TAM

$20.0 billion

Top‑down, revenue‑based estimate for the annual global addressable revenue opportunity for an AI‑driven trading‑predictions + competitive data‑science marketplace used by institutional asset managers and hedge funds. Methodology and inputs: (1) algorithmic trading / execution & SaaS platforms are an immediate addressable market for model deployment and orchestration — market research reports value the global algorithmic trading software market at roughly $17.2 billion (2024). (2) a separate, complementary revenue pool comes from third‑party alpha/model licensing and royalties to buy‑side quant and alternative strategies. Boston Consulting Group reports global AuM of ~$128 trillion (2024); assuming a conservative targetable subset of ~5% of global AuM is actively managed by quant/alternative strategies that would consider external model sourcing (0.05 * $128T = $6.4T) and that these targeted assets allocate a conservative 4 basis points (0.04%) per year to third‑party model licensing/royalties, the licensing pool is estimated at $6.4T * 0.0004 = $2.56 billion annually. Summing the platform/software opportunity ($17.2B) and the model‑licensing pool ($2.56B) yields approximately $19.8B, rounded to $20.0B to reflect estimation uncertainty. Key assumptions are conservative (5% targetable AuM; 4 bps licensing spend); PwC and other industry reports documenting rapid AI/tech adoption and growing alternative‑data budgets support the direction of these assumptions. This TAM is a revenue (annual USD) estimate and intentionally excludes broader consumer fintech AI spend to avoid double counting.

• marketresearch.com
• bcg.com
• pwc.com
• businessinsider.com
• mordorintelligence.com

SAM

$11.2 billion

Serviceable Available Market defined as the portion of the TAM realistically addressable by an early commercial rollout focused on North America + Europe buy‑side (institutional asset managers, hedge funds, multi‑strategy and dedicated quant teams). Methodology and inputs: (A) algorithmic trading / deployment software: use the $17.2B global figure and apply a conservative NA+EU regional share (roughly ~65% of the global market based on published regional breakdowns), producing ~ $11.2B in annual spend on algorithmic trading platforms and software in those regions. (B) add direct third‑party model licensing opportunity inside hedge funds: ETFGI/HFR place global hedge fund AUM at about $4.5T (end‑2024); applying the same 5% targetable fraction (funds/strategies that will source external models = $225.5B) and 4 bps licensing budget yields ~$90M. Combined SAM (NA+EU algorithmic trading software + targeted hedge‑fund licensing) ≈ $11.2B + $0.09B = ~$11.3B, presented here as $11.2B after rounding. Rationale: North America and Europe host the bulk of institutional execution infrastructure and early adopter allocators; QuantConnect and similar platforms demonstrate institutional appetite for platform‑delivered research/licensing. SAM intentionally excludes broader fintech AI use cases (payments, retail roboadvisors, fraud) to avoid overlap with other AI/fintech markets.

• marketresearch.com
• businessresearchinsights.com
• etfgi.com
• quantconnect.com
• pwc.com

SOM

$112 million

Serviceable Obtainable Market (realistic near‑term revenue target for a focused startup in years 3–5) estimated by applying a conservative penetration assumption to the SAM. Assumption and calculation: achieving ~1.0% share of the NA+EU SAM (~$11.2B) within a multi‑year ramp yields $11.2B * 0.01 = $112M annual revenue. Rationale for 1%: marketplaces and model‑licensing platforms (examples: QuantConnect’s Alpha Streams, crowdsourced hedge fund initiatives such as Numerai, plus public evidence of institutional appetite for external model pipelines) show that a specialized, production‑grade marketplace that delivers audited, integrable predictive models and strong governance can capture low‑single‑digit percentages of the addressable software/licensing spend in target verticals over a few years. The $112M figure is a forward‑looking, operational revenue estimate (competition fees, platform commissions, licensing & royalty streams) that assumes successful institutional sales, integrations, and a track record of deployed alpha; it is intentionally conservative and excludes shorter‑term promotional prize payouts and one‑off services. Key risks: institutional procurement cycles, performance persistence, integration and compliance overhead, and competition from incumbent platforms and in‑house quant teams.

• quantconnect.com
• reuters.com
• businessinsider.com
• etfgi.com
• bcg.com