Description Usage Arguments Details Value Author(s) References See Also Examples
Realized Quarticity (RQ) is an asymptotically unbiased estimator of integrated quarticity in the absence of microstructure noise.
1 | quarticity_rq(estimator)
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estimator |
Vector of (time, price) observations for market asset when external market data is used. |
- Convergence speed: m^{1/4} (m - number of observation)
- Accounts for additive noise: no
- 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 input data.
Kostin Andrey <andrei.kostin@snowfallsystems.com>
Barndorff-Nielsen, O. E. and N. Shephard (2002). Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society: Series B 64 (2), 253-280.
quarticity_mrq
quarticity_rqq
quarticity_rtq
quarticity_mtq
1 2 3 4 5 6 7 8 9 10 |
## Not run:
data(spy.data)
estimator=estimator_create(priceData=spy.data)
estimator_settings(estimator,
inputSamplingInterval = '10s',
resultsSamplingInterval = '10s')
util_plot2d(quarticity_rq(estimator),title="RQ")
## End(Not run)
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