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=29
74.1% 43.0%-55.0%-86.8% 1.5012151%
Ethereum
fast=9, slow=22
91.5% 29.8%-46.2%-95.6% 1.4510350%
XRP (Ripple)
fast=9, slow=10
73.2% 28.3%-62.5%-95.9% 1.0516142%
Samsung Electronics
fast=56, slow=83
12.2% 15.2%-44.9%-64.8% 0.565561%
Apple (AAPL)
fast=4, slow=135
17.1% 18.6%-84.2%-82.2% 0.6720964%
1x 10x 100x 2018 2020 2022 2024 2026 EMA crossoverBuy & hold
Bitcoin 2017-09-25–2026-09-08 · 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

Read next