quarticity_rtq: Realized Tripower Quarticity

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

View source: R/metrics.R

Description

Realized Tri-power Quarticity (RTQ) is an asymptotically unbiased estimator of integrated quarticity in the absence of microstructure noise.

Usage

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quarticity_rtq(estimator)

Arguments

estimator

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

Details

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

- Accounts for additive noise: no

- Accounts for finite price jumps: yes

- Accounts for time dependence in noise: no

- Accounts for endogenous effects in noise: no

Value

a numeric vector of the same length as input data.

Author(s)

Kostin Andrey <andrei.kostin@snowfallsystems.com>

References

Andersen, T. G., Bollerslev, T., and Diebold, F. X. (2005),"Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility" Tech. rep., NBER

See Also

quarticity_rq quarticity_rqq quarticity_mrq quarticity_mtq

Examples

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

## End(Not run)

PortfolioEffectEstim documentation built on May 2, 2019, 8:50 a.m.