Exchange Rates, Daily - XRU_D

Data - BIS

Author

François Geerolf

Info

Data on xrates

source dataset Title .html .rData
bis XRU_D Exchange Rates, Daily 2026-04-26 2025-05-24
bdf EXR NA NA NA
bis EER Real Effective Exchange Rates, Monthly 2025-08-25 2026-04-06
bis EER_D Real Effective Exchange Rates, Daily 2024-11-18 2024-05-10
bis XRU Exchange Rates 2026-04-26 2026-04-08
ecb EXR Exchange Rates 2026-03-25 2026-04-26
eurostat ert_bil_eur_d Euro/ECU exchange rates - daily data 2026-04-26 2026-01-27
eurostat ert_h_eur_d Former euro area national currencies vs. euro/ECU - daily data 2026-04-26 2025-05-24
fred xrates Exchange Rates 2026-04-26 2026-04-28
gfd xrates Exchange Rates 2026-04-04 2021-01-08
oecd REFSERIES_MSIT Exchange rates 2024-09-15 2025-05-24
oecd SNA_TABLE4 PPPs and exchange rates 2024-09-15 2025-05-24
wdi PA.NUS.FCRF Official exchange rate (LCU per USD, period average) 2025-05-24 2026-04-26

Data on monetary policy

source dataset Title .html .rData
bdf FM NA NA NA
bdf MIR NA NA NA
bdf MIR1 NA NA NA
bis CBPOL Policy Rates, Daily 2026-04-08 2026-04-28
ecb BSI Balance Sheet Items 2026-04-27 2026-01-11
ecb BSI_PUB NA NA NA
ecb FM Financial market data 2026-04-27 2026-04-26
ecb ILM NA NA NA
ecb ILM_PUB NA NA NA
ecb MIR NA NA NA
ecb RAI NA NA NA
ecb SUP NA NA NA
ecb YC NA NA NA
ecb YC_PUB NA NA NA
ecb liq_daily NA NA NA
eurostat ei_mfir_m Interest rates - monthly data 2026-04-26 2026-04-26
eurostat irt_st_m Money market interest rates - monthly data 2026-04-26 2026-04-26
fred r Interest Rates 2026-04-28 2026-04-26
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_DOWNLOAD

LAST_DOWNLOAD
2024-04-19

LAST_COMPILE

LAST_COMPILE
2026-04-28

Last

date Nobs
2024-04-16 63

REF_AREA

Code 
XRU_D %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(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 .}

COLLECTION

Code 
XRU_D %>%
  left_join(COLLECTION, by = "COLLECTION") %>%
  group_by(COLLECTION, Collection) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
COLLECTION Collection Nobs
A Average of observations through period 1016630

FREQ

Code 
XRU_D %>%
  left_join(FREQ, by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
FREQ Freq Nobs
D Daily 1016630

CURRENCY

Code 
XRU_D %>%
  left_join(CURRENCY, by = "CURRENCY") %>%
  group_by(CURRENCY, Currency) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

Germany, France, Italy, Spain

All-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("DE", "FR", "IT", "ES")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("1 USD in National Currency") +
  scale_x_date(breaks = seq(1940, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 10, 0.2),
                     labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "../$")) +
  scale_color_identity() + add_4flags +
  theme(legend.position = c(0.8, 0.80),
        legend.title = element_blank())

1970-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("DE", "FR", "IT", "ES")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  filter(date >= as.Date("1970-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("1 USD in National Currency") +
  scale_x_date(breaks = seq(1940, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 10, 0.2),
                     labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "../$")) +
  scale_color_identity() + add_4flags +
  theme(legend.position = c(0.8, 0.80),
        legend.title = element_blank())

1980-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("DE", "FR", "IT", "ES")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  filter(date >= as.Date("1980-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("1 USD in National Currency") +
  scale_x_date(breaks = seq(1940, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 10, 0.2),
                     labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "../$")) +
  scale_color_identity() + add_4flags +
  theme(legend.position = c(0.8, 0.80),
        legend.title = element_blank())

Russia

All

Code 
XRU_D %>%
  filter(REF_AREA == "RU") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = c(0.1, 0.2, 0.5, 1, 2, 5, 8, 10, 20, 50, 80, 100, 150),
                labels = dollar_format(a = .1, p = "", su = " RUB/$"))

2000-

Code 
XRU_D %>%
  filter(REF_AREA == "RU",
         date >= "2000-01-01") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 600, 10),
                labels = dollar_format(a = 1, p = "", su = " RUB/$"))

2010-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("RU"),
         date >= "2010-01-01") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 600, 10),
                labels = dollar_format(a = 1, p = "", su = " RUB/$"))

2016-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("RU"),
         date >= "2016-01-01") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 600, 10),
                labels = dollar_format(a = 1, p = "", su = " RUB/$"))

Japan

All

Code 
XRU_D %>%
  filter(REF_AREA == "JP") %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = c(seq(0, 600, 50), seq(50, 150, 10)),
                labels = dollar_format(a = 1, p = "", su = " ¥/$"))

1985-

Code 
XRU_D %>%
  filter(REF_AREA == "JP") %>%
  filter(date >= "1985-01-01") %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = c(seq(0, 600, 50), seq(50, 150, 10)),
                labels = dollar_format(a = 1, p = "", su = " ¥/$"))

2000-

Code 
XRU_D %>%
  filter(REF_AREA == "JP") %>%
  filter(date >= "2000-01-01") %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(seq(0, 600, 50), seq(50, 150, 10)),
                labels = dollar_format(a = 1, p = "", su = " ¥/$"))

Switzerland

All

Code 
XRU_D %>%
  filter(REF_AREA == "CH") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = c(seq(0, 600, 1), seq(0.5, 1.5, 0.1)),
                labels = dollar_format(a = .1, p = "", su = " F/$"))

1990-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("CH"),
         COLLECTION == "A",
         date >= "1990-01-01") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(seq(0, 600, 1), seq(0.5, 2.5, 0.1)),
                labels = dollar_format(a = .1, p = "", su = " F/$"))

2000-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("CH"),
         COLLECTION == "A",
         date >= "2000-01-01") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(seq(0, 600, 1), seq(0.5, 2.5, 0.1)),
                labels = dollar_format(a = .1, p = "", su = " F/$"))

2010-

Code 
XRU_D %>%
  filter(REF_AREA %in% c("CH"),
         COLLECTION == "A",
         date >= "2010-01-01") %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(seq(0, 600, 1), seq(0.5, 2.5, 0.1)),
                labels = dollar_format(a = .1, p = "", su = " F/$"))

China

Code 
XRU_D %>%
  filter(REF_AREA == "CN") %>%
  mutate(OBS_VALUE = as.numeric(OBS_VALUE)) %>%
  ggplot(.) + geom_line() + theme_minimal() +
  aes(x = date, y = OBS_VALUE) + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1940, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 20, 1),
                labels = dollar_format(a = 1, p = "", su = " ¥/$"))