Hello!
Hey jimbo --- oh sorry I am jimbo...
Market is not roulette or casino. If you think like that it means you are a loser rookie. Market price moves are not always random. People often buy or sell because price moves above or below certain levels. Roulette outcomes are completely independent, no outcome depends on previous outcome.
I think intradaybill tried to explain to you something you do not seem to understand. Let us say you look at price data (forget about APS for a moment) and you decide that a 3-bar key reversal and an inside break-out (also 3-bar pattern) seem very promising. You backtest and then forward test the two pattens and you decide to trade the key reversal. This is not optimization. You have selected a pattern based on historical testing. Your bias is based on historical performance. Maybe the other pattern will turn out to be better. You don't know that. This is the nature of trading. If you think selecting a system based on testing is curve-fitting then all systems ever thought or designed are curve-fitted because you could have chosen a different one.
Hi Jimbo,
I tested the product myself this weekend, back-tested 10 randomly selected FTSE stocks, 1:1 risk reward, 5% P/SL, 66% profitability, >2 profit factor, >20 trades per pattern, 500 days. When I walked forward the results a year, the average profitability was 48.5% - below break-even. There was no one stock more or less suited to the patterns APS found.
I then thought about the previous post on Selection Bias, and thought that maybe I should be discarding the "patterns that went bad" during walk-forward. But here's why I think that could make no difference. Imagine this scenario:
1) You buy a very fast computer, and pattern search 10,000 stocks
2) You find patterns on 1,000 of those stocks
3) You walk forward those patterns one year, and 100 are still profitable
Does that mean the 100 will remain profitable next year after that? From the previous distribution of trades in this example, my guess would be only 10 would stay profitable.
This is the reason why I have a problem with silently discarding bad patterns during walk-forward (Selection Bias). I mean, I can prove myself wrong, the test would be:
-> pattern search a large enough pool to get (a) - backtest patterns
-> walk forward (b)
-> discard loser patterns
-> walk forward again (c)
If (c) is as profitable as (a) - then Selection Bias works.