Longevity of a strategy

Since there’s no view on how long a strategy might remain profitable, and the goal of everyone here is to make money, would it not be better to push a profitable strategy to high risk, rather than run it at low risk, only to find it loses it edge over months and years?

So if you have faith in the strategy and it look good on a live account after a couple of months, ramp the risk up very high. Withdraw the original capital as soon as you have doubled your money, and then there’s nothing to lose…

Contrast running at low risk (say 2%), it would take years to make any meaningful money without a very large initial deposit, with risk of failure due to the long timescale.

And thats why ATR and volatility measures for profit targets and stop losses are more robust. They adapt to the market. Fixed (pip) stops do not. Fix pips may be successful on single pairs, but fails to be robust using the same fix pip stop across multiple pairs.

Yes, I agree threshold. That is what I was thinking the solution would be as well.

Sent from my HUAWEI MT7-TL10 using Tapatalk

Thanks for explaining guys. I love hearing how others do it to help me develop my own way.

Sent from my HUAWEI MT7-TL10 using Tapatalk

Guys here you can find interwievs with top traders. For me very inspirating. Eg interview with a.unger, p.kaufmann http://bettersystemtrader.com/

And many answers and ideas discussed in this thread

Guys here you can find interwievs with top traders. For me very inspirating. Eg interview with a.unger, p.kaufmann http://bettersystemtrader.com/

And many answers and ideas discussed in this thread

I’ve listened to every single one of his podcasts. Great interviews with some of the world’s best traders (many of which have written books)

+1

While using more years of data might seem to yield better strategies on the face of it, doesn’t this mean that you ultimately have strategies that are merely fitted to a longer set of data? Also, having data for market behaviour over the past 30 years of data is no guarantee or indicator of it (the market) behaving in a similar pattern in the future.

Finally, even if one corrects gaps and price spikes etc., don’t you test for similar events through ‘Monte Carlo’ and ‘What If’ analyses in order to find a more robust strategy? Wouldn’t this be similar to first filtering out noise from data to find a winning pattern/strategy and then reintroducing noise to test if the pattern/strategy still holds through the Monte Carlo/What If analyses?

The point being, through testing beyond a few years in the past, are there any incremental gains to be made in the robustness (as opposed to profitability) of strategies? Just my opinion, would welcome all thoughts.

I just listened to Caesar on better systems podcast. He actually commented on this very debate (testing on data and using all or segregating it).

Basically he is a successful strategy developer and he said he uses full data set. He stated that after he said that he knows someone just started yelling at the podcast in disagreement.

So thank you for your viewpoint. I just want to keep in the front of our minds thst there is no right way, people succeed with both ways, and we should share our views because we can learn from each other’s different views.

-Stearno

Sent from my HUAWEI MT7-TL10 using Tapatalk