Prop Firm Market Research

Step-by-Step Process

Phase 1: Define the Research Frame

1. Clarify the strategic question — what decision will this research inform?
2. Identify the 3-5 data points that would change the decision if different
3. Set boundaries — what's in scope, what's explicitly out

Phase 2: Ecosystem Mapping

1. Prop Firm Landscape: Map active prop firms by:
   • Challenge fee structure ($25–$999+)
   • Payout splits and scaling plans
   • Platform support (MT4, MT5, cTrader, TradingView, DXtrade, Match-Trader)
   • Geographic concentration (US futures vs global forex)
   • Estimated trader volume
2. Trader Demographics: Profile the target customer:
   • Geographic distribution (Southeast Asia, Middle East, Africa emerging fast)
   • Experience level (mostly 1-3 years, some beginners chasing funded accounts)
   • Average monthly spend on challenges ($200-800/mo for serious traders)
   • Platform preferences by region
   • Pain points ranked by severity
3. Adjacent Markets: Identify expansion opportunities:
   • Crypto prop firms (emerging, less regulated)
   • Futures prop firms (Apex, TopStep — different mechanics)
   • Signal/copy trading services
   • Trading education platforms (overlap audience)

Phase 3: Quantitative Analysis

1. Market Sizing (TAM/SAM/SOM):
   • TAM: Total global prop firm traders × average annual challenge spend
   • SAM: Traders on supported platforms (MT4/MT5/cTrader) who actively hedge
   • SOM: Realistically acquirable within 12 months given current channels
2. Economics Modeling:
   • Average prop firm challenge: $300-500 fee, 80% fail Phase 1, ~5% get funded
   • Hedge Edge value per user: (challenges_per_month × fee × recovery_rate) - subscription_cost
   • Break-even analysis: At what recovery rate does Hedge Edge pay for itself?
3. Growth Rates: Prop firm industry CAGR, regional growth differentials

Phase 4: Trend Identification

1. Regulatory Trends: Which jurisdictions are cracking down on prop firms? Which are favorable?
2. Technology Trends: Platform fragmentation (DXtrade, Match-Trader adoption), cloud vs local execution shift
3. Pricing Trends: Race to the bottom on challenge fees? Premium tier emergence?
4. Behavioral Trends: Are traders getting savvier about hedging? Is hedging becoming mainstream or staying niche?

Phase 5: Synthesis & Recommendations

1. Distill findings into 3-5 "so what" insights that directly impact Hedge Edge strategy
2. Assign confidence levels (high/medium/low) to each finding
3. Flag any findings that contradict current assumptions
4. Recommend specific follow-up research or experiments

Execution Scripts

• market_research_scraper.py — Scrapes and aggregates prop firm data from public sources
• market_sizing_calculator.py — TAM/SAM/SOM calculation model with configurable assumptions

Resources

• hedge-edge-business-context.md — Complete Hedge Edge business context (product, pricing, positioning, tech stack)
• prop-firm-directory.json — Database of major prop firms with key attributes

Definition of Done

• Research question is clearly stated and bounded
• At least 3 quantified data points are provided (with sources or estimation methodology)
• Findings are connected to specific Hedge Edge strategic decisions
• Confidence levels assigned to each major finding
• Output matches requested format (brief/report/data-pack)
• Contradictions with current assumptions are explicitly flagged

Error Handling