Financial market data - FM

Data - ECB

Last observation: Q2 2026 (N = 23) · 20 sept. 2026 (N = 6) · 16 sept. 2026 (N = 6) · août 2026 (N = 34) · 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: 20 sept. 2026, 23:32

Last compile: 21 sept. 2026, 03:35

Structure

FREQ

REF_AREA

CURRENCY

PROVIDER_FM

INSTRUMENT_FM

PROVIDER_FM_ID

DATA_TYPE_FM

OBS_STATUS

OBS_CONF

COLLECTION

COMPILING_ORG

DECIMALS

UNIT

UNIT_MULT

Real Rates

USA, Euro Area

1999

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

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-

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-

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-

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

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

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

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

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-

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-

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

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

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-

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-

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-

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-

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-

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-

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-

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 interest rates

source	dataset	Title	Updated
bdf	FM	Marché financier, taux - FM	2026-09-17
bis	CBPOL_D	Policy Rates, Daily - CBPOL_D	2026-09-20
bis	CBPOL_M	Policy Rates, Monthly - CBPOL_M	2026-09-20
ecb	FM	Financial market data - FM	2026-09-17
ecb	MIR	MFI Interest Rate Statistics - MIR	2026-09-17
eurostat	ei_mfir_m	Interest rates - monthly data - ei_mfir_m	2026-09-11
eurostat	irt_lt_mcby_m	EMU convergence criterion series - monthly data - irt_lt_mcby_m	2026-09-11
eurostat	irt_st_m	Money market interest rates - monthly data - irt_st_m	2026-09-11
fred	r	Interest Rates - r	2026-09-19
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.RINR	Real interest rate (%) - FR.INR.RINR	2026-09-18

Data on monetary policy

source	dataset	Title	Updated
bdf	FM	Marché financier, taux - FM	2026-09-17
bis	CBPOL	Policy Rates, Daily - CBPOL	2026-09-17
bis	CBPOL_D	Policy Rates, Daily - CBPOL_D	2026-09-20
bis	CBPOL_M	Policy Rates, Monthly - CBPOL_M	2026-09-20
ecb	BKN	Banknotes statistics - BKN	2026-09-17
ecb	BLS	Bank Lending Survey Statistics - BLS	2026-09-17
ecb	BSI	Balance Sheet Items - BSI	2026-09-17
ecb	BSI_PUB	Balance Sheet Items - Published series - BSI_PUB	2026-09-17
ecb	EST	Euro Short-Term Rate - EST	2026-09-17
ecb	FM	Financial market data - FM	2026-09-17
ecb	ILM	Internal Liquidity Management - ILM	2026-09-17
ecb	MIR	MFI Interest Rate Statistics - MIR	2026-09-17
ecb	RAI	Risk Assessment Indicators - RAI	2026-09-18
ecb	SUP	Supervisory Banking Statistics - SUP	2026-09-18
ecb	TGB	Target Balances - TGB	2026-09-18
ecb	YC	Financial market data - yield curve - YC	2026-09-18
ecb	YC_PUB	Financial market data - yield curve - Published series - YC_PUB	2026-09-18
ecb	liq_daily	Daily Liquidity - liq_daily	2026-09-18
eurostat	ei_mfir_m	Interest rates - monthly data - ei_mfir_m	2026-09-11
fred	r	Interest Rates - r	2026-09-19
oecd	MEI_FIN	Monthly Monetary and Financial Statistics (MEI) - MEI_FIN	2026-08-02