Multi indicator Combination Trading Strategy

Pine ScriptBreakout Mean reversion Momentum SMA ADX / DMI CCI

Author: ChaoZhang
Complexity: Intermediate · 66 lines
Parameters: 10
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy combines CCI, ADX and AO indicators to generate trading signals for long and short positions. CCI identifies overbought and oversold levels, ADX determines trend strength and direction, and AO assists in oscillating markets. The multi-indicator combination improves the stability and efficiency of the trading system.

Strategy Logic

CCI indicates overbought above 100 and oversold below -100. This strategy goes long when CCI is below 0.
ADX measures trend strength. DI+ shows uptrend strength, DI- shows downtrend strength. ADX is the average trend strength. This strategy goes long when DI+ is below 25.
AO is fast SMA minus slow SMA. Rising AO represents strengthening bullish momentum, and falling AO represents strengthening bearish momentum. This strategy goes long when AO is below 0.
The trading rules are: Go long when CCI < 0 and DI+ < 25 and AO < 0; Close long when DI+ > 25.
Dynamically calculate order size as equity divided by close price and rounded down, to adjust orders as account equity changes.
Use strategy.entry for long signals, and strategy.close for exit signals.

Advantages

CCI filters noise from ranging markets, reducing false signals.
ADX identifies stronger trends early.
AO avoids trading choppy markets.
Multiple indicators verify signals, increasing reliability.
Dynamic position sizing manages risk effectively.
Simple and clear logic, easy to follow.

Risks

CCI struggles identifying vkosd ranges.
ADX has lag in catching trend turns.
AO struggles with choppy consolidation.
Poor indicator settings lead to over-filtering and missed trades.
Dynamic sizing dependent on volatility and markets.
Potential for large drawdowns, requiring strict risk management.

Enhancements

Optimize CCI parameters for different markets.
Optimize ADX parameters to catch trend changes.
Adjust AO parameters for volatility environments.
Test combinations to find optimal indicator weighting.
Add stop loss for drawdown control.
Incorporate volume for false breakout avoidance.
Customize fixed position sizing by instrument.

Conclusion

This strategy combines CCI, ADX and AO to generate fairly reliable long signals. Dynamic sizing and position management control risk. The logic is simple and clear for beginners to follow. But it struggles in ranging markets, with significant optimization potential required for different markets. Further testing and tuning is needed for robustness across instruments and environments.

Parameters

Name	Default	What it controls
v_input_1	25	buywhenadxabove
v_input_2	10	buywhendiplusbelow
v_input_3	false	buywhenccibelow
v_input_4	false	buywhenawesomeoscillatorbelow
v_input_5	25	sellwhendiplusabove
v_input_6	20	numberofbarsforcci
v_input_7	14	ADX Smoothing
v_input_8	14	DI Length
v_input_9	34	Length Slow
v_input_10	5	Length Fast

Source Pine Script

/*backtest
start: 2022-10-19 00:00:00
end: 2023-10-25 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy("Strategy Niel", shorttitle="Strategy Niel", max_bars_back=2000, initial_capital=1000)

//Input variables
buywhenadxabove = input(25)
buywhendiplusbelow = input(10)
buywhenccibelow = input(0)
buywhenawesomeoscillatorbelow = input(0)
sellwhendiplusabove = input(25)

//CCI script
numberofbarsforcci = input(20)
CCI = cci(close,numberofbarsforcci)

//+DI and ADX
adxlen = input(14, title="ADX Smoothing")
dilen = input(14, title="DI Length")
dirmov(len) =>
	up = change(high)
	down = -change(low)
	truerange = rma(tr, len)
	plus = fixnan(100 * rma(up > down and up > 0 ? up : 0, len) / truerange)
	minus = fixnan(100 * rma(down > up and down > 0 ? down : 0, len) / truerange)
	[plus, minus]

adx(dilen, adxlen) => 
	[plus, minus] = dirmov(dilen)
	sum = plus + minus
	adx = 100 * rma(abs(plus - minus) / (sum == 0 ? 1 : sum), adxlen)
	[adx, plus, minus]

[sig, up, down] = adx(dilen, adxlen)

//plot(sig, color=red, title="ADX")
//plot(up, color=blue, title="+DI")
//plot(down, color=orange, title="-DI")


//Awesome Oscillator
nLengthSlow = input(34, minval=1, title="Length Slow")
nLengthFast = input(5, minval=1, title="Length Fast")
xSMA1_hl2 = sma(hl2, nLengthFast)
xSMA2_hl2 = sma(hl2, nLengthSlow)
xSMA1_SMA2 = xSMA1_hl2 - xSMA2_hl2
cClr = xSMA1_SMA2 > xSMA1_SMA2[1] ? blue : red
//plot(xSMA1_SMA2, style=histogram, linewidth=1, color=cClr)

buy = sig > buywhenadxabove and up < buywhendiplusbelow  and CCI < buywhenccibelow and xSMA1_SMA2 < buywhenawesomeoscillatorbelow 

ordersize=floor(strategy.equity/close) // Floor returns largest integer, strategy.equity gives total equity remaining - allows to dynamically calculate the order size as the account equity increases or decreases.
strategy.entry("long",strategy.long,ordersize,when= buy) //strategy.entry let's you enter the market variables id ("long"), strategy.long (long position entry), size of the order and when the order should happen
bought = strategy.position_size[0] > strategy.position_size[1]
entry_price = valuewhen(bought, open, 0)
sell = up > sellwhendiplusabove 
strategy.close("long", when=sell ) //strategy.close let's you close your position with variables id ('long') and when this should happen

Published by ChaoZhang on the FMZ strategy square · last modified 2023-10-26. 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/Multi-indicator-Combination-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.