def bad(list):
    maxi = 0
    mini = 0
    loss = 0
    maxLoss = 0
    for i, x in enumerate(list):
        maxi = max(x, maxi)
        mini = min(list[i:])
        loss = maxi - mini
        maxLoss = max(maxLoss,loss)
    return maxLoss

This walks through the list, updating the maximum point it has been through, and comparingit to the minimum from the remaining list, calculating a maximum loss at every step through the list. The maxLoss also updates to be the biggest value yet reached as the walk continues.

Steve

In my opinion CLSQL has always been a bit bulky and hard to get working correctly so what I did was to write my own smallish wrapper above the mysql C API.

Your lib seems to be very nice though and fit my needs perfectly.

I have only done some initial testing but it seems to work just fine under Mac OS X which I use as primary system.

Cheers!

Yes, that’s easier, but this is not peak-to-trough draw-down as I defined it. This procedure will find the largest price difference.

To appreciate the difference, consider what would happen if the minimum value is before the highest point. This is not draw-down because an investor could never ‘experience’ this loss.

Once you bear this in mind you will realise that the peak-to-trough may not actually involve the highest point in the series at-all. Any local maximum can be the highest point as long as it’s followed by a local minimum that is low enough.

Hope that helps

Steve