Moving Average Crossover Strategy 434701

Pine ScriptTrend following Volatility MACD SMA

Author: ChaoZhang
Complexity: Starter · 42 lines
Parameters: 3
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

This strategy adopts the crossover of 20-day moving average and 60-day moving average to generate trading signals. It goes long when price breaks above 20-day MA and closes position when price breaks below 20-day MA. Similarly, it forms trading signals when price crosses 60-day MA. This strategy belongs to a typical trend following system.

Strategy Logic

Calculate 20-day simple moving average and 60-day simple moving average
Go long when closing price breaks above 20-day MA
Close position when closing price breaks below 20-day MA
Go long when closing price breaks above 60-day MA
Close position when closing price breaks below 60-day MA

The above rules define the trading signals and logic for this strategy. When price crosses over the MA line, it shows a new trend is emerging and we can follow the trend to go long. When price drops below the MA line, it shows the trend is ending so we close position.

Advantages

Adopting double MAs makes the strategy more steady. The 20-day MA captures short-term opportunities faster while the 60-day MA filters out some market noises and locks in medium-long term trend.
The backtest starts from 2018 and selects Taiwan stock market, which has more developed trading system compared to China A-share market, better reflecting the strategy efficacy.
It sets proper stop loss and position sizing, maximally controlling the risk.

Risks

The strategy solely relies on MA indicator. It may generate more whipsaws when there is no obvious trend in the market.
The strategy does not optimize the buy/sell size and position, failing to maximize the capital usage.
The strategy reacts symmetrically to price ups and downs, unable to adapt to different market conditions.

Risk Solutions:

Add other indicators like KDJ, MACD to form multiple confirmation, avoiding wrong trades.
Optimize position sizing and capital usage efficiency according to market cap, volatility etc.
Adopt asymmetric moves based on market stages, reduce trading during range-bound market and increase position size during obvious trend.

Optimization Directions

Optimize buy/sell quantity. Dynamically adjust position size based on stop loss.
Optimize MA parameters. Find better parameters through walk forward optimization and random optimization.
Add stop loss strategy. Moving stop loss or stop limit order better protects profits.
Add position sizing management. Dynamically adjust position size per trade based on capital size, market cap etc.

Summary

This is a typical dual moving average crossover strategy. The core idea is to follow trends by establishing position when price crosses over MA line. The strategy is simple and practical to implement. Meanwhile, there is room for further optimization, by parameter tuning, stop loss, position sizing etc. to achieve better results.

Parameters

Name	Default	What it controls
v_input_1	2018	backtest_year
v_input_int_1	true	backtest_month
v_input_int_2	true	backtest_day

Source Pine Script

/*backtest
start: 2022-12-01 00:00:00
end: 2023-12-07 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/
// © Astorhsu

//@version=5
strategy("Astor SMA20/60 TW", overlay=true, margin_long=100, margin_short=100)
backtest_year = input(2018, title='backtest_year') //Backtest start year
backtest_month = input.int(01, title='backtest_month', minval=1, maxval=12) //Backtest start month
backtest_day = input.int(01, title='backtest_day', minval=1, maxval=31)  //Backtest start day
start_time = timestamp(backtest_year, backtest_month, backtest_day, 00, 00)  //Time function for the start of backtesting

//Indicators
sma20 = ta.sma(close,20)
sma60 = ta.sma(close,60)
plot(sma20, color=color.green, title="sma(20)")
plot(sma60, color=color.red, title="sma(60)")

//Entry Conditions
longCondition = ta.crossover(close, ta.sma(close, 20))
if (longCondition) and time >= start_time
    strategy.entry("open long20", strategy.long, qty=1, comment="On the Sitem20go long")


shortCondition = ta.crossunder(close, ta.sma(close, 20))
if (shortCondition) and time >= start_time
    strategy.close("open long20",comment="Break belowm20Close Position", qty=1)     
    
longCondition1 = ta.crossover(close, ta.sma(close, 60))
if (longCondition1) and time >= start_time
    strategy.entry("open long60", strategy.long, qty=1, comment="On the Sitem60go long")


shortCondition1 = ta.crossunder(close, ta.sma(close, 60))
if (shortCondition1) and time >= start_time
    strategy.close("open long60",comment="Break belowm60Close Position", qty=1)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-08. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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