A side-by-side comparison of Los Angeles County Employees Retirement Association and State of Wisconsin Investment Board (SWIB) across firm type, scale, strategy, and geography.
State of Wisconsin Investment Board (SWIB) manages roughly 2.0× the assets of the other firm.
No overlapping asset classes — these firms operate in entirely separate markets.
| Los Angeles County Employees Retirement Association | State of Wisconsin Investment Board (SWIB) | |
|---|---|---|
| Basics | ||
| Firm type | Public Pension Fund | Public Pension Fund |
| Country | USA - CA | USA - WI |
| Founded | 1937 | 1951 |
| Firm age | 89 yrs | 75 yrs |
| Roles | Lp | Lp |
| Scale & AUM | ||
| AUM | $87.97B | $178B |
| Market position | Large ($20–100B) | Giant ($100–500B) |
| AUM ratio | 2.0× larger | |
| Strategy & Focus | ||
| Investment style | Multi-asset | Multi-asset |
| Diversification | Diversified | Diversified |
Los Angeles County Employees Retirement Association is a public pension fund based in USA - CA, while State of Wisconsin Investment Board (SWIB) is a public pension fund based in USA - WI. This page compares their firm type, assets under management, strategies, and geographic focus.
By reported AUM, State of Wisconsin Investment Board (SWIB) is larger ($87.97B vs $178B).
| Asset classes |
| private equity, private credit, real estate, infrastructure |
| private equity, private credit, real estate, fixed income |
| Shared asset classes | 3: private equity, private credit, real estate |
| Geography | ||
| Geographic bias | North America | Global |
| Regions | United States, North America, Europe, Asia | North America, Global, Global, Global |
| Shared geographies | North America, Global, North America | |
| Team | ||
| Team-to-AUM ratio | 0.0 per $B | 0.0 per $B |
| Network & Relationships | ||
| Connectivity | 8/100 | 0/100 |
| Network strength | 1/100 | 0/100 |
| Relationships | 1 | 0 |
| Relationship density | Low | None |
| Network maturity | Emerging | No network |
| Similarity | ||
| Overall similarity | 29% | |
| Asset class overlap | 60% | |
| Geography overlap | 40% | |