Financial market data - yield curve

Data - ECB

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Info

source dataset .html .RData

ecb

YC

2024-09-19 2024-09-16

Data on monetary policy

source dataset .html .RData

bdf

FM

2024-07-26 2024-06-18

bdf

MIR

2024-07-26 2024-07-01

bdf

MIR1

2024-07-26 2024-07-01

bis

CBPOL

2024-08-09 2024-09-15

ecb

BSI

2024-10-08 2024-09-16

ecb

BSI_PUB

2024-10-08 2024-10-08

ecb

FM

2024-10-08 2024-10-08

ecb

ILM

2024-10-08 2024-10-08

ecb

ILM_PUB

2024-10-08 2024-09-10

ecb

liq_daily

2024-10-08 2024-09-11

ecb

MIR

2024-06-19 2024-10-08

ecb

RAI

2024-10-08 2024-10-08

ecb

SUP

2024-10-08 2024-10-08

ecb

YC

2024-09-19 2024-09-16

ecb

YC_PUB

2024-10-08 2024-10-08

eurostat

ei_mfir_m

2024-09-30 2024-09-15

eurostat

irt_st_m

2024-09-30 2024-10-08

fred

r

2024-09-18 2024-09-18

oecd

MEI

2024-04-16 2024-06-30

oecd

MEI_FIN

2024-09-15 2024-05-21

LAST_COMPILE

LAST_COMPILE
2024-10-09

Last

TIME_PERIOD FREQ Nobs
2024-09-13 B 2

INSTRUMENT_FM

Code
YC %>%
  left_join(INSTRUMENT_FM,  by = "INSTRUMENT_FM") %>%
  group_by(INSTRUMENT_FM, Instrument_fm) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
INSTRUMENT_FM Instrument_fm Nobs
G_N_A Government bond, nominal, all issuers whose rating is triple A 5544235
G_N_C Government bond, nominal, all issuers all ratings included 5528520
G_N_W Government bond, nominal, all issuers whose rating is between AAA and AA 7514

DATA_TYPE_FM

Code
YC %>%
  left_join(DATA_TYPE_FM,  by = "DATA_TYPE_FM") %>%
  group_by(DATA_TYPE_FM, Data_type_fm) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

TIME_PERIOD

Code
YC %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

Yield curve

Government bond, nominal, all issuers whose rating is triple A

Linear

Code
YC %>%
  filter(DATA_TYPE_FM %in% paste0("PY_", 1:30, "Y"),
         INSTRUMENT_FM == "G_N_C") %>%
  filter(TIME_PERIOD %in% c(as.Date(c("2022-11-01", "2022-03-01")), max(TIME_PERIOD))) %>%
  mutate(year = parse_number(DATA_TYPE_FM)) %>%
  ggplot + geom_line(aes(x = year, y = OBS_VALUE/100, color = paste0(TIME_PERIOD))) +
  theme_minimal() + xlab("Maturity in rates") + ylab("Par yield curve rate") +
  scale_x_continuous(breaks = c(1, 2, 5, 10, 15, 20, 25, 30),
                     labels = dollar_format(accuracy = 1, pre = "", su = "Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
                     labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.9, 0.2),
        legend.title = element_blank())

Log

Code
YC %>%
  filter(DATA_TYPE_FM %in% paste0("PY_", 1:30, "Y"),
         INSTRUMENT_FM == "G_N_C") %>%
  filter(TIME_PERIOD %in% c(as.Date(c("2023-03-01", "2022-11-03", "2022-07-01", "2022-03-01")), max(TIME_PERIOD))) %>%
  mutate(year = parse_number(DATA_TYPE_FM)) %>%
  ggplot + geom_line(aes(x = year, y = OBS_VALUE/100, color = paste0(TIME_PERIOD))) +
  theme_minimal() + xlab("Maturity in rates") + ylab("Par yield curve rate") +
  scale_x_log10(breaks = c(1, 2, 5, 10, 15, 20, 25, 30),
                     labels = dollar_format(accuracy = 1, pre = "", su = "Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
                     labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.9, 0.2),
        legend.title = element_blank())

Log2

Code
YC %>%
  filter(DATA_TYPE_FM %in% c(paste0("PY_", 1:30, "Y"), paste0("PY_", 1:12, "M")),
         INSTRUMENT_FM == "G_N_C") %>%
  filter(TIME_PERIOD %in% c(as.Date(c("2022-11-03", "2022-07-01", "2022-03-01", "2021-11-01")), max(TIME_PERIOD))) %>%
  mutate(number = parse_number(DATA_TYPE_FM),
         number = ifelse(DATA_TYPE_FM %in% paste0("PY_", 1:12, "M"), number/12, number)) %>%
  ggplot + geom_line(aes(x = number, y = OBS_VALUE/100, color = paste0(TIME_PERIOD))) +
  theme_minimal() + xlab("Maturity") + ylab("Par yield curve rate") +
  scale_x_log10(breaks = c(1/12, 3/12, 6/12, 9/12, 1, 2, 5, 10, 15, 20, 30),
                     labels = c("1M", "3M", "6M", "9M", "1Y", "2Y", "5Y", "10Y", "15Y", "20Y", "30Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
                     labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.9, 0.2),
        legend.title = element_blank())

Log2

Code
YC %>%
  filter(DATA_TYPE_FM %in% c(paste0("PY_", 1:30, "Y"), paste0("PY_", 1:12, "M"))) %>%
  filter(TIME_PERIOD %in% c(as.Date(c("2022-11-03", "2022-07-01", "2022-03-01", "2021-11-01")), max(TIME_PERIOD))) %>%
  mutate(number = parse_number(DATA_TYPE_FM),
         number = ifelse(DATA_TYPE_FM %in% paste0("PY_", 1:12, "M"), number/12, number)) %>%
  left_join(INSTRUMENT_FM,  by = "INSTRUMENT_FM") %>%
  ggplot + geom_line(aes(x = number, y = OBS_VALUE/100, color = paste0(TIME_PERIOD), linetype = Instrument_fm)) +
  theme_minimal() + xlab("Maturity") + ylab("Par yield curve rate") +
  scale_x_log10(breaks = c(1/12, 3/12, 6/12, 9/12, 1, 2, 5, 10, 15, 20, 30),
                     labels = c("1M", "3M", "6M", "9M", "1Y", "2Y", "5Y", "10Y", "15Y", "20Y", "30Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
                     labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.4, 0.4),
        legend.title = element_blank())

Yield curve

2 years

Code
YC %>%
  filter(DATA_TYPE_FM == "PY_2Y") %>%
  select_if(~ n_distinct(.) > 1) %>%
  day_to_date %>%
  arrange(desc(date)) %>%
  left_join(INSTRUMENT_FM,  by = "INSTRUMENT_FM") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/100, color = Instrument_fm)) +
  theme_minimal() + xlab("") + ylab("2-year rates") +
  scale_x_date(breaks = seq(1960, 2024, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
                     labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.6, 0.9),
        legend.title = element_blank())

10 years

Code
YC %>%
  filter(DATA_TYPE_FM == "PY_10Y") %>%
  select_if(~ n_distinct(.) > 1) %>%
  day_to_date %>%
  arrange(desc(date)) %>%
  left_join(INSTRUMENT_FM,  by = "INSTRUMENT_FM") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/100, color = Instrument_fm)) +
  theme_minimal() + xlab("") + ylab("10-year rates") +
  scale_x_date(breaks = seq(1960, 2024, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
                     labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.6, 0.9),
        legend.title = element_blank())