Last Update:

Tuesday, April 16, 2024

Opening Value:

20.85

Highest Value:

21.14

Lowest Value:

20.59

Adj. Closing Value:

21.04

  • The forecast plot shows the forecasted Cleveland-Cliffs Inc stock prices for the next 12 months.

  • The plot also shows the 80% prediction interval in dark purple and the 95% prediction interval in light purple.

  • The numeric values for these forecasted values and prediction intervals are shown in the next tab.

The table below shows the forecast values and 80% and 95% prediction intervals for the 12 requested forecasts for the Cleveland-Cliffs Inc stock.

Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
May 2024 23.22518 17.1339101 29.31646 13.9093847 32.54098
Jun 2024 23.21458 13.7050039 32.72415 8.6709405 37.75821
Jul 2024 23.11598 10.8419780 35.38998 4.3445134 41.88745
Aug 2024 23.35417 9.1010650 37.60728 1.5559244 45.15243
Sep 2024 23.45809 7.4977666 39.41841 -0.9511165 47.86729
Oct 2024 23.36450 5.6658355 41.06317 -3.7032724 50.43228
Nov 2024 23.50432 4.3153727 42.69327 -5.8426438 52.85129
Dec 2024 23.66467 3.1798320 44.14951 -7.6641875 54.99353
Jan 2025 23.61817 1.7979877 45.43835 -9.7529181 56.98925
Feb 2025 23.68202 0.6068754 46.75717 -11.6083701 58.97242
Mar 2025 23.85000 -0.3296679 48.02967 -13.1296116 60.82961
Apr 2025 23.86200 -1.4265258 49.15054 -14.8134652 62.53747
  • These three residual plots allow the analyst to examine the distribution of the residuals of the modeled time series.

This dashboard was created using Quarto in RStudio, and the R Language and Environment.

The dataset used to create this dashboard was downloaded from Yahoo Finance.

Software Citations

Arnold J (2024). ggthemes: Extra Themes, Scales and Geoms for ‘ggplot2’. R package version 5.1.0, https://CRAN.R-project.org/package=ggthemes.

Bache S, Wickham H (2022). magrittr: A Forward-Pipe Operator for R. R package version 2.0.3, https://CRAN.R-project.org/package=magrittr.

Hyndman R, Athanasopoulos G, Bergmeir C, Caceres G, Chhay L, O’Hara-Wild M, Petropoulos F, Razbash S, Wang E, Yasmeen F (2024). forecast: Forecasting functions for time series and linear models. R package version 8.22.0, https://pkg.robjhyndman.com/forecast/.

Hyndman RJ, Khandakar Y (2008). “Automatic time series forecasting: the forecast package for R.” Journal of Statistical Software, 27(3), 1-22. doi:10.18637/jss.v027.i03 https://doi.org/10.18637/jss.v027.i03.

Neuwirth E (2022). RColorBrewer: ColorBrewer Palettes. R package version 1.1-3, https://CRAN.R-project.org/package=RColorBrewer.

Posit team (2024). RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA. URL http://www.posit.co/.

R Core Team (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

Rinker, T. W. & Kurkiewicz, D. (2017). pacman: Package Management for R. version 0.5.0. Buffalo, New York. http://github.com/trinker/pacman

Vanderkam D, Allaire J, Owen J, Gromer D, Thieurmel B (2018). dygraphs: Interface to ‘Dygraphs’ Interactive Time Series Charting Library. R package version 1.1.1.6, https://CRAN.R-project.org/package=dygraphs.

Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. doi:10.21105/joss.01686 https://doi.org/10.21105/joss.01686.

Xie Y (2023). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.45, https://yihui.org/knitr/.

Yihui Xie (2015) Dynamic Documents with R and knitr. 2nd edition. Chapman and Hall/CRC. ISBN 978-1498716963

Yihui Xie (2014) knitr: A Comprehensive Tool for Reproducible Research in R. In Victoria Stodden, Friedrich Leisch and Roger D. Peng, editors, Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595