  Market making of options with different maturities and strikes is a
challenging problem due to its high dimensional nature. In this paper, we
propose a novel approach that combines a stochastic policy and reinforcement
learning-inspired techniques to determine the optimal policy for posting
bid-ask spreads for an options market maker who trades options with different
maturities and strikes. When the arrival of market orders is linearly inverse
to the spreads, the optimal policy is normally distributed.
