yzhao7322/CurVol: Curve Data Volatility Analysis

Functional time series data derived from financial markets exhibit conditional heteroscedasticity. Tests and models have been developed to depicit this property in a series of papers by Hormann et al., (2013) <doi:10.1017/S0266466612000345>, Aue et al., (2017) <doi:10.1111/jtsa.12192>, Cerovecki et al., (2019) <doi:10.1016/j.jeconom.2019.01.006>, Rice et al., (2020) <doi:10.1111/jtsa.12532>, Rice et al., (2020) <doi:10.1016/j.ijforecast.2019.10.006>. Rice et al., (2021) <https://mpra.ub.uni-muenchen.de/109231>. MPRA Paper No. 109231. These procedures enable data generating processes, functional GARCH-type model estimation, goodness-of-fit tests, and backtesting methods.

install.packages("remotes")
remotes::install_github("yzhao7322/CurVol")