Trend Following Strategy Based on Volume-weighted Average Price and Volatility

Author: ChaoZhang, Date: 2023-09-21 21:32:40


This strategy integrates multiple indicators including volume-weighted average price, Bollinger Bands and time segmented volume to identify the start and end of price trends and follow trends. The multiple confirmations can effectively filter false breakouts.

Strategy Logic

The strategy involves the following key steps:

  1. Calculate fast and slow volume-weighted average price lines. VWAP instead of close price is used to better reflect actual trading price.

  2. Take the average of the VWAP lines to plot Bollinger Bands. Expanding volatility shown by bands suggests a trend start.

  3. Introduce time segmented volume (TSV) to confirm increasing trading volume and validate the trend.

  4. Generate buy signal when fast VWAP crosses above slow VWAP, price breaks above Bollinger upper band, and TSV is positive. Sell signal when reverse occurs.

  5. Use VWAP pullback and Bollinger lower band as stop loss signals.


  • Multiple confirmations effectively filter false breakouts and identify trend start

  • VWAP calculation reflects actual trading price better

  • Volatility indicator judges if a trend is present

  • Trading volume confirms trend continuation

  • Reasonable stop loss and take profit controls risk

  • Configurable parameters allow flexible optimization


  • Difficulty in optimizing multiple indicators

  • Lagging nature of VWAP and Bollinger Bands delays stop loss

  • TSV sensitive to parameter tuning for different markets

  • More false signals in range-bound markets

  • Ignores trading costs, actual P&L weaker than backtest


  • Apply machine learning to auto optimize parameter combinations

  • Set dynamic or trailing stop loss to better lock in profits

  • Add volume momentum indicators to avoid divergence

  • Incorporate Elliott Waves to determine trend stages, adjust parameters accordingly

  • Consider trading costs, set minimum profit target to control cost efficiency


This strategy provides good trend identification by integrating multiple indicators. It can effectively determine the start and end of real trends. Further improvements in stability can be achieved through parameter optimization, stop loss optimization and filter optimization. But overall, as a trend following strategy, it still carries certain levels of drawdown and risk-reward ratios. Traders need patience to wait for opportunities and strict risk management mindset.

start: 2022-09-14 00:00:00
end: 2023-09-20 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]

// @version=4

// Credits

// "Vwap with period" code which used in this strategy to calculate the leadLine was written by "neolao" active on
// "TSV" code which used in this strategy was written by "liw0" active on The code is corrected by "vitelot" December 2018.

strategy("HYE Trend Hunter [Strategy]", overlay = true, initial_capital = 1000, default_qty_value = 100, default_qty_type = strategy.percent_of_equity, commission_value = 0.025, pyramiding = 0)
// Strategy inputs 

slowtenkansenPeriod = input(9, minval=1, title="Slow Tenkan Sen VWAP Line Length", group = "Tenkansen / Kijunsen")
slowkijunsenPeriod = input(26, minval=1, title="Slow Kijun Sen VWAP Line Length", group = "Tenkansen / Kijunsen")
fasttenkansenPeriod = input(5, minval=1, title="Fast Tenkan Sen VWAP Line Length", group = "Tenkansen / Kijunsen")
fastkijunsenPeriod = input(13, minval=1, title="Fast Kijun Sen VWAP Line Length", group = "Tenkansen / Kijunsen")
BBlength = input(20, minval=1, title= "Bollinger Band Length", group = "Bollinger Bands")
BBmult = input(2.0, minval=0.001, maxval=50, title="Bollinger Band StdDev", group = "Bollinger Bands")
tsvlength  = input(13, minval=1, title="TSV Length", group = "Tıme Segmented Volume")
tsvemaperiod = input(7, minval=1, title="TSV Ema Length", group = "Tıme Segmented Volume")

// Make input options that configure backtest date range  
startDate = input(title="Start Date", type=input.integer,
     defval=1, minval=1, maxval=31, group = "Backtest Range")
startMonth = input(title="Start Month", type=input.integer,
     defval=1, minval=1, maxval=12, group = "Backtest Range")
startYear = input(title="Start Year", type=input.integer,
     defval=2000, minval=1800, maxval=2100, group = "Backtest Range")

endDate = input(title="End Date", type=input.integer, 
     defval=31, minval=1, maxval=31, group = "Backtest Range")
endMonth = input(title="End Month", type=input.integer,
     defval=12, minval=1, maxval=12, group = "Backtest Range") 
endYear = input(title="End Year", type=input.integer,
     defval=2021, minval=1800, maxval=2100, group = "Backtest Range")
inDateRange =  true

//Slow Tenkan Sen Calculation

typicalPriceTS = (high + low + close) / 3
typicalPriceVolumeTS = typicalPriceTS * volume
cumulativeTypicalPriceVolumeTS = sum(typicalPriceVolumeTS, slowtenkansenPeriod)
cumulativeVolumeTS = sum(volume, slowtenkansenPeriod)
slowtenkansenvwapValue = cumulativeTypicalPriceVolumeTS / cumulativeVolumeTS

//Slow Kijun Sen Calculation

typicalPriceKS = (high + low + close) / 3
typicalPriceVolumeKS = typicalPriceKS * volume
cumulativeTypicalPriceVolumeKS = sum(typicalPriceVolumeKS, slowkijunsenPeriod)
cumulativeVolumeKS = sum(volume, slowkijunsenPeriod)
slowkijunsenvwapValue = cumulativeTypicalPriceVolumeKS / cumulativeVolumeKS

//Fast Tenkan Sen Calculation

typicalPriceTF = (high + low + close) / 3
typicalPriceVolumeTF = typicalPriceTF * volume
cumulativeTypicalPriceVolumeTF = sum(typicalPriceVolumeTF, fasttenkansenPeriod)
cumulativeVolumeTF = sum(volume, fasttenkansenPeriod)
fasttenkansenvwapValue = cumulativeTypicalPriceVolumeTF / cumulativeVolumeTF

//Fast Kijun Sen Calculation

typicalPriceKF = (high + low + close) / 3
typicalPriceVolumeKF = typicalPriceKS * volume
cumulativeTypicalPriceVolumeKF = sum(typicalPriceVolumeKF, fastkijunsenPeriod)
cumulativeVolumeKF = sum(volume, fastkijunsenPeriod)
fastkijunsenvwapValue = cumulativeTypicalPriceVolumeKF / cumulativeVolumeKF

//Slow LeadLine Calculation
lowesttenkansen_s = lowest(slowtenkansenvwapValue, slowtenkansenPeriod)
highesttenkansen_s = highest(slowtenkansenvwapValue, slowtenkansenPeriod)

lowestkijunsen_s = lowest(slowkijunsenvwapValue, slowkijunsenPeriod)
highestkijunsen_s = highest(slowkijunsenvwapValue, slowkijunsenPeriod)

slowtenkansen = avg(lowesttenkansen_s, highesttenkansen_s)
slowkijunsen = avg(lowestkijunsen_s, highestkijunsen_s)
slowleadLine = avg(slowtenkansen, slowkijunsen)

//Fast LeadLine Calculation
lowesttenkansen_f = lowest(fasttenkansenvwapValue, fasttenkansenPeriod)
highesttenkansen_f = highest(fasttenkansenvwapValue, fasttenkansenPeriod)

lowestkijunsen_f = lowest(fastkijunsenvwapValue, fastkijunsenPeriod)
highestkijunsen_f = highest(fastkijunsenvwapValue, fastkijunsenPeriod)

fasttenkansen = avg(lowesttenkansen_f, highesttenkansen_f)
fastkijunsen = avg(lowestkijunsen_f, highestkijunsen_f)
fastleadLine = avg(fasttenkansen, fastkijunsen)

// BBleadLine Calculation

BBleadLine = avg(fastleadLine, slowleadLine)

// Bollinger Band Calculation
basis = sma(BBleadLine, BBlength)
dev = BBmult * stdev(BBleadLine, BBlength)
upper = basis + dev
lower = basis - dev

// TSV Calculation

tsv = sum(close>close[1]?volume*(close-close[1]):close<close[1]?volume*(close-close[1]):0,tsvlength)
tsvema = ema(tsv, tsvemaperiod)

// Rules for Entry & Exit  

if(fastleadLine > fastleadLine[1] and slowleadLine > slowleadLine[1] and tsv > 0 and tsv > tsvema and close > upper and inDateRange)
    strategy.entry("BUY", strategy.long)
if(fastleadLine < fastleadLine[1] and slowleadLine < slowleadLine[1])

// Plots 

colorsettingS = input(title="Solid Color Slow Leadline", defval=false, type=input.bool)
plot(slowleadLine, title = "Slow LeadLine", color = colorsettingS ? color.aqua : slowleadLine > slowleadLine[1] ? :, linewidth=3)

colorsettingF = input(title="Solid Color Fast Leadline", defval=false, type=input.bool)
plot(fastleadLine, title = "Fast LeadLine", color = colorsettingF ? : fastleadLine > fastleadLine[1] ? :, linewidth=3)

p1 = plot(upper, "Upper BB", color=#2962FF)
p2 = plot(lower, "Lower BB", color=#2962FF)
fill(p1, p2, title = "Background",