Dual Moving Average Crossover Strategy 433969

This strategy is based on the dual moving average crossover trend following system. It combines fast simple moving average (SMA) and slow weighted moving average (VWMA), and generates trading signals when the two…

Pine ScriptTrend following Volatility RSI EMA SMA Bollinger Bands

Author: ChaoZhang
Complexity: Intermediate · 96 lines
Parameters: 15
Backtest bar: 15m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

When the fast SMA crosses above the slow VWMA, a buy signal is generated. When the fast SMA crosses below the slow VWMA, a sell signal is generated. The strategy also employs stop loss mechanism to control risks.

Strategy Logic

The core logic of this strategy lies in the dual moving average crossover system. Specifically, it utilizes the following technical indicators:

Simple Moving Average (SMA): Arithmetic mean of closing prices over the past n days, reflecting recent average price.
Weighted Moving Average (VWMA): Weighted mean of closing prices over the past n days, assigning higher weights to more recent prices, responding faster to price changes.

The fast SMA has a shorter lookback period to react swiftly to price changes, while the slow VWMA has a longer lookback period for smoothing. When short-term and long-term trends align in the same direction, the fast SMA crossing above the slow VWMA generates buy signals, while crossing below generates sell signals.

The strategy also sets up stop loss mechanisms. It cuts losses in time when price moves in unfavorable directions.

Advantage Analysis

Responds swiftly in tracing market trend changes
Good drawdown control with effective stop loss mechanisms
Simple and intuitive, easy to understand and implement
Optimizable parameters across varying market environments

Risk Analysis

Dual MA strategies tend to give false signals in bull markets
Inappropriate parameter tuning could lead to losses
Occasional flash crashes could cause losses

Risk Management:

Employ trend filtering indicators for confirmation
Optimize parameter settings
Adopt stop loss strategy to reasonably control single loss

Optimization Directions

The strategy can be enhanced in the following aspects:

Incorporate other indicators like RSI, Bollinger Bands to increase signal accuracy
Optimize length of moving averages across cycles
Combine volume indicators, trade at points with significant capital flows
Adjust parameters based on backtest results to find optimum
Employ dynamic stop loss, adjusting stops based on market volatility

Conclusion

In conclusion, this is a very practical trend following strategy. It uses intuitive dual moving average crossovers to generate trading signals, capturing trend changes effectively with the coordination of fast and slow moving averages. The stop loss mechanism also ensures good risk control. With complementary indicators and parameter optimization, the strategy can achieve even better trading performance.

Parameters

Name	Default	What it controls
v_input_1_close	0	Simple MA Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_2	6	Simple MA Length
v_input_3_high	0	VW MA Source: high \| close \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_4	7	VW MA Period
v_input_5	true	From Month
v_input_6	true	From Day
v_input_7	2018	From Year
v_input_8	true	To Month
v_input_9	true	To Day
v_input_10	9999	To Year
v_input_11	50	v_input_11
v_input_12	2	v_input_12
v_input_13	27	v_input_13
v_input_14	32.6	oversold
v_input_15	63	overbought

Source Pine Script

/*backtest
start: 2023-11-23 00:00:00
end: 2023-11-28 00:00:00
period: 15m
basePeriod: 5m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
//strategy(title="Bitlinc Entry v0.1 VWMA / SMA / MRSI SQQQ 94M", overlay=true, initial_capital=10000, currency='USD')

strategy(title="Bitlinc Entry v0.1 VWMA / SMA / MRSI SQQQ 94M", overlay=true)

// Credit goes to this developer for the "Date Range Code"
// https://www.tradingview.com/script/62hUcP6O-How-To-Set-Backtest-Date-Range/

// === GENERAL INPUTS ===
// short ma
maFastSource   = input(defval = close, title = "Simple MA Source")
maFastLength   = input(defval = 6, title = "Simple MA Length", minval = 1)
// long ma
maSlowSource   = input(defval = high, title = "VW MA Source")
maSlowLength   = input(defval = 7, title = "VW MA Period", minval = 1)


// === SERIES SETUP ===
// a couple of ma's...
maFast = sma(maFastSource, maFastLength)
maSlow = vwma(maSlowSource, maSlowLength)


// === PLOTTING ===
fast = plot(maFast, title = "Fast MA", color = color.green, linewidth = 2, style = plot.style_line, transp = 30)
slow = plot(maSlow, title = "Slow MA", color = color.red, linewidth = 2, style = plot.style_line, transp = 30)

// === INPUT BACKTEST RANGE ===
FromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12)
FromDay   = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
FromYear  = input(defval = 2018, title = "From Year", minval = 2017)
ToMonth   = input(defval = 1, title = "To Month", minval = 1, maxval = 12)
ToDay     = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
ToYear    = input(defval = 9999, title = "To Year", minval = 2017)

// === FUNCTION EXAMPLE ===
start     = timestamp(FromYear, FromMonth, FromDay, 00, 00)  // backtest start window
finish    = timestamp(ToYear, ToMonth, ToDay, 23, 59)        // backtest finish window
window()  => time >= start and time <= finish ? true : false // create function "within window of time"

// === LOGIC ===
enterLong = crossover(maFast, maSlow)
exitLong = crossover(maSlow, maFast)
//enterLong = crossover(maSlow, maFast)
//exitLong = crossover(maFast, maSlow)

// Entry //
strategy.entry(id="Long Entry", long=true, when=window() and enterLong)
strategy.entry(id="Short Entry", long=false, when=window() and exitLong)

// === FILL ====
fill(fast, slow, color = maFast > maSlow ? color.green : color.red)

// === MRSI ===
//
//

basis = rsi(close, input(50))

ma1 = ema(basis, input(2))
ma2 = ema(basis, input(27))

oversold = input(32.6)
overbought = input(63)

//plot(ma1, title="RSI EMA1", color=blue)
//plot(ma2, title="RSI EMA2", color=yellow)

obhist = ma1 >= overbought ? ma1 : overbought
oshist = ma1 <= oversold ? ma1 : oversold

//plot(obhist, title="Overbought Highligth", style=columns, color=color.maroon, histbase=overbought)
//plot(oshist, title="Oversold Highligth", style=columns, color=color.yellow, histbase=oversold)

//i1 = hline(oversold, title="Oversold Level", color=white)
//i2 = hline(overbought, title="Overbought Level", color=white)

//fill(i1, i2, color=olive, transp=100)

// === LOGIC ===
enterLongMrsi = crossover(ma1, oversold)
exitLongMrsi = crossover(ma1, overbought)

// Entry //
strategy.entry(id="MRSI Long Entry", long=true, when=window() and enterLongMrsi)
strategy.entry(id="MRSI Short Entry", long=false, when=window() and exitLongMrsi)

//hline(50, title="50 Level", color=white)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-01. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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