This ProBuilder script is designed to plot range zones that span overnight from one trading day to the next across the entire historical data set. The zones are visualized using rectangles that highlight the high and low prices between specific time intervals.

defparam drawonlastbaronly=true
start = time>=180000 and time<235900
end = time<080000 and time>=000000
if time=180000 then
    i=i+1
    $x1[i]=barindex
    $y1[i]=low
    $y2[i]=high
    hh=high
    ll=low
endif
if start or end then
    $x2[i]=barindex
    ll=min(ll,low)
    hh=max(hh,high)
    $y1[i]=ll
    $y2[i]=hh
endif
if islastbarupdate and isset($x1[2]) then
    for y = 1 to i do
        drawrectangle($x1[y],$y1[y],$x2[y],$y2[y]) //plot in history
    next
endif
return //hh,ll

The code snippet above is structured to perform the following steps:

• Initialization: The defparam drawonlastbaronly=true setting ensures that drawing commands are executed only on the last available bar of data to optimize performance.
• Time Conditions: Two time conditions are defined to identify the start and end of the overnight period. The ‘start’ condition captures times from 18:00:00 to 23:59:00, and the ‘end’ condition captures times from 00:00:00 to 08:00:00.
• Tracking Highs and Lows: When the time is exactly 18:00:00, the script initializes or updates indices and price levels for drawing. It stores the bar index and the high and low prices at this time, setting these as initial values for the highest (hh) and lowest (ll) prices.
• Updating Range: During the start and end periods, the script updates the highest and lowest values encountered and adjusts the rectangle’s end position to the current bar index.
• Drawing Rectangles: Once the last bar is updated and if there are at least two recorded indices, the script iterates through each recorded period and draws rectangles from the start to the end indices, using the recorded lowest and highest prices as the rectangle’s boundaries.

This approach is useful for visually analyzing price movements and behaviors during specific overnight trading sessions across historical data.