Package: forecastdom 0.1.0.9000

Gabriel Cabrera

forecastdom: (Un)Conditional Forecast Dominance

A unified toolkit for out-of-sample forecast dominance testing. Covers unconditional and conditional equal and superior predictive ability, encompassing, and nested-model comparison. Implements the Diebold-Mariano test with the Harvey, Leybourne, and Newbold (1997) <doi:10.1016/S0169-2070(96)00719-4> small-sample correction; the Clark-West mean squared forecast error (MSFE) adjusted statistic (Clark and West, 2007) <doi:10.1016/j.jeconom.2006.05.023>; the ENC-NEW encompassing test of Clark and McCracken (2001) <doi:10.1016/S0304-4076(01)00071-9>; the Giacomini-White conditional equal predictive ability test (Giacomini and White, 2006) <doi:10.1111/j.1468-0262.2006.00718.x>; Hansen's superior predictive ability (SPA) test (Hansen, 2005) <doi:10.1198/073500105000000063>; the conditional superior predictive ability test of Li, Liao, and Quaedvlieg (2022) <doi:10.1093/restud/rdab039>; and the uniform and average multi-horizon SPA tests of Quaedvlieg (2021) <doi:10.1080/07350015.2019.1620074>.

Authors:Gabriel Cabrera [aut, cre]

forecastdom_0.1.0.9000.tar.gz
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forecastdom_0.1.0.9000.tar.gz(r-4.7-arm64)forecastdom_0.1.0.9000.tar.gz(r-4.7-x86_64)forecastdom_0.1.0.9000.tar.gz(r-4.6-arm64)forecastdom_0.1.0.9000.tar.gz(r-4.6-x86_64)
forecastdom_0.1.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
forecastdom/json (API)

# Install 'forecastdom' in R:
install.packages('forecastdom', repos = c('https://gabbocg.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gabbocg/forecastdom/issues

Pkgdown/docs site:https://gabbocg.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • cm2001 - US Unemployment and Inflation
  • gw2006 - SPF Mean CPI Inflation Forecasts
  • hl2005 - IBM Volatility Forecasts and Realized-Variance Proxies
  • llq2022 - S&P 500 Realized-Variance Forecasts
  • llq2022_jnj - Johnson & Johnson Realized-Variance Forecasts
  • llq2022_uv_cspa - Pairwise CSPA Rejection Counts Across 28 Stocks
  • nrtz2014 - Equity Premium and Technical Indicators
  • quaedvlieg2021 - Loss-Differential Path Forecasts from Quaedvlieg
  • rossi2006 - Bilateral Nominal Exchange Rates
  • rrz2016 - Equity Premium and Short Interest Index
  • rz2013 - Equity Premium and Macro Predictors
  • wg2008 - Welch & Goyal (2008) Annual Equity-Premium Dataset

On CRAN:

Conda:

cpp

6.29 score 3 stars 13 scripts 273 downloads 14 exports 19 dependencies

Last updated from:8965c741a6. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK140
linux-devel-x86_64OK138
source / vignettesOK238
linux-release-arm64OK129
linux-release-x86_64OK138
macos-release-arm64OK141
macos-release-x86_64OK218
macos-oldrel-arm64OK138
macos-oldrel-x86_64OK269
windows-devel-arm64OK320
windows-devel-x86_64OK163
windows-release-arm64OK339
windows-release-x86_64OK253
windows-oldrel-x86_64OK93
wasm-releaseOK122

Exports:aspa_mh_testcsmscspa_testcspa_test_plotcw_testdm_testdo_simenc_newgw_testivx_waldmse_f_testqll_hatspa_testuspa_mh_test

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleMASSR6RColorBrewerRcpprlangS7scalesvctrsviridisLitewithr

Replicating Welch & Goyal (2008)
Helper: recursive forecasts (WG procedure) | Table 1: five tests across three OOS specifications | WG Figure 1: cumulative SSE difference for DP | Takeaway | References
Rendered fromwg2008-dp.Rmdusingknitr::rmarkdown

Last update: 2026-07-16
Started: 2026-05-12

Replicating Rapach et al. (2016)
The data | Replicating Table A2 | References
Rendered fromrrz2016-ivx-qll.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-09

Replicating Clark & McCracken (2001)
Recursive forecasts | ENC-NEW across lag orders | Comparison with Clark-West MSFE-adjusted | References
Rendered fromcm2001-enc-new.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-12

Replicating Quaedvlieg (2021)
Per-horizon picture | Uniform multi-horizon SPA | Average multi-horizon SPA | Custom weights | Block-length sensitivity | Takeaways | References
Rendered fromquaedvlieg2021-mh-spa.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-10

Replicating Rossi (2006)
The data | Forecasting setup | Replicating the OOS DM panel of Table 1 | AR(1) | AR(2) | Single-country deep dive: Japan, AR(1), recursive | References
Rendered fromrossi2006-dm.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-09

Get Started with forecastdom
Overview | Pairwise Forecast Comparison | Diebold-Mariano test | Clark-West test | Giacomini-White test | Multiple Forecast Comparison | Hansen's SPA test | CSPA test | Visualization | CSMS: confidence set for the most superior | Predictive Regressions | IVX-Wald test | Elliott-Muller test | References
Rendered fromforecastdom.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-04-24

Replicating Giacomini & White (2006)
CEPA across forecast horizons | Choice of instruments | Note on the original paper | References
Rendered fromgw2006-spf-cepa.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-12

Replicating Hansen & Lunde (2005)
Setup | SPA test against the primary RV proxy | Robustness across realised-variance proxies | Top 10 alternatives by mean loss (5-min proxy) | References
Rendered fromhl2005-spa-garch.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-12

Replicating Li et al. (2022)
Figure 2: JNJ, one-versus-one CSPA | Figure 3: JNJ, one-versus-all CSPA | Table 4 Panel A: cross-stock rejection counts | S&P 500: confidence set for the most superior method | Takeaway | References
Rendered fromllq2022-cspa-rv.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-12

Replicating Neely et al. (2014)
Helpers | Technical indicators | Takeaway | References
Rendered fromnrtz2014-cw-technical.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-10

Replicating Rapach & Zhou (2013)
Helpers | Macro predictors | Takeaway | References
Rendered fromrz2013-cw-macro.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2026-05-10

Readme and manuals

Help Manual

Help pageTopics
Average Multi-Horizon Superior Predictive Ability Testaspa_mh_test
US Unemployment and Inflation (Clark & McCracken, 2001 setup)cm2001
Confidence Set for the Most Superior (CSMS) Forecasting Methodcsms
Conditional Superior Predictive Ability (CSPA) Testcspa_test
Plot CSPA Test Resultscspa_test_plot
Clark-West Test for Predictive Ability of Nested Modelscw_test
Diebold-Mariano Test for Equal Predictive Abilitydm_test
Simulate Data from the CSPA Paper DGPdo_sim
Clark-McCracken ENC-NEW Encompassing Testenc_new
Conditional Equal Predictive Ability (CEPA) Testgw_test
SPF Mean CPI Inflation Forecasts (Giacomini & White, 2006 setup)gw2006
IBM Volatility Forecasts and Realized-Variance Proxies (Hansen & Lunde, 2005)hl2005
IVX-Wald Test for Predictive Regressionsivx_wald
S&P 500 Realized-Variance Forecasts (Li, Liao & Quaedvlieg, 2022)llq2022
Johnson & Johnson Realized-Variance Forecasts (Li, Liao & Quaedvlieg, 2022)llq2022_jnj
Pairwise CSPA Rejection Counts Across 28 Stocksllq2022_uv_cspa
McCracken MSE-F Test for Equal Forecast Accuracymse_f_test
Equity Premium and Technical Indicators (Neely, Rapach, Tu, & Zhou, 2014)nrtz2014
Print Method for CSPA Test Resultsprint.cspa_test
Elliott-Muller Test for Time-Varying Coefficientsqll_hat
Loss-Differential Path Forecasts from Quaedvlieg (2021)quaedvlieg2021
Bilateral Nominal Exchange Rates (Rossi, 2006)rossi2006
Equity Premium and Short Interest Index (Rapach, Ringgenberg & Zhou, 2016)rrz2016
Equity Premium and Macro Predictors (Rapach & Zhou, 2013)rz2013
Unconditional Superior Predictive Ability (USPA/SPA) Testspa_test
Summary Method for CSPA Test Resultssummary.cspa_test
Uniform Multi-Horizon Superior Predictive Ability Testuspa_mh_test
Welch & Goyal (2008) Annual Equity-Premium Datasetwg2008