The SMA 3 Trading Strategy

The SMA-3 trading strategy is a technical analysis approach that uses 3 simple moving averages to identify trading opportunities. It was created by trader Noro and aims to capitalize on short-term price trends. How…

Pine ScriptBreakout Trend following SMA

Author: ChaoZhang
Complexity: Intermediate · 49 lines
Parameters: 12
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

How It Works

The strategy utilizes 3 SMA lines - a middle line, an upper line, and a lower line. The middle SMA tracks the closing price. The upper and lower SMAs are offset by a fixed percentage above and below the middle SMA.

When price breaks above the upper SMA, a long position is entered. When price falls below the lower SMA, a short position is taken. Profit targets are set at the opposite SMA line.

The SMA parameters, capital allocation, date filters, and other settings are customizable. The strategy aims to ride short-term trends until a SMA breakout occurs in the opposite direction.

Advantages and Risks

A key advantage of SMA-3 is its simplicity. It aims to capitalize on high probability breakouts confirmed by moving average crossovers. The fixed percentage stops help lock in profits if the trend continues.

However, like all technical strategies, it is prone to whipsaws and false breakouts. Slippage on entries and exits can erode profitability. Optimizing the SMA lengths and offset percentages is crucial for results.

The strategy may underperform in sideways or volatile markets. Strict risk management is advised when position sizing. Applying prudent money management is key.

Overall, SMA-3 offers a straightforward approach to trading short-term price swings. It can be robust if implemented properly, but requires fine-tuning and discipline. Trailing stops and prudent adjustments can aid strategy longevity.

Parameters

Name	Default	What it controls
v_input_1	true	Long
v_input_2	false	Short
v_input_3	100	Capital, %
v_input_4	20	bars
v_input_5	15	percent
v_input_6	true	Show Lines?
v_input_7	1900	From Year
v_input_8	2100	To Year
v_input_9	true	From Month
v_input_10	12	To Month
v_input_11	true	From day
v_input_12	31	To day

Source Pine Script

/*backtest
start: 2022-09-04 00:00:00
end: 2023-09-10 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//Noro
//2018

//@version=2
strategy(title = "Noro's SMA-3 Strategy v1.0", shorttitle = "SMA-3 str 1.0", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 5)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(false, defval = false, title = "Short")
capital = input(100, defval = 100, minval = 1, maxval = 10000, title = "Capital, %")
p = input(20, "bars")
d = input(15, "percent")
showlines = input(true, defval = true, title = "Show Lines?")
fromyear = input(1900, defval = 1900, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day")

//SMAs
sma = sma(close, p)
upex = sma * ((100 + d) / 100)
dnex = sma * ((100 - d) / 100)
exit = high > sma and low < sma

//Lines
col = showlines ? blue : na
plot(upex, linewidth = 3, color = col, transp = 0)
plot(sma, linewidth = 3, color = col, transp = 0)
plot(dnex, linewidth = 3, color = col, transp = 0)

//Trading
lot = strategy.position_size != strategy.position_size[1] ? strategy.equity / close * capital / 100 : lot[1]

if true
    strategy.entry("Long", strategy.long, needlong == false ? 0 : lot, limit = dnex, when = (time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)))
    strategy.entry("Short", strategy.short, needshort == false ? 0 : lot, limit = upex, when = (time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)))

if time > timestamp(toyear, tomonth, today, 23, 59) or exit
    strategy.close_all()

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-11. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/The-SMA-3-Trading-Strategy.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.

Parameters

Source Pine Script

Build this with AgenKit

Understand it first

Related specs