SleepWell Trade

Trend-Following Backtester · Guide · Strategies 한국어

Strategies

EMA crossover

Uses two exponential averages (more weight on recent prices) and trades their crossover.

Parameters 2 Assets tested 5 Costs 0.5% Optimized Sharpe · 120

The rules

Those numbers are the values optimized for Bitcoin. They differ per asset — the table below lists each.

There are 2 tunable values: fast, slow. Fewer knobs make it harder to fit noise, so a count this low keeps overfitting risk relatively contained.

Results by asset

The same strategy across 5 very different assets, each over its full history, with parameters optimized per asset. It beat buy and hold on 3 of 5.

Asset · parameters CAGRHold CAGR Max drawdownHold DD SharpeTradesTime in market
Bitcoin
fast=4, slow=120
51.8% 43.7%-39.8%-86.8% 1.324150%
Ethereum
fast=7, slow=25
93.0% 30.2%-46.5%-95.6% 1.4610350%
XRP (Ripple)
fast=3, slow=6
83.7% 29.5%-73.5%-95.9% 1.1140543%
Samsung Electronics
fast=56, slow=82
12.3% 15.0%-45.1%-64.8% 0.565561%
Apple (AAPL)
fast=3, slow=130
17.5% 18.6%-79.3%-82.2% 0.6823764%
1x 10x 2018 2020 2022 2024 2026 EMA crossoverBuy & hold
Bitcoin 2017-09-25–2026-08-25 · EMA crossover (solid) vs buy and hold (dashed). Log scale.
These are in-sample figures. The same data chose the parameters and scored them, so they sit above what live trading would return. Use them to rank strategies against each other, not as a return target. See optimization and overfitting.

When this one works

EMA crossover belongs to the trend-following family. All of them earn in sustained directional moves and bleed costs in range-bound markets. The trade count and time in market columns above show how each variant leans.

Run this strategyCompare the others

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