Research Report: EMA/SMA Crossover on KXBTC15M

1. Short Disclaimer

This report presents historical simulation results only. Past performance does not guarantee future outcomes. All strategies shown lost money. Nothing here is a trade recommendation.

2. Intro / Thesis

We tested a simple thesis: 1-minute BTC spot EMA/SMA crossovers on Coinbase can predict short-term direction in Kalshi’s 15-minute Bitcoin binary (YES/NO) contracts. A bullish crossover (12-period EMA crosses above 20-period SMA) signals a YES entry. A bearish crossover (SMA above EMA) signals a NO entry. Exit conditions include opposite crossover, two minutes remaining until expiry, or a $5 stop-loss.

We ran 100 parameterized variants of this core logic to see if any calibration could extract an edge. The results are conclusive, and not in a good way.

3. Variant and Strategy Explanation

Market: Kalshi KXBTC15M — 15-minute binary contracts on Bitcoin price movement.
Data Source: Coinbase BTC-USD 1-minute candles, providing 12-period EMA and 20-period SMA refreshed every 10 seconds.
Base Rules:

• Enter long YES when EMA > SMA, time to expiry exceeds 5 minutes, spread is under $0.03, and position is flat.
• Enter long NO when SMA > EMA under the same guard conditions.
• Exit on opposite crossover, time hitting the 2-minute mark, or unrealized PnL reaching -$5.
• Position size fixed at 5 contracts per entry.

Variant Space: All 100 variants preserved the crossover thesis but modified parameters such as lookback periods, entry timing thresholds, spread filters, position sizing, and exit triggers. Each successful simulation was saved as a runnable Turbine strategy. Every single one lost money.

4. Top Results

The "best" variants were simply the ones that lost the least. Here are the top eight:

A few things stand out. Win rates cluster around 3.4–3.7%, which is catastrophically low for a binary outcome where random guessing would yield roughly 50%. The drawdowns closely track total losses, meaning these strategies bleed steadily with no recovery. Variants within each cluster are behaviorally identical (mirroring parameter symmetries), so the effective number of truly distinct outcomes is much smaller than 100. All Sharpe ratios are zero — not negative, but zero — because there was never a risk-free excess return period to even calculate meaningful risk-adjusted returns against.

5. Bottom Results

The worst performers lost even more, faster:

ROI percentages range from -518% to -2,903%, which makes sense given small account equity assumptions against steady losses. The bottom variants took more trades (1,090–1,098 vs. ~1,016 for the top), typically because relaxed entry filters let them trigger more frequently. More trades meant more exposure to the same broken edge, accelerating the drawdown.

Win rates in the bottom group actually look slightly higher than the middle of the pack (3.6% vs. 3.4%), illustrating that win rate alone tells you nothing useful here. Every variant's win rate is so far below 50% that the strategy is essentially an anti-signal — if you flipped every trade, you'd have a 96% win rate and a massive profit. The crossover thesis is not just weak; it is directionally inverted versus the 15-minute settlement outcome.

6. Conclusion

No variant of the 1-minute EMA/SMA crossover strategy on Coinbase BTC-USD showed any predictive power for KXBTC15M contracts. Win rates between 3.4% and 3.7% across 100 variants and over 1,000 trades each represent a deeply anticorrelated signal. The stop-loss and time-exit rules did not salvage performance. Drawdowns were essentially total capital depletion.

The takeaway is straightforward: a 1-minute technical signal on spot BTC does not translate to a 15-minute binary options edge in this venue over the period tested. If anything, the crossover was a consistent contrarian indicator. Future research in this market should look elsewhere for an edge. As always, each completed variant is preserved as a runnable Turbine strategy for archival and audit purposes.

7. Long Disclaimer

This document is a historical simulation research report produced for internal analytical purposes. All performance figures are backward-looking and derived from completed simulations over past market data. No live trading occurred, and no actual capital was at risk.

Simulated results do not account for real-world execution factors including, but not limited to: order book depth, partial fills, latency, exchange fees, Kalshi-specific contract settlement mechanics, or market impact. The strategies described are not investment advice, do not constitute a solicitation to trade, and should not be interpreted as predictions of future performance.

All 100 variants tested lost money in simulation. Past simulation losses do not preclude future losses. Trading binary options and cryptocurrencies involves substantial risk of total loss. Turbine makes no representation that any strategy — whether saved, shared, or deployed — will be profitable. Use at your own risk.