Develops a stochastic control model for option market making with hedging-induced impact on the underlying, analyzes manipulation and arbitrage risks, proves well-posedness of the mixed control problem, and numerically approximates optimal strategies via policy optimization.
Quantitative Finance , volume =
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
A deep learning dynamic programming scheme prices path-dependent convertible bonds under GBM, CEV and Heston dynamics, showing that reset and call clauses dominate the underlying process in determining value and that downward resets can paradoxically lower bond prices.
Extends rough fractional stochastic volatility to a multivariate fOU model with GMM estimation, simulation validation, and empirical analysis of realized volatility series showing correlations and spillover effects.
citing papers explorer
-
Option market making with hedging-induced market impact
Develops a stochastic control model for option market making with hedging-induced impact on the underlying, analyzes manipulation and arbitrage risks, proves well-posedness of the mixed control problem, and numerically approximates optimal strategies via policy optimization.
-
A deep learning approach for pricing convertible bonds with path-dependent reset and call provisions
A deep learning dynamic programming scheme prices path-dependent convertible bonds under GBM, CEV and Heston dynamics, showing that reset and call clauses dominate the underlying process in determining value and that downward resets can paradoxically lower bond prices.
-
Multivariate Rough Volatility
Extends rough fractional stochastic volatility to a multivariate fOU model with GMM estimation, simulation validation, and empirical analysis of realized volatility series showing correlations and spillover effects.