OHLC Data and plotly

plotly for OHLC

OHLC data on Intel stock price. The tidyquant packages makes the acquisition of stock market data easy by entering the ticker. Let’s try this for Intel, ticker INTC.

Code

library(tidyquant)
library(tidyverse)
library(magrittr)
# Use tidyquant to get the data
INTC <- tq_get("INTC")
# Slice off the most recent 120 days
# INTC.tail <- tail(INTC, 120)
INTC %<>% mutate(
    open = round(open, digits=2),
    close = round(close, digits=2),
    high = round(high, digits=2),
    low = round(low, digits=2),
    adjusted = round(adjusted, digits=2)
    )

Let’s have a look at the data.

Code

library(DT)
datatable(INTC.tail)

The Plot

There are a few charts specifically designed for OHLC data that are included in plotly. Here I want to deploy a basic one with one modification. I want daily increases in black and daily decreases in red.

Code

library(plotly)
# basic example of ohlc charts
# custom colors
i <- list(line = list(color = '#000000')) # black
d <- list(line = list(color = '#FF0000')) # red
# Create the figure
fig.2 <- INTC %>%
  plot_ly(x = ~date, type="ohlc",
          open = ~open, close = ~close,
          high = ~high, low = ~low,
          increasing = i, decreasing = d)
fig.2

References

Code

knitr::write_bib(names(sessionInfo()$otherPkgs), file="bibliography.bib")

References

Bache, Stefan Milton, and Hadley Wickham. 2022. Magrittr: A Forward-Pipe Operator for r. https://CRAN.R-project.org/package=magrittr.

Dancho, Matt, and Davis Vaughan. 2022. Tidyquant: Tidy Quantitative Financial Analysis. https://github.com/business-science/tidyquant.

Grolemund, Garrett, and Hadley Wickham. 2011. “Dates and Times Made Easy with lubridate.” Journal of Statistical Software 40 (3): 1–25. https://www.jstatsoft.org/v40/i03/.

Müller, Kirill, and Hadley Wickham. 2022. Tibble: Simple Data Frames. https://CRAN.R-project.org/package=tibble.

Peterson, Brian G., and Peter Carl. 2020. PerformanceAnalytics: Econometric Tools for Performance and Risk Analysis. https://github.com/braverock/PerformanceAnalytics.

Ryan, Jeffrey A., and Joshua M. Ulrich. 2022a. Quantmod: Quantitative Financial Modelling Framework. https://CRAN.R-project.org/package=quantmod.

———. 2022b. Xts: eXtensible Time Series. https://github.com/joshuaulrich/xts.

Sievert, Carson. 2020. Interactive Web-Based Data Visualization with r, Plotly, and Shiny. Chapman; Hall/CRC. https://plotly-r.com.

Sievert, Carson, Chris Parmer, Toby Hocking, Scott Chamberlain, Karthik Ram, Marianne Corvellec, and Pedro Despouy. 2022. Plotly: Create Interactive Web Graphics via Plotly.js. https://CRAN.R-project.org/package=plotly.

Spinu, Vitalie, Garrett Grolemund, and Hadley Wickham. 2023. Lubridate: Make Dealing with Dates a Little Easier. https://CRAN.R-project.org/package=lubridate.

Ulrich, Joshua. 2021. TTR: Technical Trading Rules. https://github.com/joshuaulrich/TTR.

Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.

———. 2022a. Stringr: Simple, Consistent Wrappers for Common String Operations. https://CRAN.R-project.org/package=stringr.

———. 2022b. Tidyverse: Easily Install and Load the Tidyverse. https://CRAN.R-project.org/package=tidyverse.

———. 2023. Forcats: Tools for Working with Categorical Variables (Factors). https://CRAN.R-project.org/package=forcats.

Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.

Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, Kara Woo, Hiroaki Yutani, and Dewey Dunnington. 2022. Ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. https://CRAN.R-project.org/package=ggplot2.

Wickham, Hadley, Romain François, Lionel Henry, Kirill Müller, and Davis Vaughan. 2023. Dplyr: A Grammar of Data Manipulation. https://CRAN.R-project.org/package=dplyr.

Wickham, Hadley, and Lionel Henry. 2023. Purrr: Functional Programming Tools. https://CRAN.R-project.org/package=purrr.

Wickham, Hadley, Jim Hester, and Jennifer Bryan. 2022. Readr: Read Rectangular Text Data. https://CRAN.R-project.org/package=readr.

Wickham, Hadley, Davis Vaughan, and Maximilian Girlich. 2023. Tidyr: Tidy Messy Data. https://CRAN.R-project.org/package=tidyr.

Xie, Yihui, Joe Cheng, and Xianying Tan. 2023. DT: A Wrapper of the JavaScript Library DataTables. https://github.com/rstudio/DT.

Zeileis, Achim, and Gabor Grothendieck. 2005. “Zoo: S3 Infrastructure for Regular and Irregular Time Series.” Journal of Statistical Software 14 (6): 1–27. https://doi.org/10.18637/jss.v014.i06.

Zeileis, Achim, Gabor Grothendieck, and Jeffrey A. Ryan. 2022. Zoo: S3 Infrastructure for Regular and Irregular Time Series (z’s Ordered Observations). https://zoo.R-Forge.R-project.org/.