Barclays Bank (ATMP) EBITDA (2009 - 2022)
Barclays Bank (ATMP) posted EBITDA of -$8.2 billion for Q2 2022, down 195.9% on a QoQ basis from $8.5 billion in Q1 2022, and down 322.3% year-over-year from $3.7 billion in Q2 2021.
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Analysis
Barclays Bank (ATMP) EBITDA (2009 - 2022) Analysis & Trends
Barclays Bank has reported EBITDA for 12 years, with the latest figure at -$8.2 billion in Q2 2022.
- On a quarterly basis, EBITDA fell 322.3% year-over-year to -$8.2 billion in Q2 2022; TTM through Jun 2022 was $12.1 billion, a 37.37% decrease from a year earlier, with the FY2025 full-year figure at -$11.0 billion, up 32.07% from the prior year.
- EBITDA was -$8.2 billion for Q2 2022 at Barclays Bank, down from $8.5 billion in the prior quarter.
- The five-year high for EBITDA was $8.5 billion in Q1 2022, with the low at -$8.2 billion in Q2 2022.
- Average EBITDA over 3 years is $3.6 billion, with a median of $5.6 billion recorded in 2018.
- The sharpest annual moves came in 2018 and 2022: EBITDA jumped 30.59% in 2018, then slumped 322.3% in 2022.
- Over 3 years, EBITDA stood at $7.6 billion in 2018, then tumbled by 51.35% to $3.7 billion in 2021, then plunged by 322.3% to -$8.2 billion in 2022.
- The last three EBITDA figures came in at -$8.2 billion (Q2 2022), $8.5 billion (Q1 2022), and $3.7 billion (Q2 2021), per Business Quant data.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Bank Of America | 394.48 Bn | -194.01 Bn | 30.39 Bn | 11.77 Bn |
| 2 | Hsbc Holdings | 348.97 Bn | 349.02 Bn | - | - |
| 3 | Morgan Stanley | 314.73 Bn | 154.60 Bn | - | 20.47 Bn |
| 4 | Royal Bank Of Canada | 285.58 Bn | 58.73 Bn | - | 18.35 Bn |
| 5 | Goldman Sachs | 276.87 Bn | -699.48 Bn | - | 26.66 Bn |
| 6 | Mitsubishi Ufj Financial | 274.03 Bn | -110.29 Bn | 10.89 Bn | 5.11 Bn |
| 7 | Wells Fargo & Company | 251.82 Bn | 49.99 Bn | - | 19.01 Bn |
| 8 | Banco Santander | 212.85 Bn | 220.46 Bn | 28.01 Bn | 10.44 Bn |
| 9 | Toronto Dominion Bank | 207.22 Bn | 45.89 Bn | - | 1.33 Bn |
| 10 | Barclays Bank | 40.38 Bn | 40.38 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2022 | -8.18 Bn |
| Mar 31, 2022 | 8.53 Bn |
| Jun 30, 2021 | 3.68 Bn |
| Mar 31, 2021 | 8.06 Bn |
| Jun 30, 2018 | 7.56 Bn |
| Mar 31, 2018 | 2.15 Bn |
| Dec 31, 2017 | -2.81 Bn |
| Sep 30, 2017 | 5.84 Bn |
| Jun 30, 2017 | 5.79 Bn |
| Mar 31, 2017 | 6.56 Bn |
| Dec 31, 2016 | 5.39 Bn |
| Sep 30, 2016 | 6.12 Bn |
| Jun 30, 2016 | 7.88 Bn |
| Mar 31, 2016 | 6.59 Bn |
| Dec 31, 2015 | 5.91 Bn |
| Sep 30, 2015 | 7.83 Bn |
| Jun 30, 2015 | 9.29 Bn |
| Mar 31, 2015 | 7.98 Bn |
| Dec 31, 2014 | 5.71 Bn |
| Sep 30, 2014 | 9.28 Bn |
API Access
Barclays Bank EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=ATMP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "ATMP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=ATMP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();