Nonparametric Bayesian estimation of a Hölder continuous diffusion coefficient
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Publication:783274
DOI10.1214/19-BJPS433zbMath1445.62071arXiv1706.07449MaRDI QIDQ783274
Shota Gugushvili, Moritz Schauer, Peter Spreij, Frank H. van der Meulen
Publication date: 12 August 2020
Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1706.07449
stochastic differential equationdiffusion coefficientvolatilitypseudo-likelihoodposterior contraction ratenonparametric Bayesian estimationGaussian likelihood
Applications of statistics to economics (62P20) Density estimation (62G07) Economic time series analysis (91B84) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Diffusion processes (60J60) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70)
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Cites Work
- Understanding predictive information criteria for Bayesian models
- A sharp adaptive confidence ball for self-similar functions
- Estimating the diffusion coefficient function for a diversified world stock index
- Rates of contraction for posterior distributions in \(L^{r}\)-metrics, \(1 \leq r \leq \infty\)
- Gaussian pseudo-maximum likelihood estimation of fractional time series models
- Asymptotic statistics. With a view to stochastic processes
- On the Bernstein-von Mises phenomenon for nonparametric Bayes procedures
- Handbook of computational statistics. Concepts and methods.
- Martingale methods in financial modelling.
- A Bernstein-von Mises theorem for smooth functionals in semiparametric models
- Honest Bayesian confidence sets for the \(L^2\)-norm
- Convergence rates of posterior distributions for non iid observations
- Testing diffusion processes for non-stationarity
- Pricing of derivatives on mean-reverting assets
- \(L_p\) estimation of the diffusion coefficient
- Minimax estimation of the diffusion coefficient through irregular samplings
- An algorithm for nonparametric Bayesian estimation of a Poisson intensity
- Statistical inference for ergodic diffusion processes.
- Adaptive estimation in diffusion processes.
- Reversible jump MCMC for nonparametric drift estimation for diffusion processes
- Gaussian pseudo-likelihood estimation for stationary processes on a lattice
- Nonparametric estimation of scalar diffusions based on low frequency data
- Convergence rates of posterior distributions.
- Rates of convergence of posterior distributions.
- Consistent nonparametric Bayesian inference for discretely observed scalar diffusions
- Nonparametric Bayesian drift estimation for multidimensional stochastic differential equations
- The rate of convergence of option prices on the asset following a geometric Ornstein-Uhlenbeck process
- A Fourier transform method for nonparametric estimation of multivariate volatility
- Bayesian estimation of discretely observed multi-dimensional diffusion processes using guided proposals
- Nonparametric Bayesian posterior contraction rates for discretely observed scalar diffusions
- Efficient maximum likelihood estimation for Lévy-driven Ornstein-Uhlenbeck processes
- Simulation and inference for stochastic differential equations. With R examples.
- Misspecification in infinite-dimensional Bayesian statistics
- Frequentist coverage of adaptive nonparametric Bayesian credible sets
- ARCH models as diffusion approximations
- On inference for partially observed nonlinear diffusion models using the Metropolis-Hastings algorithm
- ESTIMATION OF STOCHASTIC VOLATILITY MODELS BY NONPARAMETRIC FILTERING
- Maximum penalized quasi-likelihood estimation of the diffusion function
- Inference for Diffusion Processes
- Nonparametric estimation of diffusions: a differential equations approach
- Posterior contraction rate for non-parametric Bayesian estimation of the dispersion coefficient of a stochastic differential equation
- Julia: A Fresh Approach to Numerical Computing
- Séries temporelles avec R
- Estimation of Integrated Volatility in Continuous-Time Financial Models with Applications to Goodness-of-Fit Testing
- On Rates of Convergence for Bayesian Density Estimation
- Least Squares Volatility Change Point Estimation for Partially Observed Diffusion Processes
- Probability with Martingales
- Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
- Non-parametric Bayesian Estimation of a Spatial Poisson Intensity
- On estimating the diffusion coefficient from discrete observations
- Non parametric estimation of the diffusion coefficient of a diffusion process
- Likelihood Inference for Discretely Observed Nonlinear Diffusions
- Introduction to Time Series and Forecasting
- Bayesian Measures of Model Complexity and Fit
- Non‐parametric Kernel Estimation of the Coefficient of a Diffusion
- Consistent non-parametric Bayesian estimation for a time-inhomogeneous Brownian motion
- NONPARAMETRIC FILTERING OF THE REALIZED SPOT VOLATILITY: A KERNEL-BASED APPROACH
- All of Nonparametric Statistics
- The Deviance Information Criterion: 12 Years on
- Introduction to nonparametric estimation
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