Financial market data

Data - ECB

Author

François Geerolf

PROVIDER_FM_ID

Code 
FM %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  group_by(PROVIDER_FM_ID, PROVIDER_FM_ID_desc) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

FREQ

Code 
FM %>%
  left_join(FREQ,  by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
FREQ Freq Nobs
A Annual 840
B Daily - businessweek 356
D Daily 56726
M Monthly 20507
Q Quarterly 3462

REF_AREA

Code 
FM %>%
  left_join(REF_AREA,  by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n()) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

CURRENCY

Code 
FM %>%
  left_join(CURRENCY,  by = "CURRENCY") %>%
  group_by(CURRENCY, Currency) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
CURRENCY Currency Nobs
EUR Euro 71246
USD US dollar 5484
JPY Japanese yen 3523
GBP UK pound sterling 801
DKK Danish krone 434
SEK Swedish krona 403

PROVIDER_FM

Code 
FM %>%
  left_join(PROVIDER_FM,  by = "PROVIDER_FM") %>%
  group_by(PROVIDER_FM, Provider_fm) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
PROVIDER_FM Provider_fm Nobs
4F ECB 67191
DS DataStream 9448
RT Reuters 5252

INSTRUMENT_FM

Code 
FM %>%
  left_join(INSTRUMENT_FM,  by = "INSTRUMENT_FM") %>%
  group_by(INSTRUMENT_FM, Instrument_fm) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
INSTRUMENT_FM Instrument_fm Nobs
KR Key interest rate 57253
EI Equity/index 8611
BB Benchmark bond 7787
MM Money Market 6044
BZ Zero-coupon yield bond 822
SP Spread 789
CY Commodity 585

DATA_TYPE_FM

Code 
FM %>%
  left_join(DATA_TYPE_FM,  by = "DATA_TYPE_FM") %>%
  group_by(DATA_TYPE_FM, Data_type_fm) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
DATA_TYPE_FM Data_type_fm Nobs
LEV Level 38006
CHG Change in percentage points compared to previous rate 19076
HSTA Historical close, average of observations through period 14574
YLDA Yield, average of observations through period 4497
YLD Yield 3290
ASKA Ask price or primary activity, average of observations through period 837
YLDE Yield, end of period 822
SPRE Spread, end of period 789

COLLECTION

Code 
FM %>%
  left_join(COLLECTION,  by = "COLLECTION") %>%
  group_by(COLLECTION, Collection) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
COLLECTION Collection Nobs
A Average of observations through period 19929
E End of period 61962

UNIT

Code 
FM %>%
  left_join(UNIT,  by = "UNIT") %>%
  group_by(UNIT, Unit) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
UNIT Unit Nobs
EUR Euro 157
PC Percent 19076
PCPA Percent per annum 54047
POINTS Points 8611

TITLE

Code 
FM %>%
  group_by(TITLE) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Real Rates

USA, Euro Area

1999

Code 
plot <- FM %>%
  filter(PROVIDER_FM_ID %in% c("R_US10YT_RR", "R_U2_10Y")) %>%
  month_to_date %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  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 %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(color = ifelse(REF_AREA == "U2", color2, color)) %>%
  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 %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(color = ifelse(REF_AREA == "U2", color2, color)) %>%
  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 %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(color = ifelse(REF_AREA == "U2", color2, color)) %>%
  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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
  scale_x_date(breaks = seq(1960, 2025, 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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
  scale_x_date(breaks = seq(1960, 2025, 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"))) %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  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, 2025, 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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  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, 2025, 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 %>%
  #add_row(date = as.Date("2024-09-12"), PROVIDER_FM_ID = "DFR", OBS_VALUE = 3.5) %>%
  #add_row(date = as.Date("2024-09-12"), PROVIDER_FM_ID = "MRR_RT", OBS_VALUE = 3.65) %>%
  #add_row(date = as.Date("2024-09-12"), PROVIDER_FM_ID = "MLFR", OBS_VALUE = 3.9) %>%
  #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) %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  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("2022-01-01")) %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = Provider_fm_id)) + 
  theme_minimal() + xlab("") + ylab("Interest Rates (%)") +
  scale_x_date(breaks = 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))

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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  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_desc)) + 
  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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  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")) %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  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")) %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  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 %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  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")) %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  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")) %>%
  left_join(PROVIDER_FM_ID,  by = "PROVIDER_FM_ID") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = OBS_VALUE / 100, color = PROVIDER_FM_ID_desc)) + 
  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())

Info

source dataset .html .RData
ecb FM 2024-11-18 2024-11-19

Data on monetary policy

source dataset .html .RData
bdf FM 2024-11-18 2024-11-18
bdf MIR 2024-07-26 2024-07-01
bdf MIR1 2024-10-16 2024-10-16
bis CBPOL 2024-08-09 2024-09-15
ecb BSI 2024-11-19 2024-11-19
ecb BSI_PUB 2024-11-19 2024-11-19
ecb FM 2024-11-18 2024-11-19
ecb ILM 2024-10-08 2024-11-11
ecb ILM_PUB 2024-10-08 2024-09-10
ecb liq_daily 2024-10-08 2024-09-11
ecb MIR 2024-06-19 2024-11-18
ecb RAI 2024-10-08 2024-10-30
ecb SUP 2024-10-08 2024-10-08
ecb YC 2024-11-19 2024-11-19
ecb YC_PUB 2024-10-08 2024-10-08
eurostat ei_mfir_m 2024-11-18 2024-11-18
eurostat irt_st_m 2024-11-18 2024-11-18
fred r 2024-11-18 2024-11-18
oecd MEI 2024-04-16 2024-06-30
oecd MEI_FIN 2024-09-15 2024-11-18

Data on interest rates

source dataset .html .RData
bdf FM 2024-11-18 2024-11-18
bdf MIR 2024-07-26 2024-07-01
bdf MIR1 2024-10-16 2024-10-16
bis CBPOL_D 2024-11-18 2024-05-10
bis CBPOL_M 2024-11-18 2024-04-19
ecb FM 2024-11-18 2024-11-19
ecb MIR 2024-06-19 2024-11-18
eurostat ei_mfir_m 2024-11-18 2024-11-18
eurostat irt_lt_mcby_d 2024-11-18 2024-11-18
eurostat irt_st_m 2024-11-18 2024-11-18
fred r 2024-11-18 2024-11-18
oecd MEI 2024-04-16 2024-06-30
oecd MEI_FIN 2024-09-15 2024-11-18
wdi FR.INR.RINR 2024-11-18 2024-11-18

LAST_COMPILE

LAST_COMPILE
2024-11-19

Last

TIME_PERIOD FREQ Nobs
2024-Q3 Q 24
2024-11-19 D 6
2024-10-23 B 6
2024-10 M 37
2023 A 26

Last Day

TITLE TIME_PERIOD OBS_VALUE
Deposit facility - date of changes (raw data) - Change in percentage points compared to previous rate 2024-11-19 -0.25
Deposit facility - date of changes (raw data) - Level 2024-11-19 3.25
Marginal lending facility - date of changes (raw data) - Change in percentage points compared to previous rate 2024-11-19 -0.25
Marginal lending facility - date of changes (raw data) - Level 2024-11-19 3.65
Main refinancing operations - fixed rate tenders (fixed rate) (date of changes) - Level 2024-11-19 3.40
Main refinancing operations - Minimum bid rate/fixed rate (date of changes) - Level 2024-11-19 3.40