Nothing
knitr::opts_chunk$set( collapse = TRUE, comment = "#>", out.width = "100%" )
Visualization of yield curves is fairly relevant and the package fixedincome brings the usual
plot
function to create plots with the SpotRateCurve objects and also a ggplot2 set of methods
that helps with the visualization of the term structures using all ggplot2 features.
Before the start let's get the necessary packages loaded.
library(rb3) library(dplyr) library(fixedincome) library(ggplot2)
As the second step, the yield curve must be created and this is done with data from {rb3} package.
refdate <- as.Date("2022-08-09") yc_ <- yc_get(refdate) fut_ <- futures_get(refdate) yc_ss <- yc_superset(yc_, fut_) yc <- bind_rows( yc_ss |> slice(1), yc_ss |> filter(!is.na(symbol)) ) |> filter(!duplicated(biz_days)) curve <- spotratecurve( yc$r_252, yc$biz_days, "discrete", "business/252", "Brazil/ANBIMA", refdate = refdate )
base::plot
plot(curve)
plot(curve, show_forward = TRUE)
curve |> fixedincome::first("3 years") |> plot(curve, show_forward = TRUE)
curve_2y <- curve |> fixedincome::first("2 years") interpolation(curve_2y) <- interp_naturalspline() plot(curve_2y, use_interpolation = TRUE)
plot(curve_2y, use_interpolation = TRUE, show_forward = TRUE)
plot(curve_2y, use_interpolation = TRUE, show_forward = TRUE, legend_location = "bottomleft")
ggspotratecurveplot(curve, title = "DI1 spot rates", subtitle = format(refdate), caption = "Data from {rb3} package" )
ggspotratecurveplot(curve, title = "DI1 spot rates", subtitle = format(refdate), caption = "Data from {rb3} package", curve.x.axis = "terms" )
ggspotratecurveplot(curve, title = "DI1 spot rates", subtitle = format(refdate), caption = "Data from {rb3} package" ) + autolayer(forwardrate(curve), size = 1)
ggspotratecurveplot(curve_2y, title = "DI1 spot rates", subtitle = format(refdate), caption = "Data from {rb3} package", curve.interpolation = TRUE )
autoplot(curve_2y, curve.geom = "point") + autolayer(curve_2y, curve.geom = "line", curve.name = "Interpolation", curve.interpolation = TRUE)
terms_ <- do.call(seq, as.list(range(curve_2y@terms))) curve_2y_interp <- curve_2y[[terms_]] autoplot(curve_2y, curve.geom = "point") + autolayer(curve_2y_interp, curve.geom = "line") + autolayer(forwardrate(curve_2y_interp), curve.geom = "line", curve.name = "Forward Rate" )
refdate2 <- as.Date("2022-03-09") yc_ <- yc_get(refdate2) fut_ <- futures_get(refdate2) yc_ss <- yc_superset(yc_, fut_) yc <- bind_rows( yc_ss |> slice(1), yc_ss |> filter(!is.na(symbol)) ) |> filter(!duplicated(biz_days)) curve2 <- spotratecurve( yc$r_252, yc$biz_days, "discrete", "business/252", "Brazil/ANBIMA", refdate = refdate2 )
ggspotratecurveplot(curve, title = "DI1 spot rates", caption = "Data from {rb3} package", curve.x.axis = "terms" ) + autolayer(curve2, curve.x.axis = "terms", size = 1) + autolayer(curve2, curve.geom = "point", curve.x.axis = "terms", size = 2)
curve2_2y <- curve2 |> fixedincome::first("2 years") ggspotratecurveplot(curve_2y, title = "DI1 spot rates", caption = "Data from {rb3} package", curve.x.axis = "terms" ) + autolayer(curve2_2y, curve.x.axis = "terms", size = 1) + autolayer(curve2_2y, curve.geom = "point", curve.x.axis = "terms", size = 2)
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