Portfolio Risk Exposure Overview
This dataset provides a comprehensive overview of risk exposure across investment portfolios, including risk scores, asset allocation, leverage, and overexposure flags. It enables financial analysts to identify portfolios with high risk, monitor asset concentration, and optimize allocations for better risk-adjusted returns. The dataset supports regulatory reporting, internal risk reviews, and strategic portfolio management.
Sample rows
preview · 8 of 60 rows · all 16 columns| portfolio_idstring | risk_levelstring | risk_scorefloat | overexposed_flagboolean | asset_classstring | portfolio_namestring | manager_idstring | as_of_datedate | total_assets_usdfloat | asset_class_exposure_pctfloat | geographic_regionstring | sector_exposurestring | largest_single_asset_pctfloat | leverage_ratiofloat | value_at_risk_99_pct_usdfloat | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PF1001 | Moderate | 42.7 | false | Equities | Alpha Growth Fund | MGR23 | 2024-04-12 | 75000000.25 | 81.5 | North America | Technology | 13.2 | 1.05 | 2500000.45 | Well diversified, slight overweight in tech |
| PF1002 | Low | 21.3 | false | Fixed Income | Global Balanced Portfolio | MGR11 | 2024-04-15 | 120000000.9 | 67.8 | Global | Diversified | 6.7 | 0.98 | 1300000.7 | Conservative allocation, low volatility |
| PF1003 | High | 76.8 | true | Equities | Emerging Markets Focus | MGR17 | 2024-04-13 | 54500000 | 92.3 | Asia-Pacific | Financials | 22.7 | 1.3 | 4700000 | High EM exposure, closely monitor currency risk |
| PF1004 | Low | 11.4 | false | Fixed Income | Stable Income Trust | MGR32 | 2024-04-16 | 9700000.25 | 88.9 | Europe | Healthcare | 9.1 | 1 | 650000.2 | Low risk, healthcare bonds overweight |
| PF1005 | Moderate | 48.6 | false | Real Estate | Real Asset Allocation | MGR05 | 2024-04-11 | 56000000 | 71.4 | North America | Energy | 19 | 1.12 | 1900000 | Energy sector REITs driving returns |
| PF1006 | High | 82.2 | true | Alternatives | Alternative Strategies Fund | MGR14 | 2024-04-17 | 40000000 | 86 | Global | Diversified | 28.6 | 2.1 | 8000000 | High leverage, closely monitor derivatives |
| PF1007 | Moderate | 39.7 | false | Commodities | Commodities Income Fund | MGR22 | 2024-04-14 | 30500000 | 72.5 | Asia-Pacific | Energy | 15 | 1.2 | 1200000 | Oil futures overweight |
| PF1008 | High | 72.5 | true | Equities | Tech Innovators Portfolio | MGR01 | 2024-04-13 | 86000000 | 94 | North America | Technology | 31.8 | 1.11 | 7400000 | Concentrated in large-cap tech stocks |
| PF1009 | Moderate | 51.8 | false | Equities | Healthcare Opportunities | MGR04 | 2024-04-15 | 48000000.75 | 79.2 | Europe | Healthcare | 11.2 | 1.08 | 1700000 | Strong performance in biotech |
| PF1010 | Low | 18.9 | false | Mixed | Defensive Multi-Asset | MGR29 | 2024-04-16 | 67500000 | 54.5 | Global | Diversified | 4.5 | 0.97 | 900000 | Balanced across equities and bonds |
| PF1011 | High | 68.3 | true | Equities | Asia-Pacific Growth | MGR19 | 2024-04-17 | 62000000 | 86.4 | Asia-Pacific | Technology | 18.7 | 1.25 | 3100000 | Emerging market tech leaders overweight |
| PF1012 | Moderate | 47.2 | false | Equities | Diversified Equity Income | MGR07 | 2024-04-11 | 99000000.5 | 65.3 | North America | Financials | 8.9 | 1.03 | 1400000 | Stable dividend payers |
| PF1013 | Moderate | 50.9 | false | Commodities | Commodities Edge | MGR13 | 2024-04-12 | 21000000 | 73.3 | Europe | Energy | 14.3 | 1.07 | 1100000 | Heavy in metals and oil |
| PF1014 | Moderate | 44.1 | false | Real Estate | Real Estate Value | MGR31 | 2024-04-10 | 35500000 | 70.8 | North America | Financials | 17.5 | 1.1 | 1200000 | REITs with financial sector focus |
| PF1015 | Moderate | 40.6 | false | Mixed | Global Infrastructure | MGR21 | 2024-04-17 | 80000000 | 62.6 | Global | Energy | 10 | 1.02 | 2100000 | Infrastructure blend, focus on renewables |
| PF1016 | High | 82.9 | true | Alternatives | Alternative Yield | MGR03 | 2024-04-12 | 64000000 | 91.5 | Europe | Diversified | 26.6 | 2.23 | 9000000 | Private credit and distressed debt exposure |
| PF1017 | Low | 10.1 | false | Fixed Income | Core Bond Fund | MGR27 | 2024-04-08 | 29000000 | 95.2 | North America | Financials | 8.2 | 0.97 | 500000 | Short duration bonds |
| PF1018 | Critical | 95.6 | true | Alternatives | Emerging Alt Strategies | MGR18 | 2024-04-09 | 21000000 | 99.1 | Asia-Pacific | Technology | 47.5 | 2.5 | 14500000 | Extreme concentration in high-yield strategies |
| PF1019 | Low | 19.2 | false | Mixed | Income Blend Portfolio | blank | 2024-04-10 | 63000000 | 58.1 | Europe | Healthcare | 7.6 | 1 | 800000 | Blend of income-focused assets |
| PF1020 | Moderate | 36.8 | false | Mixed | Global Diversification Fund | MGR30 | 2024-04-13 | 112000000 | 62 | Global | Diversified | 7.2 | 1 | 1700000 | Strong international allocation |
What the 60 rows show
from the 60-row sampleHigh (risk level) stands out: 17 of its 17 rows have overexposed_
- 32%overexposed_
flag = true - 48.4median risk_
score - 4geographic regions
- 5sector exposures
- 19,400,000median total_
assets_ usd - 80.5median asset_
class_ exposure_ pct
High (risk level)'s mean risk_
Every row with risk_
- string 8
- float 6
- date 1
- boolean 1
Columns
16 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 8 columns | |||
portfolio_id | string | Unique identifier for each investment portfoliounique | PF1001 |
portfolio_name | string | Descriptive name of the investment portfolio | Alpha Growth Fund |
manager_id | string | Unique identifier for the portfolio manager or analyst responsibleoptional | MGR23 |
risk_level | string | Overall risk assessment for the portfolioLow · Moderate · High · Critical | Moderate |
asset_class | string | Primary asset class represented in the portfolio (e.g., Equities, Fixed Income, Commodities, Real Estate, Alternatives, Mixed)6 values | Equities |
geographic_region | string | Primary geographic region of portfolio investments (e.g., North America, Europe, Asia-Pacific, Global)4 regions · optional | North America |
sector_exposure | string | Primary industry sector exposure (e.g., Technology, Healthcare, Financials, Energy, Diversified)5 exposures · optional | Technology |
notes | string | Additional analyst comments or notes regarding the portfolio's risk profileoptional | Oil futures overweight |
| Numbers 6 columns | |||
total_assets_usd | float | Total value of assets in the portfolio, in US dollars0 or more | 75000000.25 |
risk_score | float | Numerical risk score for the portfolio, typically between 0 and 1000 to 100 | 42.7 |
asset_class_exposure_pct | float | Percentage of portfolio allocated to the primary asset class (0-100)0 to 100 | 81.5 |
largest_single_asset_pct | float | Percentage of the portfolio allocated to the single largest asset (0-100)0 to 100 | 13.2 |
leverage_ratio | float | Portfolio leverage ratio (total assets/total equity), where 1.0 means no leverage0 or more · optional | 1.05 |
value_at_risk_99_pct_usd | float | Value at Risk (99% confidence) in USD, representing the maximum expected loss over a defined period0 or more · optional | 2500000.45 |
| Dates and times 1 column | |||
as_of_date | date | Date on which the risk exposure data was last updated | 2024-04-12 |
| True or false 1 column | |||
overexposed_flag | boolean | Indicates whether the portfolio is considered overexposed based on internal risk thresholds | false |
Use it for
A finance dashboard
The overexposed_
flag rate, risk_ score by risk_ level and a breakdown of asset_ class. Excel, Power BI or Tableau. Why do 19 of 60 rows have overexposed_
flag = true? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Portfolios60PF100142.7ModeratePF100376.8HighPF100682.2High
A software demo
Believable portfolios with portfolio_
name, manager_ id and as_ of_ date to fill a screen in front of a buyer.
This dataset60 rows16 columns
Yours1,000 rows16 columnsgeographic_region: UK only
blueprint · portfolio-risk-exposure-overview
Behind this dataset
Same schema. As many rows as you need.
These 60 rows came out of a blueprint — 16 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
Rules it was built with
- List portfolio ID, asset classes, and risk rating.
- Calculate Value at Risk (VaR) for each portfolio.
- Flag portfolios with risk above defined threshold.
- Update exposure metrics weekly.
Open the blueprint in Data Factory
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- portfolio-risk-exposure-overview