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ETH–BTC Cross Trend Alpha Strategy (1H)

Dual-Probability Crypto Trend Strategy

Overview

ETH–BTC Cross Trend Alpha Strategy is a quantitative, probability-based trend-following strategy that trades Ethereum (ETHUSDT) using cross-confirmation from both Ethereum and Bitcoin trend probabilities.

The strategy activates positions only when trend acceleration is statistically confirmed across both assets, dramatically reducing false entries caused by isolated or low-quality market moves.

This updated version introduces additional probability filtering, resulting in higher expectancy, stronger outperformance, and improved trade quality.

What Makes This Strategy Different

Most crypto strategies rely on:

single-asset signals
lagging indicators
price-only confirmation

This strategy answers a more important question:

> Is Ethereum trending — and is Bitcoin confirming that trend?

Only when both markets align does the strategy allow exposure.

Core Strategy Logic

Entry Conditions

A long position is opened when:

ETH Trend Slope Probability confirms strong upward momentum
BTC Trend Slope Probability confirms broader market alignment
An additional slope-strength filter confirms trend persistence across the selected horizon

This extra rule significantly reduces:

early entries
choppy regime trades
false ETH-only breakouts

Exit Conditions

Positions are exited when:

ETH trend probability deteriorates below a defined threshold
Trend slope begins to flatten, signaling a regime shift

The strategy prioritizes capital preservation during non-trending phases.

Updated Performance Snapshot (ETHUSDT · 1H)

Backtested over 13.9 months on BINANCE:ETHUSDT data:

Net Strategy Performance: +103.2%
Buy & Hold Performance: +3.7%
Trades: 122
Win Rate: ~73%
Max Drawdown: −30.9%
Beta vs Asset: 0.38
Average Trade Return: 0.66%
Expectancy: 0.20

The strategy demonstrates significant alpha with controlled market exposure, driven by probability-based filtering rather than constant participation.

Why the Update Matters

The newly added rule improves the strategy by:

increasing average trade quality
reducing low-conviction trend entries
improving overall equity smoothness
enhancing robustness across market regimes

This results in fewer but higher-quality trades — exactly what systematic trend strategies aim for.

Ideal Use Cases

Traders focused on ETH trend participation
Crypto portfolios seeking BTC-confirmed exposure
Systematic and algorithmic traders
TrendSpider Signal Bot automation
Traders who prefer probability-driven decisions over indicators

Strategy Characteristics

Timeframe: 1 Hour
Traded Asset: ETHUSDT
Confirmation Asset: BTCUSDT
Signal Type: Trend slope probability
Repainting: No
Lookahead: None
Platform: TrendSpider Strategy Tester & Signal Bot

Technical Keywords

Ethereum Trading · Bitcoin Confirmation · Cross-Market Strategy ·
Trend Probability · Momentum Slope · Machine Learning ·
Crypto Trend Alpha · Algorithmic Trading · TrendSpider Strategy

Disclaimer: This strategy is based on probabilistic models and historical data. Past performance is not indicative of future results. Use proper risk management.

Entry Conditions

All of the following: # Quebec
  60min ETH_slope_prob (yes, yes, yes, yes, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0, 1, 2, 3, yes), P (24h) > 0.7
  60min BTC_slope_prob (yes, yes, yes, yes, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0, 1, 2, 3, yes), P (24h) > 0.8
  60min ETH_slope_prob (yes, yes, yes, yes, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0, 1, 2, 3, yes), P (4h) > 60min BTC_slope_prob (yes, yes, yes, yes, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0, 1, 2, 3, yes), P (4h)

Exit Conditions

All of the following: # Bravo
  60min ETH_slope_prob (yes, yes, yes, yes, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0, 1, 2, 3, yes), P (24h) < 0.6
  60min ETH_slope_prob (yes, yes, yes, yes, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01, 0, 1, 2, 3, yes), P (4h) > 0.6

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