Profitability of strategy

Hi traders,

I would like to ask more experienced traders than me, how many trades is necessary to execute, if I want to consider that strategy as profitable ( or was profitable ) . I wanna know what is the min. sample to consider the strategy as solid in long-term.

thanks for answers

use forex tester to speed up the process and consider using minimum a year cycle to test the strategy on a full year market, begin with 2013 and move backwards year to year, the more trades the better but at least some hundreds for a short-term strategy… I run 300-500 trades before going demo.

you have to also consider pairs to use, past economic news and data, market sessions, etc… try to reproduce or figure out your future live trading intentions or opportunities. hope it helps you

A strategy identifies a specific way of executing a transaction. A transaction means 1 or more positions. You need to execute it only 1 time to know if it is good or not.

[QUOTE=“mihk;622149”]A strategy identifies a specific way of executing a transaction. A transaction means 1 or more positions. You need to execute it only 1 time to know if it is good or not.[/QUOTE]

So… you’re saying one trade and you’re good testing the strategy? just with one trade?

Milos, I know you are an expert and I am always looking forward to learn from the best.
In my opinion however the execution is the key. It’s not the entry, and not even the exit as much as it is the execution that matters.

The answer to this question isn’t particularly straightforward, but few things in this game are.

Try to think about it this way, imagine you have a coin, with a 50% chance of landing heads or tails. How many times would you have to toss the coin to PROVE EXPERIMENTALLY that the chances of getting a head or a tail was 50% ?

If you toss it once, the experimental result is going to be 100% heads! or 100% tails right, so you need to toss it at least twice! but then you might get a head and a tail and the correct answer of 50%, but you might get 2 heads and 2 tails !

The more times that you toss the coin, the closer to the theoretical 50% you’ll get. So how many trials do you need. Well the error between the true probability of throwing a head, and the probability that you measured is proportional to the square root of the number of trials. So if you toss the coin 9 times, you’d expect an error of plus or minus 3 from what the theoretical result should be, so from 9 tosses, you might expect somewhere between 1 and 8 heads ! If you tossed the coin 400 times, you’d expect to get 200 heads theoretically but with an error of + or - 20, so somewhere between 180 and 220 heads, so within about 5%

So how does this relate to trading systems ?

Well if I gave you a trading system with a 50% win rate! it’s going to be like the coin example. In your first 9 trades for example you might expect anywhere between 1 and 8 wins. If you only got 1 win and 8 losses the chances are you’d abandon the system. If you got 8 wins, you’d think you found the holy grail, but in reality, you’d have a system with a 50% win rate.

Now imagine I gave you a weighted coin that when tossed came up heads 100% of the time, how many trials would you need to perform to get the correct answer by experimentation ?

So as the system win rate deviates from the 50% level this is going to effects the error in your experimental testing to. It gets even more complex because for most systems, it’s not just a matter of wins and losses, the size of those wins and losses varies too.

The answer to your question is that you probably have to go down the simulation route. So simulate 10 trades, and find the upper and lower boundaries in profit or loss, then simulate 50 trades, 100 trades, 200 trades etc and the range between the upper and lower boundaries should start to converge. At that point it’s up to you to decide what sort of error rate in testing you can live with.

The size of your edge is important to, very large edges require less testing, smaller edges need longer testing to differentiate themselves from statistical noise.

And of course, as all this is happening in real time, the market is constantly changing too, so any assumptions you make about win rate, or volatility in your simulation are probably going to be wrong, but it’s a starting point.

It’s all well and good anyone telling you that you need 400 trades, or even showing you the maths to calculate a number, but if you are trading a daily chart, there may not have been 400 trading opportunities over the past 20 years then you are pretty much screwed, what are you going to do, spend the next 100 years forward testing ? So you have to take practical constraints into account, or design a system with a trading frequency that can be forward tested in a reasonable time period.

Perhaps not the answer you where looking for, but hopefully it’s useful to somebody

Thanks for your answer, mate. I was usefull, now I can think more deeply about this problem, anyway I think you have right philosophy about this.

So we can say longer time-frame trades = less testing ? Basically I think intraday strategies need more testing, because small movements can take you to losing trades.

You gotta think statistically to make good pips. Trading is less about economics than most people think.