interest_rates_predictions_plots.R

library(tidyverse)
library(lubridate)
library(glue)
library(jsonlite)
library(cowplot)

# thanks to u/doubleunplussed on reddit for this dataset
json_url <- "https://pastebin.com/raw/gxZAUJwd"
ib_rate_data_orig <- fromJSON(json_url)

# make a tidy data frame
ib_rate_data <- 
  tibble(fetch_date = names(ib_rate_data_orig),
         dat = ib_rate_data_orig) %>%
  unnest_longer(
    col = dat,
    values_to = "rate",
    indices_to = "rate_date"
  ) %>%
  mutate(
    fetch_date = ymd(fetch_date),
    rate_date = dmy(glue("01-{rate_date}")),
    latest = fetch_date == max(fetch_date),
    freshness = (as.numeric(fetch_date - min(fetch_date)) / 
                   as.numeric(max(fetch_date) - min(fetch_date)))
  )

# plot settings
theme_set(
  theme_cowplot(font_size = 11, rel_small = 1, rel_tiny = 8/11, rel_large = 1) +
    background_grid("xy") +
    theme(legend.position = "off",
          plot.background = element_rect(colour = NA, fill = "white"))
)

# plot of predictions overlaid with most recent highlighted in red
ib_rate_data %>%
  ggplot(aes(x = rate_date, y = rate, group = fetch_date, 
             colour = latest, size = latest, alpha = latest)) +
  geom_line() +
  scale_colour_manual(values = c("dodgerblue3", "firebrick3")) +
  scale_size_manual(values = c(0.5, 2.0)) +
  scale_alpha_manual(values = c(0.3, 1.0)) +
  expand_limits(y = c(0, 4.5)) +
  scale_x_date(date_labels = "%b %Y",
               limits = ymd(c("2022-01-01", "2024-01-01"))) +
  labs(x = "Month interest rate predicted for", 
       y = "Market-implied interest rate (%)",
       caption = "Red line shows most recent prediction. Data from asx.com.au via u/doubleunplussed.")
ggsave("interest_rate_predictions_1.png", width = 7, height = 5, dpi = 600)

# panel plot showing time series for each future month's predictions
ib_rate_data %>%
  filter(rate_date != "2022-04-01") %>%
  mutate(rate_date = rate_date %>%
           format("%b %Y") %>%
           fct_inorder()) %>%
  ggplot(aes(x = fetch_date, y = rate, group = rate_date)) +
  expand_limits(y = c(0, 4.5)) +
  geom_line() +
  geom_point(colour = "firebrick3", size = 2.0, data = ~filter(., latest)) +
  facet_wrap(~rate_date) +
  panel_border() +
  labs(x = "Date prediction made", 
       y = "Market-implied interest rate (%)",
       caption = "Red point shows most recent prediction. Data from asx.com.au via u/doubleunplussed.") +
  theme(axis.text.x = element_text(size = rel(8/11)))
ggsave("interest_rate_predictions_2.png", width = 7, height = 6, dpi = 600)