Experienced growth investor and operator focused on technology and software businesses. Drew Garner brings a background in corporate finance, M&A and growth-stage investing, having led deal execution, portfolio strategy and operational value creation across SaaS and fintech companies. Known for cross-functional leadership, capital allocation discipline and scaling commercial go-to-market models to drive revenue expansion and exit value.
Experienced growth investor and operator focused on technology and software businesses. Drew Garner brings a background in corporate finance, M&A and growth-stage investing, having led deal execution, portfolio strategy and operational value creation across SaaS and fintech companies. Known for cross-functional leadership, capital allocation discipline and scaling commercial go-to-market models to drive revenue expansion and exit value.
Drew focuses on growth-stage technology and software opportunities, prioritizing capital-efficient SaaS and fintech businesses with clear unit economics and scalable go-to-market models. He favors active, operationally-oriented investments where hands-on portfolio support accelerates commercial scaling, margin expansion and exit readiness. Investment decisions blend rigorous financial underwrite—cash-flow sensitivity, M&A optionality—and practical operating KPIs. Typical horizon is medium-term (3–7 years) with disciplined allocation, staged capital deployment, and downside protection via governance and performance-based milestones.
Drew focuses on growth-stage technology and software opportunities, prioritizing capital-efficient SaaS and fintech businesses with clear unit economics and scalable go-to-market models. He favors active, operationally-oriented investments where hands-on portfolio support accelerates commercial scaling, margin expansion and exit readiness. Investment decisions blend rigorous financial underwrite—cash-flow sensitivity, M&A optionality—and practical operating KPIs. Typical horizon is medium-term (3–7 years) with disciplined allocation, staged capital deployment, and downside protection via governance and performance-based milestones.
| Trades 716 | Longs Won 593/716 82% | Profit Factor 164.91 |
| Profitability | Shorts Won 0/0 0% | Standard Deviation $1.12M |
| Average Win $184,449.63 | Best Trade (Jul 15) $23.86M | Sharpe Ratio -11.02 |
| Average Loss -$5,392.22 | Worst Trade (Jul 10) -$89,751.39 | Z-Score 22.33 (100%) |
| Commissions $0 | Avg. Trade Length 1y 4m 1w 6d | Expectancy $151,837.14 |
| Loss Size | 100% | 90% | 80% | 70% | 60% | 50% | 40% | 30% | 20% | 10% |
| Probability of Loss | <0.01% | <0.01% | <0.01% | <0.01% | <0.01% | <0.01% | <0.01% | <0.01% | <0.01% | <0.01% |
| Consecutive Losing Trades | 76,923 | 69,231 | 61,538 | 53,846 | 46,154 | 38,462 | 30,769 | 23,077 | 15,385 | 7,692 |