13 citations · 27 across the 9 of their papers we have counts for
13 papers
A secondary index map on relative K-homology
Matti Lyko
We introduce a secondary index map from relative K-homology to the K-theory of a relative structure algebra. We prove an algebraic Mayer-Vietoris sequence for the relative structur…
Asymptotically uniformly most powerful tests for diffusion processes with nonsynchronous observations
Teppei Ogihara, Futo Ueno
This paper introduces a quasi-likelihood ratio testing procedure for diffusion processes observed under nonsynchronous sampling schemes. High-frequency data, particularly in financ…
Asymptotically efficient estimation for diffusion processes with nonsynchronous observations
Teppei Ogihara
We study maximum-likelihood-type estimation for diffusion processes when the coefficients are nonrandom and observation occurs in nonsynchronous manner. The problem of nonsynchrono…
Efficient drift parameter estimation for ergodic solutions of backward SDEs
Teppei Ogihara, Mitja Stadje
We derive consistency and asymptotic normality results for quasi-maximum likelihood methods for drift parameters of ergodic stochastic processes observed in discrete time in an und…
Local Asymptotic Mixed Normality via Transition Density Approximation and an Application to Ergodic Jump-Diffusion Processes
Teppei Ogihara, Yuma Uehara
We study sufficient conditions for local asymptotic mixed normality. We weaken the sufficient conditions in Theorem 1 of Jeganathan (Sankhya Ser. A 1982) so that they can be applie…
Malliavin calculus techniques for local asymptotic mixed normality and their application to degenerate diffusions
Masaaki Fukasawa, Teppei Ogihara
We study sufficient conditions for a local asymptotic mixed normality property of statistical models. We develop a scheme with the regularity condition proposed by Jeganathan…
Misspecified diffusion models with high-frequency observations and an application to neural networks
Teppei Ogihara
We study the asymptotic theory of misspecified models for diffusion processes with noisy nonsynchronous observations. Unlike with correctly specified models, the original maximum-l…
Quasi likelihood analysis of point processes for ultra high frequency data
Teppei Ogihara, Nakahiro Yoshida
We introduce a point process regression model that is applicable to price models and limit order book models. Hawkes type autoregression in the intensity process is generalized to…
Asymptotic error distributions of the Euler method for continuous-time nonlinear filtering
Teppei Ogihara, Hideyuki Tanaka
We deduce the asymptotic error distribution of the Euler method for the nonlinear filtering problem with continuous-time observations. Previous works by several authors have shown…
Parametric Inference for Nonsynchronously Observed Diffusion Processes in the Presence of Market Microstructure Noise
Teppei Ogihara
We study parametric inference for diffusion processes when observations occur nonsynchronously and are contaminated by market microstructure noise. We construct a quasi-likelihood…
On Asymptotic Properties of Bayes Type Estimators with General Loss Functions
Teppei Ogihara
We study asymptotic behaviors of Bayes type estimators and give sufficient conditions to obtain asymptotic limit distribution of estimation error. We assume polynomial type large d…
Local asymptotic mixed normality property for nonsynchronously observed diffusion processes
Teppei Ogihara
We prove the local asymptotic mixed normality (LAMN) property for a family of probability measures defined by parametrized diffusion processes with nonsynchronous observations. We…
Quasi-Likelihood Analysis for Stochastic Regression Models with Nonsynchronous Observations
Teppei Ogihara, Nakahiro Yoshida
We consider nonsynchronous sampling of parameterized stochastic regression models, which contain stochastic differential equations. Constructing a quasi-likelihood function, we pro…