| Type: | Package |
| Title: | Class of GARCH-Ito Models |
| Version: | 0.1.0 |
| Author: | Xinyu Song |
| Maintainer: | Xinyu Song <song.xinyu@mail.shufe.edu.cn> |
| Description: | Provides functions to estimate model parameters and forecast future volatilities using the Unified GARCH-Ito [Kim and Wang (2016) <doi:10.1016/j.jeconom.2016.05.003>] and Realized GARCH-Ito [Song et. al. (2020) <doi:10.1016/j.jeconom.2020.07.007>] models. Optimization is done using augmented Lagrange multiplier method. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.1 |
| Imports: | Rsolnp, stats |
| Depends: | R (≥ 2.10) |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2020-09-05 07:43:14 UTC; cindysong |
| Repository: | CRAN |
| Date/Publication: | 2020-09-14 09:10:14 UTC |
Realized GARCH-Ito Model
Description
Estimate model parameters for the Realized GARCH-Ito Model
Usage
RealizedEst(RV = RV, JV = NULL)
Arguments
RV |
Time series of daily realized volatilities. |
JV |
Time series of daily jump variations, |
Value
Estimated parameter values and daily conditional volatilities:
- coefficients
parameter estimates of the realized GARCH-Ito model
- sigma
daily conditional volatility estimates of the realized GARCH-Ito model
- pred
one-step-ahead predicted volatility value
References
Song, X., Kim, D., Yuan, H., Cui, X., Lu, Z., Zhou, Y., & Wang, Y. (2020). Volatility Analysis with Realized GARCH-Ito Models. Journal of Econometrics, in press.
Examples
sample_data
RealizedEst(sample_data$RV)
RealizedEst(sample_data$BPV, sample_data$JV)
Realized GARCH-Ito Model with Options
Description
Estimate model parameters for the Realized GARCH-Ito Model with Options
Usage
RealizedEst_Option(RV = RV, JV = NULL, NV = NULL, homogeneous = TRUE)
Arguments
RV |
Time series of daily realized volatilities. |
JV |
Time series of daily jump variations, |
NV |
Time series of daily volatilities estimated using option data |
homogeneous |
Whether to assume homogeneous error in the linear regression model between conditional volatility of the realized GARCH-Ito model and volatility estimated from the option data, default is TRUE. |
Value
Estimated parameter values and daily conditional volatilities:
- coefficients
parameter estimates of the realized GARCH-Ito model
- sigma
daily conditional volatility estimates of the realized GARCH-Ito model
- pred
one-step-ahead predicted volatility value
References
Song, X., Kim, D., Yuan, H., Cui, X., Lu, Z., Zhou, Y., & Wang, Y. (2020). Volatility Analysis with Realized GARCH-Ito Models. Journal of Econometrics, in press.
Unified GARCH-Ito Models
Description
Estimate model parameters for the Unified GARCH-Ito Model.
Usage
UnifiedEst(RV = RV, return = return)
Arguments
RV |
Time series of daily realized volatilities. |
return |
Time series of daily log returns. |
Value
Estimated parameter values and daily conditional volatilities:
- coefficients
parameter estimates of the realized GARCH-Ito model
- sigma
daily conditional volatility estimates of the realized GARCH-Ito model
- pred
one-step-ahead predicted volatility value
References
Kim, D. & Wang, Y. (2016). Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data. Journal of Econometrics. 194:220-230.
Examples
sample_data
UnifiedEst(sample_data$RV, sample_data$return)
CSI 300 Index Realized Measures
Description
This sample data set contains realized measures, such as realized volatility (RV), bi-power realized volatility (BPV) and jump variation (JV) estimated from CSI 300 Index high-frequency data, it also includes daily low-frequency log returns (return).
Usage
sample_data
Format
An object with the following elements:
- RV
times series of daily realized volatility estimates
- BPV
times series of daily bi-power realized volatility estimates
- JV
time series of daily jump variation estimates
- return
time series of daily low-frequency returns