Test anti-speculation regulations before they harm Brazilian markets
Investors and the public repeatedly misunderstand the necessary role of speculation in markets, leading to fear-driven reactions and regulations after crashes like 1929 and 2008
RegSpec provides policymakers and analysts with a modeling tool to predict outcomes of proposed regulations targeting speculation, using historical precedents from 1929, 2008, and Brazilian crises. It highlights unintended consequences and demonstrates speculation's role in price discovery and liquidity.
Brazilian investors, financial professionals, and policymakers following economic history
Pre-loaded econometric models validated against actual outcomes of past Brazilian regulations (IOF tax changes, circuit breakers, etc.) with one-click comparison to real historical results.
objective and data-driven
No-code interface to define rules on leverage, derivatives, short-selling etc
20+ validated models from past Brazilian and global regulatory interventions
Runs Monte Carlo style simulations across multiple economic scenarios
Visualizes impacts on liquidity, volatility, capital formation and innovation proxies
Creates professional PDF briefs with citations and historical comparisons
Compare your regulation against what actually happened in past similar rules
Breaks down effects on retail investors, institutions, and government revenue
Real-time editing and commenting for policy teams
Test how robust outcomes are to different assumptions
Train on user simulations to improve future predictions
| Column | Type | Nullable |
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| id | uuid | No |
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| organization | text | Yes |
| role | text | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
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| id | uuid | No |
| name | text | No |
| crisis | text | No |
| regulation_description | text | No |
| actual_outcomes | text | No |
| model_parameters | text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| base_model_id | uuid | Yes |
| regulation_parameters | text | No |
| results | text | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
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| id | uuid | No |
| user_id | uuid | No |
| simulation_id | uuid | No |
| title | text | No |
| content | text | Yes |
| generated_at | timestamp | No |
Relationships:
/api/simulateRun economic impact simulation for a proposed regulation
/api/modelsRetrieve historical regulatory models
/api/reportsGenerate policy report from simulation results
/api/benchmarkCompare proposed rule against actual historical regulation outcomes
3 simulations/month
None
Custom
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 95 | 18% | $376 | $4,512 |
| Month 6 | 680 | 21% | $3,160 | $37,920 |
Model the real impact of anti-speculation rules using Brazil's own economic history before they become law.
Direct outreach to 40 economic advisors and analysts working with Brazilian Congress members and CVM using LinkedIn Sales Navigator, offering free Enterprise trials with personalized onboarding. Partner with two major Brazilian think tanks (FGV and IBRE) to co-host webinars demonstrating the tool on current hot regulatory topics. Present the platform to the Brazilian Association of Financial Institutions (ABBC) policy committee.
Very sophisticated global economic models
Not focused on speculation specifically or Brazilian regulatory history
Purpose-built for speculation regulation questions with Brazilian data
Strong development economics focus
Too general, complex interface, not tailored for rapid policy testing
Simple no-code interface designed for busy Brazilian policymakers
Dataset of validated Brazilian regulatory intervention outcomes that grows more accurate as more policymakers use and validate the models.
Brazil is currently debating multiple new rules around crypto, offshore investments, and market circuit breakers while memories of past regulatory mistakes are still fresh after the 2022-2023 volatility.
Policymakers slow to adopt new tools
Start with think tanks and academics who influence policy, then move up to government users
Models perceived as overly simplistic
Partner with Brazilian economists for initial model validation and publish methodology transparently
Being seen as trying to influence regulation
Position strictly as educational and simulation tool with strong disclaimers
Success: Clear demand for such a tool and feedback on most useful historical cases
Success: At least 70% say they would use it regularly for their work
Success: First 3 paid Enterprise customers and 15 Pro users
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