R/hl2005-data.R

#' IBM Volatility Forecasts and Realized-Variance Proxies (Hansen & Lunde, 2005)
#'
#' Daily IBM data from the replication archive of Hansen and Lunde
#' (2005). Contains 254 trading days (1999-06-01 to 2000-05-31),
#' 8 realized-variance proxies of varying quality, and 330
#' one-step-ahead conditional variance forecasts produced by GARCH-family
#' models. The benchmark GARCH(1,1) with constant mean and Gaussian
#' errors is identified by the index \code{garch11_idx}.
#'
#' @format A list with the following components:
#' \describe{
#'   \item{date}{Trading-day \code{Date} vector (length 254).}
#'   \item{rv}{Numeric vector (length 254); the 5-minute
#'     linear-interpolation realized-variance proxy. The paper's
#'     headline series.}
#'   \item{rv_proxies}{\eqn{254 \times 8} matrix of alternative RV
#'     proxies: \code{sq_ccr} (squared close-to-close returns),
#'     \code{spline_50_3min}, \code{spline_250_2min}, \code{fourier_M85},
#'     \code{linear_5min}, \code{prevtick_5min}, \code{linear_1min},
#'     \code{prevtick_1min}.}
#'   \item{forecasts}{\eqn{254 \times 330} matrix of one-step-ahead
#'     conditional variance forecasts. Columns index a base GARCH
#'     specification (55 specs: LGARCH, IGARCH, TS-GARCH, A-GARCH,
#'     NA-GARCH, V-GARCH, THR-GARCH, GJR-GARCH, LOG-GARCH, EGARCH,
#'     NGARCH, A-PARCH, GQ-ARCH, H-GARCH, AUG-GARCH) crossed with
#'     mean-equation and error-distribution combinations (zero/const/
#'     GARCH-in-mean \eqn{\times} Gaussian/t-distributed).}
#'   \item{garch11_idx}{Integer (= 57); the column of \code{forecasts}
#'     corresponding to GARCH(1,1) with constant mean and Gaussian
#'     errors, used as the benchmark in the paper.}
#' }
#'
#' @source Journal of Applied Econometrics data archive for Hansen and
#'   Lunde (2005), volume 20, issue 7.
#'
#' @references
#' Hansen, P. R. and Lunde, A. (2005). A forecast comparison of
#' volatility models: does anything beat a GARCH(1,1)?
#' \emph{Journal of Applied Econometrics}, 20(7), 873-889.
"hl2005"

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