Price Crossing Moving Average Trend Following Strategy

This strategy generates buy and sell signals based on the crossing of price with a moving average. It provides various types of moving averages and a tolerance parameter to filter false breakouts. The strategy aims…

Pine ScriptTrend following Breakout EMA SMA

Author: ChaoZhang
Complexity: Starter · 50 lines
Parameters: 5
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy calculates a length N moving average based on the closing price. Typical moving average types include Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA) etc. Then a tolerance level is set, e.g. 5%, and upper band (1.05 times moving average) and lower band (0.95 times moving average) are calculated. When closing price crosses above upper band, a buy signal is generated. When closing price crosses below lower band, a sell signal is generated. This helps filter some false breakouts. Also, a Boolean parameter "Short Only" is provided. When enabled, only sell signals are generated for shorting the market.

Advantages

Effectively follows price trends using moving average's trend following characteristics
Provides various moving average types for flexible combinations
Tolerance parameter helps filter false breakouts and avoid unnecessary trades
Can go short only, suitable for catching downward trends

Risks

Moving averages have lagging effect, may miss price turning points
Not suitable for range-bound market environments
Improper tolerance parameter settings may filter valid signals
Going short has higher risks, need prudent operations

Optimization Directions

Optimize moving average type and length parameters
Test different tolerance parameter settings
Add other indicators to filter signals
Employ position sizing strategies

Conclusion

Overall this is a typical trend following strategy. It uses the relationship between price and moving average to determine trends, with some flexibility. Through parameter optimization and proper signal filtering, it can become a decent quant strategy. But controlling downside risks when shorting is important to avoid excessive losses.

Parameters

Name	Default	What it controls
v_input_1	0	MA Type: HMA \| EMA \| WMA \| SMA \| VWMA \| RMA \| TEMA
v_input_2	100	Length
v_input_3_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_4	false	Tolerance (%)
v_input_5	false	Short only

Source Pine Script

/*backtest
start: 2023-12-26 00:00:00
end: 2024-01-25 00:00:00
period: 1h
basePeriod: 15m
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/
// © RafaelPiccolo

//@version=4
strategy("Price X MA Cross", overlay=true)

typ = input("HMA", "MA Type", options=["SMA", "EMA", "WMA", "HMA", "VWMA", "RMA", "TEMA"])
len = input(100, minval=1, title="Length")
src = input(close, "Source", type=input.source)
tol = input(0, minval=0, title="Tolerance (%)", type=input.float)
shortOnly = input(false, "Short only")

tema(src, len)=>
    ema1 = ema(src, len)
    ema2 = ema(ema1, len)
    ema3 = ema(ema2, len)
    return = 3 * (ema1 - ema2) + ema3

getMAPoint(type, len, src)=>
    return = type == "SMA" ? sma(src, len) : type == "EMA" ? ema(src, len) : type == "WMA" ? wma(src, len) : type == "HMA" ? hma(src, len) : type == "VWMA" ? vwma(src, len) : type == "RMA" ? rma(src, len) : tema(src, len)

ma = getMAPoint(typ, len, src)
upperTol = ma * (1 + tol/100)
lowerTol = ma * (1 - tol/100)

longCondition = crossover(close, upperTol)
shortCondition = crossunder(close, lowerTol)

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

if (longCondition)
    if (shortOnly)
        strategy.close("Short")
    else
        strategy.entry("Long", strategy.long)

plot(ma, "Moving Average", close > ma ? color.green : color.red, linewidth = 2)
t1 = plot(tol > 0 ? upperTol : na, transp = 70)
t2 = plot(tol > 0 ? lowerTol : na, transp = 70)
fill(t1, t2, color = tol > 0 ? color.blue : na)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-26. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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