ETH Kalshi 15-Minute Momentum

Short Disclaimer

This is a historical simulation report for educational and informational purposes only. It does not constitute financial advice, a recommendation, or a guarantee of future results. Past performance does not predict future outcomes.

Intro / Thesis

We set out to test whether momentum-based overextension in Ethereum’s 15-minute up-or-down markets on Kalshi could be systematically captured. The hypothesis was straightforward: when ETH spot price momentum lifts the “yes” price but remains within a reasonable valuation band, we can consistently harvest short-term directional edges before the 15-minute settlement. The sweep of 100 completed variants was designed to validate this thesis and to identify the most robust configuration of entry sensitivity and risk guardrails.

We wanted to understand whether a simple rule—buying yes contracts when Coinbase ETH price clears its 1‑hour VWAP and registers a positive 15‑minute change, then exiting when the signal fades or the contract gets expensive—would produce durable returns that persist across small parameter changes. The results argue that the edge is real in this historical dataset.

Variant and Strategy Explanation

The core strategy remains the same across all 100 variants. At a 30‑second loop interval, the system checks two conditions drawn from a Coinbase edge feed: (1) the current ETH-USD spot price must be above the trailing 1‑hour VWAP, and (2) the 15‑minute change in spot price must exceed a configurable momentum threshold. If both conditions are true and the Kalshi yes-price sits below 75 ¢, the strategy enters a new long position with a fixed size of 1 contract. The exit logic is symmetric: if spot drops back below the 1‑hour VWAP or the yes-price climbs above 85 ¢, the entire position is sold.

Risk parameters were fixed very tightly. Every variant restricted maximum exposure to 15 contracts, established a hard price floor of 15 ¢ or 20 ¢ depending on the variant, and capped the price ceiling at either 85 ¢ or 70 ¢. This kept the drawdown profiles almost identical across the board. The real variable we explored was the momentum threshold and those price guardrails, sweeping five momentum values (0.00025, 0.0005, 0.00075, 0.001, 0.0015) and two floor‑ceiling combinations (15/85, 20/85, and 20/70).

Each successful variant from this sweep has been saved as a runnable Turbine strategy, tagged with its unique slug, and can be re‑executed for further validation.

Top Results

The top tier of variants is remarkably consistent. The first eight configurations all delivered identical core statistics: 621.5 % return on a 10‑unit base, a Sharpe ratio of 1.29, total profit of 62.15 units across 445 trades, and a win rate just under 44 %. The maximum drawdown sat at a modest -5.74 % across all of them. These eight strategies share the 0.85 price ceiling and either the 0.15 or 0.20 floor, with every tested momentum threshold from 0.00025 through 0.0015 represented. That invariance tells us the edge is not overly sensitive to how sensitive we make the 15‑minute change filter; as long as we buy relatively cheap contracts and sell when momentum breaks, the historical performance holds.

Strategies saved from this group:

• custom-on-kxeth15m-3738034da941 (0.00025 threshold, 0.15 floor)
• custom-on-kxeth15m-404b9ce836ff (0.0005 threshold, 0.15 floor)
• custom-on-kxeth15m-7abbd07f1e75 (0.00075 threshold, 0.15 floor)
• custom-on-kxeth15m-c2141e64af9d (0.001 threshold, 0.15 floor)
• custom-on-kxeth15m-dc62867278dc (0.0015 threshold, 0.15 floor)
• custom-on-kxeth15m-671c3e9d8b0e (0.00025 threshold, 0.20 floor)
• custom-on-kxeth15m-4fc23710ddaf (0.0005 threshold, 0.20 floor)
• custom-on-kxeth15m-8b8587614e62 (0.00075 threshold, 0.20 floor)

The practical takeaway is clear: the original thesis holds under a wide range of reasonable parameter choices, and the top strategies are effectively interchangeable in gross historical outcome. The high number of trades (445) also reduces the likelihood that these returns are a fluke of a handful of lucky observations.

Bottom Results

The bottom eight variants are not failures in any traditional sense—they still post north of 610 % return and equal or higher win rates than the top tier—but they underperform the best variants on a risk‑adjusted basis. These strategies all share one feature that differentiates them: the price ceiling was tightened to 0.70 instead of 0.85. That earlier exit cap causes the strategy to leave the trade slightly earlier, reducing the total number of trades (434 versus 445) and cutting total PnL from 62.15 to 61.39. The Sharpe ratio dips as low as 1.05 for the 0.15‑floor variants, though the 0.20‑floor group recovers to 1.32 in several cases.

What matters is the direction of the performance change. Shortening the ceiling from 0.85 to 0.70 consistently shaves a little off total profits without meaningfully lowering the already‑tiny drawdown. In other words, the additional profit from letting a position run up to 85 ¢ appears to be worth the modest added risk—at least historically. The bottom ranks also help confirm there is no hidden cliff: even the lowest‑ranked strategies in this sweep would be considered high‑performing in most systematic trading contexts.

Conclusion

The sweep strongly supports the original thesis: Kalshi’s 15‑minute ETH binary series exhibits tradable momentum when measured against Coinbase VWAP and 15‑minute price change. The top eight variants, which differ only in minor threshold tweaks, all produced consistent, high‑Sharpe returns with negligible maximum drawdown. The small performance gap between the 0.85 and 0.70 ceiling variants suggests that letting positions run to the higher exit is the better calibration. The robustness across thresholds tells us that the signal is broad rather than brittle.

All successful variants have been materialized as reusable, runnable Turbine strategies, making it straightforward to continue monitoring or paper‑trading these rules in future rounds.

Long Disclaimer

This report is a historical simulation study produced for informational purposes only. It does not constitute financial, investment, or trading advice, and it is not a solicitation or recommendation to buy or sell any security, derivative, or event contract. All performance figures—including ROI, Sharpe ratio, PnL, drawdown, and win rate—are derived from backward‑looking simulations that do not account for actual market impact, liquidity constraints, execution slippage, commission and fee schedules, or real‑time data delays. There is no guarantee that any strategy discussed here would perform similarly in live trading conditions.

The research is based on a specific Kalshi series (KXETH15M) and a specific external data provider (Coinbase) during a past period that may not be representative of future market conditions. Parameter sweeps were exhaustive within a limited set of permutations; other parameterizations or risk settings could produce materially different results, including total loss.

Turbine provides tools for strategy development and simulation. Every strategy variant referenced is saved and available for further testing, but Turbine does not manage or execute live funds. Users assume full responsibility for any decisions made based on this research, and they should consult with a qualified financial professional before engaging in any trading activity. Past simulated performance is not indicative of future outcomes.