Coppock Curve Based Quantitative Trading Strategy

Author: ChaoZhang
Complexity: Starter · 61 lines
Parameters: 5
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy utilizes the lesser known Coppock Curve technical indicator to implement quantitative trading. The Coppock Curve is derived by taking a weighted moving average of the rate of change (ROC) of a market index like S&P 500 or a trading equivalent like SPY ETF. Buy signals are generated when the Coppock Curve crosses above zero and sell signals when it crosses below. An optional trailing stop loss is available to lock in profits. The strategy uses $SPY Coppock curve as a proxy to generate trade signals on other ETFs and stocks.

Principles

The strategy uses Coppock Curve as the technical indicator for generating trading signals. The Coppock Curve formula is:

Coppock Curve = 10-period WMA (14-period ROC + 11-period ROC)

Where ROC rate of change is calculated as: (Current Close - Close N periods ago) / Close N periods ago

The strategy calculates the Coppock Curve based on the closing price of $SPY. Buy signals are generated when the curve crosses above zero and sell signals when it crosses below.

Advantages

Uses unique Coppock Curve indicator which has better predictive power than common indicators like moving averages
Configurable parameters for optimization like WMA period, ROC period etc.
Uses $SPY as signal source which has strong market representativeness
Optional trailing stop loss to lock in profits and reduce drawdowns

Risks

Coppock Curve is not a widely used indicator, its efficacy needs validation
Signal lag may exist, parameters need to be optimized
Overly wide stop loss may miss pullback opportunities
Reliance on single indicator can produce false signals

Optimization Directions

Test optimal parameter combinations across different markets and stocks
Combine with other indicators to filter out false signals e.g. volume
Dynamic optimization of stop loss percentage
Consider other entry signals like number of bars or price breakthroughs

Conclusion

The strategy utilizes the unique curve shape characteristics of the Coppock Curve to generate trade signals. Compared to common indicators, the Coppock Curve has stronger predictive power. But as a standalone indicator, its reliability needs validation. It's recommended to combine it with other factors to filter false signals. Through parameter optimization, stop loss optimization and combining with other indicators, this strategy can become an effective quantitative trading system.

Parameters

Name	Default	What it controls
v_input_1	100	Trail Long Loss (%)
v_input_2	SPY	security
v_input_3	10	WMA Length
v_input_4	14	Long RoC Length
v_input_5	11	Short RoC Length

Source Pine Script

/*backtest
start: 2023-10-13 00:00:00
end: 2023-11-12 00:00:00
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/
// © RolandoSantos

//@version=4
strategy(title = "Coppock Curve", shorttitle = "Copp Curve Strat", default_qty_type=strategy.cash, default_qty_value=10000, initial_capital=10000)

///trail stop
longTrailPerc = input(title="Trail Long Loss (%)", minval=0.0, step=0.1, defval=100) * 0.01

// Determine trail stop loss prices
longStopPrice = 0.0

longStopPrice := if (strategy.position_size > 0)
    stopValue = close * (1 - longTrailPerc)
    max(stopValue, longStopPrice[1])
else
    0
//Use SPY for Copp Curve entries and exits//
security = input("SPY")
ticker = security(security, "D", close)

///Copp Curve////
wmaLength = input(title="WMA Length", type=input.integer, defval=10)
longRoCLength = input(title="Long RoC Length", type=input.integer, defval=14)
shortRoCLength = input(title="Short RoC Length", type=input.integer, defval=11)
source = ticker
curve = wma(roc(source, longRoCLength) + roc(source, shortRoCLength), wmaLength)

///Lower Band Plot///
band1 = hline(0)
band0 = hline(100)
band2 = hline(-100)
fill(band1, band0, color=color.green, transp=90)
fill(band2, band1, color=color.red, transp=90)
plot(curve, color=color.white)

///Trade Conditions///
Bull = curve > 0
Bear = curve < 0

///Entries and Exits//
if (Bull)
    strategy.entry("Long", strategy.long, comment = "LE")
    

if (Bear)
    strategy.close("Long", qty_percent=100, comment="close")
    
// Submit exit orders for trail stop loss price
if (strategy.position_size > 0)
    strategy.exit(id="Long Trail Stop", stop=longStopPrice)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-13. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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