Financial market data - yield curve
Data - ECB
Info
Data on monetary policy
| source | dataset | Title | .html | .rData |
|---|---|---|---|---|
| ecb | YC | Financial market data - yield curve | 2025-12-13 | 2025-08-29 |
| bdf | FM | Marché financier, taux | 2025-12-13 | 2025-12-13 |
| bdf | MIR | Taux d'intérêt - Zone euro | 2025-12-13 | 2025-08-04 |
| bdf | MIR1 | Taux d'intérêt - France | 2025-12-13 | 2025-08-04 |
| bis | CBPOL | Policy Rates, Daily | 2025-10-11 | 2025-10-11 |
| ecb | BSI | Balance Sheet Items | 2025-12-13 | 2025-08-29 |
| ecb | BSI_PUB | Balance Sheet Items - Published series | 2025-12-13 | 2025-08-29 |
| ecb | FM | Financial market data | 2025-12-13 | 2025-08-29 |
| ecb | ILM | Internal Liquidity Management | 2025-12-13 | 2025-08-29 |
| ecb | ILM_PUB | Internal Liquidity Management - Published series | 2025-08-29 | 2024-09-10 |
| ecb | MIR | MFI Interest Rate Statistics | 2025-12-13 | 2025-08-29 |
| ecb | RAI | Risk Assessment Indicators | 2025-12-13 | 2025-08-29 |
| ecb | SUP | Supervisory Banking Statistics | 2025-12-13 | 2025-08-29 |
| ecb | YC_PUB | Financial market data - yield curve - Published series | 2025-12-13 | 2025-08-29 |
| ecb | liq_daily | Daily Liquidity | 2025-12-13 | 2025-06-06 |
| eurostat | ei_mfir_m | Interest rates - monthly data | 2025-12-13 | 2025-12-13 |
| eurostat | irt_st_m | Money market interest rates - monthly data | 2025-12-13 | 2025-12-13 |
| fred | r | Interest Rates | 2025-12-13 | 2025-12-13 |
| oecd | MEI | Main Economic Indicators | 2024-04-16 | 2025-07-24 |
| oecd | MEI_FIN | Monthly Monetary and Financial Statistics (MEI) | 2024-09-15 | 2025-07-24 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2025-12-19 |
Last
| TIME_PERIOD | FREQ | Nobs |
|---|---|---|
| 2025-08-28 | 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 | 5807404 |
| G_N_C | Government bond, nominal, all issuers all ratings included | 5790960 |
| G_N_W | Government bond, nominal, all issuers whose rating is between AAA and AA | 7996 |
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_conditionalTIME_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, 2100, 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, 2100, 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())