Description Usage Arguments Details Value Author(s) References See Also Examples
Realized Variance (RV) is the sum of squared returns. For instance the RV can be the sum of squared daily returns for a particular month, which would yield a measure of price variation over this month. This variance estimator does not account for market microstructure effects.
1 2 | variance_rv(estimator)
variance_rvRolling(estimator,wLength=23400)
|
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) |
- Convergence speed: m^{1/2} (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 vector of integrated variance estimates
Kostin Andrey <andrey.kostin@portfolioeffect.com>
T. G. Andersen, T. Bollerslev, F. X. Diebold, and P. Labys. "The distribution of realized exchange rate volatility". Journal of American Statistical Association, 96(453):4255, March 2001. 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.
variance_jrmrv
variance_tsrv
variance_msrv
variance_mrv
variance_uzrv
variance_krv
1 2 3 4 5 6 7 8 9 10 11 |
## Not run:
data(spy.data)
estimator=estimator_create(priceData=spy.data)
estimator_settings(estimator,
inputSamplingInterval = '10s',
resultsSamplingInterval = '10s')
util_plot2d(variance_rv(estimator),title='RV',legend='Simple')+
util_line2d(variance_rvRolling(estimator,wLength=3600),legend='Rolling Window')
## End(Not run)
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