Decision Markets

#Definition

A decision market is a prediction market specifically designed to inform a decision by forecasting outcomes contingent on different choices. Rather than predicting what will happen, decision markets predict what would happen if a specific action is taken.

The structure typically involves paired conditional markets: "What will outcome be if we choose Option A?" versus "What will outcome be if we choose Option B?" Decision-makers can then compare market prices to see which option the collective wisdom predicts will produce better results.

#Why It Matters in Prediction Markets

Decision markets represent prediction markets' most practical application: turning forecasting into actionable guidance.

Aggregating dispersed knowledge

Organizations have information scattered across employees, stakeholders, and observers. Decision markets aggregate this knowledge into a single, interpretable signal; which option does the crowd expect to work better?

Reducing agency problems

When employees or consultants advise decisions, they may have biases or conflicts of interest. Decision markets incentivize participants to reveal true beliefs rather than tell decision-makers what they want to hear.

Quantifying uncertainty

Traditional decision-making often relies on point estimates ("this will increase revenue 15%"). Decision markets produce probability distributions, revealing how certain or uncertain the collective is about each option's effects.

Foundation of futarchy

Decision markets are the mechanism underlying futarchy, the governance concept where policy is chosen based on which option markets predict will maximize a defined welfare metric.

#Decision Market Use Cases

#How It Works

#Market Structure

Decision markets require:

1. A decision with discrete options: Option A vs. Option B (or multiple options)
2. A measurable outcome: What will be measured to determine success
3. Conditional markets for each option: "Outcome if A" and "Outcome if B"
4. Resolution mechanism: Only the chosen option's market resolves; others void

#The Decision Process

1. Define the decision with discrete options
2. Specify a measurable success metric
3. Create conditional markets for each option
4. Allow trading to reveal predicted outcomes
5. Select the option with highest predicted success
6. Chosen option's market resolves; others void

#Interface Example

Imagine a dashboard for a corporate decision:

Traders buy "Revenue if Product A" stocks. The price reflects the crowd's revenue forecast contingent on that choice.

#Decision Market Flowchart

/**
 * Evaluates a decision rule based on market prices.
 * 
 * @param priceOptionA - Market price for outcome if Option A chosen
 * @param priceOptionB - Market price for outcome if Option B chosen
 * @param threshold - Minimum difference required to act
 * @returns The recommended option ('A', 'B', or 'Neutral')
 */
function evaluateDecisionRule(priceOptionA, priceOptionB, threshold = 0.05) {
  const diff = priceOptionA - priceOptionB;
  
  if (diff > threshold) return 'A'; // Market strongly favors A
  if (diff < -threshold) return 'B'; // Market strongly favors B
  
  return 'Neutral'; // Difference too small to be decisive
}

// Example: Price A = 0.65, Price B = 0.55
const decision = evaluateDecisionRule(0.65, 0.55);
// Result: 'A' (0.10 diff > 0.05 threshold)

#Numerical Example

A company considers two strategies:

Market A: "Stock price in 12 months if we acquire Company X"

• Current price: $0.75 (implying expected price$75, if shares represent scaled outcome)

Market B: "Stock price in 12 months if we don't acquire"

• Current price: $0.65 (implying expected price$65)

The decision market suggests the acquisition would create value; the market expects 15% higher stock price with the acquisition than without.

Important caveat: The company doesn't have to follow the market. They might have reasons (strategic, ethical, risk-related) to choose differently. The market provides information, not commands.

#Resolution Mechanics

After the decision is made:

• If the company acquires: Market A resolves based on actual stock price; Market B is voided and positions refunded
• If the company doesn't acquire: Market B resolves; Market A is voided

This structure ensures traders bet on outcomes conditional on each option, not on which option will be chosen.

#Examples

#Example 1: Corporate Strategy

A tech company considers launching Product A (new market) vs. Product B (existing market expansion).

Decision markets created:

• "Revenue in 2 years if we launch Product A"
• "Revenue in 2 years if we launch Product B"

Employees from R&D, sales, and operations trade based on their knowledge. Engineering knows Product A has technical risks; Sales knows Product B faces competitive pressure. The market aggregates these insights.

Market prices suggest Product B will generate higher expected revenue. Leadership reviews this alongside other factors and makes their decision.

#Example 2: Policy Evaluation

A city government considers two approaches to traffic congestion:

• "Average commute time if we implement congestion pricing"
• "Average commute time if we expand public transit"

Urban planners, transportation experts, residents, and economists trade based on their knowledge of traffic patterns, behavioral economics, and local conditions.

#Example 3: Personnel Decisions

A company considers promoting Candidate A or Candidate B to VP.

• "Department performance if Candidate A is promoted"
• "Department performance if Candidate B is promoted"

Employees who work with both candidates have information about their leadership styles, competencies, and relationships. The market aggregates this otherwise hard-to-collect information.

#Example 4: Investment Allocation

An investment committee considers allocating to Strategy A (growth stocks) vs. Strategy B (value stocks).

• "Portfolio return if we allocate to Strategy A"
• "Portfolio return if we allocate to Strategy B"

Analysts and portfolio managers trade based on their market views. The resulting prices inform the allocation decision.

#Risks, Pitfalls, and Misunderstandings

Self-fulfilling prophecies

If the decision market predicts Option A will succeed, and decision-makers always follow the market, Option A is always chosen. The market might be "right" simply because it's followed, not because Option A was genuinely better.

Manipulation to influence decisions

If market prices directly determine decisions, participants have incentive to manipulate prices for reasons beyond forecasting accuracy. A stakeholder who prefers Option A might buy its market regardless of true beliefs.

Correlation between choice and outcome

Sometimes the same factors that lead to choosing Option A also affect the outcome. If a strong economy makes the board choose acquisition AND makes the stock price rise, the decision market conflates the choice's effect with broader conditions.

Thin liquidity undermines signal

Decision markets on niche topics may attract few participants. Prices set by a handful of traders may not represent collective wisdom.

Scope of market vs. scope of decision

Markets can only measure specified outcomes. A decision market predicting stock price won't capture effects on employee morale, customer relationships, or strategic positioning that don't immediately affect stock price.

Counterfactual resolution problems

If only the chosen option's market resolves, the other is voided. This means traders never learn if their predictions about the unchosen option were accurate, limiting learning and accountability.

#Practical Tips for Traders

• Separate your preference from your prediction: You might want Option A chosen, but trade based on which option would produce better outcomes if chosen; these are different questions

• Consider who else is trading: Decision markets on corporate issues may have insiders with superior information. Consider whether you have genuine edge

• Account for void probability: The option you're betting on may not be chosen, voiding your position. Factor this into expected return calculations

• Trade the outcome metric, not the decision quality: Markets resolve on specified metrics (stock price, revenue, etc.), not on whether the decision was "good" in broader terms

• Watch for manipulation signals: Large, sudden price movements from single traders may indicate manipulation rather than information. Be skeptical of prices that seem designed to influence rather than forecast

• Provide liquidity on information basis: If you have genuine insight into how an option would affect outcomes, you can profit by trading against manipulators or uninformed traders

#Theoretical Application: Futarchy

The ultimate form of decision markets is Futarchy, a governance system where policy decisions are automatically determined by market prices. If the market predicts that Policy A leads to better national welfare than Policy B, Policy A is enacted.

#Related Terms

• Conditional Market
• Futarchy
• Prediction Market
• Information Aggregation
• Governance
• Skin in the Game

#FAQ

#How is a decision market different from a regular prediction market?

Regular prediction markets forecast what will happen. Decision markets forecast what would happen if a specific choice is made. They use conditional markets where the outcome is contingent on a decision being taken. This structure allows comparison of options before the decision is made.

#Do decision-makers have to follow the market?

No. Decision markets provide information, not commands. Decision-makers can weigh market prices alongside other factors: strategic considerations, risk tolerance, values, information not captured in the outcome metric. Some futarchy proposals would make market-following automatic, but most current decision markets are advisory.

#What happens if I bet on an option that isn't chosen?

Your position is voided, and you receive your original investment back. You neither profit nor lose on the outcome question, since that option was never implemented. This void mechanism is essential; it ensures you're trading on "what would happen if" rather than "what will be chosen."

#Can decision markets be manipulated?

Yes, especially when the market directly influences the decision. Someone who wants Option A chosen might buy its market regardless of true outcome beliefs. Defenses include: treating markets as advisory rather than determinative, monitoring for suspicious trading patterns, and ensuring sufficient liquidity that manipulation is expensive.

#Why would a company use decision markets instead of just asking employees?

Asking employees produces cheap talk; there's no cost to giving inaccurate or biased answers. Decision markets require putting capital (real or play money with reputation stakes) behind beliefs. This filters for genuine conviction, incentivizes research, and aggregates information from people who might not speak up in meetings but do have relevant knowledge.