Conditionally Gaussian random sequences for an integrated variance estimator with correlation between noise and returns
From MaRDI portal
Publication:6574633
DOI10.1002/asmb.2476MaRDI QIDQ6574633
Antonietta Mira, Pietro Muliere, Stefano Peluso
Publication date: 18 July 2024
Published in: Applied Stochastic Models in Business and Industry (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Robust Kalman tracking and smoothing with propagating and non-propagating outliers
- Estimating quadratic variation consistently in the presence of endogenous and diurnal measurement error
- Fractional integration versus level shifts: the case of realized asset correlations
- Sequential monitoring of portfolio betas
- Quasi-maximum likelihood estimation of volatility with high frequency data
- Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations
- Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading
- State space mixed models for longitudinal observations with binary and binomial responses
- Bayesian analysis of stochastic volatility models with fat-tails and correlated errors
- Exact mean integrated squared error
- Estimation of stochastic volatility models via Monte Carlo maximum likelihood
- Microstructure noise in the continuous case: the pre-averaging approach
- Shape bias of robust covariance estimators: an empirical study
- Modeling tick-by-tick realized correlations
- Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach
- Generalized dynamic linear models for financial time series
- AMERICAN OPTIONS WITH REGIME SWITCHING
- Monitoring Renal Transplants: An Application of the Multiprocess Kalman Filter
- Sensitivity Analysis for Mean-Variance Portfolio Problems
- Sampling-Based Approaches to Calculating Marginal Densities
- Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Non-Gaussian State-Space Modeling of Nonstationary Time Series
- Markov chain Monte Carlo in conditionally Gaussian state space models
- Normal Inverse Gaussian Distributions and Stochastic Volatility Modelling
- DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
- Multivariate Stochastic Variance Models
- On Gibbs sampling for state space models
- Markowitz's Mean-Variance Portfolio Selection with Regime Switching: A Continuous-Time Model
- A simple and efficient simulation smoother for state space time series analysis
- Mixture Kalman Filters
- On the Correlation Structure of Microstructure Noise: A Financial Economic Approach
- Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
- The simulation smoother for time series models
- Equation of State Calculations by Fast Computing Machines
- High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data
- Modeling and Forecasting Realized Volatility
- Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics
- Monte Carlo sampling methods using Markov chains and their applications
- A Tale of Two Time Scales
This page was built for publication: Conditionally Gaussian random sequences for an integrated variance estimator with correlation between noise and returns