Research Report: KXBTC15M Momentum Strategy

Short Disclaimer

This report presents historical simulation results only. Past performance does not guarantee future outcomes. All analysis is hypothetical and does not represent live trading.

Intro / Thesis

We tested whether a multi-factor momentum filter — combining EMA/SMA crossovers, VWAP alignment, and one-minute price velocity — could improve entry quality on Kalshi’s BTC 15-minute binary options contracts. The base strategy required bullish entries when BTC traded above its 50-period SMA and VWAP, with short-term EMA crossing above SMA, plus positive velocity. Bearish entries required the inverse. A simple price threshold above or below 0.50 determined direction.

Our research question: does adding a momentum stack actually matter, or are simple price-level entries good enough? The results say yes — the momentum filters matter enormously.

Variant and Strategy Explanation

We ran 100 systematic variants of the base strategy, each saved as a runnable Turbine configuration. Across every variant, the core entry logic remained unchanged: momentum-filtered entries using EMA 12 (1m), SMA 20 (1m), SMA 50 (5m), VWAP (1h), and velocity (1m) from Coinbase BTC-USD data. The strategy looped every 10 seconds, checking conditions against the KXBTC15M market on Kalshi.

What varied between runs were two risk parameters:

• Price floor (the minimum acceptable contract price): ranged from 0.05 to 0.45
• Price ceiling (the maximum acceptable contract price): ranged from 0.55 to 0.95

Entry sizing was fixed at 5 contracts per trade with a $5 max position. A stop-loss kicked in at -$2.20 unrealized PnL. Time-based stop-losses triggered when contracts fell below $0.10 with less than one minute to expiry, with final settlement forced at 5 seconds to expiry.

This parameter sweep answered a practical question: how wide should the acceptable price band be for this momentum strategy on 15-minute BTC binaries?

Top Results

The best-performing variants all used wider price bands with lower floors. The top eight variants delivered ROI between 10,846% and 10,957% with Sharpe ratios from 1.47 to 1.49 and remarkably consistent max drawdowns of -15.45%.

Top 8 Variants Summary

Key observations:

• Every top variant used a floor at or below $0.14 and a ceiling between $0.59 and $0.68
• Trade counts were high (1,539–1,557), suggesting these parameters didn't overly restrict opportunity
• Win rates clustered tightly around 61.7–61.9%
• Max drawdown was identical across all top performers (-15.45%), indicating the momentum filter plus stop-loss provided consistent downside control independent of the specific floor/ceiling within this range

The top-ranked variant (floor 0.05, ceiling 0.64) generated $547.87 total PnL over 1,557 trades — meaning the strategy captured meaningful edge even with a tight $5 max position constraint.

Bottom Results

The worst performers were defined not by strategy failure but by parameter choices that choked opportunity. The bottom eight variants all used a floor of 0.45, which severely restricted the number of tradable setups.

Bottom 8 Variants Summary

Key observations:

• Win rates remained strong (61.9–62.3%), confirming the momentum filter itself was still effective
• But trade counts dropped to 1,153–1,239 — roughly 20–25% fewer trades than top performers
• Max drawdown worsened to -22.03% in most cases, as fewer trades meant less opportunity to recover from losses
• ROI fell roughly 35–37% from the top variant, purely from constraining entry prices
• The 0.45 floor meant the strategy only entered when contracts traded at $0.45 or below — for bullish entries, the base rule already required price ≤ 0.50, and this additional constraint eliminated many valid setups

The bottom-ranked variant (floor 0.45, ceiling 0.55) was the most restrictive, with the narrowest band and fewest trades (1,153). Its max drawdown was -18.40% rather than -22.03%, but only because it took so few trades that it avoided some of the loss clusters the other bottom variants experienced.

Conclusion

The momentum-filtered entry approach demonstrated strong historical performance across all 100 variants, with win rates consistently above 61% regardless of floor and ceiling settings. The quality of the entry signal held up — what separated top from bottom was trade frequency, not signal quality.

The clearest finding: lower floors and moderately wide ceilings maximize opportunity without degrading edge. Floors between 0.05 and 0.14 paired with ceilings between 0.59 and 0.68 produced the best risk-adjusted returns. Tightening the floor to 0.45 killed 20–25% of potential trades without improving win rate, and the lost diversification from fewer trades led to deeper drawdowns.

The momentum stack — EMA/SMA crossover plus VWAP alignment plus velocity direction — consistently identified favorable directional setups on 15-minute BTC binaries. The parameters around the stack determine how often you get to use it.

Each successful variant from this sweep has been saved as a runnable Turbine strategy for further analysis or paper trading.

Long Disclaimer

This report describes a historical simulation study conducted on KXBTC15M, a Kalshi binary options contract tied to Bitcoin price movements. All results are hypothetical and backward-looking. The analysis used historical market data and did not involve real capital or live execution.

No representation is made that any strategy discussed here will achieve similar results in the future. Binary options involve significant risk, including the possibility of total loss. Market conditions change. Execution quality, liquidity, fees, slippage, and other real-world factors are not reflected in simulation results.

The variants described are parameter sweeps of a single base strategy. They do not constitute investment advice, trading recommendations, or solicitations to trade any instrument. The performance metrics shown — ROI, Sharpe ratio, max drawdown, win rate, PnL — are derived from simulation output and should not be interpreted as targets or expectations.

Turbine is a research platform. Strategies saved on the platform are for analytical purposes and further testing. Users should conduct their own due diligence before engaging in any trading activity.