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Strategy vault / Trend following

AlphaTrend Strategy

The strategy version of AlphaTrend indicator for backtesting and optimisation purposes for TradingView users: AlphaTrend Screener / Explorer version and an English explantion video will be published soon..…

Author
ChaoZhang
Complexity
Starter · 53 lines
Parameters
5
Backtest bar
1d · swing
Tested on
BTC/USDT · futures

The strategy version of AlphaTrend indicator for backtesting and optimisation purposes for TradingView users:

AlphaTrend IMG

Screener / Explorer version and an English explantion video will be published soon...

AlphaTrend's parameters are designed for daily and 4H charts, feel free to optimize on all time frames.

Hope you all use Alphatrend in your profitable trades.

Kıvanç

backtest

IMG

Parameters

NameDefaultWhat it controls
v_input_float_1trueMultiplier
v_input_114Common Period
v_input_2_close0src: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4
v_input_3falseShow Signals?
v_input_4falseChange calculation (no volume data)?

Source Pine Script

/*backtest
start: 2021-08-11 00:00:00
end: 2022-08-10 23:59:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// author © KivancOzbilgic
// developer © KivancOzbilgic
//@version=5

strategy("AlphaTrend Strategy", shorttitle='ATst', overlay=true, format=format.price, precision=2, margin_long=100, margin_short=100)
coeff = input.float(1, 'Multiplier', step=0.1)
AP = input(14, 'Common Period')
ATR = ta.sma(ta.tr, AP)
src = input(close)
showsignalsk = input(title='Show Signals?', defval=false)
novolumedata = input(title='Change calculation (no volume data)?', defval=false)
upT = low - ATR * coeff
downT = high + ATR * coeff
AlphaTrend = 0.0
AlphaTrend := (novolumedata ? ta.rsi(src, AP) >= 50 : ta.mfi(hlc3, AP) >= 50) ? upT < nz(AlphaTrend[1]) ? nz(AlphaTrend[1]) : upT : downT > nz(AlphaTrend[1]) ? nz(AlphaTrend[1]) : downT

color1 = AlphaTrend > AlphaTrend[2] ? #00E60F : AlphaTrend < AlphaTrend[2] ? #80000B : AlphaTrend[1] > AlphaTrend[3] ? #00E60F : #80000B
k1 = plot(AlphaTrend, color=color.new(#0022FC, 0), linewidth=3)
k2 = plot(AlphaTrend[2], color=color.new(#FC0400, 0), linewidth=3)

fill(k1, k2, color=color1)

buySignalk = ta.crossover(AlphaTrend, AlphaTrend[2])
sellSignalk = ta.crossunder(AlphaTrend, AlphaTrend[2])


K1 = ta.barssince(buySignalk)
K2 = ta.barssince(sellSignalk)
O1 = ta.barssince(buySignalk[1])
O2 = ta.barssince(sellSignalk[1])

plotshape(buySignalk and showsignalsk and O1 > K2 ? AlphaTrend[2] * 0.9999 : na, title='BUY', text='BUY', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(#0022FC, 0), textcolor=color.new(color.white, 0))

plotshape(sellSignalk and showsignalsk and O2 > K1 ? AlphaTrend[2] * 1.0001 : na, title='SELL', text='SELL', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(color.maroon, 0), textcolor=color.new(color.white, 0))


longCondition = buySignalk
if (longCondition)
    strategy.entry("Long", strategy.long)

shortCondition = sellSignalk
if (shortCondition)
    strategy.entry("Short", strategy.short)
 

Published by ChaoZhang on the FMZ strategy square · last modified 2022-08-12. 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/AlphaTrend-Strategy.md
  1. npx agenkit install engineering-kit in your project
  2. Paste the command into your agent and approve each phase
  3. Get tests, backtest, risk controls and a paper-trading switch

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.

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