Quadratic Momentum Double Indicators Timing Strategy

This strategy fuses the SuperTrend indicator with Elliott Wave theory to build a robust technical trading tool. It employs multi-level trend analysis to provide a more comprehensive market perspective that can early…

Pine ScriptMomentum Machine learning Mean reversion ATR Supertrend

Author: ChaoZhang
Complexity: Intermediate · 92 lines
Parameters: 9
Backtest bar: 5m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

The core idea lies in its multi-tiered approach:

Use 4 SuperTrend indicators, each with different ATR lengths and multipliers, to judge the trend from short to long term
Pinpoint robust long and short signals through indicator convergence
Refer to Elliott Wave's pattern recognition method to identify similar market behaviors to confirm trade signals

Thus, it utilizes multiple indicators and adds pattern recognition to make the strategy more robust.

Advantage Analysis

Multi-indicator design provides comprehensive judgment
Wave theory inspiration increases stability through pattern recognition
Real-time direction adjustment adapts to market changes
Configurable parameters suit different products and time frames

Risk Analysis

Parameter setting relies on experience, requiring tuning to determine optimal parameter combinations
Multi-indicator design is complex, increasing computational load
Cannot completely avoid incorrect signal generation

Parameters can be optimized to gradually determine the optimum; cloud computing can improve computational performance; stop losses can control risk.

Optimization Directions

Optimizations can be made in several aspects:

Add adaptive parameter adjustment module to dynamically tune parameters based on market conditions
Incorporate machine learning models to aid in judging signal reliability
Combine sentiment indicators, news events etc. to determine market regimes
Support multi-product parameter templates to reduce testing workload

This will make strategy parameters more intelligent, judgments more accurate, and practical application more convenient.

Summary

The strategy comprehensively considers both trend and pattern dimensions, ensuring judgment robustness while increasing flexibility. Multi-indicators and parameter settings ensure full market applicability. With further incorporation of intelligent and automated methods, strategy practicality can be greatly enhanced. It provides valuable inspiration and reference for the advancement of technical trading.

Parameters

Name	Default	What it controls
v_input_string_1	0	Select Trading Direction: Both \| Short \| Long
v_input_1	7	ATR Length for SuperTrend 1
v_input_2	4	Multiplier for SuperTrend 1
v_input_3	14	ATR Length for SuperTrend 2
v_input_4	3.618	Multiplier for SuperTrend 2
v_input_5	21	ATR Length for SuperTrend 3
v_input_6	3.5	Multiplier for SuperTrend 3
v_input_7	28	ATR Length for SuperTrend 3
v_input_8	3.382	Multiplier for SuperTrend 3

Source Pine Script

/*backtest
start: 2024-01-27 00:00:00
end: 2024-02-03 00:00:00
period: 5m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Elliott's Quadratic Momentum - Strategy [presentTrading]",shorttitle = "EQM Strategy [presentTrading]", overlay=true )

// Inputs for selecting trading direction
tradingDirection = input.string("Both", "Select Trading Direction", options=["Long", "Short", "Both"])


// SuperTrend Function
supertrend(src, atrLength, multiplier) =>
    atr = ta.atr(atrLength)
    up = hl2 - (multiplier * atr)
    dn = hl2 + (multiplier * atr)
    trend = 1
    trend := nz(trend[1], 1)
    up := src > nz(up[1], 0) and src[1] > nz(up[1], 0) ?   math.max(up, nz(up[1], 0)) : up
    dn := src < nz(dn[1], 0) and src[1] < nz(dn[1], 0) ? math.min(dn, nz(dn[1], 0)) : dn
    trend := src > nz(dn[1], 0) ?  1 : src < nz(up[1], 0)? -1 : nz(trend[1], 1)
    [up, dn, trend]

// Inputs for SuperTrend settings
atrLength1 = input(7, title="ATR Length for SuperTrend 1")
multiplier1 = input(4.0, title="Multiplier for SuperTrend 1")
atrLength2 = input(14, title="ATR Length for SuperTrend 2")
multiplier2 = input(3.618, title="Multiplier for SuperTrend 2")
atrLength3 = input(21, title="ATR Length for SuperTrend 3")
multiplier3 = input(3.5, title="Multiplier for SuperTrend 3")
atrLength4 = input(28, title="ATR Length for SuperTrend 3")
multiplier4 = input(3.382, title="Multiplier for SuperTrend 3")

// Calculate SuperTrend
[up1, dn1, trend1] = supertrend(close, atrLength1, multiplier1)
[up2, dn2, trend2] = supertrend(close, atrLength2, multiplier2)
[up3, dn3, trend3] = supertrend(close, atrLength3, multiplier3)
[up4, dn4, trend4] = supertrend(close, atrLength4, multiplier4)


// Entry Conditions based on SuperTrend and Elliott Wave-like patterns
longCondition = trend1 == 1 and trend2 == 1 and trend3 == 1 and trend4 == 1
shortCondition = trend1 == -1 and trend2 == -1 and trend3 == -1 and trend4 == - 1

// Strategy Entry logic based on selected trading direction
if tradingDirection == "Long" or tradingDirection == "Both"
    if longCondition
        strategy.entry("Long", strategy.long)
        // [Any additional logic for long entry]

if tradingDirection == "Short" or tradingDirection == "Both"
    if shortCondition
        strategy.entry("Short", strategy.short)
        // [Any additional logic for short entry]


// Exit conditions - Define your own exit strategy
// Example: Exit when any SuperTrend flips
if trend1 != trend1[1] or trend2 != trend2[1] or trend3 != trend3[1] or trend4 != trend4[1] 
    strategy.close_all()

// Function to apply gradient effect
gradientColor(baseColor, length, currentBar) =>
    var color res = color.new(baseColor, 100)
    if currentBar <= length
        res := color.new(baseColor, int(100 * currentBar / length))
    res

// Apply gradient effect
color1 = gradientColor(color.blue, atrLength1, bar_index % atrLength1)
color4 = gradientColor(color.blue, atrLength4, bar_index % atrLength3)


// Plot SuperTrend with gradient for upward trend
plot1Up = plot(trend1 == 1 ? up1 : na, color=color1, linewidth=1, title="SuperTrend 1 Up")
plot4Up = plot(trend4 == 1 ? up4 : na, color=color4, linewidth=1, title="SuperTrend 3 Up")

// Plot SuperTrend with gradient for downward trend
plot1Down = plot(trend1 == -1 ? dn1 : na, color=color1, linewidth=1, title="SuperTrend 1 Down")
plot4Down = plot(trend4 == -1 ? dn4 : na, color=color4, linewidth=1, title="SuperTrend 3 Down")

// Filling the area between the first and third SuperTrend lines for upward trend
fill(plot1Up, plot4Up, color=color.new(color.green, 80), title="SuperTrend Upward Band")

// Filling the area between the first and third SuperTrend lines for downward trend
fill(plot1Down, plot4Down, color=color.new(color.red, 80), title="SuperTrend Downward Band")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-04. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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