• Corpus ID: 59399566

Central limit theorems for pre-averaging covariance estimators under endogenous sampling times

@article{Koike2013CentralLT,
  title={Central limit theorems for pre-averaging covariance estimators under endogenous sampling times},
  author={Yuta Koike},
  journal={arXiv: Statistics Theory},
  year={2013}
}
  • Yuta Koike
  • Published 6 May 2013
  • Mathematics
  • arXiv: Statistics Theory
We consider two continuous It\^o semimartingales observed with noise and sampled at stopping times in a nonsynchronous manner. In this article we establish a central limit theorem for the pre-averaged Hayashi-Yoshida estimator of their integrated covariance in a general endogenous time setting. In particular, we show that the time endogeneity has no impact on the asymptotic distribution of the pre-averaged Hayashi-Yoshida estimator, which contrasts the case for the realized volatility in a pure… 
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References

SHOWING 1-10 OF 50 REFERENCES

Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling

On Covariation Estimation for Multivariate Continuous Itô Semimartingales with Noise in Non-Synchronous Observation Schemes

This paper presents a Hayashi-Yoshida-type estimator for the covariation matrix of continuous Ito semimartingales observed with noise and shows the associated central limit theorem for the proposed estimator and provides a feasible asymptotic result.

Realized volatility with stochastic sampling

Quasi-Maximum Likelihood Estimation of Volatility with High Frequency Data

This paper investigates the properties of the well-known maximum likelihood estimator in the presence of stochastic volatility and market microstructure noise, by extending the classic asymptotic

Multivariate Realised Kernels: Consistent Positive Semi-Definite Estimators of the Covariation of Equity Prices with Noise and Non-Synchronous Trading

We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to

Estimating the Quadratic Covariation Matrix from Noisy Observations: Local Method of Moments and Efficiency

An efficient estimator is constructed for the quadratic covariation or integrated covolatility matrix of a multivariate continuous martingale based on noisy and non-synchronous observations under