PortfolioEffectEstim (version 1.4)

noise_urnv: Unbiased Rescaled Noise Variance

Description

Unbiased Rescaled Noise Variance (URNV) corrects for a bias of Rescaled Noise Variance.

Usage

noise_urnv(estimator)

Arguments

estimator

Vector of (time, price) observations for market asset when external market data is used.

Value

Details

- Convergence speed: $m^{1/2}$ (m - number of observation)

- Accounts for additive noise: yes

- Accounts for finite price jumps: no

- Accounts for time dependence in noise: no

- Accounts for endogenous effects in noise: no

References

L. Zhang, P. A. Mykland, and Y. Ait-Sahalia, "A tale of two time scales: Determining integrated volatility with noisy high-frequency data," Journal of the American Statistical Association, vol. 100, No. 472, pp. 1394-1411, December 2005.

See Also

noise_rnv noise_acnv noise_uznv

Examples

## Not run: 
# data(spy.data) 
# estimator=estimator_create(priceData=spy.data)
# estimator_settings(estimator,
# 				   inputSamplingInterval = '10s',
# 				   resultsSamplingInterval = '10s')
# util_plot2d(noise_urnv(estimator),title="URNV")
# ## End(Not run)