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EA Optimizing: WFA , Walkbackward Analysis, Curvefit = Robbust

ORDExhaust (ORDExhaust)
May 30 at 08:21
72 posts
in 2014 i do WFA,

tons of learning also in asirikuy about how robust is WFA method, trade on open bar only, etc2

but its an effort too much, i always WFA my EA for weeks or month. And an Open Bar EA surely had long stagnant Drawdown period.



As at the end , im coming to my own conclusion, continous WFA is also curve fitting it self. In a different way.

I even see another silly method 'WALKBACKWARD analysist' LMAO Hahahahah.



Hey, i mean it in esential way,

If we curve fit the last period, and we test the ea in the oldest period as out of sampling, it also an OUT OF SAMPLING METHOD

Even lanchester the developer of Multiple ea do that. Optimized for last 6 month, but make sure the results in the early year also profitable.

In early years period means = OUT OF SAMPLE.

No mater what we trade in the past or future, esentially it still OOS for testing robustness



In WFA The Best Out of sample we pick, is the best that we choose to live trade.

So whats different than curve fitting??

The results in Live trade, the market always change beyond our expectation.

Even with continous development.

The last market behaviour is the least we could adapt with our optimization.



Even i know a friend works in a real Financial Institution, a 20 years trading experience in a hedge fund.

From what i see, the way he do to adapt market change is no different than curve fitting.



Im not saying WFA is a wrong method, i also still had WFA tools, but rarely using it now.



So, as a simple statistic approach, why dont we build a most robust system that all in sample data we could had?

Even it tooks hundreds hour for a single curency. (With TickData also now!)

The more sample we optimized is the more statisticly robust proven. No matter what the market behavior change, historicly some of it repeated itself.

Market Trade only know 4 behaviour : Trend, Reversal, Breakout, and Ranging. Only the volume volatility that changing.

Then i optimized all the historical data as robust at we can with as much data as i had.

And build porftolio with those 4 character inside to minimize stagnant period. And took every chance in every condition change.



Then picking up the best KPI from it optimization results.

Such as Profit factor, CAGR, etc. But Not get too shiny on the score itself, since those Profit Factor, CAGR, Payoff, etc always had flaws statisticly

So i pick with the most trades as posible first, that mean the more data, more sample and most market condition as we could had.

Run montecarlo, stagnancy period, drawdown % and period analysis with the risk that we could stomach.

And dont change the rules and system before that max risk happened. Wich mean market still in our portfolio prediction.

(So actually i do WFA also now, but my out of sample is a live trade. LOL. Kidding)



However this is my personal conclusion. Dont pick it if you dont walk the path yourself.



Im not bashing out Asirikuy with WFA approach, but i felt like im wasting times backthen sticking to others personal rules to build a systems.

But however, he build a great platform and different insight.



No matter what system we build, tick scalping, swing, to long trend trading, or even a Grid.

Whatever approach we choose, Even now im doing curve fitting to 'latest market condition' approach. From the base parameters that already robust entire period as much i can have. And back using TDS Variable spreads ON.

As It IS the 'TRUE real market condition'. Not open bar.



At the end of the day, we trade to made money.

Not to be a smart academicly.



So for me the hints is as i mention above 'Run the system with the max risk we could stomach with'.

No matter we use WFA or Curve fitting the whole period method.

Managing Risk first, then profits follow.





Cheers,

My two cents





Once again : this is my personal conclusion. Dont pick it if you dont walk the path yourself.

I trade my Own EA, Never Sell EA
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