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Trend Following Grid Strategy

Author: ChaoZhang, Date: 2023-12-08 12:05:17
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Overview

This strategy is a trend following grid strategy that only goes long and does not go short, choosing time periods when the major trend is up. The default grid size is 1xATR, building 1, 2, 3 grid levels downward for chasing orders, and the 5th grid stops loss. When the empty position reaches the previous grid, the entire grid moves up to track the price.

Strategy Logic

  1. Use EMA lines to judge the major trend direction, EMA12 greater than EMA144 means the major trend is up
  2. Only open long positions when the major trend is up
  3. The default grid size is 1xATR, the multiplier can be adjusted
  4. Build 1, 2, 3 grid levels downward to track the price and open long positions separately
  5. Set the stop loss point at the 5th grid
  6. After opening positions, set stop loss points and take profit points
  7. Close positions when the price breaks through the take profit point on rise
  8. Close positions when the price hits the stop loss point on fall
  9. After all positions are closed, if the price breaks through the last grid again, recalculate the grid location and quantity to track upwards

This strategy combines EMA to determine the major trend direction and grid trading to track the price. It can obtain greater returns in an uptrend. The grid sets multiple price points to open positions separately, which reduces the risk per position. The stop loss and take profit settings lock in profits and also limit maximum losses. After all positions are closed, the strategy can recalculate new high levels of grids to open positions again, maximizing profits.

Advantage Analysis

  1. Use EMA to determine major trend direction, avoid opening positions against the trend
  2. Grid trading can open positions separately to reduce single position risk
  3. Stop loss and take profit lock in profits, control maximum losses
  4. After closing all positions, recalculating grids to continue chasing can expand profit space

The main advantage is combining trend trading and grid trading, which ensures the correctness of trend direction and also achieves risk dispersion of grid trading. In addition, recalculating grids after closing positions allows unlimited chasing, obtaining huge profits when there is a big rally.

Risk Analysis

  1. Major trend judgment may be wrong, entering in the wrong direction
  2. Significant sideways volatility that causes heavy losses in grids
  3. Stop loss triggered too fast, closing all positions
  4. Unable to re-enter optimal entry point after pullback

The main risk is the wrong judgment of major trend direction, which will lead to opening positions against the trend and huge losses. Also, if there is high sideways volatility with multiple grids being trapped, losses would be exacerbated. In addition, fast price drops may trigger stop loss and close all positions, losing subsequent profit opportunities. It would be hard to re-enter initial optimal grid levels after pullbacks.

Accuracy of major trend judgment can be improved by optimizing EMA parameters. Adjusting grid interval and size of first entry can also control overall losses. Stop loss position needs to consider market volatility frequency. Also, profit taking can be considered for partial positions instead of closing all positions.

Optimization Directions

This strategy can also be optimized in the following aspects:

  1. Optimize EMA parameters to improve accuracy of major trend judgment
  2. Adjust grid intervals and quantities to optimize risk-reward ratio
  3. Improve stop loss and take profit logic, e.g. partial take profit, trailing stop loss etc
  4. Add more restrictions on re-entry conditions to avoid premature re-entry during pullbacks
  5. Incorporate more indicators to determine optimal entry timing, e.g. candlestick patterns, indicator sensitivity etc
  6. Add outlier detection to avoid huge losses in anomalous market conditions

With these optimization measures, the strategy can obtain greater profits during significant trends, while also controlling risks and reducing losses in normal sideways volatility.

Summary

This strategy combines trend trading and grid trading organically. It uses EMA to determine major direction and uses grid trading to open positions separately for chasing trends. With proper risk management including stop loss, take profit and grid recalculation mechanisms, this strategy can produce decent profits during major trends, while also controlling risks. Further optimizations on parameters and judgment accuracy can lead to higher profits. It is worth detailed testing and optimization for live trading.

/*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/
// © zxcvbnm3260

//@version=5
strategy("grid strategy long", overlay=true)


// 版本更新记录：
// v1.0 2021/11/09 只做多、不做空，选择大趋势向上的时间段。网格大小默认为1倍ATR，往下1、2、3个网格吃单，第5个网格止损。空仓时到达往上一个网格则网格整体抬升。（Only go long, not short, choose a time period when the general trend is up. The default grid size is 1x ATR, the next one, two, and three grids will take orders, and the fifth grid will stop loss. When the empty position reaches the upper grid, the grid as a whole rises.）


X_ATR = input.float(title='网格大小是多少倍ATR？', defval = 1)


// 1.基础变量
ema169 = ta.ema(close, 169)
ema144 = ta.ema(close, 144)
ema12 = ta.ema(close, 12)

ema576 = ta.ema(close, 576)
ema676 = ta.ema(close, 676)

plot(ema169, color=color.new(color.orange, 0), linewidth=2)
// plot(ema144, color=color.orange)
plot(ema12,  color=color.blue)
// plot(ema676, color=color.orange, linewidth=1)

mtr = math.max(high - low, math.abs(close[1] - high), math.abs(close[1] - low))
atr = ta.ema(mtr, 30)

is_0930 = hour(time, 'GMT-4') == 9  and minute(time, 'GMT-4') == 30
is_1500 = hour(time, 'GMT-4') == 15 and minute(time, 'GMT-4') == 00
is_1530 = hour(time, 'GMT-4') == 15 and minute(time, 'GMT-4') == 30

is_yangxian = close>open
is_yinxian = close<open

// 2.基本趋势标记

big_trend  = ema12 >= ema169 ? 1 : 0
big_trend2 = ema12 <= ema169 ? 1 : 0

// 背景的变色处理：
bgcolor(big_trend == 1 ? color.new(color.green, 90) : color.new(color.red, 90) )

// 3.网格点位初始化

grid_size = atr * X_ATR // 网格大小
        
price_entry1 = open - grid_size*1
price_entry2 = open - grid_size*2
price_entry3 = open - grid_size*3
price_stop_loss = open - grid_size*5

price_exit1 = price_entry1 + grid_size*1
price_exit2 = price_entry2 + grid_size*1
price_exit3 = price_entry3 + grid_size*1

qty1 = int(1000/price_entry1)
qty2 = int(1000/price_entry2)
qty3 = int(1000/price_entry3)


// 标出各种点位
slm_lines_time(time, price_entry1, price_entry2, price_entry3, price_stop_loss, price_exit1)=>
    time2 = time + 1000*3600*24*5
    line.new(time, price_stop_loss, time2, price_stop_loss, color=color.red, xloc = xloc.bar_time, width=2)  // 止损位
    line.new(time, price_entry1, time2, price_entry1, color=color.green, xloc = xloc.bar_time)  // 
    line.new(time, price_entry2, time2, price_entry2, color=color.green, xloc = xloc.bar_time)  // 
    line.new(time, price_entry3, time2, price_entry3, color=color.green, xloc = xloc.bar_time)  // 
    line.new(time, price_exit1,  time2, price_exit1,  color=color.green, xloc = xloc.bar_time, width=2)  // 

slm_lines(time, price_entry1, price_entry2, price_entry3, price_stop_loss, price_exit1)=>
    line.new(bar_index, price_stop_loss, bar_index[5], price_stop_loss, color=color.red, xloc = xloc.bar_index, width=2)  // 止损位
    line.new(bar_index, price_entry1, bar_index[5], price_entry1, color=color.green, xloc = xloc.bar_index)  // 
    line.new(bar_index, price_entry2, bar_index[5], price_entry2, color=color.green, xloc = xloc.bar_index)  // 
    line.new(bar_index, price_entry3, bar_index[5], price_entry3, color=color.green, xloc = xloc.bar_index)  // 
    line.new(bar_index, price_exit1,  bar_index[5], price_exit1,  color=color.green, xloc = xloc.bar_index, width=2)  // 


// 4.网格点位更新和下单

is_entry0 = big_trend==1 and year>=2020

var is_entry = false

// 未进场时：
if is_entry0 and not is_entry
    is_entry := true
    
    grid_size := atr * X_ATR // 网格大小
    
    price_entry1 := close - grid_size*1
    price_entry2 := close - grid_size*2
    price_entry3 := close - grid_size*3
    price_stop_loss := close - grid_size*5
    
    price_exit1 := price_entry1 + grid_size*1
    price_exit2 := price_entry2 + grid_size*1
    price_exit3 := price_entry3 + grid_size*1
    
    qty1 := int(1000/price_entry1)
    qty2 := int(1000/price_entry2)
    qty3 := int(1000/price_entry3)
    
    // slm_lines(time, price_entry1, price_entry2, price_entry3, price_stop_loss, price_exit1)
    
    strategy.entry("open1", strategy.long, qty1, limit = price_entry1)
    strategy.entry("open2", strategy.long, qty2, limit = price_entry2)
    strategy.entry("open3", strategy.long, qty3, limit = price_entry3)
    
    strategy.exit("close1", qty = qty1, limit = price_exit1, stop = price_stop_loss)
    strategy.exit("close2", qty = qty2, limit = price_exit2, stop = price_stop_loss)
    strategy.exit("close3", qty = qty3, limit = price_exit3, stop = price_stop_loss)

// 已进场的各类情况

// 1.止损
if is_entry and close <= price_stop_loss
    strategy.close_all()
    is_entry := false

// 2.网格抬升
if is_entry and close >= price_exit1
    is_entry := false
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