[[abstract]]It is documented that realized variance (RV) sampled at ultra-high frequency is unreliable when observed prices are contaminated by market microstructure noise. Accordingly, in practice, it is common to choose a moderate frequency ranges from 5 to 30 minutes instead of at every tick for balancing a bias/variance trade-off. This study aims to investigate the efficient frequency for daily RV of spot and futures assets, and compare the performance of forecasting spot-futures distribution using the sparsely sampled RV estimates. Obtaining tick-by-tick records from NASDAQ 100 markets, both unconditional and the conditional sampling rules are investigated. It is found that the optimal frequency for sampling the assets is more likely t...
textabstractThis paper investigates the merits of high-frequency intraday data when forming minimum ...
We compare the forecasts of Quadratic Variation given by the Realized Volatility (RV) and the Two Sc...
This article investigates the merits of high-frequency intraday data when forming mean-variance effi...
In this article I study the statistical properties of a bias-corrected realized variance measure whe...
This article evaluates the economic benefit of methods that have been suggested to optimally sample ...
This paper investigates the statistical properties of the realized variance estimator in the presenc...
In this paper I study the statistical properties of a bias corrected realized variance measure when ...
In this paper we study the impact of market microstructure effects on the properties of realized var...
A recent and extensive literature has pioneered the summing of squared observed intra-daily returns,...
In this paper we study various MIDAS models in which the future daily variance is directly related t...
In this paper I study the statistical properties of a bias corrected realized variance measure when ...
The realized variance (RV) is known to be biased because intraday returns are con-taminated with mar...
ACL-2International audienceIn this paper we study various MIDAS models for which the future daily va...
Predicting volatility of financial assets based on realized volatility has grown popular in the lite...
Assessing the economic value of increasingly precise covariance estimates is of great interest in fi...
textabstractThis paper investigates the merits of high-frequency intraday data when forming minimum ...
We compare the forecasts of Quadratic Variation given by the Realized Volatility (RV) and the Two Sc...
This article investigates the merits of high-frequency intraday data when forming mean-variance effi...
In this article I study the statistical properties of a bias-corrected realized variance measure whe...
This article evaluates the economic benefit of methods that have been suggested to optimally sample ...
This paper investigates the statistical properties of the realized variance estimator in the presenc...
In this paper I study the statistical properties of a bias corrected realized variance measure when ...
In this paper we study the impact of market microstructure effects on the properties of realized var...
A recent and extensive literature has pioneered the summing of squared observed intra-daily returns,...
In this paper we study various MIDAS models in which the future daily variance is directly related t...
In this paper I study the statistical properties of a bias corrected realized variance measure when ...
The realized variance (RV) is known to be biased because intraday returns are con-taminated with mar...
ACL-2International audienceIn this paper we study various MIDAS models for which the future daily va...
Predicting volatility of financial assets based on realized volatility has grown popular in the lite...
Assessing the economic value of increasingly precise covariance estimates is of great interest in fi...
textabstractThis paper investigates the merits of high-frequency intraday data when forming minimum ...
We compare the forecasts of Quadratic Variation given by the Realized Volatility (RV) and the Two Sc...
This article investigates the merits of high-frequency intraday data when forming mean-variance effi...