noise_rnv: Rescaled Noise Variance
In PortfolioEffectEstim: High Frequency Price Estimators by PortfolioEffect

Description Usage Arguments Details Value Author(s) References See Also Examples

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.

1	noise_rnv(estimator)

estimator

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

- 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

a numeric vector of the same length as data.

Kostin Andrey <andrey.kostin@portfolioeffect.com>

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.

noise_acnv noise_urnv noise_uznv

 
## 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)