PortfolioEffectEstim (version 1.4)

variance_msrv: Multiple Scales Realized Variance

Description

Multiple Series Realized Variance (MSRV) is a generalization of the TSRV estimator of integrated volatility. It uses multiple time scales to account for the effects of additive market microstructure noise.

Usage

variance_msrv(estimator,K=2,J=1)
variance_msrvRolling(estimator,K=2,J=1,wLength=23400)

Arguments

estimator

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

K

number of subsamples in the slow time series (default: 2)

J

number of subsamples in the fast time series (default: 1)

wLength

Length of a rolling window for rolling estimators. Default window length is 23400 (number of seconds in a trading day)

Value

Details

- Convergence speed: $m^{1/4}$ (m - number of observation)

- Accounts for additive noise: yes

- Accounts for finite price jumps: no

- Accounts for time dependence in noise: yes

- Accounts for endogenous effects in noise: no

References

Zhang, L. (2006). Efficient estimation of stochastic volatility using noisy observations: A multiscale approach.

See Also

variance_rv variance_tsrv variance_jrmrv variance_mrv variance_uzrv variance_krv

Examples

## Not run: 
# data(spy.data) 
# estimator=estimator_create(priceData=spy.data)
# estimator_settings(estimator,
# 				   inputSamplingInterval = '10s',
# 				   resultsSamplingInterval = '10s')
# util_plot2d(variance_msrv(estimator),title='MSRV',legend='Simple')+
# util_line2d(variance_msrvRolling(estimator,wLength=3600),legend='Rolling Window')
# ## End(Not run)