Reinforcement Learning and Deep Trajectory-based Stochastic Optimal Control, under a stepwise mean-variance objective. We compare their performance for a European call option in the presence of transaction costs under discrete trading schedules....

This work introduces two new financial derivatives into the finance literature. The first is the Return Barrier Option, which has emerged recently as a popular contract in the OTC markets. This contract is similar to a barrier option, but the knock-out event depends on an asset’s returns,...

A common shortcut to forecasting initial margin requirements and margin valuation adjustments that are aligned with the International Swaps and Derivatives Association's Standard Initial Margin Model relies on simulating and recalibrating value-at-risk quantiles. Doing so largely avoids costly...

This research explores upside and downside jumps in the dynamic processes of three rates: domestic interest rates, foreign interest rates, and exchange rates. To fill the gap between the asymmetric jump in the currency market and the current models, a correlated asymmetric jump model is proposed...

We calculate the social cost of carbon (SCC) under stochastic climate volatility resulting from uncertainty about future climate risk regimes where weather extremes are becoming more frequent and intense. Using a stochastic dynamic integrated climate-economy model where representative agents are...