Trend-Following Backtester · Guide · Strategies 한국어

Strategies

SMA crossover

When the short average rises above the long average, it reads that as an uptrend starting.

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=2, slow=35
78.2% 41.2%-50.5%-86.8% 1.5514852%
Ethereum
fast=6, slow=32
89.6% 27.1%-49.0%-95.6% 1.4210750%
XRP (Ripple)
fast=9, slow=34
69.6% 25.7%-82.9%-95.9% 1.0110641%
Samsung Electronics
fast=24, slow=89
12.2% 14.2%-42.5%-64.8% 0.577558%
Apple (AAPL)
fast=11, slow=34
15.6% 18.8%-55.9%-82.2% 0.6335558%
1x 10x 100x 2018 2020 2022 2024 2026 SMA crossoverBuy & hold
Bitcoin 2017-09-25–2026-07-30 · SMA 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

SMA 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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