PortfolioEffectEstim (version 1.4)

variance_jrmrv: Jump Robust Modulated Realized Variance

Description

Jump Robust Modulated Realized Variance (JRMRV) is an integrated variance estimator introduced by Podolskij and Vetter. It is based on the concept of multipower variation, is robust to finite activity jumps and assumes additive noise structure.

Usage

variance_jrmrv(estimator)
variance_jrmrvRolling(estimator,wLength=23400)

Arguments

estimator

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

wLength

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

Value

Details

Converges to integrated variance

- Convergence speed: $m^{1/6}$ (m - number of observation)

- Accounts for additive noise: yes

- Accounts for finite price jumps: yes

- Accounts for time dependence in noise: no

- Accounts for endogenous effects in noise: no

References

M. Podolskij and M. Vetter, "Estimation of volatility functionals in the simultaneous presence of microstructure noise and jumps," Bernoulli, vol. 15, No. 3, pp. 634-658, 2009.

See Also

variance_rv variance_tsrv variance_msrv 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_jrmrv(estimator),title='JRMRV',legend='Simple')+
# util_line2d(variance_jrmrvRolling(estimator,wLength=3600),legend='Rolling Window')
# ## End(Not run)