prediction-market-strategy Checked

| Strategy | Verdict | Mechanism | Key Catch |

|----------|---------|-----------|-----------|

| Favorite–longshot fade, maker-side | ✅ Durable | Rest maker NO bids on ~$0.05–$0.20 brackets; behavioral tail overpricing | Rare longshot hit; measure fill-rate forward |

| Bracket YES-only (forecast-driven) | ✅ Works, fee-sensitive | Buy YES when calibrated model says bracket is materially underpriced | Requires net_edge > θ gate; not raw win-rate |

| Market-making / liquidity provision | ⚠️ Structurally favored, infra-heavy | Two-sided quotes, capture spread + maker rebates | Inventory risk, adverse selection, queue priority |

| Overround / dutching arbitrage | ⚠️ Real in theory, marginal in practice | Sum-to->$1.00 across brackets; buy the underpriced residual | Legs must fill simultaneously; Kalshi fills are sequential |

| Cross-venue arb (Kalshi ↔ Polymarket) | ❌ Blocked for most | Simultaneous position in equivalent contracts on two venues | Transfer time/cost destroys edge; geo-lock |

| Latency / news front-running (crypto/index hourlies) | ❌ HFT game | React to public feeds before market reprices | Sub-100ms requirement; co-location; not retail |

| Near-certainty intraday repricing | ⚠️ Information/latency edge | Markets slow to reprice near-certain contracts; capture the residual | Requires real-time feed + automation |

| Copy-the-sharps | ❌ Survivorship illusion | Mirror apparent winning accounts | No reliable signal on public data; past winners regress |

**Bottom line:** Two strategies survive correct accounting — the behavioral tail fade (maker-side) and the forecast-driven YES entry past the θ gate. Everything else is either HFT-scale, infrastructure-heavy, or dissolves under correct settlement + fees.

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Fee-Aware Sizing & Edge Gates

All selection is on **fee-adjusted net edge**. Raw win-rate, return on notional, and % correct are not selection metrics.

### Net Edge Formula

net_edge = p_model - ask - kalshi_fee(ask)
# Kalshi taker fee: ceil(0.07 * price * (1 - price) * 100) / 100 per contract
# Polymarket fee: 0 (no explicit taker fee; spread is the cost)

Select a trade only when net_edge > θ.

### Expected-Edge Gate (θ)

| Account size | θ (Kalshi) | Rationale |

|---|---|---|

| < $2,000 | 15% | Small account; fee drag is proportionally higher |

| ≥ $2,000 | 20% | Standard gate covering fee + execution uncertainty |

| Polymarket | ~5% | No explicit taker fee; spread and gas are the cost |

### Limit Price Posting

When placing maker orders, post your bid θ below model fair value:

limit_price_cents = floor((p_model - θ) × 100)

This ensures you only fill when the market moves in your favor by at least θ.

### Fractional-Kelly Sizing

f_star = edge / (1 - entry_price)          # full Kelly fraction
stake = min(kelly_frac * f_star * bankroll, max_bet_fraction * bankroll)
contracts = stake / entry_price
# Defaults: kelly_frac=0.25 (quarter-Kelly), max_bet_fraction=0.015

The 1.5% bankroll cap is the binding constraint for most trades. Quarter-Kelly is aggressive enough to compound but mild enough to survive a bad run of correlated hits.

### Exposure Caps (observed defaults)

| Cap | Value |

|---|---|

| Per-contract bankroll limit | 1.5% of account |

| Single-city / single-event | 5% of account |

| Total open exposure | 20–25% of account |

| Max slippage as fraction of edge | 50% |

### Slippage Is Part of Selection

Walk the **real NO/YES ladder** to your full size to compute the depth-weighted entry price. If the walk pushes net_edge below θ — or slippage exceeds 50% of the edge — skip the trade. Phantom penny levels (≤2¢ asks that don't persist across snapshots and lack trade-print corroboration) must be excluded from the ladder before walking it.

### Maker vs. Taker

Resting a limit order (maker) captures the spread instead of paying it, avoids (or reduces) the taker fee, and is the execution mode used by profitable accounts. The maker edge compounds the structural longshot fade. Market orders (taker) should be used only when the fill probability of a limit order is unacceptably low relative to the opportunity.

All sizing functions are in scripts/sizing.py. Run directly for a worked example.

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Backtesting Methodology

### Cardinal Rule: Settle on the Venue's Own Result

Never re-derive settlement from a third-party source. Use the venue's result field (Kalshi: result: "yes"/"no"; Polymarket: settlement transaction). Any derived truth that merely correlates with the venue's resolution can flip ~10% of outcomes and manufacture double-digit fake edges.

### Method Checklist

• [ ] Use venue result for settlement — never self-computed truth
• [ ] Use close_time (or settlement date from the ticker), not date-of-crawl
• [ ] Decision features cut at the city/event's own local decision time — no UTC mismatch
• [ ] Entry prices from a decision-time snapshot, not near-close prices (which have already converged)
• [ ] Walk the real ladder to your size; cap by top-of-book depth; deduplicate fills
• [ ] Fee-deducted PnL only — never notional
• [ ] Temporal holdout or expanding-window walk-forward only — no shuffled CV
• [ ] Forward paper-trading before live capital: log model p, decision-time ask, and outcome; compare to the backtest Brier/accuracy

### Phantom-Edge Hall of Fame

Each of these produced a plausible-looking backtest that dissolved on closer inspection.

| Bug | Symptom | Fix |

|---|---|---|

| Wrong settlement source | Re-derived truth flipped ~10% of outcomes → fake +18% fade edge | Use venue result |

| Bracket off-by-one | 2°F inclusive brackets {floor,cap} treated as 1°F half-open → **+1640%** phantom backtest | Read contract spec carefully |

| Phantom penny asks | ≤2¢ s