This code snippet demonstrates how to calculate a weighted average of trend durations in financial markets, emphasizing trends with smaller price movements. The weighting is based on both the duration and the price difference of each trend.

// --- settings
SignalPeriod = 12
ArrowPeriod = 2
xTrendDurationAverage = 10
// --- end of settings

bbup = average[signalperiod]+std[signalperiod]*arrowperiod
bbdn = average[signalperiod]-std[signalperiod]*arrowperiod

if ts=0 then
    if close crosses over bbup then
        ts=bbdn
        trend=1
        startPrice = close
    elsif close crosses under bbdn then
        ts=bbup
        trend=-1
        startPrice = close
    endif
endif

if trend=1 then
    ts=max(ts,bbdn)
elsif trend=-1 then
    ts=min(ts,bbup)
endif

if trend=1 and close crosses under ts then
    trend=-1
    ts=bbup
    t=t+1 //trend count
    $bardiff[t]=barindex-lastbarindex //trend duration in bars
    $pricediff[t]=abs(close-startPrice) //price movement
    startPrice=close
    lastbarindex=barindex
endif

if trend=-1 and close crosses over ts then
    trend=1
    ts=bbdn
    t=t+1 //trend count
    $bardiff[t]=barindex-lastbarindex //trend duration in bars
    $pricediff[t]=abs(close-startPrice) //price movement
    startPrice=close
    lastbarindex=barindex
endif

//weighted average of trend duration
if t>xTrendDurationAverage then
    diff=0
    totalWeight=0
    for i = t downto t-xTrendDurationAverage do
        weightDuration=xTrendDurationAverage-(t-i)
        weightPrice=1/$pricediff[i]
        weightTotal=weightDuration*weightPrice
        diff=diff+weightTotal*$bardiff[i]
        totalWeight=totalWeight+weightTotal
    next
    trendavg=diff/totalWeight
endif

return trendavg as "weighted average of previous X trend duration"

This ProBuilder code snippet is designed to calculate a weighted average of trend durations where the weights are influenced by the price movements within those trends. The smaller the price movement, the higher the weight, emphasizing periods of low volatility.

• Settings: Initial settings define periods used for calculations.
• Calculating Bollinger Bands: ‘bbup’ and ‘bbdn’ are calculated using the average and standard deviation over a defined period.
• Detecting Trend Changes: The script checks for crossings over or under these bands to determine trend changes and initializes variables accordingly.
• Tracking Trend Duration and Price Movement: When a trend change is detected, the duration and price difference from the start of the trend are recorded.
• Weighted Average Calculation: For each trend, a weight is calculated based on the duration and the inverse of the price difference. These weights are then used to compute a weighted average of the trend durations.

This approach can be particularly useful for analyzing market conditions where less volatile periods are given more significance, potentially aiding in decision-making processes in trading strategies.