PortfolioEffectEstim (version 1.4)

noise_rnv: Rescaled Noise Variance

Description

Rescaled Noise Variance (RNV) is an asymptotically consistent estimator of noise volatility when daling with additive microstructure noise. It is derived based on Realized Variance property of convergence to noise variance wih the increase of sampling frequency.

Usage

noise_rnv(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

Bandi, F. M., and J. R. Russell, 2004, "Microstructure Noise, Realized Variance, and Optimal Sampling" manuscript GSB, The University of Chicago. 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_acnv noise_urnv noise_uznv

Examples

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