RASP Alpha Engine - Vol Target Trend — Strategy by HyperSignals
By HyperSignals
Performance Metrics
- Author: HyperSignals
- Symbol: BINANCE:BTCUSD
- Timeframe: 1 day
- Net P&L: +48,849.37 USD (+488.49%)
- Win Rate: 37.9%
- Profit Factor: 1.746
- Max Drawdown: 35,432.41 USD (37.90%)
- Total Trades: 29
Description
RASP Alpha Engine is a regime-aware, volatility-targeted trading strategy built by HyperSignals for BTC and other high-volatility markets.The strategy is designed around a simple idea: markets behave differently in bull trends, bear trends, high-volatility periods, and neutral chop. Instead of applying one static signal everywhere, RASP Alpha adapts exposure based on trend structure, momentum, volatility, and macro regime.Core features:• Regime-aware trend detection using daily and weekly EMA structure• Volatility-targeted position sizing• Long-biased trend participation for risk-on environments• Optional crash-only shorts during confirmed risk-off regimes• ATR-based trailing stop and hard-stop protection• Breakout and pullback-style entries• Built-in dashboard for strategy return, buy-and-hold comparison, exposure, realized volatility, and estimated Sharpe• Designed to reduce overtrading in noisy conditions using cooldowns and trend-quality filtersThis script is not meant to predict every candle. It is built to help traders study how adaptive exposure, trend filters, and volatility management can affect long-term strategy performance.Suggested use:Start with Long Only or Long + Crash Shorts modeCompare results against buy-and-hold in Strategy TesterTune volatility target, max exposure, ATR trailing stop, and breakout length for the asset and timeframeAvoid assuming that optimized settings will continue to work unchanged in future market regimesBest suited for:• BTC and crypto trend-following research• Regime-aware strategy testing• Volatility targeting experiments• Comparing active strategy performance against buy-and-hold• Studying long-biased versus crash-short behaviorImportant: This script is for education, research, and strategy development only. It is not financial advice. Backtested performance does not guarantee future results. Always test carefully before using any strategy in live markets.Open source under MPL 2.0.