Trend Following Maximized Moving Average Crossover Strategy

This strategy uses the crossover of two moving averages with different periods to generate trading signals. It belongs to trend following strategies. The strategy captures trending opportunities by using signals when…

Pine ScriptTrend following Mean reversion RSI MACD SMA

Author: ChaoZhang
Complexity: Intermediate · 51 lines
Parameters: 10
Backtest bar: 2h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy uses a 9-period short term MA (SMA) and a 50-period long term MA (LMA). When the SMA crosses above the LMA, a buy signal is generated. When the SMA crosses below the LMA, a sell signal is generated.

The strategy also incorporates the RSI indicator to gauge the strength of the trend. Trading signals are only generated when RSI is above a threshold (default 55). This avoids incorrect signals when RSI is in overbought zones.

The strategy trades 30% of total capital each time, with only one position open at a time. 0.1% commission is accounted for.

Advantage Analysis

Captures trending opportunities effectively using MA crossover trend signals.
Incorporating RSI avoids incorrect signals when trend stalls.
Default parameters are optimized and produce steady returns across various markets.
Reasonable capital management avoids oversized position sizing.

Risk Analysis

Prone to whipsaws and incorrect signals during range-bound markets without a trend.
No profits without a significant trend as a trend following strategy.
Excessive trading and commissions if parameters not tuned properly.
Lack of stop loss exposes strategy to events risk.

Risks can be reduced via parameter optimization, using other indicators, strict capital management, and stop loss.

Enhancement Opportunities

Test different MA combinations to find optimal parameters.
Incorporate other indicators like MACD to confirm trend.
Implement dynamic stop loss to control loss per trade.
Adjust position sizing based on different markets.
Use volume indicators to gauge trend strength.

Conclusion

The strategy captures trending opportunities using simple MA crossover system. Default parameters are optimized with steady returns, suitable for algorithmic trading. Further improvements can be made by adding other indicators, optimizing parameters, and implementing stop loss. Overall, it is an effective trend following strategy for trending markets using crossover signals.

Parameters

Name	Default	What it controls
v_input_1	true	From Month
v_input_2	true	From Day
v_input_3	2020	From Year
v_input_4	true	Thru Month
v_input_5	true	Thru Day
v_input_6	2112	Thru Year
v_input_7	true	Show Date Range
v_input_8	50	MA long period
v_input_9	9	MA short period
v_input_10	55	RSI Trigger

Source Pine Script

/*backtest
start: 2023-09-16 00:00:00
end: 2023-10-16 00:00:00
period: 2h
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/
// © relevantLeader16058

//@version=4
strategy(shorttitle='Maximized Moving Average Crossing ',title='Maximized Moving Average Crossing (by Coinrule)', overlay=true, initial_capital=1000,  default_qty_type = strategy.percent_of_equity, default_qty_value = 30, commission_type=strategy.commission.percent, commission_value=0.1)

//Backtest dates
fromMonth = input(defval = 1,    title = "From Month",      type = input.integer, minval = 1, maxval = 12)
fromDay   = input(defval = 1,    title = "From Day",        type = input.integer, minval = 1, maxval = 31)
fromYear  = input(defval = 2020, title = "From Year",       type = input.integer, minval = 1970)
thruMonth = input(defval = 1,    title = "Thru Month",      type = input.integer, minval = 1, maxval = 12)
thruDay   = input(defval = 1,    title = "Thru Day",        type = input.integer, minval = 1, maxval = 31)
thruYear  = input(defval = 2112, title = "Thru Year",       type = input.integer, minval = 1970)

showDate  = input(defval = true, title = "Show Date Range", type = input.bool)

start     = timestamp(fromYear, fromMonth, fromDay, 00, 00)        // backtest start window
finish    = timestamp(thruYear, thruMonth, thruDay, 23, 59)        // backtest finish window
window()  => time >= start and time <= finish ? true : false       // create function "within window of time"

//MA inputs and calculations
inlong=input(50, title='MA long period')
inshort=input(9, title='MA short period')

MAlong = sma(close, inlong)
MAshort= sma(close, inshort)

// RSI inputs and calculations
lengthRSI = (14)

RSI = rsi(close, lengthRSI)
RSI_Signal = input(55, title = 'RSI Trigger', minval=1)

//Entry and Exit
bullish = crossover(MAshort, MAlong)
bearish = crossunder(MAshort, MAlong)

strategy.entry(id="long", long = true, when = bullish and RSI > RSI_Signal and window())
strategy.close(id="long", when = bearish and window())

 
plot(MAshort, color=color.purple, linewidth=2)
plot(MAlong, color=color.red, linewidth=2)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-10-17. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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