Price Channel Trend Following Strategy

Author: ChaoZhang, Date: 2024-01-08 11:05:11



This strategy is a trend following strategy based on the price channel principle. It calculates the highest and lowest prices over a certain historical period to form a price channel, and uses the channel boundaries as buy and sell signals to track price trends.

Strategy Logic

The core idea of the price channel strategy is: when the stock price is in an upward trend, it will break through the historical high; when it is in a downward trend, it will break through the historical low. Therefore, a price channel can be constructed based on the highest and lowest prices over a certain historical period (such as 21 days). The upper and lower rails of the channel serve as buy and sell signals respectively.

Specifically, this strategy uses the highest() and lowest() functions to calculate the highest and lowest prices over the most recent 21 days to form a price channel. If the closing price of the day is higher than the 21-day high (i.e. breaking through the upper rail of the channel), a buy signal is generated. If the closing price is lower than the 21-day low (i.e. breaking through the lower rail), a sell signal is generated.

In addition, the strategy also checks for gaps to judge potential trend reversals. If there is a down gap, the price channel will be set to red to hedge risks. If there is an up gap, it will be set to green.

Advantage Analysis

The main advantages of the price channel strategy are:

  1. The strategy logic is simple, easy to understand and implement
  2. Can effectively identify price trends of stocks and track trends in a timely manner
  3. Reduces transaction costs by generating signals through breakouts
  4. The price channel can play the role of stop loss
  5. Checking for gaps indicates possible trend changes

Risk Analysis

There are also some risks with this strategy:

  1. It only relies on price data, ignoring other fundamentals, technical indicators, etc.
  2. Improper settings of the channel parameters could lead to over-aggressiveness or over-conservativeness
  3. Breakout buys can face pullback risks causing a stop loss
  4. It does not consider the impact of price volatility and liquidity
  5. Differences across industries and individual stocks are not taken into account

To overcome these risks, the following optimizations could be considered:

  1. Incorporate key technical indicators to avoid wrong signals
  2. Add adaptive channel parameter algorithms
  3. Use moving averages to judge trend persistence
  4. Set channel width factors to correct different volatility levels
  5. Distinguish parameters by industry and concepts

Optimization Directions

The main directions to optimize this strategy include:

  1. Optimize price channel parameter calculations, e.g. adaptive channels, volatility channels, etc.
  2. Incorporate other technical indicators to improve signal accuracy
  3. Add stop loss and take profit strategies to control risks and lock in profits
  4. Set dynamic parameters across industries and individual stocks
  5. Enhance strategy by incorporating fundamentals and event drives
  6. Apply machine learning algorithms for adaptive optimization and condition judgment


The price channel strategy builds a simple channel using historical peaks and troughs and uses the channel boundaries as trading signals. It is a typical trend following strategy that is easy to understand and implement and can effectively track price trends, with the price channel serving as a stop loss mechanism. However there are also risks with this strategy. The main optimization dimensions include parameter tuning, combining other indicators, implementing stop loss/profit taking, dynamic parameterization, etc. Overall, the price channel strategy provides a simple and practical trend following framework for quantitative trading, but needs further enhancements and optimizations to achieve better performance in live trading.

start: 2023-01-01 00:00:00
end: 2024-01-07 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]

//  作品: [LunaOwl] 樂活投資:價格通道
//  英文: [LunaOwl] LOHAS Investor - PriceChannel
//     ~~!!*(๑╹◡╹๑) **      //
//  製作: @LunaOwl 彭彭      //
//  一版: 2019年12月07日     //
//  二版: 2019年12月09日     //
//  介紹:
//--1) 設定溫和的投資報酬率期望
//--2) 使用適合的選股方式建立投資組合,減少單一股票的失誤率
//--3) 使用簡單的進出場策略,規律的執行它
//--4) 財富依靠時間積累,每天學習

strategy("[LunaOwl] 價格通道",
     initial_capital = 10000, commission_value = 0.07, 
     default_qty_type = strategy.percent_of_equity,
     default_qty_value = 50, overlay = true,
     calc_on_order_fills = true


Channel_Price  = input(close, title = "通道價格")
Channel_Length = input(21, title = "通道回溯長度")
Channel_High = highest(high, Channel_Length)
Channel_Low  = lowest(low, Channel_Length)

gapUp   = (low > high[1])
gapDown = (high < low[1])

BackgroundColour = (gapUp == true) ? :
                   (gapDown == true) ? : na
bgcolor(BackgroundColour, transp=60)

BorderlineA = plot(Channel_High, title = "通道上線", color =, style = plot.style_line)
BorderlineB = plot(Channel_Low, title = "通道下線", color =, style = plot.style_line)
fill(BorderlineA, BorderlineB, title = "通道底色", color = color.gray, transp = 85)

Long_entry = close >= Channel_High
Long_close_all = close <= Channel_Low

if (not na(close[Channel_Length]))
    strategy.entry("買入", strategy.long, comment = "高於近期", stop = Channel_High)
    strategy.entry("賣出", strategy.short, comment = "低於近期", stop = Channel_Low)