Linear perpetual (paper default)v0.3.0PAPER READY

K-Trend Rider

Invert the trend and signal logic to trade short positions instead of long. Change `uptrend` to `downtrend` (emaFast < emaSlow), `momentumOk` to `rsi < 50`, and execute `strategy.entry('S', 'short', ...)` with inverted stop/take-profit calculations. Given the strong negative Sharpe and net PnL, the long bias may be fighting a prevailing downtrend in the tested market.

BTCHyperliquid实验趋势高波动
Hosted coming soon Export for local runtimeHosted feasibility is under review; only released Local support produces a runtime configuration
Strategy categoryK 策略迁移研究
Market / timeframeBTC/USDC · 1h
Default riskHIGH
Current runtimeslocal
Strategy thesis

Why it might work

第三方公开时序研究的技术指标迁移草稿;待 QuantElse 使用原始行情复现。

Key risks
  • 第三方自报回测,尚未由 QuantElse 复现。
  • 永续合约含资金费、滑点、清算和交易所可用性风险。
Stop / invalidation conditions
  • 原始规则或数据无法复现时停止发布为可运行版本。
Published backtest

Evidence used to compare strategies

Self-reported
Period180 days
Total return+13.78%
Max drawdown7.42%
Trades139
Risk-adjusted metricsOnly fields included in this published result are shown.
Annualized return+27.94%
Sharpe ratio0.28
Interactive backtestHover or use the arrow keys to inspect each sample
110.5106.9103.399.7696.182026-01-222026-03-082026-04-222026-06-062026-07-21
Detail curve · 1h samplingK-Trend RiderNormalized baseline
DATA PERIOD2026-01-22 — 2026-07-21

Minara public Marketplace API (third-party, pending QuantElse replay)
ohlcv · 1h · 240 samples
2026-07-21T00:00:00Z · Public third-party claim; retain attribution and source terms.

BENCHMARK PROFILECatalog defaults

catalog-default-v1
model-based fees · model-based slippage

METHODOLOGY

Imported from Minara public Marketplace API; no QuantElse execution, fees, funding or slippage were recomputed.

LIMITATIONS
  • Third-party self-reported result; not independently verified.
  • Replace this curve after a native QuantElse backtest.
Published records
  • 2026-01-22 — 2026-07-21+13.78%Minara public Marketplace API (third-party, pending QuantElse replay)

Historical results do not guarantee future performance.