Daily Liquidity

Data - ECB

Author

François Geerolf

Info

source dataset Title .html .rData
ecb liq_daily Daily Liquidity 2026-07-24 2026-07-24

Info

Monetary financial institutions in the euro area are legally obliged to report data to their National Central Banks, which in turn report to the ECB.

Data on monetary policy

source dataset Title .html .rData
ecb liq_daily Daily Liquidity 2026-07-24 2026-07-24
bdf FM Marché financier, taux 2026-07-24 2026-07-24
bdf MIR Taux d'intérêt - Zone euro 2026-07-24 2026-07-24
bdf MIR1 Taux d'intérêt - France 2026-07-24 2026-07-24
bis CBPOL Policy Rates, Daily 2026-07-25 2026-07-25
ecb BSI Balance Sheet Items 2026-07-24 2026-07-23
ecb BSI_PUB Balance Sheet Items - Published series 2026-07-24 2026-07-24
ecb FM Financial market data 2026-07-24 2026-07-24
ecb ILM Internal Liquidity Management 2026-07-24 2026-07-24
ecb ILM_PUB Internal Liquidity Management - Published series 2026-07-24 2026-07-24
ecb MIR MFI Interest Rate Statistics 2026-07-24 2026-07-24
ecb RAI Risk Assessment Indicators 2026-07-24 2026-07-24
ecb SUP Supervisory Banking Statistics 2026-07-24 2026-07-24
ecb YC Financial market data - yield curve 2026-07-24 2026-07-23
ecb YC_PUB Financial market data - yield curve - Published series 2026-07-24 2026-07-24
eurostat ei_mfir_m Interest rates - monthly data 2026-07-23 2026-07-23
eurostat irt_st_m Money market interest rates - monthly data 2026-07-24 2026-07-23
fred r Interest Rates 2026-07-24 2026-07-24
oecd MEI Main Economic Indicators 2026-07-24 2025-07-24
oecd MEI_FIN Monthly Monetary and Financial Statistics (MEI) 2024-09-15 2025-07-24

LAST_COMPILE

LAST_COMPILE
2026-07-26

variable

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  group_by(variable, Variable) %>%
  summarise(Nobs = n()) %>%
  arrange(variable) %>%
  print_table_conditional
variable Variable Nobs
ABSPP ABSPP - ABS purchase programme 616
CBPP1 CBPP1 - Covered bond purchase programme 2729
CBPP2 CBPP2 - Covered bond purchase programme 2 1999
CBPP3 CBPP3 - Covered bond purchase programme 3 616
CSPP CSPP - Corporate sector purchase programme 531
DF Deposit facility 9271
MLF Marginal lending facility 9271
OMO Open market operations excl. MonPol portfolios 9271
PEPP PEPP - Pandemic emergency purchase programme 330
PSPP PSPP - Public sector purchase programm 595
SMP SMP - Securities Markets programme 657
current_accounts Current accounts 9307
excess_liquidity Excess liquidity 1792
net_autonomous_monpol Net liquidity effect from Autonomous Factors and MonPol portfolios 9307
reserve_requirements Reserve requirements 9307

duplicates

Same + different values

Code 
liq_daily %>%
  group_by(variable, date) %>%
  filter(n()>1) %>%
  arrange(date, variable) %>%
  print_table_conditional

Different values

Code 
liq_daily %>%
  unique %>%
  group_by(variable, date) %>%
  filter(n()>1) %>%
  arrange(date, variable) %>%
  print_table_conditional
date variable value
2008-01-01 OMO 535514
2008-01-01 OMO 535503
2008-01-01 net_autonomous_monpol 256501
2008-01-01 net_autonomous_monpol 256490
2008-01-02 OMO 468454
2008-01-02 OMO 468443
2008-01-02 net_autonomous_monpol 262467
2008-01-02 net_autonomous_monpol 262456
2008-01-03 OMO 437094
2008-01-03 OMO 437083
2008-01-03 net_autonomous_monpol 269250
2008-01-03 net_autonomous_monpol 269239
2008-01-15 current_accounts 168183
2008-01-15 current_accounts 168187
2008-01-15 net_autonomous_monpol 232059
2008-01-15 net_autonomous_monpol 232055

Data on liquidity

Last date

Code 
liq_daily %>%
  filter(date == max(date)) %>%
  print_table_conditional
date variable value
2026-07-23 OMO 30991
2026-07-23 MLF 84
2026-07-23 DF 2009216
2026-07-23 net_autonomous_monpol -2300304
2026-07-23 current_accounts 322164
2026-07-23 reserve_requirements 173861
2026-07-23 excess_liquidity 2157434

Last date by variable

Code 
liq_daily %>%
  group_by(variable) %>%
  filter(date == max(date)) %>%
  print_table_conditional
date variable value
2026-07-23 OMO 30991
2026-07-23 MLF 84
2026-07-23 DF 2009216
2026-07-23 net_autonomous_monpol -2300304
2026-07-23 current_accounts 322164
2026-07-23 reserve_requirements 173861
2026-07-17 CBPP1 0
2026-07-17 CBPP2 0
2026-07-17 SMP 14
2026-07-17 CBPP3 191884
2026-07-17 ABSPP 2070
2026-07-17 PSPP 1693012
2026-07-17 CSPP 218392
2026-07-23 excess_liquidity 2157434
2026-07-17 PEPP 1303591

Asset purchase program

CBPP1, CBPP2, CBPP3, SMP, ABSPP, PSPP, CSPP, PEPP

All

Lines

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(variable %in% c("CBPP1", "CBPP2", "CBPP3", "SMP", "ABSPP", "PSPP", "CSPP", "PEPP")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2030, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.7),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

Stock

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(variable %in% c("CBPP1", "CBPP2", "CBPP3", "SMP", "ABSPP", "PSPP", "CSPP", "PEPP")) %>%
  ggplot + geom_area(aes(x = date, y = value/10^3, fill = Variable), alpha = 0.5) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
    # Add labels manually with matching colors
  annotate("text", x = as.Date("2023-01-01"), y = 3000, label = "PEPP", color = scales::hue_pal()(8)[6], size = 4) +
  annotate("text", x = as.Date("2021-01-01"), y = 1300, label = "PSPP", color = scales::hue_pal()(8)[7], size = 4) +
  theme(legend.position = c(0.3, 0.7),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

2020-

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(date >= as.Date("2020-01-01")) %>%
  filter(variable %in% c("CBPP1", "CBPP2", "CBPP3", "SMP", "ABSPP", "PSPP", "CSPP", "PEPP")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(from = as.Date("2020-01-01"), Sys.Date(), by = "6 months"),
               labels = date_format("%b %Y")) +
  theme(legend.position = c(0.5, 0.5),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

2022-

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(date >= as.Date("2022-01-01")) %>%
  filter(variable %in% c("CBPP1", "CBPP2", "CBPP3", "SMP", "ABSPP", "PSPP", "CSPP", "PEPP")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(from = as.Date("2022-01-01"), as.Date("2026-01-01"), by = "2 months"),
               labels = date_format("%b %Y")) +
  theme(legend.position = c(0.45, 0.5),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

Excess Liquidity

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(Variable == "Excess liquidity") %>%
  ggplot + geom_line(aes(x = date, y = value/10^3)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2030, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

Excess Liquidity & Deposit Facility

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2030, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

Synthesis excess liquidity

All

Code 
liq_daily %>%
  filter(variable %in% c("excess_liquidity", "reserve_requirements", "current_accounts", "DF", "MLF")) %>%
  group_by(date, variable) %>%
  filter(row_number(value) == 1) %>%
  spread(variable, value) %>%
  transmute(date, `Excess Liquidity (ECB)` = excess_liquidity,
            `Excess Liquidity (own)` = current_accounts-reserve_requirements+DF-MLF) %>%
  gather(Variable, value, -date) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable, linetype = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_color_manual(values = c("red", "black")) +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2030, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

2022

Code 
liq_daily %>%
  filter(variable %in% c("excess_liquidity", "reserve_requirements", "current_accounts", "DF", "MLF")) %>%
  group_by(date, variable) %>%
  filter(row_number(value) == 1) %>%
  spread(variable, value) %>%
  transmute(date, `Excess Liquidity (ECB)` = excess_liquidity,
            `Excess Liquidity (own)` = current_accounts-reserve_requirements+DF-MLF) %>%
  gather(Variable, value, -date) %>%
  filter(date >= as.Date("2022-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(from = as.Date("2022-01-01"), as.Date("2026-01-01"), by = "2 months"),
               labels = date_format("%b %Y")) +
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

Excess Liquidity

Code 
liq_daily %>%
  filter(variable %in% c("excess_liquidity", "reserve_requirements", "current_accounts", "DF", "MLF")) %>%
  group_by(date, variable) %>%
  filter(row_number(value) == 1) %>%
  spread(variable, value) %>%
  transmute(date, value = current_accounts-reserve_requirements+DF-MLF) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3)) +
  xlab("") + ylab("Excess liquidity") + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2030, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

Excess Liquidity & Deposit Facility & Current accounts

All

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility", "Current accounts")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2030, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

2020-

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(date >= as.Date("2020-01-01")) %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility", "Current accounts")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(from = as.Date("2020-01-01"), Sys.Date(), by = "6 months"),
               labels = date_format("%b %Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

2022-

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(date >= as.Date("2022-01-01")) %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility", "Current accounts")) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(from = as.Date("2022-01-01"), as.Date("2026-01-01"), by = "2 months"),
               labels = date_format("%b %Y")) +
  theme(legend.position = c(0.15, 0.5),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

Excess Liquidity & Deposit Facility & Current accounts

All

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility", "Current accounts", "Marginal lending facility", "Reserve requirements")) %>%
  mutate(Variable = factor(Variable, levels = c("Current accounts", "Reserve requirements", "Deposit facility", "Marginal lending facility", "Excess liquidity"))) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2030, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

2020-

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(date >= as.Date("2020-01-01")) %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility", "Current accounts", "Marginal lending facility", "Reserve requirements")) %>%
  mutate(Variable = factor(Variable, levels = c("Current accounts", "Reserve requirements", "Deposit facility", "Marginal lending facility", "Excess liquidity"))) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(from = as.Date("2020-01-01"), Sys.Date(), by = "6 months"),
               labels = date_format("%b %Y")) +
  theme(legend.position = c(0.5, 0.5),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

2022-

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(date >= as.Date("2022-01-01")) %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility", "Current accounts", "Marginal lending facility", "Reserve requirements")) %>%
  mutate(Variable = factor(Variable, levels = c("Current accounts", "Reserve requirements", "Deposit facility", "Marginal lending facility", "Excess liquidity"))) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(from = as.Date("2022-01-01"), as.Date("2026-01-01"), by = "2 months"),
               labels = date_format("%b %Y")) +
  theme(legend.position = c(0.15, 0.5),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))

July 2022- Novembre 2022

Code 
liq_daily %>%
  left_join(variable, by = "variable") %>%
  filter(date >= as.Date("2022-09-05"),
         date <= as.Date("2022-09-20")) %>%
  filter(Variable %in% c("Excess liquidity", "Deposit facility", "Current accounts", "Marginal lending facility", "Reserve requirements")) %>%
  mutate(Variable = factor(Variable, levels = c("Current accounts", "Reserve requirements", "Deposit facility", "Marginal lending facility", "Excess liquidity"))) %>%
  ggplot + geom_line(aes(x = date, y = value/10^3, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  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")) +
  theme(legend.position = c(0.15, 0.5),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = 1000*seq(-100, 90, .5),
                     labels = scales::dollar_format(acc = 1, su = " Bn€", pre = ""))