Nov 6, 2025 · 49m · capital-allocators
Dave Thornton – Unlocking Venture Access Through Stock Options at Vested (EP.469)
gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
Dave Thornton, co-founder and CEO of Vested, discusses how his platform provides liquidity to startup employees by financing option exercises at 409A discounts while creating a diversified, data-driven index of top venture-backed companies for investors.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Ted holds 9.6% of the talking time here. How this is scored →
speaking balance: gold is Ted, purple is the guest (3 minute bins)
Dave bluntly affirms Ted's skepticism regarding power laws, agreeing that predicting single top winners is impossible and rejecting the premise of narrow portfolio concentration.
Hardest push from Ted ▶ 34:38 Ted questioning pricing accuracy in power-law marketsTed presses Dave on how any pricing model can provide meaningful accuracy when venture capital outcomes are dominated by extreme tail power-law distributions.
Biggest teaching moment ▶ 23:15 Breaking down the mechanics of option exercise taxationDave delivers a comprehensive breakdown of strike prices, fair market value spreads, AMT, and ordinary income tax burdens faced by startup employees.
Ted holds their own ▶ 38:16 Ted pressing on the operational limits of long-tail scalingTed directly highlights the structural friction of scaling small, labor-intensive long-tail trades into an institutional-grade investment firm.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Ted as informed peer | Guest teaching | Guest disagreement | Ted pushing back | Why |
|---|---|---|---|---|---|---|
| Dave Thornton’s Career Background and Formative Experiences | 4 | 6 | 1 | 1 | Ted opens with an open-ended prompt about Dave's background. Dave explains his evolution from Citi Alternative Investments to startups, law school, and discovering the startup equity tax trap through a mistake with an employee. | |
| Early Ventures in Sports Analytics and High-Stakes Poker | 4 | 6 | 1 | 1 | Ted asks Dave to elaborate on non-traditional ventures mentioned in passing. Dave details his work creating algorithms for NBA teams, underground poker games, municipal bond pricing, and DFS betting. | |
| Identifying the Liquidity Gap for Rank-and-File Startup Employees | 5 | 7 | 2 | 1 | Ted asks how Dave turned the employee equity insight into a business. Dave explains the initial educational pivot when inbound users kept asking for money within their 90-day post-termination exercise windows. | |
| Structuring Vested’s Investment Strategy and Valuation Discounts | 5 | 7 | 1 | 1 | Ted probes into how Vested accesses capital and constructs value. Dave explains capturing discounts on common stock fair market value and combining it with a quantitative selection model to pick top-quartile venture companies. | |
| Quantitative Modeling and Unique Data Signals for Startups | 6 | 7 | 2 | 2 | Ted asks for details on the data streams feeding the selection model and how Dave tests hypotheses. Dave categorizes the signals into table stakes, differentiated public/filing data, and unique behavioral employee responses. | |
| Sourcing Deals and Calculating Option Exercise Transaction Costs | 5 | 7 | 1 | 1 | Ted asks about deal sourcing mechanics and option pricing calculations. Dave outlines automated outreach via LinkedIn changes and walks through a clear numeric breakdown of exercise strike prices, AMT, and ordinary income tax burdens. | |
| Mitigating Delivery Risk and Aligning Counterparty Incentives | 5 | 7 | 1 | 1 | Ted inquires about mitigating delivery risk when purchasing future stock from individuals. Dave explains why historical non-delivery is virtually nonexistent in smaller rank-and-file ticket sizes due to aligned incentives and post-liquidity payouts. | |
| Harnessing AI and Structuring Diversified Venture Portfolios | 5 | 6 | 1 | 1 | Ted asks about the application of AI and resulting portfolio construction. Dave clarifies using traditional regression and LLMs solely for unstructured message processing, noting the natural stage distribution across Series B through E. | |
| Pricing Model Calibration, Power Laws, and Defensible Moats | 6 | 7 | 2 | 2 | Ted pushes back on whether a pricing model can accurately evaluate power-law startup returns. Dave agrees individual winner picking is impossible, explaining that the model identifies the top 20% bucket and takes broad diversified exposure across it. | |
| Brand Expansion, the Vestimate Tool, and LP Reception | 5 | 6 | 1 | 1 | Ted asks about building the Vested brand and LP sentiment toward an unconventional venture secondaries strategy. Dave discusses the 'Vestimate' tool and differing LP profiles from skeptics to access-starved allocators. | |
| Scalability, Company Relationships, and the Future of Private Secondaries | 6 | 7 | 2 | 2 | Ted challenges the scalability of small-ticket secondary strategies and asks where friction arises. Dave details why early startup boards prefer indirect employee funding over formal retitling until transaction volumes grow substantial. | |
| Reflections on Mentorship, Career Lessons, and Private Market Indexing | 4 | 6 | 1 | 1 | Ted closes with standard personal reflection questions. Dave shares stories about his first dot-com job, mentors Randy Wynn and Emilio Cejo, and compares private secondary development to the evolution of public indexing. |