Dynamic SMA Cross Trend Strategy

Pine ScriptTrend following Mean reversion SMA ATR

Author: ChaoZhang
Complexity: Intermediate · 54 lines
Parameters: 9
Backtest bar: 3h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is a simple moving average (SMA) crossover strategy suitable for cryptocurrency markets. It uses fast, medium and slow SMAs to identify potential entry and exit signals. When the fast SMA crosses over the medium SMA, a buy signal is generated. When the fast SMA crosses under the medium SMA, a sell signal is generated.

Strategy Logic

Parameter Settings

The strategy allows traders to set the following key parameters:

Price source: close price or other prices
Consider incomplete bars or not
SMA forecast method: shift prediction or linear regression prediction
Fast SMA length: default 7
Medium SMA length: default 30
Slow SMA length: default 50
Account funds
Risk percentage per trade

SMA Calculation

Fast SMA, medium SMA and slow SMA are calculated based on the SMA lengths set by the user.

Trading Signals

When the fast SMA crosses over the medium SMA, a buy signal is generated. When the fast SMA crosses under the medium SMA, a sell signal is generated.

Risk and Position Sizing

The strategy calculates the nominal principal per trade based on account funds and acceptable risk percentage per trade. It then uses ATR to calculate the stop loss range and eventually determines the position sizing for each trade.

Advantage Analysis

Uses multiple SMAs to identify trends with greater conviction
Optional SMA forecast methods for stronger adaptability
Simple and clear trading signals easy to implement
Incorporates scientific risk and position management

Risk Analysis

Lagging nature of SMAs may miss price reversal points
Only considers technical indicators without combining fundamentals
Does not consider impact of sudden events

Can optimize by shortening SMA periods, adding other indicators etc.

Optimization Directions

Add other indicators to filter false signals
Incorporate fundamental analysis
Optimize SMA period parameters
Optimize risk and position sizing parameters

Conclusion

This strategy integrates SMA crossover rules, risk management and position sizing for a robust trend following system suitable for crypto markets. Traders can tweak parameters like trading style, market conditions etc. to customize and optimize.

Parameters

Name	Default	What it controls
v_input_1_close	0	Price Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_2	true	Consider Incomplete Bars
v_input_3	0	Moving Average Prediction Method: flat \| linreg
v_input_4	3	Linear Regression Length
v_input_5	7	Fast Moving Average Length
v_input_6	30	Medium Moving Average Length
v_input_7	50	Slow Moving Average Length
v_input_8	100000	Trading Capital
v_input_9	true	Trade Risk (%)

Source Pine Script

/*backtest
start: 2024-01-05 00:00:00
end: 2024-02-04 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("Onchain Edge Trend SMA Strategy", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=10)

// Configuration Parameters
priceSource = input(close, title="Price Source")
includeIncompleteBars = input(true, title="Consider Incomplete Bars")
maForecastMethod = input(defval="flat", options=["flat", "linreg"], title="Moving Average Prediction Method")
linearRegressionLength = input(3, title="Linear Regression Length")
fastMALength = input(7, title="Fast Moving Average Length")
mediumMALength = input(30, title="Medium Moving Average Length")
slowMALength = input(50, title="Slow Moving Average Length")
tradingCapital = input(100000, title="Trading Capital")
tradeRisk = input(1, title="Trade Risk (%)")

// Calculation of Moving Averages
calculateMA(source, period) => sma(source, period)
predictMA(source, forecastLength, regressionLength) => 
    maForecastMethod == "flat" ? source : linreg(source, regressionLength, forecastLength)

offset = includeIncompleteBars ? 0 : 1
actualSource = priceSource[offset]

fastMA = calculateMA(actualSource, fastMALength)
mediumMA = calculateMA(actualSource, mediumMALength)
slowMA = calculateMA(actualSource, slowMALength)

// Trading Logic
enterLong = crossover(fastMA, mediumMA)
exitLong = crossunder(fastMA, mediumMA)

// Risk and Position Sizing
riskCapital = tradingCapital * tradeRisk / 100
lossThreshold = atr(14) * 2
tradeSize = riskCapital / lossThreshold

if (enterLong)
    strategy.entry("Enter Long", strategy.long, qty=tradeSize)

if (exitLong)
    strategy.close("Enter Long")

// Display Moving Averages
plot(fastMA, color=color.blue, linewidth=2, title="Fast Moving Average")
plot(mediumMA, color=color.purple, linewidth=2, title="Medium Moving Average")
plot(slowMA, color=color.red, linewidth=2, title="Slow Moving Average")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-05. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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