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#' 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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