Hi D5QM54S7,

thank you for answer.

I am confused.

Some Trader here say, it is better longer datas use (20 years and more) and others say it is better not so long data use.

i am desperately....can EA Studio make Strategies, that work good or is it only pastime?

1 year back i have much much strategies testet, used, optimizated and the result was, i have more loss then win.

Now 1 year later i thinked, new chance for all...but it is not better

i total desperately what i make in future.

Please be honest all user here. have you success or not?

please write here, i have no hope this time.

Thank you again for your helping and Info / Tips.

Can you say me, in EA-Studio it is good all Indikators to use for searching or use you only 3-5 for searching?

I am not sure with that.

I self trading since 2004. In the beginning much loss, later +-0 all with Selftrading.

Since two years i use EA but it is not better

I have no time 10 hours every day for trading, this is the reason, why i use EA. I have 2 Companys in real life to work

But i will not give up here, but i have no input for coming forward. All books that he posted in forum are englisch. But i german and my Englisch is to bad for this

My english isn't good too but I know that good information are often in english, I try to understand even if I spend a lot of time. For me trading is research and study, I think that a few hours every day are needed for learn how to trade. Indicators? try and see because no one will tell you what combination or pattern really work, and they are really but really few.
Problem isn't FSB, Strategyquant or Adaptrade …. problem are you, if you put into these machine wrong data/information/bad knowledge the result will be always a loss.

Regards

You have a problem with statistics and probability, if you don't study these subjects you will continue to lose. If your strategy fails in live you have overfitted, used wrong statistics instruments or badly used these. No one can help you in this case because only you know the method used for build ea's. Is not a indicators problem. Machine Learning is a black beast

Regards

Try this very simple tric: delete (or save in a desktop folder) all strategies you've build and restart -> split all data in 50% (IS), 25% (OOS) and 25%. Exclude last 25% with machine settings and try to build ea like you have always do. When an ea pass your tests try that into MT4 with full data and with modality control point (no tick data). If all your strategies fail you're in a right way because the first step is know when us are wrong. Try for few day and then tell me.

Regards

Hi Rantampla

Here are a few thoughts to consider.

With data mining software, one of the key issues you need to address is 'curve fitting'. Curve fitting is not only restricted to data mining but is also a feature associated with mean reverting strategies that possess negative skew over the long term.

There are two broad types of strategy within which any strategy can be classified. These are convergent strategies and divergent strategies.

Convergent strategies are 'backwards looking' with a central assumption that price will converge to a past equilibrium. In a sense these strategies are predictive in nature and include all mean reversion strategies, value investing approaches, grid trading and Martingale methods. Given the repetitive nature of price converging towards the current market equilibrium, these strategies are typically quite complex in nature based on the 'expected certainty of this outcome'. The complexity is a symptom of 'fitting' the strategy to the nature of the current market condition.

These types of strategies are what most retail traders prefer given their linear equity curves and high win rates over the periods that equilibrium persists....however when market conditions change to new equilibria, the past stable equilibrium is not respected and you quickly find that your strategy no longer performs as expected and you are left with a sequence of large unfavourable losses that frequently ends up in  account blow ups. Because the 'true' equity curve is revealed over the long term, it is advised to use long term data horizons that span a broad array of market conditions to detect them.

If you use short term data horizons to develop your strategy, the chances are great that you are biasing your outcomes to 'convergent styles' that in the long term have negative skew. It is not advised. You will find that this approach means that you need to continuously mine new strategies when existing strategies fail....and you will become a victim of 'strategy hopping'. Be aware that the need to continuously replace your strategies is a form of 'market timing'....and there are swags of white papers available that demonstrate that market timing methods used to 'switch on or switch off' your strategies is a fools errand as the decisions are always lagging in nature.

The other class of strategy type is referred to as 'divergent strategies'. They are the opposite to convergent styles in that they are non-predictive in nature and simply operate off the principle that stable market conditions will not persist and that conditions will move in the future towards new equilibrium. The location of this new equilibrium is unknown given market uncertainty....and the only assumption you use is that it will either be higher or lower than the current equilibrium. As a result, these strategies are said to 'follow' price as opposed to 'predict future price'.

To avoid trading during normal market conditions representative of the current market equilibrium what they do is apply trade filters so that it is only during more exotic times where price moves outside the 'normal', that these strategies participate in the market. The filter is used to significantly reduce your trade frequency and only participate when market conditions become more 'exotic' which provides hints that a new equilibrium may be established. 

The way these strategies are developed is through logical design build considerations that enforce an asymmetry into the design through cutting losses short and letting profits run. They all use stop losses and tend to use different forms of trailing stop to manage adverse risk exposure in cutting losses short....but they keep their profit potential open and do not use profit targets. The reason for this open-ended condition statement is simply to be in a position to catch the occasional white swan that according to Ed Seykota 'pays for them all'.

Given the 'cutting losses short' condition applied to these strategies and given the applied filters, these form of strategies are far more long lasting than their convergent cousins. Furthermore these form of strategy only require very simple rules to allow for 'degrees of market freedom' in price movement. They typically have volatile equity curves over their long lifetimes where drawdowns are a result of many small sequential losses but ........ so do convergent strategies if measured over the same time-spans...in fact the vast majority of convergent strategy equity curves over these long periods result in >100% failure. We unfortunately only see the nice linear equity curves when convergent strategies are performing.

So in essence if you are interested in mining over long term data, then consider using the following principles in your workflow:
1. Preserve at least 30% OOS to your long range data set. This ensures that optimisation is only performed on the In Sample 70% component. The OOS component is simply used to ensure that the previous performance metrics are maintained in the future. Discard all strategies where the OOS component falls well below the IS performance metrics. The closer the OOS performance against the IS benchmark the better.
2. Ensure stops and trailing stops are allowed for in the reactor settings and keep profits unlimited in nature.
3. Use a preset filter to avoid trading during the normal 'day to day' conditions.
4. Use the multi-market feature to test your strategy on other unseen data. The greater the number of alternative markets the strategy works on the better.
5. Use stringent settings on your Monte Carlo...but do not set high acceptance levels. Expect variance in your results, but ensure that the MC array is overall generally profitable. This is used to ensure that your strategy requires a 'weak edge'.

Remember that over the long term say 20 years plus...your equity curve is quite deceptive. Despite the 'apparent' fairly linear nature of the curve when viewed from a height, when you drill down, there is considerable volatility and long periods of stagnation. For those looking for 'instant' results, it is unlikely that they will have the patience to tolerate them.

So the way we overcome this volatility and uncertainty associated with the future of a particular strategy, is to diversify into a broad array of different strategies, each with slight positive expectancy that are uncorrelated in nature. The 'uncorrelated' requirement is used to ensure that over 'most times' your portfolio has positive momentum and your 'stagnation period' of your entire portfolio is minimised. The uncorrelated nature of each strategy also ensures that the drawdowns of each component strategy are reduced when compiled into a portfolio.

So the decision to turn off the strategy is a long term one in the divergent space but a short term one in the convergent space. It is very difficult to determine between drawdowns versus total risk of ruin with convergent strategies.....but drawdowns in divergent strategies take a long time to play out plus under diversification where each strategy comprises a small portion of your total equity....you are very unlikely to meet 'total risk of ruin'.

Under a diversified portfolio of divergent strategies you continuously monitor live performance against your long term backtest. You set performance benchmarks for your live trading that uses the backtest performance metrics as a guide. You only drop the strategy when those benchmarks (based on long term data) are exceeded. In this game...you need to rely on the Law of Large numbers as your guide.

I hope this helps.

Rich

One can and should do this in Pro or Studio, why use inferior backtest for validation? Double backtest is not validating anything, not to mention other obvious gains with Pro/Studio like time and speed and hence the overall work efficiency. Some strategies cannot be backtested correctly in MT because of its bugs. There's only one thing to keep in mind - that is equal trading performance in live and in a backtest in Pro/Studio.

No offense, D5. I'm just trying to give my insight for using the tools to maximum extent possible. There are many and much quicker ways to determine equal behaviour between a backtest and live trading, that's all I'm saying. And the inferiority of MT and the possibility to get fooled by MT one way or another is real, one must take this into account, I'm not making this up. Mind you, I'm not stopping anyone of conducting tests in MT, but for me it is hard to see the rationale behind it.

Regarding the topic there's already much said and written in this forum. I would especially mark out Geektrader, Hannah, Steve... Quoting Geek: if someone thinks making a quick buck the easy way in FX is the right mindset, then that person is a fool! It is tremendous amount of work among other things. Hannah, for instance, developed her own methodology, which she has outlined here, and I believe that such a success has kind of "bored her out" that she's making new strides in different type of development avenues.
Secondly, different strokes for different folks. Or there's more than one way of skinning a cat. I'm no fan of step-by-step plans in FX, I've been there and done that. For me they did not work out the way I hoped, but I did learn a lot. The approach, demands, expectations are not equally similar between us. What I might find acceptable, might not be for you, do you understand? I very much like your say about knowledge and skill etc. What I'm trying to convey is that there are many concepts laid out in here and other places, and what I do is taking those, making sense of them (understanding), and then making them work for me.

footon
You have not offended anyone :-) there is a person who is losing real money and I think I understand what his problem is. As you say, the roads are different but they are very few. What I have recommended is a small part of a journey that has improved me. In this post, where a person asks for help because his strategies fail shortly after, does it make sense to criticize my method without proposing anything else below? Rantampla does not need a faster research and development method, but to understand why statistics and data mining are ruining it and the path I have recommended has this purpose. I'm happy that in 3 we are participating in the post and Rantampla, if want, can combine the information collected here and test.
Rantampla
There is no precise answer, there are those who love the simple and those who love the complex. The more complex the greater the chances of overfitting, but also the ability to earn well if predictive. Are you looking for a momentum, trendfollowing or mean-reverting strategy? Have you observed the volatility of the financial instrument you are trading on? ... You have seen Rantampla, there is a world to discover :-)

Regards

footon
If MT4 were reliable I could avoid the test on it, but we agree that it is not. Is the platform on which I trade? yes, personally this is enough for me. If I have to choose I do it, no one of us has predictive capabilities and FSB can not guarantee the correct functioning of MT4. If you want to know I test eas on different brokers and, to be worthy, the algorithm must behave well everywhere. This path is a crushing stones

Rantampla
It's a pleasure. Yes, the goal is to save oneself from statistics and data mining. Remember to use 50% with IS, 25% with OOS and 25% "remove" it from the software with the time limit settings, leave it only on MT4 and then test the whole period (100%) in MT4. If you have not found a good strategy after a few days, you're on the right direction. If you find a single strategy in a month you're already good/lucky. Once you have found the strategy with this method you will have to start examining it carefully. Trading is a minefield, if you want to survive and make money you have to study and study. I was referring to this at the beginning when I told you that you are the problem. Whatever site or blog you open, be careful. Trading with fake money is useless, if you build a strategy with a solid foundation you can immediately put it live. Try to build 1 or 2 and then put them on demo, if they work forget the demo and use only real money with 0.01 lots until you feel safe.

Regards