Dynamic Price Channel Trading Strategy

This article introduces a short-term trading strategy based on dynamic price channels. It judges trend direction by calculating price dynamic channels and trades at channel breakouts.

Pine ScriptBreakout Momentum Trend following SMA

Author: ChaoZhang
Complexity: Intermediate · 62 lines
Parameters: 7
Backtest bar: 2d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This article introduces a short-term trading strategy based on dynamic price channels. It judges trend direction by calculating price dynamic channels and trades at channel breakouts.

Strategy Logic

The strategy is based on the following logic:

Calculate dynamic price channels using highest and lowest prices. The upper band is the average of the highest price and channel midpoint. The lower band is the midpoint minus the difference between lowest price and midpoint.
When price breaks above the upper band, an uptrend begins. When price breaks below the lower band, a downtrend begins.
In uptrends, go long when two consecutive bearish bars appear. In downtrends, go short when two consecutive bullish bars appear.
Consider counter-trend entries to chase market momentum. For example, short in uptrends and long in downtrends.
Set take profit percentages, like x% of entry price, to lock in profits.

Advantage Analysis

The advantages of this strategy include:

The dynamic channels reflect market changes in real time for better trend judgment.
Combining trends and breakouts filters false breakouts.
Counter-trend entries capitalize on market momentum for excess returns.
Take profit stops effectively control risks.
The logic is simple and clear for easy implementation.

Risk Analysis

There are also some risks to consider:

Channels may fail during volatile markets. Adjust parameters for robustness.
Counter-trend trades are vulnerable to losses. Control loss size.
Fake breakouts can cause bad trades. Confirm validity with trends.
Avoid overtrading to control costs.

Conclusion

This strategy integrates dynamic channels, breakouts, and take profits. With proper tuning, it can be an effective short-term trading tool. But traders should note risk control and tailor it to their own styles.

Parameters

Name	Default	What it controls
v_input_1	true	Long
v_input_2	true	Short
v_input_3	false	take, %
v_input_4	false	Counter-trend entry
v_input_5	20	Period
v_input_6	true	Show Bands
v_input_7	true	Show Background

Source Pine Script

/*backtest
start: 2022-09-09 00:00:00
end: 2023-09-15 00:00:00
period: 2d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/


//@version=2
strategy("Noro's Bands Scalper Strategy v1.1", shorttitle = "Scalper str 1.1", 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, %")
needct = input(false, defval = false, title = "Counter-trend entry")
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
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
sma = sma(close, 20)
smatrend = close > sma ? 1 : close < sma ? -1 : smatrend[1]
trend = close < ld and high < hd ? -1 : close > hd and low > ld ? 1 : trend[1]

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

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

//Signals
bar = close > open ? 1 : close < open ? -1 : 0
up7 = trend == 1 and bar == -1 and bar[1] == -1 ? 1 : 0
dn7 = trend == 1 and bar == 1 and bar[1] == 1 and close > strategy.position_avg_price * (100 + takepercent) / 100 ? 1 : 0
up8 = trend == -1 and bar == -1 and bar[1] == -1 and close < strategy.position_avg_price * (100 - takepercent) / 100 ? 1 : 0
dn8 = trend == -1 and bar == 1 and bar[1] == 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 2023-09-16. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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