arXiv subjects
Publications and source records attributed to Ryoji Takano.
We extend the semigroup approach used in [23,21] to provide alternative proofs of the reconstruction theorem and the multilevel Schauder estimate for singular modelled distributions. As an application of them, we construct the local-in-time solution of the two dimensional parabolic Anderson model with a non-translation invariant differential operator.
In this paper, we prove the large deviation principle (LDP) for stochastic differential equations driven by stochastic integrals in one dimension. The result can be proved with a minimal use of rough path theory, and this implies the LDP for many class of rough volatility models, and it characterizes the asymptotic behavior of implied volatility. First, we introduce a new concept called $\alpha$-Uniformly Exponentially Tightness, and prove the LDP for stochastic integrals on H\"{o}lder spaces. Second, we apply this type of LDP to deduce the LDP for stochastic differential equations driven by stochastic integrals in one dimension. Finally, we derive the asymptotic behavior of the implied volatility as an application of main results.
We develop a variant of rough path theory tailor-made for analyzing a class of financial asset price models known as rough volatility models. As an application, we prove a pathwise large deviation principle (LDP) for a certain class of rough volatility models, which in turn describes the limiting behavior of implied volatility for short maturity under those models. First, we introduce a partial rough path space and an integration map on it and then investigate several fundamental properties including local Lipschitz continuity of the integration map from the partial rough path space to a rough path space. Second, we construct a rough path lift of a rough volatility model. Finally, we prove an LDP on the partial rough path space, and the LDP for rough volatility then follows by the continuity of the solution map of rough differential equations.