3d yield curve with Plotly in R

Readme.md

Nowhere near as spectacular as the Upshot/New York Times 3d yield curve by Amanda Cox and Gregor Aisch, but not bad at all for a couple of lines of R code with the plotly htmlwidget.

library(plotly)
library(dplyr)
library(tidyr)
library(purrr)
library(quantmod)
library(magrittr)


# get yields from St. Louis Fed FRED
yield_curve <- list("DTB3", "DGS2", "DGS5", "DGS10", "DGS30") %>%
  map(
    ~getSymbols(.x, auto.assign=FALSE, src="FRED")
  ) %>%
  do.call(merge,.)

# create our 3d surface yield curve
yield_curve["1980::"] %>%
  # convert to numeric matrix
  data.matrix() %>% 
  # transpose
  t() %>%
  # draw our Plotly 3d surface
  plot_ly(
    x=as.Date(index(yield_curve["1980::"])),
    y=c(0.25,2,5,10,30),
    z=.,
    type="surface"
  ) %>%
  plotly::layout(
    scene=list(
      xaxis=list(title="date"),
      yaxis=list(title="term"),
      zaxis=list(title="yield")
    )
  )

  
# 3d scatter chart
yield_curve_tidy <- yield_curve %>%
  data.frame() %>%
  add_rownames(var="date") %>%
  gather(symbol,yield,-date) %>%
  mutate(term=c(0.25,2,5,10,30)[match(symbol,colnames(yield_curve))])

yield_curve_tidy[which(!is.na(yield_curve_tidy$yield)),] %>%
  group_by(symbol) %>%
  plot_ly(
    x = ~date, y = ~term, z = ~yield,
    type="scatter3d",
    mode="markers",
    size=3,
    color=~yield
  )

code.R

library(plotly)
library(dplyr)
library(tidyr)
library(purrr)
library(quantmod)
library(magrittr)


# get yields from St. Louis Fed FRED
yield_curve <- list("DTB3", "DGS2", "DGS5", "DGS10", "DGS30") %>%
  map(
    ~getSymbols(.x, auto.assign=FALSE, src="FRED")
  ) %>%
  do.call(merge,.)

# create our 3d surface yield curve
yield_curve["1980::"] %>%
  # convert to numeric matrix
  data.matrix() %>% 
  # transpose
  t() %>%
  # draw our Plotly 3d surface
  plot_ly(
    x=as.Date(index(yield_curve["1980::"])),
    y=c(0.25,2,5,10,30),
    z=.,
    type="surface"
  ) %>%
  plotly::layout(
    scene=list(
      xaxis=list(title="date"),
      yaxis=list(title="term"),
      zaxis=list(title="yield")
    )
  )

# 3d scatter chart
yield_curve_tidy <- yield_curve %>%
  data.frame() %>%
  add_rownames(var="date") %>%
  gather(symbol,yield,-date) %>%
  mutate(term=c(0.25,2,5,10,30)[match(symbol,colnames(yield_curve))])

yield_curve_tidy[which(!is.na(yield_curve_tidy$yield)),] %>%
  group_by(symbol) %>%
  plot_ly(
    x = ~date, y = ~term, z = ~yield,
    type="scatter3d",
    mode="markers",
    size=3,
    color=~yield
  )

@ntankova thanks for the comment. This code is pretty old, and I'm surprised that it works at all :) I think when I posted I was trying to show different ways of getting yields at various maturities and did not include the code for IRX, FVX, etc. These indices still exist and are available, but you are correct that the options on them no longer trade.

I made changes in https://gist.github.com/timelyportfolio/4da9d6b6c89cce26effabccca30124dd/revisions to hopefully get the code working again only using the Federal Reserve series on yields as we did in the surface chart.

The final 3-d scatter plot needs the argument:

mode = 'markers'

This code is used for teaching, as it is.
I am a student.
I found an error and searched for the origin of the code, for check.

Thank you.

@ntankova I commend you on your drive to look into the error, report the error, and comment. Thanks. I made a couple more changes while we are at it, but in general I think the 3d scatter is not all that helpful compared to the surface chart.

@ntankova you might like these other yield curve explorations

http://timelyportfolio.blogspot.com/2013/05/even-more-jgb-yield-charts-with-r.html
http://timelyportfolio.blogspot.com/2013/05/japan-jgb-yieldsmore-lattice-charts.html

@timelyportfolio Thanks for sharing, found this useful.

@daniel-finnan thanks so much for letting me know. So happy to hear that this was helpful.