Chapter 38 Exercises: The Regulatory Landscape

Exercise 1: Jurisdiction Classification

A new prediction market platform wants to offer contracts on weather events, election outcomes, and cryptocurrency prices. For each contract type, identify:

(a) Which US federal agency (CFTC, SEC, or both) would likely claim jurisdiction and why. (b) Whether the contract would qualify as an "event contract" under Dodd-Frank Section 745. (c) Any additional state-level regulatory concerns.

Exercise 2: Howey Test Application

Apply the Howey test to each of the following prediction market products. For each prong, explain whether it is satisfied and why:

(a) A binary contract on whether US GDP growth exceeds 3% in Q3 2026, traded on a CFTC-registered DCM. (b) A tokenized outcome share representing "Yes" on a Polymarket question, tradable on secondary markets. (c) A governance token for a decentralized prediction market protocol that entitles holders to a share of trading fees. (d) A liquidity provider position in an automated market maker pool for prediction market outcomes.

Exercise 3: Regulatory Risk Scoring

Using the regulatory risk model from Section 38.1.4:

$$R = \sum_{j \in J} w_j \cdot \left( P(\text{enforcement}_j) \times L(\text{penalty}_j) \right)$$

Calculate the regulatory risk score for a platform with the following user distribution:

Compare this to a platform that serves only US users through a registered DCM (P(enforcement for violation) drops to 0.05, expected penalty drops to $5M).

Exercise 4: No-Action Letter Analysis

Read the conditions of the PredictIt no-action letter described in Section 38.4.2. Then answer:

(a) Why did the CFTC issue the letter to Victoria University rather than to PredictIt directly? What are the legal implications of this choice? (b) Identify three ways in which PredictIt's actual operations arguably exceeded the scope of the no-action letter. (c) Draft a set of modified conditions that might have allowed PredictIt to continue operating while addressing the CFTC's concerns. (d) If you were advising a new platform seeking a no-action letter today, would you recommend this approach? Why or why not?

Exercise 5: State Gambling Law Analysis

A prediction market platform operates from New York and serves users in all 50 states. Using the three legal tests for gambling (predominant purpose, any chance, material element):

(a) Construct the strongest argument that prediction market trading is a game of skill under each test. (b) Construct the strongest argument that prediction market trading is gambling under each test. (c) Identify which test is most favorable for prediction markets and explain why. (d) How does federal preemption under the CEA affect the state gambling law analysis?

Exercise 6: MiCA Compliance Checklist

You are the compliance officer for a blockchain-based prediction market platform seeking to operate in the EU under MiCA. Create a detailed compliance checklist covering:

(a) CASP licensing requirements and the application process. (b) White paper requirements for outcome tokens. (c) Stablecoin compliance for USDC collateral. (d) Market abuse prevention measures. (e) Consumer protection and disclosure obligations.

For each item, estimate the time and cost to achieve compliance.

Exercise 7: Cross-Border Regulatory Mapping

Map the regulatory requirements for offering a single prediction market contract (e.g., "Will the Federal Reserve raise rates in June 2026?") across the following five jurisdictions:

• United States
• United Kingdom
• European Union (Germany as the reference country)
• Singapore
• Australia

For each jurisdiction, identify: (a) the primary regulator, (b) the applicable regulatory framework, (c) the license or registration required, (d) key compliance obligations, and (e) whether the specific contract is likely permissible.

Exercise 8: DeFi Enforcement Analysis

Consider a fully decentralized prediction market protocol deployed on Ethereum with no identifiable operator, no governance token, and immutable smart contracts. Analyze:

(a) What enforcement tools are available to the CFTC? (b) What enforcement tools are available to OFAC? (c) How could regulators target the front-end interface? (d) What role do stablecoin issuers play in potential enforcement? (e) Is this protocol truly "unregulatable"? Defend your answer.

Exercise 9: KYC/AML Program Design

Design a KYC/AML compliance program for a centralized prediction market platform. Your program should include:

(a) Customer identification procedures (what information to collect, how to verify it). (b) Risk-based due diligence tiers (low-risk, medium-risk, high-risk customers). (c) Transaction monitoring rules (what patterns trigger alerts). (d) SAR filing procedures (when to file, what to include). (e) Sanctions screening procedures (which lists to check, how often).

Write Python pseudocode for the transaction monitoring rules.

Exercise 10: Tax Calculation Comparison

A trader made the following prediction market trades during the tax year:

Calculate the total tax owed under each of the following classifications: (a) Section 1256 contracts (60/40 rule) (b) Short-term capital gains (all treated as short-term) (c) Gambling income (with losses deductible against winnings only)

Assume the trader is in the 37% ordinary income / 20% long-term capital gains bracket.

Exercise 11: Regulatory Timeline Construction

Create a detailed timeline of prediction market regulation in the United States from 2000 to 2025. Include:

(a) At least 10 significant regulatory events (enforcement actions, legislation, court decisions, no-action letters). (b) For each event, describe the impact on the prediction market industry. (c) Identify the three most consequential events and explain why they were pivotal.

Exercise 12: Compliance Checker Implementation

Extend the compliance checker in code/example-01-compliance-checker.py to add the following features:

(a) A "politically exposed person" (PEP) screening function that checks whether a user's name matches a list of known PEPs. (b) A velocity check that flags users who make more than 20 trades in a single hour. (c) A round-number detection function that flags deposits of exactly $1,000, $5,000, or $10,000 (potential structuring indicators). (d) An age verification check that ensures users are at least 18 years old.

Test your implementation with sample data.

Exercise 13: Regulatory Arbitrage Analysis

Platform A is registered as a DCM in the US. Platform B operates from an unregulated offshore jurisdiction. Compare:

(a) Compliance costs (estimated annual cost for Platform A's regulatory obligations vs. Platform B's minimal costs). (b) Market access (which types of users each platform can and cannot serve). (c) Contract flexibility (what types of contracts each platform can offer). (d) Trust and credibility (how institutional users and media perceive each platform). (e) Long-term viability (which platform is more likely to survive a regulatory crackdown).

Exercise 14: Wire Act Analysis

A US-based user places a prediction market trade through a platform hosted in Malta. The trade is transmitted over the internet and involves a contract on the outcome of a state legislative election.

(a) Does the Federal Wire Act apply to this transaction? Analyze under both the 2011 and 2018 DOJ interpretations. (b) How does the platform's CFTC registration status (if any) affect the analysis? (c) If the platform is not CFTC-registered, what criminal liability might the user face? (d) What about the platform operator?

Exercise 15: Section 1256 vs. Gambling Treatment

Write a Python function that takes a list of prediction market trades and calculates the tax difference between Section 1256 treatment and gambling treatment. Use the following tax rates:

• Ordinary income: 37%
• Short-term capital gains: 37%
• Long-term capital gains: 20%
• Section 1256 blended rate: 0.6 * 20% + 0.4 * 37% = 26.8%

The function should output the total tax under each treatment and the dollar difference.

Exercise 16: Sanctions Screening Simulation

Using the OFAC SDN list (or a simplified mock version), implement a sanctions screening system that:

(a) Accepts a user's name, date of birth, and nationality. (b) Performs fuzzy matching against the SDN list (accounting for spelling variations, transliterations, and aliases). (c) Returns a risk score from 0 to 100. (d) Escalates matches above a threshold for manual review.

Discuss the trade-offs between false positives (blocking legitimate users) and false negatives (missing sanctioned individuals).

Exercise 17: Event Contract Classification

Classify each of the following proposed prediction market contracts as: (a) clearly permissible, (b) likely permissible, (c) uncertain, (d) likely impermissible, or (e) clearly impermissible under current US law. Justify each classification.

1. "Will the S&P 500 close above 5,500 on March 31, 2026?"
2. "Will the US Senate pass a carbon tax bill by December 2026?"
3. "Will a Category 5 hurricane make landfall in Florida in 2026?"
4. "Will a specific named individual die before January 1, 2027?"
5. "Will Country X launch a military invasion of Country Y?"
6. "Will the Academy Award for Best Picture go to Film Z?"
7. "Will the US unemployment rate exceed 5% in Q4 2026?"
8. "Will a specific drug receive FDA approval by June 2026?"
9. "Will there be a terrorist attack in the US in 2026?"
10. "Will the Bitcoin price exceed $200,000 on December 31, 2026?"

Exercise 18: Regulatory Sandbox Proposal

Draft a proposal for a CFTC regulatory sandbox program specifically for prediction markets. Your proposal should include:

(a) Eligibility criteria for participating platforms. (b) Permitted activities and limitations during the sandbox period. (c) Consumer protection safeguards. (d) Reporting and transparency requirements. (e) Criteria for "graduating" from the sandbox to full DCM registration. (f) Duration and renewal provisions.

Exercise 19: Geofencing Effectiveness Analysis

A prediction market platform implements the following geofencing measures:

• IP address geolocation blocking for restricted jurisdictions
• VPN detection using a commercial database
• ID verification requiring a government-issued document with address

(a) Estimate the effectiveness of each measure individually (what percentage of restricted users would it block?). (b) Estimate the combined effectiveness when all three are used together. (c) Identify three methods that a determined user could use to circumvent all three measures. (d) What additional measures could the platform implement to improve geofencing? (e) At what point does the platform's duty to geofence end? Can it be held liable for sophisticated circumvention?

Exercise 20: Multi-Jurisdiction Tax Optimization

A prediction market trader has dual UK/US citizenship and trades on platforms in both jurisdictions. In a given tax year, the trader has:

• $50,000 in gains on a US DCM-registered platform
• GBP 30,000 in gains on a UK gambling platform
• $20,000 in losses on a non-US crypto prediction market

(a) Calculate the tax owed under US law (assuming Section 1256 treatment for the DCM gains). (b) Calculate the tax owed under UK law (assuming gambling treatment for the UK gains). (c) How does the US-UK tax treaty affect the analysis? (d) Can the trader use the non-US platform losses to offset the US gains? Under what conditions? (e) What record-keeping obligations does the trader have in both jurisdictions?

Exercise 21: Compliance Cost-Benefit Analysis

A startup prediction market platform is deciding between three regulatory strategies:

Strategy A: Full DCM registration in the US (estimated cost: $5M upfront + $2M/year). Strategy B: Operate offshore with no US users (estimated cost: $200K upfront + $100K/year). Strategy C: Decentralized protocol with no central operator (estimated cost: $1M development + $50K/year maintenance).

For each strategy, analyze: (a) Addressable market size (estimated number of potential users and trading volume). (b) Revenue potential (estimated annual revenue at maturity). (c) Regulatory risk (probability and expected cost of enforcement action). (d) Operational complexity (staffing, technology, and legal requirements). (e) Calculate the expected net present value (NPV) of each strategy over 5 years using a 15% discount rate.

Exercise 22: Comparative Regulatory Analysis

Compare the regulatory approaches to prediction markets in the US, EU, and Singapore along the following dimensions:

(a) Definitional approach: How does each jurisdiction define the products offered by prediction markets? (b) Licensing requirements: What licenses or registrations are required? (c) Consumer protection: What consumer protection measures are mandated? (d) Enforcement philosophy: Is the approach rules-based, principles-based, or risk-based? (e) Innovation friendliness: How accommodating is each regime to prediction market innovation?

Create a comparative matrix summarizing your findings.

Exercise 23: Smart Contract Audit for Compliance

You are asked to audit a prediction market smart contract for regulatory compliance. The contract:

• Accepts ETH deposits as collateral
• Creates binary outcome tokens
• Settles based on an oracle feed
• Charges a 2% fee to the contract deployer
• Has no KYC, geofencing, or access controls

(a) Identify all regulatory compliance gaps. (b) For each gap, propose a technical solution that could be implemented at the smart contract level. (c) For each gap, propose a solution that could be implemented at the front-end level. (d) Are there compliance requirements that cannot be addressed technically and require legal/structural solutions? (e) Draft a compliance risk report for the protocol's governance body.

Exercise 24: Prediction Market for Regulation

Design a prediction market that forecasts regulatory outcomes for the prediction market industry itself. Specifically:

(a) Propose 5 specific contracts that would be valuable for industry participants (e.g., "Will the CFTC approve a new DCM for event contracts by December 2026?"). (b) For each contract, identify who would be natural buyers and sellers. (c) Analyze whether these contracts themselves would face regulatory challenges (can you legally trade on regulatory outcomes?). (d) Discuss the "self-referential" problem: if the market predicts its own regulation, does this create feedback loops?

Exercise 25: Comprehensive Compliance Framework

You are the General Counsel of a prediction market platform preparing for launch. The platform will be centralized, US-based, and seek DCM registration. Design a comprehensive compliance framework that addresses:

(a) Federal regulatory compliance (CFTC, FinCEN, OFAC). (b) State regulatory compliance (gambling laws, money transmitter licensing). (c) International user management (geofencing, cross-border compliance). (d) Tax reporting obligations (to users and to the IRS). (e) Data privacy compliance (GDPR for EU users, CCPA for California users). (f) Cybersecurity and system safeguards (CFTC system safeguards requirements). (g) Market surveillance and manipulation prevention. (h) Incident response procedures (regulatory inquiries, enforcement actions, data breaches).

For each area, identify the key requirements, the responsible team or role, the estimated cost, and the timeline for implementation.