Barclays (BCS) Trading Liabilities (2009 - 2026)
Barclays (BCS) recorded Trading Liabilities of $111.31 billion in Q3 2026, up 16.5% from $95.51 billion a year earlier and up 7.1% from the prior quarter.
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Analysis
Barclays (BCS) Trading Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, Barclays reported Trading Liabilities of $77.76 billion, up 8.9% from FY2024.
- Annual Trading Liabilities has a five-year compound annual growth rate of 3.8% (FY2020 to FY2025).
- Across earlier years, Trading Liabilities came in at $71.41 billion in FY2024 (-4.4%), $74.71 billion in FY2023 (-15.0%), $87.92 billion in FY2022 (+20.2%) and $73.12 billion in FY2021 (+13.2%).
- The Q3 2026 figure is the highest quarterly Trading Liabilities since Q1 2023.
- On a year-over-year basis, Trading Liabilities has increased for seven consecutive quarters, with growth averaging 11.4% over the last eight quarters.
- Peak year-over-year performance for Trading Liabilities in the last five years was growth of 26.8% in Q2 2025, against a decline of 20.8% in Q1 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $103.92 billion (Q2 2026), $109.22 billion (Q1 2026) and $77.76 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Trading Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 918.86 Bn | 918.86 Bn | - | - |
| 2 | Bank Of America | 355.02 Bn | -2,021.04 Bn | - | 123.16 Bn |
| 3 | Hsbc Holdings | 299.60 Bn | -1,803.99 Bn | - | 78.41 Bn |
| 4 | Morgan Stanley | 288.82 Bn | 288.82 Bn | - | - |
| 5 | Royal Bank Of Canada | 288.46 Bn | -541.58 Bn | - | - |
| 6 | Goldman Sachs | 269.80 Bn | 269.80 Bn | - | 331.00 Bn |
| 7 | Wells Fargo & Company | 258.84 Bn | 258.84 Bn | - | 56.13 Bn |
| 8 | Mitsubishi Ufj Financial | 244.75 Bn | -96.64 Bn | 10.89 Bn | 225.74 Bn |
| 9 | American Express | 221.16 Bn | 20.64 Bn | - | - |
| 10 | Barclays | 79.79 Bn | -1,629.13 Bn | - | 111.31 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 111.31 Bn |
| Jun 30, 2026 | 103.92 Bn |
| Mar 31, 2026 | 109.22 Bn |
| Dec 31, 2025 | 77.76 Bn |
| Sep 30, 2025 | 95.51 Bn |
| Jun 30, 2025 | 95.08 Bn |
| Mar 31, 2025 | 91.22 Bn |
| Dec 31, 2024 | 71.41 Bn |
| Sep 30, 2024 | 86.03 Bn |
| Jun 30, 2024 | 75.01 Bn |
| Mar 31, 2024 | 88.32 Bn |
| Dec 31, 2023 | 74.71 Bn |
| Sep 30, 2023 | 82.00 Bn |
| Jun 30, 2023 | 89.54 Bn |
| Mar 31, 2023 | 111.58 Bn |
| Dec 31, 2022 | 87.92 Bn |
| Sep 30, 2022 | 97.53 Bn |
| Jun 30, 2022 | 92.98 Bn |
| Mar 31, 2022 | 102.60 Bn |
| Dec 31, 2021 | 73.12 Bn |
API Access
Barclays Trading Liabilities 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=trading-liabilities&ticker=BCS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "trading-liabilities", "ticker": "BCS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=trading-liabilities&ticker=BCS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();