Financial market data - FM
Data - ECB
Last observation: Q2 2026 (N = 23) · 1 sept. 2026 (N = 6) · juil. 2026 (N = 34) · 17 juin 2026 (N = 6) · 2025 (N = 24)
First observation: janv. 1900 (N = 1) · 1964 (N = 1) · Q1 1964 (N = 1) · 1 janv. 1999 (N = 3) · 1 janv. 1999 (N = 4)
Last data update: 01 sept. 2026, 01:43
Last compile: 02 sept. 2026, 23:06
Structure
Real Rates
USA, Euro Area
1999
Code
plot <- FM |>
filter(PROVIDER_FM_ID %in% c("R_US10YT_RR", "R_U2_10Y")) |>
month_to_date() |>
mutate(Ref_area = ifelse(REF_AREA == "U2", "Zone euro", "États-Unis")) |>
filter(date >= as.Date("1999-01-01")) |>
mutate(OBS_VALUE = OBS_VALUE/100) |>
ggplot() + theme_minimal() + xlab("") + ylab("Taux d'intérêt réels à 10 ans") +
geom_line(aes(x = date, y = OBS_VALUE, color = Ref_area)) +
scale_color_manual(values = c("#B22234", "#003399")) +
geom_rect(data = nber_recessions |>
filter(Peak > as.Date("1999-01-01")),
aes(xmin = Peak, xmax = Trough, ymin =-Inf, ymax = +Inf),
fill = '#B22234', alpha = 0.1) +
geom_rect(data = cepr_recessions |>
filter(Peak > as.Date("1999-01-01")),
aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf),
fill = '#003399', alpha = 0.1) +
scale_x_date(breaks = c(seq(1999, 2100, 5), seq(1997, 2100, 5)) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.26, 0.2),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 1),
labels = percent_format(accuracy = 1)) +
labs(caption = "Source: BCE, Données sur les marchés financiers")
save(plot, file = "FM_files/figure-html/real-rates-USA-EUR-1999-1.RData")
plot
USA, Japan, Euro Area
All
Code
FM |>
filter(PROVIDER_FM_ID %in% c("R_US10YT_RR", "R_JP10YT_RR", "R_U2_10Y")) |>
month_to_date() |>
mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
add_flag_color("Ref_area") |>
mutate(OBS_VALUE = OBS_VALUE/100) |>
ggplot() + theme_minimal() + xlab("") + ylab("Real rates, 10-year") +
geom_line(aes(x = date, y = OBS_VALUE, color = color)) +
add_flags(3) + scale_color_identity() +
scale_x_date(breaks = seq(1900, 2100, 10) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 1),
labels = percent_format(accuracy = 1))
2010-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("R_US10YT_RR", "R_JP10YT_RR", "R_U2_10Y")) |>
month_to_date() |>
mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
filter(date >= as.Date("2010-01-01")) |>
add_flag_color("Ref_area") |>
mutate(OBS_VALUE = OBS_VALUE/100) |>
ggplot() + theme_minimal() + xlab("") + ylab("Real rates, 10-year") +
geom_line(aes(x = date, y = OBS_VALUE, color = color)) +
add_flags(3) + scale_color_identity() +
scale_x_date(breaks = seq(1960, 2100, 1) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 1),
labels = percent_format(accuracy = 1))
2015-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("R_US10YT_RR", "R_JP10YT_RR", "R_U2_10Y")) |>
month_to_date() |>
mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
filter(date >= as.Date("2015-01-01")) |>
add_flag_color("Ref_area") |>
mutate(OBS_VALUE = OBS_VALUE/100) |>
ggplot() + theme_minimal() + xlab("") + ylab("Real rates, 10-year") +
geom_line(aes(x = date, y = OBS_VALUE, color = color)) +
add_flags(3) + scale_color_identity() +
scale_x_date(breaks = seq(1960, 2100, 1) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 1),
labels = percent_format(accuracy = 1))
2017-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("R_US10YT_RR", "R_JP10YT_RR", "R_U2_10Y")) |>
month_to_date() |>
mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
filter(date >= as.Date("2017-01-01")) |>
add_flag_color("Ref_area") |>
mutate(OBS_VALUE = OBS_VALUE/100) |>
ggplot() + theme_minimal() + xlab("") + ylab("Real rates, 10-year") +
geom_line(aes(x = date, y = OBS_VALUE, color = color)) +
add_flags(3) + scale_color_identity() +
scale_x_date(breaks = seq(1960, 2100, 1) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 1),
labels = percent_format(accuracy = 1))
ECB Key Interest rates
EONIA
All
Code
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT", "EONIA"),
FREQ == "M") |>
month_to_date() |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest 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, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.45, 0.92),
legend.title = element_blank())
Deposit Facility, Marginal Lending Facility
All
Code
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT", "MRR_FR", "MRR_MBR", "MRR"),
DATA_TYPE_FM == "LEV",
FREQ == "D") |>
day_to_date() |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest 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, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.45, 0.92),
legend.title = element_blank())
Deposit Facility, Marginal Lending Facility
All
Code
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT"),
DATA_TYPE_FM == "LEV",
FREQ == "D") |>
day_to_date() |>
mutate(Provider_fm_id = factor(PROVIDER_FM_ID,
levels = c("MLFR", "MRR_RT", "DFR"),
labels = c("ECB Marginal lending facility",
"ECB Main refinancing operations",
"ECB Deposit facility"))) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest 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, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.65, 0.92),
legend.title = element_blank()) +
geom_hline(yintercept = 3.75/100, linetype = "dashed")
2010
Code
dates_ecb <- FM |>
filter(PROVIDER_FM_ID == "DFR") |>
day_to_date() |>
mutate(OBS_VALUE = OBS_VALUE-lag(OBS_VALUE)) |>
filter(OBS_VALUE != 0) |>
pull(date)
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT"),
DATA_TYPE_FM == "LEV",
FREQ == "D") |>
day_to_date() |>
mutate(Provider_fm_id = factor(PROVIDER_FM_ID,
levels = c("MLFR", "MRR_RT", "DFR"),
labels = c("ECB Marginal lending facility",
"ECB Main refinancing operations - Minimum bid rate/fixed rate",
"ECB Deposit facility"))) |>
filter(date >= as.Date("2010-01-01"))|>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = dates_ecb,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
labels = percent_format(accuracy = .1)) +
theme(legend.position = c(0.45, 0.92),
legend.title = element_blank())
2016-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT"),
DATA_TYPE_FM == "LEV",
FREQ == "D") |>
day_to_date() |>
filter(date >= as.Date("2016-01-01"))|>
mutate(Provider_fm_id = factor(PROVIDER_FM_ID,
levels = c("MLFR", "MRR_RT", "DFR"),
labels = c("ECB Marginal lending facility",
"ECB Main refinancing operations - Minimum bid rate/fixed rate",
"ECB Deposit facility"))) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = seq(1960, 2100, 1) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.45, 0.92),
legend.title = element_blank())
2022-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT"),
DATA_TYPE_FM == "LEV",
FREQ == "D") |>
day_to_date() |>
filter(date >= as.Date("2022-01-01")) |>
add_row(date = as.Date("2025-06-11"), PROVIDER_FM_ID = "DFR", OBS_VALUE = 2) |>
add_row(date = as.Date("2025-06-11"), PROVIDER_FM_ID = "MRR_RT", OBS_VALUE = 2.15) |>
add_row(date = as.Date("2025-06-11"), PROVIDER_FM_ID = "MLFR", OBS_VALUE = 2.4) |>
add_row(date = as.Date("2025-06-10"), PROVIDER_FM_ID = "DFR", OBS_VALUE = 2.25) |>
add_row(date = as.Date("2025-06-10"), PROVIDER_FM_ID = "MRR_RT", OBS_VALUE = 2.4) |>
add_row(date = as.Date("2025-06-10"), PROVIDER_FM_ID = "MLFR", OBS_VALUE = 2.65) |>
arrange(desc(date)) |>
#add_row(date = as.Date("2024-09-17"), PROVIDER_FM_ID = "DFR", OBS_VALUE = 3.5) %>%
#add_row(date = as.Date("2024-09-17"), PROVIDER_FM_ID = "MRR_RT", OBS_VALUE = 3.65) %>%
#add_row(date = as.Date("2024-09-17"), PROVIDER_FM_ID = "MLFR", OBS_VALUE = 3.9) %>%
mutate(Provider_fm_id = factor(PROVIDER_FM_ID,
levels = c("MLFR", "MRR_RT", "DFR"),
labels = c("ECB Marginal lending facility",
"ECB Main refinancing operations - Minimum bid rate/fixed rate",
"ECB Deposit facility"))) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = c(dates_ecb),
labels = date_format("%d %B %Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
labels = percent_format(accuracy = .1)) +
theme(legend.position = c(0.65, 0.2),
legend.title = element_blank(),
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
geom_label_repel(data = . %>% filter(date == max(date)),
aes(x = date, y = OBS_VALUE / 100, label = percent(OBS_VALUE / 100, acc = 0.01), color = Provider_fm_id))
2022 - Dates of change
Schedules for the meetings of the Governing Council. html
Key ECB interest rates: Dates of change. html
Code
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT"),
DATA_TYPE_FM == "LEV",
FREQ == "D") |>
day_to_date() |>
mutate(Provider_fm_id = factor(PROVIDER_FM_ID,
levels = c("MLFR", "MRR_RT", "DFR"),
labels = c("ECB Marginal lending facility",
"ECB Main refinancing operations",
"ECB Deposit facility"))) |>
filter(date >= as.Date("2022-07-01")) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = c(dates_ecb, Sys.Date()),
labels = date_format("%d %B %Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.5),
labels = percent_format(accuracy = .1)) +
theme(legend.position = c(0.7, 0.2),
legend.title = element_blank(),
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
Around September 2022
Code
FM |>
filter(PROVIDER_FM_ID %in% c("DFR", "MLFR", "MRR_RT"),
DATA_TYPE_FM == "LEV",
FREQ == "D") |>
day_to_date() |>
filter(date >= as.Date("2022-09-05"),
date <= as.Date("2022-09-20")) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = seq(from = as.Date("2022-01-01"), as.Date("2026-01-01"), by = "1 day"),
labels = date_format("%d %b %Y")) +
scale_y_continuous(breaks = 0.01*seq(-10, 50, 0.25),
labels = percent_format(accuracy = .01)) +
theme(legend.position = c(0.4, 0.92),
legend.title = element_blank(),
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
Japan
1970-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("JP10YT_RR", "R_JP10YT_RR")) |>
month_to_date() |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = seq(1960, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-50, 50, 2),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.75, 0.9),
legend.title = element_blank())
2000-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("JP10YT_RR", "R_JP10YT_RR")) |>
month_to_date() |>
filter(date >= as.Date("2000-01-01")) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest 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(-50, 50, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.75, 0.9),
legend.title = element_blank())
United States
1970-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("US10YT_RR", "R_US10YT_RR")) |>
month_to_date() |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = seq(1900, 2100, 10) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-50, 50, 2),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.75, 0.9),
legend.title = element_blank())
2000-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("US10YT_RR", "R_US10YT_RR")) |>
month_to_date() |>
filter(date >= as.Date("2000-01-01")) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest 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(-50, 50, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.75, 0.9),
legend.title = element_blank())
Euro area
1970-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("U2_10Y", "R_U2_10Y")) |>
month_to_date() |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = seq(1900, 2100, 10) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-50, 50, 2),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.75, 0.9),
legend.title = element_blank())
2000-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("U2_10Y", "R_U2_10Y")) |>
month_to_date() |>
filter(date >= as.Date("2000-01-01")) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest 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(-50, 50, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.35, 0.2),
legend.title = element_blank())
2015-
Code
FM |>
filter(PROVIDER_FM_ID %in% c("U2_10Y", "R_U2_10Y")) |>
month_to_date() |>
filter(date >= as.Date("2015-01-01")) |>
ggplot() +
geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) +
theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
scale_x_date(breaks = seq(1960, 2100, 1) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-50, 50, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.35, 0.2),
legend.title = element_blank())
Related Data
Data on monetary policy
| source | dataset | Title | Updated |
|---|---|---|---|
 bdf |
FM | Marché financier, taux - FM | 2026-08-31 |
| ecb |
FM | Financial market data - FM | 2026-08-31 |
| bdf |
MIR | Taux d'intérêt - Zone euro - MIR | 2026-08-28 |
| bdf |
MIR1 | Taux d'intérêt - France - MIR1 | 2026-08-28 |
 bis |
CBPOL | Policy Rates, Daily - CBPOL | 2026-08-31 |
| ecb |
BSI | Balance Sheet Items - BSI | 2026-08-31 |
| ecb |
BSI_PUB | Balance Sheet Items - Published series - BSI_PUB | 2026-08-31 |
| ecb |
ILM | Internal Liquidity Management - ILM | 2026-09-01 |
| ecb |
ILM_PUB | Internal Liquidity Management - Published series - ILM_PUB | 2026-09-01 |
| ecb |
MIR | MFI Interest Rate Statistics - MIR | 2026-09-01 |
| ecb |
RAI | Risk Assessment Indicators - RAI | 2026-09-01 |
| ecb |
SUP | Supervisory Banking Statistics - SUP | 2026-09-01 |
| ecb |
YC | Financial market data - yield curve - YC | 2026-09-01 |
| ecb |
YC_PUB | Financial market data - yield curve - Published series - YC_PUB | 2026-09-01 |
| ecb |
liq_daily | Daily Liquidity - liq_daily | 2026-09-01 |
 eurostat |
ei_mfir_m | Interest rates - monthly data - ei_mfir_m | 2026-08-14 |
| eurostat |
irt_st_m | Money market interest rates - monthly data - irt_st_m | 2026-08-13 |
 fred |
r | Interest Rates - r | 2026-09-01 |
 oecd |
MEI | Main Economic Indicators - MEI | 2026-08-02 |
| oecd |
MEI_FIN | Monthly Monetary and Financial Statistics (MEI) - MEI_FIN | 2026-08-02 |
Data on interest rates
| source | dataset | Title | Updated |
|---|---|---|---|
| bdf |
FM | Marché financier, taux - FM | 2026-08-31 |
| ecb |
FM | Financial market data - FM | 2026-08-31 |
| bdf |
MIR | Taux d'intérêt - Zone euro - MIR | 2026-08-28 |
| bdf |
MIR1 | Taux d'intérêt - France - MIR1 | 2026-08-28 |
| bis |
CBPOL_D | NA | NA |
| bis |
CBPOL_M | NA | NA |
| ecb |
MIR | MFI Interest Rate Statistics - MIR | 2026-09-01 |
| eurostat |
ei_mfir_m | Interest rates - monthly data - ei_mfir_m | 2026-08-14 |
| eurostat |
irt_lt_mcby_d | NA | NA |
| eurostat |
irt_st_m | Money market interest rates - monthly data - irt_st_m | 2026-08-13 |
| fred |
r | Interest Rates - r | 2026-09-01 |
| oecd |
MEI | Main Economic Indicators - MEI | 2026-08-02 |
| oecd |
MEI_FIN | Monthly Monetary and Financial Statistics (MEI) - MEI_FIN | 2026-08-02 |
 wdi |
FR.INR.DPST | Deposit interest rate (%) - FR.INR.DPST | 2026-09-01 |
| wdi |
FR.INR.LEND | Lending interest rate (%) - FR.INR.LEND | 2026-08-30 |
| wdi |
FR.INR.RINR | Real interest rate (%) - FR.INR.RINR | 2026-09-01 |