Derives non-asymptotic MSE bounds separating discretization and fluctuation errors for expected signature estimation via block averaging under weak dependence for rough paths.
Quantitative Finance , volume =
7 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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UNVERDICTED 7representative citing papers
Rough-path market models satisfying no-controlled-free-lunch reduce admissible drivers to Itô lifts of Brownian motion (up to time change) once signature-type strategies are allowed.
Develops a Hilbert space-valued Markovian lift framework for stochastic Volterra equations and establishes existence of limit distributions, LLN with convergence rate, and CLT for time averages in the Gaussian domain.
Constructs QMLE for drift parameter in singular Volterra SDE with small diffusion, proving path reconstruction error O(h^{1/2}) independent of roughness α and yielding efficient estimator as ε→0.
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.
Develops a singular stochastic control model for optimal execution with stochastic resilience dynamics and regime-switching liquidity, proving the value function is the unique viscosity solution to a system of variational HJB inequalities.
Constructs a consistent and asymptotically normal trajectory fitting estimator for the drift parameter θ* in singular-kernel stochastic Volterra equations under small-noise asymptotics.
citing papers explorer
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Finite-Sample Bounds for Expected Signature Estimation under Weak Dependence
Derives non-asymptotic MSE bounds separating discretization and fluctuation errors for expected signature estimation via block averaging under weak dependence for rough paths.
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Unbiased Rough Integrators and No Free Lunch in Rough-Path-Based Market Models
Rough-path market models satisfying no-controlled-free-lunch reduce admissible drivers to Itô lifts of Brownian motion (up to time change) once signature-type strategies are allowed.
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Limit theorems for stochastic Volterra processes
Develops a Hilbert space-valued Markovian lift framework for stochastic Volterra equations and establishes existence of limit distributions, LLN with convergence rate, and CLT for time averages in the Gaussian domain.
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Drift estimation for rough processes under small noise asymptotic : QMLE approach
Constructs QMLE for drift parameter in singular Volterra SDE with small diffusion, proving path reconstruction error O(h^{1/2}) independent of roughness α and yielding efficient estimator as ε→0.
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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.
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Optimal Execution under Liquidity Uncertainty
Develops a singular stochastic control model for optimal execution with stochastic resilience dynamics and regime-switching liquidity, proving the value function is the unique viscosity solution to a system of variational HJB inequalities.
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Drift estimation for rough processes under small noise asymptotic : trajectory fitting method
Constructs a consistent and asymptotically normal trajectory fitting estimator for the drift parameter θ* in singular-kernel stochastic Volterra equations under small-noise asymptotics.