Description Usage Arguments Details Value Author(s) References See Also Examples
Realized Tri-power Quarticity (RTQ) is an asymptotically unbiased estimator of integrated quarticity in the absence of microstructure noise.
1 | quarticity_rtq(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: yes
- 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>
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
quarticity_rq
quarticity_rqq
quarticity_mrq
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_rtq(estimator),title="RTQ")
## End(Not run)
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