#Definition
Risk management in prediction markets is the practice of controlling potential losses through position sizing, diversification, and disciplined exit strategies. It ensures that no single bad outcome eliminates your ability to continue trading.
Unlike traditional investing where losses are typically partial, prediction markets feature binary outcomes: a losing position goes to zero. This makes risk management not just important but essential for survival. The best forecaster who ignores risk management will eventually go broke.
#Why It Matters in Prediction Markets
Prediction markets present unique risk challenges that demand careful management:
Binary outcomes create total loss scenarios
When a binary market resolves against your position, you lose 100% of that investment. A stock might drop 20%; a losing prediction market position drops 100%. This asymmetry requires smaller position sizes than other investment types.
Overconfidence is the default
Most traders overestimate their forecasting ability. Without risk management, overconfident traders concentrate positions and eventually encounter the inevitable wrong prediction that wipes them out.
Variance is high, even for skilled forecasters
Even a trader with genuine edge faces significant variance. A 70% win rate means losing 30% of the time, and losing streaks will happen. Risk management ensures you survive variance long enough for skill to manifest.
Opportunity cost matters
Capital locked in losing positions can't be deployed to new opportunities. Risk management includes knowing when to exit and redeploy capital more effectively.
#How It Works
#Position Sizing
The most fundamental risk management tool is controlling how much capital goes into any single position.
Fixed percentage rule
Never risk more than X% of your bankroll on a single market:
Maximum Position = Bankroll × Maximum Risk Percentage
Example: With $10,000 bankroll and 5% maximum risk:
Maximum Position = $10,000 × 0.05 = $500 per market
Kelly Criterion approach
The Kelly Criterion provides a mathematically optimal position size based on edge and odds:
Kelly % = (p × b - q) / b
Where:
p = probability of winning (your estimate)
q = probability of losing (1 - p)
b = odds (potential profit / potential loss)
#Kelly Growth Curve
Note: The peak (Full Kelly) maximizes growth but has high variance. Betting more than Kelly (overbetting) rapidly destroys wealth.
For a binary market where you estimate 60% probability and price is $0.50:
b = $0.50 / $0.50 = 1
Kelly % = (0.60 × 1 - 0.40) / 1 = 0.20 or 20%
Most traders use fractional Kelly (25-50% of the Kelly recommendation) to account for estimation error and reduce variance.
#Diversification
Spreading bets across uncorrelated markets reduces the impact of any single loss:
Market diversification
Trade multiple markets rather than concentrating in one:
- Political markets
- Economic indicators
- Sports outcomes
- Entertainment predictions
Time diversification
Spread exposure across different resolution dates rather than having everything resolve simultaneously.
Platform diversification
Using multiple platforms (Polymarket, Kalshi, etc.) reduces platform-specific risk.
#Numerical Example: Portfolio Risk
A trader allocates 1,000 each, with 55% win rate per position.
Worst case (all 10 lose): -1,000 - 4.5 losses × 1,000 Standard deviation: Much lower than a single $10,000 bet
Compare to concentrating $10,000 in one market:
- 55% chance of +$10,000 (100% gain)
- 45% chance of -$10,000 (100% loss)
The diversified approach has the same expected value but far lower risk of ruin.
#Examples
#Example 1: Position Sizing Gone Wrong
A trader with 4,000 in Yes shares at $0.70.
Reality: Their 90% confidence was overestimated (true probability was 65%). They lose $4,000 (80% of their bankroll) on a single market.
Proper risk management would have limited this to 5-10% of bankroll ($250-500), preserving capital for future opportunities.
#Example 2: Diversification in Practice
A trader allocates across:
- 3 political markets (20% each)
- 2 economic indicator markets (10% each)
- 2 sports markets (10% each)
When an unexpected political event causes losses across political markets, the economic and sports positions are unaffected, limiting total portfolio drawdown.
#Example 3: Using Stop Losses
A trader buys Yes at 0.45. When negative news drops the price to $0.45, they exit, accepting a 25% loss rather than holding to resolution and potentially losing 100%.
#Example 4: Kelly Sizing Adjustment
A trader calculates Kelly suggests 25% position size. Recognizing uncertainty in their probability estimate, they use quarter-Kelly (6.25%) instead. This slower growth rate dramatically reduces risk of ruin while still capturing most of the expected value.
#Risks, Pitfalls, and Misunderstandings
Ignoring correlation
Ten "different" markets aren't diversified if they're all correlated. Five political markets in the same election have correlated outcomes; a single event can cause losses across all of them.
Revenge trading after losses
After a loss, some traders increase position sizes to "make it back quickly." This is the opposite of sound risk management and accelerates ruin.
Confusing expected value with safety
A positive expected value position can still be inappropriately large. EV measures average outcome; risk management addresses the range of outcomes.
Neglecting platform risk
Money on a prediction market platform faces counterparty risk. A platform failure, hack, or regulatory action could cause losses independent of market outcomes.
Over-diversification
Too many small positions create transaction cost drag and make it difficult to monitor effectively. Find the balance between concentration risk and spreading too thin.
Assuming past performance predicts variance
A string of wins doesn't reduce future variance. Each new prediction faces full uncertainty regardless of track record.
#Practical Tips for Traders
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Set a maximum position size before looking at any specific market: Decide your rules (e.g., "never more than 5% in one market") before evaluating opportunities. This prevents emotions from overriding discipline
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Track your actual win rate: You can't properly size positions without knowing your true edge. Keep records and calculate your historical accuracy
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Use fractional Kelly: Full Kelly maximizes growth but creates large drawdowns. Most practitioners use 25-50% of Kelly to smooth returns
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Review correlation between positions: Before adding a new position, ask: "If I'm wrong about this, am I also wrong about my other positions?" Correlated bets aren't diversification
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Plan exits before entry: Decide in advance at what price you'll exit if wrong. Writing it down makes you more likely to follow through
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Reserve cash for opportunities: Don't deploy 100% of your bankroll. Holding reserves means you can capitalize on new opportunities and survive unexpected losses
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Accept that losses are inevitable: Even the best traders lose regularly. Risk management isn't about avoiding losses; it's about ensuring losses don't destroy you
#Bankroll Management
The foundation of risk management is protecting your bankroll (total trading capital).
- Rule of Thumb: Never bet more than 1-5% of your bankroll on a single trade.
- Kelly Criterion: A mathematical formula for optimal sizing, but often too aggressive. Use "Half Kelly" for safety.
- Survival First: If you lose 50% of your bankroll, you need a 100% gain to get back to even. Avoid big drawdowns at all costs.
#Related Terms
#FAQ
#What's the biggest risk management mistake in prediction markets?
Oversizing positions based on overconfidence. Most traders are more confident than their accuracy warrants. When that overconfidence meets a wrong prediction and an oversized position, the result is devastating losses. Start with position sizes that feel "too small"; if your forecasting is genuinely good, you'll still profit, just more slowly.
#How is prediction market risk different from stock market risk?
The key difference is binary outcomes. A stock might decline 30% and recover; a prediction market position either pays 0 at resolution. There's no middle ground and no recovery. This makes position sizing more critical; appropriate stock positions (e.g., 10% of portfolio) would be reckless in prediction markets.
#Should I use stop losses in prediction markets?
When available, stop losses can be valuable for limiting losses on positions that move against you before resolution. However, many prediction markets don't offer native stop-loss functionality, and prices can gap past your stop level in fast-moving markets. Consider mental stops (commit to exit at certain price) or position sizing that accepts full loss if necessary.
#How do I know if I'm too concentrated?
Ask: "If my three largest positions all lost, how would I feel? Could I continue trading?" If the answer suggests unacceptable damage, you're too concentrated. A rough guideline: if losing your top three positions would reduce your bankroll by more than 25%, consider reducing concentration.
#Is risk management different for play money vs. real money markets?
The math is identical, but psychological discipline differs. In play money markets, it's tempting to take extreme positions since "it's not real money." However, if you're using play money to develop skills for real money trading, you should practice the same risk management discipline you'd use with real stakes.