Finance Investment Portfolio Returns
This dataset provides detailed investment portfolio return metrics, including absolute and annualized returns, risk-adjusted performance indicators, and benchmark comparisons for funds and financial advisors. It is ideal for performance benchmarking, risk analysis, and regulatory reporting in the finance industry.
Sample rows
preview · 8 of 200 rows · all 20 columns| portfolio_idstring | return_absolutefloat | currencystring | portfolio_namestring | fund_idstring | fund_namestring | advisor_idstring | advisor_namestring | reporting_period_startdate | reporting_period_enddate | return_annualizedfloat | benchmark_idstring | benchmark_namestring | benchmark_returnfloat | risk_metric_volatilityfloat | risk_metric_sharpe_ratiofloat | risk_metric_sortino_ratiofloat | risk_metric_max_drawdownfloat | aumfloat | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PF1001 | 14.25 | USD | Global Growth Equity | FND01 | Alpha Capital Fund | ADV001 | Sophia Lee | 2023-01-01 | 2023-12-31 | 13.5 | BMK001 | MSCI World Index | 11.9 | 10.2 | 1.32 | 1.74 | -7.8 | 15000000 | Outperformed benchmark due to strong tech sector. |
| PF1002 | 7.9 | USD | US Dividend Focus | FND01 | Alpha Capital Fund | ADV002 | James Carter | 2023-01-01 | 2023-12-31 | 7.2 | BMK002 | S&P 500 Dividend Aristocrats | 6.8 | 5.7 | 1.01 | 1.35 | -3.2 | 8500000 | Stable returns, low volatility. |
| PF1003 | 5.4 | EUR | Eurozone Balanced | FND02 | Beta Asset Management | ADV003 | Marie Dubois | 2023-04-01 | 2023-12-31 | 5.8 | BMK003 | Euro Stoxx 50 | 4.1 | 6.3 | 0.86 | 1.21 | -4.9 | 6200000 | Mixed equity/bond portfolio. |
| PF1004 | 9.8 | JPY | Asia Pacific Value | FND03 | Gamma Investments | ADV004 | Wei Zhang | 2023-07-01 | 2023-12-31 | 10.1 | BMK004 | FTSE Asia Pacific ex Japan | 8.2 | 12.4 | 0.97 | 1.43 | -8.7 | 10500000 | Strong performance in Australia and Korea. |
| PF1005 | 16.2 | USD | Emerging Markets Growth | FND03 | Gamma Investments | ADV005 | Carlos Ramirez | 2023-01-01 | 2023-12-31 | 15.7 | BMK005 | MSCI EM Index | 13.4 | 14.9 | 1.21 | 1.66 | -10.1 | 13200000 | High volatility, strong returns from China and India. |
| PF1006 | -3.7 | GBP | UK Small Cap | FND04 | Delta Wealth Partners | blank | blank | 2023-10-01 | 2023-12-31 | -5.8 | BMK006 | FTSE Small Cap Index | -2.9 | 15.2 | -0.23 | 0.11 | -13.3 | 2900000 | Challenging market conditions. |
| PF1007 | 3.3 | EUR | European Bond Income | FND02 | Beta Asset Management | ADV003 | Marie Dubois | 2023-01-01 | 2023-12-31 | 3.1 | BMK007 | Bloomberg Euro Aggregate Bond | 2.8 | 3.6 | 0.61 | 0.89 | -2.2 | 9200000 | Consistent fixed income performance. |
| PF1008 | 12.1 | USD | Global ESG Leaders | FND01 | Alpha Capital Fund | ADV006 | Linda Green | 2023-01-01 | 2023-12-31 | 11.4 | BMK008 | MSCI World ESG Leaders | 10.2 | 9.1 | 1.27 | 1.69 | -6.4 | 7800000 | Sustainable investing focus. |
| PF1009 | 6.7 | HKD | Asia Dividend Income | FND03 | Gamma Investments | blank | blank | 2023-01-01 | 2023-12-31 | 6.3 | BMK009 | MSCI AC Asia Pacific | 5.8 | 8.3 | 0.79 | 1.19 | -7.5 | 6000000 | Steady income from Asian blue chips. |
| PF1010 | 22.3 | USD | US Tech Innovators | FND01 | Alpha Capital Fund | ADV002 | James Carter | 2023-07-01 | 2023-12-31 | 23.1 | BMK010 | NASDAQ Composite | 20.5 | 16.6 | 1.29 | 1.88 | -9.4 | 20400000 | Strong gains from AI and cloud sector. |
| PF1011 | 6.2 | JPY | Japan Value Strategy | FND03 | Gamma Investments | ADV004 | Wei Zhang | 2023-01-01 | 2023-12-31 | 6 | BMK011 | TOPIX | 5.1 | 7.7 | 0.91 | 1.28 | -5.9 | 4600000 | Focus on undervalued industrials. |
| PF1012 | 2.9 | CHF | Swiss Defensive | FND05 | Epsilon Funds | ADV007 | Hans Mueller | 2023-04-01 | 2023-12-31 | 2.7 | BMK012 | Swiss Market Index | 2.2 | 4.1 | 0.54 | 0.77 | -2.8 | 3800000 | Low risk, focus on consumer staples. |
| PF1013 | 8.4 | USD | Global Infrastructure | FND02 | Beta Asset Management | ADV008 | Sarah Johnson | 2023-01-01 | 2023-12-31 | 8.1 | BMK013 | S&P Global Infrastructure | 7.2 | 7.9 | 1.04 | 1.46 | -4.6 | 9800000 | Stable income from utilities. |
| PF1014 | 10.3 | CAD | Canada Core Equity | FND06 | Zeta Investment Group | ADV009 | Ava Patel | 2023-04-01 | 2023-12-31 | 10.1 | BMK014 | S&P/TSX Composite Index | 9.2 | 9.5 | 1.13 | 1.56 | -6.1 | 4100000 | Strong performance from energy sector. |
| PF1015 | 6.5 | USD | Global Balanced Income | FND01 | Alpha Capital Fund | ADV001 | Sophia Lee | 2023-01-01 | 2023-12-31 | 6.2 | BMK015 | Bloomberg Global Aggregate | 5.7 | 5.2 | 0.95 | 1.29 | -3.7 | 7500000 | Conservative allocation. |
| PF1016 | 4.7 | AUD | Australian Real Estate | FND07 | Sigma Real Assets | blank | blank | 2023-07-01 | 2023-12-31 | 4.9 | BMK016 | S&P/ASX 200 A-REIT | 3.8 | 6.2 | 0.66 | 1.03 | -5.2 | 5300000 | Stable demand for commercial property. |
| PF1017 | 18.6 | USD | Global Health Innovation | FND01 | Alpha Capital Fund | ADV006 | Linda Green | 2023-04-01 | 2023-12-31 | 18.2 | BMK017 | S&P Global Healthcare | 16.5 | 13.3 | 1.38 | 1.85 | -8.1 | 12600000 | Biotech sector drove returns. |
| PF1018 | 7.1 | EUR | Germany Growth Equity | FND02 | Beta Asset Management | ADV003 | Marie Dubois | 2023-07-01 | 2023-12-31 | 7.4 | BMK018 | DAX | 6.2 | 8.8 | 0.88 | 1.17 | -4.7 | 3100000 | Strong manufacturing sector. |
| PF1019 | 3.8 | EUR | Spain Income Portfolio | FND02 | Beta Asset Management | blank | blank | 2023-01-01 | 2023-12-31 | 3.5 | BMK019 | IBEX 35 | 3.1 | 4.7 | 0.71 | 0.98 | -2.5 | 2700000 | Focus on Spanish government bonds. |
| PF1020 | 20.8 | USD | Global Tech Select | FND01 | Alpha Capital Fund | ADV002 | James Carter | 2023-10-01 | 2023-12-31 | 21.5 | BMK010 | NASDAQ Composite | 19.6 | 15.4 | 1.36 | 1.91 | -10.5 | 15800000 | Concentration in cloud computing. |
What the 200 rows show
from the 200-row sample- 5.5median return_
absolute - 7.3median return_
annualized - 5.1median benchmark_
return - 10.2median risk_
metric_ volatility - 0.68median risk_
metric_ sharpe_ ratio - 0.88median risk_
metric_ sortino_ ratio
Median 5.5, from -4.2 to 22.3.
- string 10
- float 8
- date 2
Columns
20 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 10 columns | |||
portfolio_id | string | Unique identifier for the investment portfoliounique | PF1001 |
portfolio_name | string | Descriptive name of the investment portfolio | Global Growth Equity |
fund_id | string | Unique identifier for the fund managing the portfolio | FND01 |
fund_name | string | Name of the fund managing the portfolio | Alpha Capital Fund |
advisor_id | string | Unique identifier for the financial advisor responsible for the portfoliooptional | ADV001 |
advisor_name | string | Name of the financial advisor responsible for the portfoliooptional | Sophia Lee |
benchmark_id | string | Unique identifier for the benchmark used for comparisonoptional | BMK001 |
benchmark_name | string | Name of the benchmark used for comparisonoptional | MSCI World Index |
currency | string | Currency code for portfolio values (ISO 4217) | USD |
notes | string | Additional notes or comments about the portfolio or reporting periodoptional | Conservative allocation. |
| Numbers 8 columns | |||
return_absolute | float | Absolute return of the portfolio for the reporting period (percentage)-100 to 100 | 14.25 |
return_annualized | float | Annualized return of the portfolio for the reporting period (percentage)-100 to 100 · optional | 13.5 |
benchmark_return | float | Return of the benchmark for the reporting period (percentage)-100 to 100 · optional | 11.9 |
risk_metric_volatility | float | Portfolio volatility (standard deviation of returns) for the reporting period0 or more · optional | 10.2 |
risk_metric_sharpe_ratio | float | Portfolio Sharpe ratio for the reporting periodoptional | 1.32 |
risk_metric_sortino_ratio | float | Portfolio Sortino ratio for the reporting periodoptional | 1.74 |
risk_metric_max_drawdown | float | Maximum drawdown of the portfolio during the reporting period (percentage)-100 to 0 · optional | -7.8 |
aum | float | Assets under management for the portfolio at the end of the reporting period (in base currency)0 or more · optional | 15000000 |
| Dates and times 2 columns | |||
reporting_period_start | date | Start date of the reporting period for portfolio returns | 2023-01-01 |
reporting_period_end | date | End date of the reporting period for portfolio returns | 2023-12-31 |
Use it for
A finance dashboard
Return_
absolute and a breakdown of currency. Excel, Power BI or Tableau. What pattern can you find in 200 rows?
A class exercise
Hand out the rows and one question. Everyone works from the same 200 rows.
- Portfolios200PF100114.25PF10027.9PF10035.4
A software demo
Believable portfolios with portfolio_
name, fund_ id and fund_ name to fill a screen in front of a buyer.
This dataset200 rows20 columns
Yours1,000 rows20 columns
blueprint · finance-investment-portfolio-returns
Behind this dataset
Same schema. As many rows as you need.
These 200 rows came out of a blueprint — 20 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
- Track returns by asset class
- Segment by investor profile
- Include risk-adjusted metrics
- Flag high-volatility portfolios
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
- finance-investment-portfolio-returns