Single Side Trend Shock Breakout Strategy

The Single Side Trend Shock Breakout Strategy is a breakout strategy that utilizes price channels and trend judgment. It aims to identify trend direction, enter on breakouts during range-bound periods, and exit when…

Pine ScriptBreakout Trend following Mean reversion EMA SMA

Author: ChaoZhang
Complexity: Intermediate · 75 lines
Parameters: 10
Backtest bar: 3m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy calculates upper and lower bands of a price channel using highest and lowest prices over a recent N periods. It then computes a price midline. Distances between prices and midline are averaged to obtain the channel bands.

For trend detection, the strategy checks if recent candles all close above (bullish) or below (bearish) the channel. Upon trend confirmation, it awaits price shocks near the bands and enters in reverse direction.

Body breakouts supplement the entry signals when body length exceeds a multiple of average body length. The strategy sets a profit target after entry and takes profit when price reaches it.

Advantage Analysis

The main advantages of this strategy are:

Price channel filters reduce false breakout risks
Reverse entries profit from trend shocks
Body breakouts improve entry accuracy
Profit target allows taking gains actively

Risk Analysis

There are also some risks:

Improper channel parameter may widen/narrow the channel excessively
Reversals against strong trends can lead to large losses
Body breakouts tend to generate false signals on tops
Rigid profit target may leave profits on the table

These can be addressed via parameter tuning, avoiding reversals during strong trends, optimizing exit logic etc.

Enhancement Opportunities

Some ways to improve the strategy:

Add trend indicators to confirm trends
Optimize body breakout parameters to reduce false signals
Additional filters on entry timing
Dynamic adjustment of profit target

Conclusion

The Single Side Trend Shock Breakout Strategy profits from breakouts against the trend in ranging periods. It has the advantage of trend identification and active profit-taking, but also has some risks. These risks can be reduced through multi-factor confirmation, parameter optimization etc. The strategy suits short-term trading and can complement trend-following strategies.

Parameters

Name	Default	What it controls
v_input_1	true	Long
v_input_2	true	Short
v_input_3	false	take, %
v_input_4	true	Bands Entry
v_input_5	false	Counter-trend entry
v_input_6	10	Body length
v_input_7	true	Trend bars
v_input_8	20	Period
v_input_9	true	Show Bands
v_input_10	true	Show Background

Source Pine Script

/*backtest
start: 2024-01-10 00:00:00
end: 2024-01-17 00:00:00
period: 3m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/


//@version=2
strategy("Noro's Bands Scalper Strategy v1.5", shorttitle = "Scalper str 1.5", overlay=true, default_qty_type = strategy.percent_of_equity, default_qty_value=100.0, pyramiding=0)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
takepercent = input(0, defval = 0, minval = 0, maxval = 1000, title = "take, %")
needbe = input(true, defval = true, title = "Bands Entry")
needct = input(false, defval = false, title = "Counter-trend entry")
bodylen = input(10, defval = 10, minval = 0, maxval = 50, title = "Body length")
trb = input(1, defval = 1, minval = 1, maxval = 5, title = "Trend bars")
len = input(20, defval = 20, minval = 2, maxval = 200, title = "Period")
needbb = input(true, defval = true, title = "Show Bands")
needbg = input(true, defval = true, title = "Show Background")
src = close

//PriceChannel 1
lasthigh = highest(src, len)
lastlow = lowest(src, len)
center = (lasthigh + lastlow) / 2

//Distance
dist = abs(src - center)
distsma = sma(dist, len)
hd = center + distsma
ld = center - distsma
hd2 = center + distsma * 2
ld2 = center - distsma * 2

//Trend
chd = close > hd
cld = close < ld
uptrend = trb == 1 and chd ? 1 : trb == 2 and chd and chd[1] ? 1 : trb == 3 and chd and chd[1] and chd[2] ? 1 : trb == 4 and chd and chd[1] and chd[2] and chd[3] ? 1 : trb == 5 and chd and chd[1] and chd[2] and chd[3] and chd[4] ? 1 : 0
dntrend = trb == 1 and cld ? 1 : trb == 2 and cld and cld[1] ? 1 : trb == 3 and cld and cld[1] and cld[2] ? 1 : trb == 4 and cld and cld[1] and cld[2] and cld[3] ? 1 : trb == 5 and cld and cld[1] and cld[2] and cld[3] and cld[4] ? 1 : 0
trend = dntrend == 1 and high < center ? -1 : uptrend == 1 and low > center ? 1 : trend[1]

//trend = close < ld and high < center ? -1 : close > hd and low > center ? 1 : trend[1]

//Lines
colo = needbb == false ? na : black
plot(hd2, color = colo, linewidth = 1, transp = 0, title = "High band 2")
plot(hd, color = colo, linewidth = 1, transp = 0, title = "High band 1")
plot(center, color = colo, linewidth = 1, transp = 0, title = "center")
plot(ld, color = colo, linewidth = 1, transp = 0, title = "Low band 1")
plot(ld2, color = colo, linewidth = 1, transp = 0, title = "Low band 2")

//Background
col = needbg == false ? na : trend == 1 ? lime : red
bgcolor(col, transp = 80)

//Body
body = abs(close - open)
smabody = ema(body, 30) / 10 * bodylen

//Signals
bar = close > open ? 1 : close < open ? -1 : 0
up7 = trend == 1 and ((bar == -1 and bar[1] == -1) or (body > smabody and bar == -1)) ? 1 : 0
dn7 = trend == 1 and ((bar == 1 and bar[1] == 1) or (close > hd and needbe == true)) and close > strategy.position_avg_price * (100 + takepercent) / 100 ? 1 : 0
up8 = trend == -1 and ((bar == -1 and bar[1] == -1) or (close < ld2 and needbe == true)) and close < strategy.position_avg_price * (100 - takepercent) / 100 ? 1 : 0
dn8 = trend == -1 and ((bar == 1 and bar[1] == 1) or (body > smabody and bar == 1)) ? 1 : 0

if up7 == 1 or up8 == 1 
    strategy.entry("Long", strategy.long, needlong == false ? 0 : trend == -1 and needct == false ? 0 : na)

if dn7 == 1 or dn8 == 1
    strategy.entry("Short", strategy.short, needshort == false ? 0 : trend == 1 and needct == false ? 0 : na)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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