README.md

In yzhao7322/CurVol: Curve Data Volatility Analysis

CurVol

Functional time series data derived from financial markets exhibit conditional heteroscedasticity. The goal of ‘CurVol’ is to document useful functions to analyze the volatility of functional time series data. Methods and tools in this package replicate hypothesis testing, model estimation, and backtesting in a series of papers:

Hormann, S., Horvath, L., Reeder, R. (2013). A functional version of the ARCH model. Econometric Theory. 29(2), 267-288. .

Aue, A., Horvath, L., F. Pellatt, D. (2017). Functional generalized autoregressive conditional heteroskedasticity. Journal of Time Series Analysis. 38(1), 3-21. .

Cerovecki, C., Francq, C., Hormann, S., Zakoian, J. M. (2019). Functional GARCH models: The quasi-likelihood approach and its applications. Journal of Econometrics. 209(2), 353-375. .

Rice, G., Wirjanto, T., Zhao, Y. (2020) Tests for conditional heteroscedasticity of functional data. Journal of Time Series Analysis. 41(6), 733-758. .

Rice, G., Wirjanto, T., Zhao, Y. (2020) Forecasting Value at Risk via intra-day return curves. International Journal of Forecasting. .

Rice, G., Wirjanto, T., Zhao, Y. (2021) Exploring volatility of crude oil intra-day return curves: a functional GARCH-X model. MPRA Paper No.109231. https://mpra.ub.uni-muenchen.de/109231.

Installation

You can install the released version of CurVol from CRAN with:

install.packages("CurVol")

R topics documented

1. backtest.var - backtest the intra-day VaR forecasts.
2. basis.est - estimate non-negative basis functions.
3. dgp.fgarch - generate functional data following the functional ARCH(1) or GARCH(1,1) process.
4. dgp.fiid - generate iid functional data following Ornstein–Uhlenbeck process.
5. diagnostic.fGarch - estimation parameters as the inputs for diagnostic purposes.
6. est.fArch - estimate functional ARCH (q) model.
7. est.fGarch - estimate Functional GARCH (p,q) model.
8. est.fGarchx - estimate Functional GARCH-X model.
9. fun_hetero - test conditional heteroscedasticity for functional data.
10. gof.fgarch - goodness-of-fit test for functional ARCH/GARCH model.
11. intra.return - intra-day return curves: intra-day return (IDR), cumulative intra-day return (CIDR), overnight cumulative intra-day return (OCIDR).
12. sample_data - a sample data containing S&P 500 intra-day price.
13. var.forecast - forecast daily/intra-day Value-at-Risk.
14. var.vio - a violation process for the intra-day VaR curves.

yzhao7322/CurVol documentation built on Sept. 5, 2021, 8:41 p.m.