Serial entrepreneur, policy advocate and investor Andrew Yang is known for scaling startups and elevating tech-forward policy discourse into mainstream politics. He founded a fintech-focused firm and a nonprofit emphasizing universal basic income while later launching investment initiatives targeting early-stage tech and consumer companies. Background combines business-building, product and digital marketing experience with public-market engagement; frequently cited by investors for founder-market fit, platform-driven distribution strategies and consumer data monetization insights.
Serial entrepreneur, policy advocate and investor Andrew Yang is known for scaling startups and elevating tech-forward policy discourse into mainstream politics. He founded a fintech-focused firm and a nonprofit emphasizing universal basic income while later launching investment initiatives targeting early-stage tech and consumer companies. Background combines business-building, product and digital marketing experience with public-market engagement; frequently cited by investors for founder-market fit, platform-driven distribution strategies and consumer data monetization insights.
Combines founder-first, product-centric investing with a preference for early-stage tech and consumer companies—especially fintech, platform businesses and data-driven consumer models. Emphasizes founder-market fit, scalable distribution and unit-economics discipline, making concentrated, conviction-driven bets with reserved follow-on capital for winners. Favors long horizons to build network effects and policy-aware macro views to assess regulatory risk. Underwriting prioritizes measurable KPIs, rapid user growth paired with path to monetization and operational partnership from board or advisory roles.
Combines founder-first, product-centric investing with a preference for early-stage tech and consumer companies—especially fintech, platform businesses and data-driven consumer models. Emphasizes founder-market fit, scalable distribution and unit-economics discipline, making concentrated, conviction-driven bets with reserved follow-on capital for winners. Favors long horizons to build network effects and policy-aware macro views to assess regulatory risk. Underwriting prioritizes measurable KPIs, rapid user growth paired with path to monetization and operational partnership from board or advisory roles.
| Trades 235 | Longs Won 114/235 48% | Profit Factor 2.2 |
| Profitability | Shorts Won 0/0 0% | Standard Deviation $575,198.57 |
| Average Win $459,082.21 | Best Trade (Jul 15) $3.25M | Sharpe Ratio -9.49 |
| Average Loss -$196,216.61 | Worst Trade (Jun 29) -$1.73M | Z-Score -0.12 (9.33%) |
| Commissions $0 | Avg. Trade Length 8m 3d | Expectancy $121,673.03 |
| Loss Size | 100% | 90% | 80% | 70% | 60% | 50% | 40% | 30% | 20% | 10% |
| Probability of Loss | - | - | - | - | - | - | - | - | - | - |
| Consecutive Losing Trades | 1,934 | 1,741 | 1,547 | 1,354 | 1,161 | 967 | 774 | 580 | 387 | 193 |