I remember reading in one of Van Tharp's books where they did a back test with a random entry, trailing stop and small position size over several futures contracts and got an overall profitable result.
Van Tharp demonstrated that a carefully selected string of random entries was profitable when applying "good money management". Apply the same logic to a string of not so carefully selected random entries and see what you get.
If memory serves, Tharp had access to a profitable system and they replaced the entry logic with "random entries". Using various MM rules they could "prove" the system was still profitable.
More specifically, the
exits were certainly not random. So saying he demonstrated that a "random entry" system can be profitable using "money management" only, is wrong. He demonstrated that a profitable system remained profitable. Most likely curve fitting the data (just guessing here, but hey, he was trying to make a point in a book).
If you've done any systems testing you know entry/exit/profit/money management-logic are interrelated in mysterious ways and trying to optimize or test one part without affecting another is near impossible. It's like a game of whack-a-mole.
So finding a profitable random entry system for a limited time series is not really a problem. If you're writing a book and need to make a point, it's not an issue. Making it work across multiple timeframes and instruments is a completely different thing.
Don't believe everything you read. When in doubt, test it yourself and don't trust anyone else to do it for you. :eek:
Sorry to repeat myself, I've mentioned this before.