Search Results - subject:"microstructure noise"

Can microstructure noise explain the MAX effect?

Zhang, Xindong; Xie, Lixu; Zhai, Yue; Wang, Dong - In: Finance research letters 26 (2018), pp. 185-191

Persistent link: https://www.econbiz.de/10012005667

Is the diurnal pattern sufficient to explain intraday variation in volatility? : a nonparametric assessment

Christensen, Kim; Hounyo, Ulrich; Podolskij, Mark - In: Journal of econometrics 205 (2018) 2, pp. 336-362

Persistent link: https://www.econbiz.de/10012110287

Efficient asymptotic variance reduction when estimating volatility in high frequency data

Clinet, Simon; Potiron, Yoann - In: Journal of econometrics 206 (2018) 1, pp. 103-142

Persistent link: https://www.econbiz.de/10012110370

A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data

Lam, Clifford; Feng, Phoenix - In: Journal of econometrics 206 (2018) 1, pp. 226-257

Persistent link: https://www.econbiz.de/10012110378

Estimation of spot volatility with superposed noisy data

Liu, Qiang; Liu, Yiqi; Liu, Zhi; Wang, Li - In: The North American journal of economics and finance : a … 44 (2018), pp. 62-79

Persistent link: https://www.econbiz.de/10012036296

Realized mixed-frequency factor models for vast dimensional covariance estimation

van Dijk, Dick; Bannouh, Bannouh, K.; Martens, Martens, … - Erasmus Research Institute of Management (ERIM), … - 2012

) as factors. Prices for these contracts are observed essentially free of microstructure noise at high frequencies …

Persistent link: https://www.econbiz.de/10010730865

Microstructure effect on firm’s volatility risk

Barsotti, Flavia; Sanfelici, Simona - Dipartimento di Scienze per l'Economia e l'Impresa, … - 2012

introducing market microstructure noise as a direct effect of using noisy high-frequency data and propose the use of non … performance of different non-parametric volatil- ity estimators in their capability of i) filtering out the market microstructure … noise, ii) extracting the (unobservable) true underlying asset volatility level, iii) predicting default probabilies …

Persistent link: https://www.econbiz.de/10010734984

Forecasting Volatility with the Realized Range in the Presence of Noise and Non-Trading

van Dijk, Dick; Bannouh, Bannouh, K.; Martens, Martens, … - Erasmus Research Institute of Management (ERIM), … - 2012

We introduce a heuristic bias-adjustment for the transaction price-based realized range estimator of daily volatility in the presence of bid-ask bounce and non-trading. The adjustment is an extension of the estimator proposed in Christensen et al. (2009). We relax the assumption that all...

Persistent link: https://www.econbiz.de/10010837698

Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices

Shephard, Neil; Xiu, Dacheng - Department of Economics, Oxford University - 2012

Estimating the covariance and correlation between assets using high frequency data is challenging due to market microstructure effects and Epps effects. In this paper we extend Xiu's univariate QML approach to the multivariate case, carrying out inference as if the observations arise from an...

Persistent link: https://www.econbiz.de/10011004207

An Empirical Analysis of the Nikkei 225 Put Options Using Realized GARCH Models

Takeuchi-Nogimori, Asuka - Institute of Economic Research, Hitotsubashi University - 2012

for the bias in realized volatility caused by the presence of market microstructure noise and non-trading hours, and …

Persistent link: https://www.econbiz.de/10011144001