  In this paper, we examine the capacity of an arbitrage-free neural-SDE market
model to produce realistic scenarios for the joint dynamics of multiple
European options on a single underlying. We subsequently demonstrate its use as
a risk simulation engine for option portfolios. Through backtesting analysis,
we show that our models are more computationally efficient and accurate for
evaluating the Value-at-Risk (VaR) of option portfolios, with better coverage
performance and less procyclicality than standard filtered historical
simulation approaches.
