Binary vs Scalar vs Index Markets

Choosing the Right Market Type for Your Edge

Prediction markets come in three fundamental structures: binary (YES/NO), scalar (range buckets), and index (composite metrics). Each has distinct payoff mechanics, risk profiles, and optimal use cases. Your forecasting edge determines which market type offers the best risk-adjusted returns.

This module compares all three market types, explains when to use each, and teaches you how to match your analytical advantage to market structure.

Binary Markets: Directional Simplicity

Structure

Two outcomes: YES or NO Threshold: Single cutoff value Payout: $1 if your outcome occurs, $0 if it doesn't

Example: "Will Port of Los Angeles exceed 900,000 TEUs in December 2024?"

• YES pays $1 if ≥900,001 TEUs
• NO pays $1 if ≤900,000 TEUs

When to Use Binary Markets

Scenario 1: Strong Directional View, Uncertain Magnitude

You believe LA Port will have strong December (holiday imports), but you're unsure if 920k, 940k, or 960k TEUs.

Binary Strategy: Trade "Will LA exceed 900k?" (YES)

• You don't need to predict exact value, just that it's above 900k
• Forecast of 920k and forecast of 960k both win equally

Scenario 2: Clear Threshold with Real-World Significance

"Will Panama Canal transits fall below 950 in January?" (drought restrictions)

• 950 is meaningful threshold (below indicates severe capacity constraint)
• Market is event-driven (will restrictions ease or persist?)

Scenario 3: Better Liquidity in Binary Format

Major ports and chokepoints often have more trading activity in binary markets (YES/NO on thresholds) than scalar buckets. Tighter spreads mean lower transaction costs.

Binary Market Advantages

1. Simplicity: One threshold to analyze, clear win/loss
2. Liquidity: Concentrated trading (not fragmented across buckets)
3. Lower cognitive load: Easier to forecast "above/below" than exact range
4. Forgiving on precision: Being right by 1 TEU or 100,000 TEUs pays the same

Binary Market Limitations

1. No magnitude differentiation: Can't profit from precision (920k pays same as 1.1M if threshold is 900k)
2. Binary risk: All-or-nothing (miss threshold by 1 unit, lose 100%)
3. Can't trade volatility: Can't express views on wide vs narrow outcomes
4. No hedging within market: Can't buy multiple brackets for insurance

Scalar Markets: Precision Rewarded

Structure

Multiple buckets: Typically 3-5 outcome ranges Two boundaries per bucket: Lower and upper thresholds Payout: $1 if outcome lands in your bucket, $0 otherwise

Example: "Port of Charleston December 2024 TEU Volume"

| Bucket | Range | Price | Implied Probability | |--------|-------|-------|---------------------| | Low | 200k-240k | $0.15 | 15% | | Medium | 240k-280k | $0.50 | 50% | | High | 280k-320k | $0.30 | 30% | | Very High | 320k+ | $0.05 | 5% |

Buying Medium Bucket at $0.50:

• Win if Charleston handles 240k-280k TEUs (anywhere in range)
• Lose if fewer than 240k or more than 280k

When to Use Scalar Markets

Scenario 1: Precise Magnitude Forecast

Your analysis: Houston Port December = 285,000 TEUs (±10k confidence interval)

Scalar Strategy: Buy 280k-300k bucket

• Your forecast sits in middle of bucket (safety margin on both boundaries)
• Precision edge translates to profit (binary market wouldn't capture this)

Scenario 2: Volatility Views

You believe Suez Canal transits will be either very high (over 1,900) or very low (under 1,600), but unlikely in middle (1,700-1,800).

Scalar Strategy: Buy both tail buckets (under 1,600 + over 1,900)

• Express view that distribution is wide (bimodal), not narrow
• If market prices middle buckets expensively, you profit from tails

Scenario 3: Spread Trades Between Buckets

Market prices two adjacent buckets irrationally:

• 240k-280k bucket at $0.55 (expensive)
• 280k-320k bucket at $0.30 (cheap)

Scalar Strategy: Sell 240k-280k, buy 280k-320k (spread trade)

• Profit from relative mispricing without taking directional risk
• Only lose if outcome is in overpriced bucket

Scalar Market Advantages

1. Magnitude matters: Precision in forecasting is rewarded
2. Multiple entry points: Can buy several buckets to hedge precision risk
3. Volatility trading: Express views on distribution width
4. Spread opportunities: Trade relative value between buckets

Scalar Market Limitations

1. Precision risk: Two boundaries to miss (vs binary's one threshold)
2. Fragmented liquidity: Each bucket has separate order book (wider spreads)
3. Higher cognitive load: Must forecast exact range, not just direction
4. Complexity: More buckets = more analysis required

Index Markets: Thematic Diversification

Structure

Composite metric: Weighted average of multiple components Index value: Normalized to 0-150 scale (baseline=100) Buckets: Scalar-like structure applied to index value

Example: "Trans-Pacific Supply Chain Index — December 2024"

Components:

• LA Port TEUs (35% weight)
• Long Beach TEUs (30% weight)
• Shanghai outbound TEUs (25% weight)
• Freight rate index (10% weight)

Index Calculation:

Index = (LA_normalized × 0.35) + (LB_normalized × 0.30) + (Shanghai_normalized × 0.25) + (Freight_normalized × 0.10)

Buckets (scalar structure on index value):

| Bucket | Index Range | Price | |--------|-------------|-------| | 75-100 | Below baseline | $0.20 | | 100-125 | Above baseline | $0.55 | | 125-150 | Well above baseline | $0.25 |

When to Use Index Markets

Scenario 1: Systemic Theme, Not Tactical View

You believe Trans-Pacific trade will strengthen broadly (holiday demand surge) but don't have strong views on LA vs Oakland specifically.

Index Strategy: Buy 100-125 bucket (above-baseline index)

• Captures entire supply chain in one position
• Diversifies away single-port noise (e.g., LA labor strike doesn't ruin trade)

Scenario 2: Component Correlation is Moderate

If LA, Long Beach, Shanghai, and freight rates have correlation 0.5-0.7:

• They move together somewhat (shared trade trend)
• But not perfectly (local factors differ)
• Index smooths out single-component volatility while capturing theme

Scenario 3: Simplifying Multi-Component Exposure

Instead of managing 4 separate positions (LA, LB, Shanghai, freight), one index position gives thematic exposure with less capital and fewer trades (lower transaction costs).

Index Market Advantages

1. Diversification: Single-component shocks are dampened
2. Thematic exposure: Capture broad trends without tactical precision
3. Lower volatility: Composite metric is smoother than individual components
4. Simplified management: One position vs multiple

Index Market Limitations

1. No tactical control: Can't overweight LA if you think it outperforms LB
2. Diluted edge: If your edge is specific component, index waters down signal
3. Opacity: Must understand component weights and correlations
4. Liquidity varies: Flagship indices are liquid; custom indices are not

Decision Framework: Which Market Type to Trade?

Step 1: Assess Your Edge

Question: What is your analytical advantage?

Directional Edge ("Port will be strong/weak") → Binary markets

• Example: "LA will exceed 900k" (YES)
• You don't need magnitude precision

Magnitude Edge ("Port will be 920k ±15k") → Scalar markets

• Example: Buy 900k-950k bucket
• You have precise forecast, can profit from it

Thematic Edge ("Trans-Pacific trade broadly up") → Index markets

• Example: Buy Trans-Pacific Index 100-125 bucket
• You have systemic view, not component-specific

Volatility Edge ("Outcome will be extreme, not middle") → Scalar markets (buy tails)

• Example: Buy under-1,600 + over-1,900 Suez buckets
• Express distribution view

Relative Value Edge ("LA overpriced vs LB") → Component markets (spread trade)

• Example: Sell LA binary YES, buy LB binary YES
• Don't use index (hides relative mispricing)

Step 2: Check Liquidity and Spreads

If spreads are wide (over 8%) → trade market type with best liquidity

• Usually binary markets for major ports/chokepoints
• Scalar and index markets have fragmented liquidity

If spreads are narrow (2-4%) → trade market type matching your edge

• Liquidity is adequate; choose based on strategy

Step 3: Match Confidence to Structure

High confidence + broad forecast range → Binary

• Example: "95% sure LA exceeds 900k, but could be 920k or 1.05M"
• Binary forgives magnitude uncertainty

High confidence + narrow forecast range → Scalar

• Example: "85% sure Charleston is 270k-290k"
• Scalar rewards precision

Moderate confidence + systemic view → Index

• Example: "70% sure Trans-Pacific strengthens overall"
• Index diversifies away single-component risk you're uncertain about

Worked Example: Same Forecast, Three Market Types

Forecast: Oakland Port December 2024 will handle 225,000 TEUs (vs historical avg of 210k)

Option 1: Binary Market

Market: "Will Oakland exceed 220k TEUs?"

• YES price: $0.52
• NO price: $0.48

Your View: 225k forecast → YES (above 220k threshold)

Trade: Buy YES at $0.52

Payoff:

• If ≥220,001 TEUs: $1 payout → $0.48 profit (92% return)
• If ≤220,000 TEUs: $0 → $0.52 loss (100% loss)

Win Probability: High (5k TEU margin of safety above threshold)

Best if: You're confident about direction (above 220k) but uncertain if 225k, 230k, or 240k.

Option 2: Scalar Market

Market: "Oakland December TEU Buckets"

| Bucket | Range | Price | |--------|-------|-------| | Low | 180k-210k | $0.25 | | Medium | 210k-240k | $0.58 | | High | 240k+ | $0.17 |

Your View: 225k forecast → Medium bucket

Trade: Buy Medium at $0.58

Payoff:

• If 210k-240k TEUs: $1 payout → $0.42 profit (72% return)
• If under 210k or over 240k: $0 → $0.58 loss (100% loss)

Win Probability: High (15k margin on both boundaries)

Best if: You have precise 225k forecast and want to profit from that precision (binary doesn't reward being exactly right).

Option 3: Component of Index Market

Market: "West Coast Port Index — December 2024"

• Components: LA (40%), Oakland (25%), Long Beach (20%), Seattle (15%)
• Oakland normalized value if 225k: (225k / 210k baseline) × 100 = 107

Your View: Oakland will outperform (107), but uncertain about LA/LB/Seattle

Index Calculation (if other ports are 100-105):

Index = (102 × 0.40) + (107 × 0.25) + (103 × 0.20) + (100 × 0.15) = 103.1

Trade: Buy Index 100-110 bucket at $0.50

Payoff:

• If index 100-110: $1 payout → $0.50 profit (100% return)
• Oakland's 107 contributes 25% to index (diluted)

Best if: You think entire West Coast will be strong (not just Oakland). Index diversifies away Oakland-specific risk (e.g., labor strike at Oakland doesn't kill entire position).

Comparison

| Factor | Binary | Scalar | Index | |--------|--------|--------|-------| | Edge Type | Directional | Magnitude | Thematic | | Cost | $0.52 | $0.58 | $0.50 | | Max Profit | $0.48 (92%) | $0.42 (72%) | $0.50 (100%) | | Precision Required | Low (just greater than 220k) | High (210k-240k range) | Medium (diversified) | | Single-Port Risk | 100% exposed to Oakland | 100% exposed to Oakland | 25% exposed to Oakland |

Best Choice: If your edge is specifically Oakland forecast (225k), trade scalar (rewards precision). If uncertain about Oakland but bullish on West Coast broadly, trade index. If you only know "Oakland strong" but not exact magnitude, trade binary.

Common Mistakes

Mistake 1: Trading Scalar When Edge is Directional

Problem: You think LA Port will be "strong" but buy 900k-950k scalar bucket without precise forecast.

Why It Fails: If LA hits 960k (still strong, you're right directionally), you lose (outcome outside bucket). Binary YES greater than 900k would've won.

Solution: Match precision of forecast to market type. Directional edge → binary. Precise forecast → scalar.

Mistake 2: Trading Index When Edge is Component-Specific

Problem: You have strong Oakland-specific forecast (labor productivity up 20%) but trade West Coast Index (Oakland only 25% weight).

Why It Fails: Index dilutes your edge. Oakland outperforms but other ports drag index down.

Solution: Trade component directly if edge is specific. Use index only for thematic, not tactical, views.

Mistake 3: Over-Precision in Low-Data Environments

Problem: You forecast Charleston 270k-280k bucket but historical data has ±15k monthly volatility.

Why It Fails: 10k bucket width is too narrow relative to noise. You'll miss bucket due to randomness, not forecast error.

Solution: Match bucket width to forecast confidence interval. If forecast is 270k ±20k, don't buy 10k-wide bucket.

Ready to Apply What You've Learned?

Turn knowledge into action.

Start Trading on Ballast Markets →

Compare binary, scalar, and index markets side-by-side on real ports and chokepoints. Choose the market structure that matches your analytical edge.

Next Steps

Continue Learning:

• Binary vs Scalar Markets (Deep Dive) — Advanced strategies for each type
• Index Basket Construction — Build custom indices
• Position Sizing — Size differently for binary vs scalar risk profiles

Practice Exercises:

1. Given forecast "LA Port 950k ±30k," choose binary (greater than 900k), scalar (900k-1M bucket), or pass (uncertainty too high)
2. Calculate index value from 4 components, determine which bucket it falls in
3. Compare expected value of binary vs scalar trade on same forecast

Try on Ballast Markets:

• Port of Los Angeles — Compare binary and scalar markets on same port
• Suez Canal — Trade volatility using scalar buckets
• Trans-Pacific Index — Thematic exposure to supply chain

Disclaimer

This content is for informational purposes only and does not constitute investment advice, financial advice, trading advice, or recommendations. Market conditions can change rapidly. Always conduct your own research and consult with qualified professionals before making trading decisions.