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Artificial General Intelligence V.6.1 (By leo23 )

Прибыль : +6.58M%
Просадка 35.76%
Пипс: 13731.7
Сделки 9338
Тип: Демо
Кредитное плечо: 1:200
Трейдинг: Автоматически

Artificial General Intelligence V.6.1 Обсуждение

Dec 19 2018 at 22:23
88 комментариев
Wait, you mean you are training your SNN model in MT4? And then you are reading/writing to the disk during every calculation? Then no wonder your model behaves so slow... You could try to do some profiling to see where your model is slow, I believe it is most likely during the disk read/write process. MT4 is also extremely slow to run backtests compared to other methods. I train my models in Matlab and just use the trading platform for trade execution.

Whoever said money can't buy happiness didn't know where to shop.
Dec 19 2018 at 23:23
566 комментариев
Yonex posted:
Wait, you mean you are training your SNN model in MT4? And then you are reading/writing to the disk during every calculation? Then no wonder your model behaves so slow... You could try to do some profiling to see where your model is slow, I believe it is most likely during the disk read/write process. MT4 is also extremely slow to run backtests compared to other methods. I train my models in Matlab and just use the trading platform for trade execution.

No, for any machine learning algos we don't use MT4. Yes, we tried in MT4, but left. We use only MT5 for now and we are aware about MT4 backtesting issues.

That's why we keep telling machine learning and NN separately.For us, NN means no learning at all and everything is simple and coded in MQL4 with no models or anything like that. All the input optimised weights are hard coded inside the MQL4 code with indicator values and it's internal algorithm etc and there are no trained models in it, but it has just optimised weights for neurons and we keep changing the weights time to time. Probably, you are confusing the weights of the neurons as models.

But when we say machine learning, we actually mean algorithm based separate training models in MT5 using SNN and, then either we create a bridge using libraries to trade in MT4 or we simply copy trades as well from MT5 to MT4 if we want to use MT4.

We are not sure what exactly you mean by 'disk read/write process' and how you can then search the trading conditions inside the trained model if you will not read. May be you are referring to loading the model to virtual memory or something like that permanently during the live trading.

By the way, we are not concerned about slowness during training. We are referring to slowness while trading.

We are perfectly fine if it takes a couple of days for training also and in fact, we already tried this as well. It doesn't matter if it takes a month to complete the training if it is a one time training and then, if the trained model can execute all trades perfectly, then it will trade like a holy grail. It is very much normal and in fact, we can directly write the 'Monte Carlo tree search' algo to train itself without any past trading history at all and without using any MT5 backtester and purely based on self training to itself. It is very simple, but the model size will grow exponentially large may be in terms of GB.

So it is mostly the computational power, because if more data will be trained or more filters will be added, then file size will be more and ultimately it will not execute the trades.Otherwise, it is very simple task for us if any file size models can be execute the trades in real live markets since the algos are already available.

Irrespective of wherever you keep the trained model, you need to feed the input variables to the model and search inside the model for the output signal and it is always a whole bunch of nested for or while loops of 4 to 5 layers in it with if else statements while searching inside the models. Each model is like a trained brain structure where the search operation need to happen before making a trading decision.

Note that we are not talking about feeding 4 to 5 input variables or indicator values to generate a output signal like a 2 to 3 layer NN. The input variables to the NN usually vary in order of few thousands which are calculated from formulas and each variable going through the search inside 50 different models. It is basically similar to trying to imitate the human brain based on which SNN functions considering a time factor.

Dec 21 2018 at 13:55
566 комментариев
We want to update our fund management clients that we are not going to trade in any live account during the christmas and New Year holiday period though we may continue to trade in this demo account. We already stopped trading before few weeks due to low liquidity in the market. The normal trading will be started during first or second week of January 2019.

Also, though we mentioned earlier we would like to repeat for our EA users to be careful while using the EA during this period since the spread might be very high and also, make sure to use stoploss in each trade. Also, people can switch to higher time-frame temporarily to reduce the frequency of trades and hence, bringing more safety to the account balance.

Dec 24 2018 at 19:47
566 комментариев
Trading in this demo account has been stopped for next few days due to Holidays and will be resumed shortly . Trading in the live accounts of our fund management clients will be resumed only in January first or second week depending on market conditions.

Merry Christmas and Happy New Year to all of our EA users, fund management clients and to all myfxbook users!!!!

Dec 27 2018 at 17:42
566 комментариев
Trading in this demo account has been resumed.

As per our previous post, we will resume trading in fund management clients accounts in January first or second week.

Dec 28 2018 at 18:32
566 комментариев
While we are waiting for the live testing of our machine learning algo in demo or live accounts which we might do after few weeks, in the mean while we have been continuously improving our algo and it's coding. Now we have got sufficient time to fully focus on backtesting and adding new concepts to our algo to try out since markets are unreliable now and there is no point in forward testing before first or second week of January.

Backtesting results seems to be very interesting. However, until we do forward testing in demo and finally forward test in a live account for a couple of months, we don't want to conclude anything.

Now, we are completely working on MQL5 since the backtesting is much more reliable in MT5 terminal as compared to MT4. We have added multiple timeframe filters to filter noise from the trading signals and the results seem to be improved significantly. Apart from that there are few new concepts we have added to our algo and they don't have any existing technical terms or descriptions available and solely developed by our team. We might publish a test live account within next couple of weeks or months.

Jan 02 2019 at 14:44
566 комментариев
We have received multiple emails from EA users asking for recommended brokers for our EA. Though our EA can work fine with most of the regulated brokers we are listing some of our recommended brokers for the EA.

The recommended brokers are as follows:
Pepperstone, IC Markets, FxChoice, Dukascopy, XM,FxPro,TickMill,Forex.com,Forex4you

Jan 05 2019 at 04:32
566 комментариев
Now the markets have resumed to normal conditions. So we recommend our EA users to resume the trading of our EA from next week in their respective mt4 accounts with default settings of the EA.

We will also resume trading in our fund management clients accounts by end of next week or beginning of the third week of January.

Jan 09 2019 at 15:10
566 комментариев
Recently there were not enough trading opportunity for our system. So we have not yet resumed trading in all our fund management clients.

For now we have been focusing mainly on backtesting of our system, demo trading and improving the trading system further.

Trading in the fund management accounts will be resumed from next week from Monday.

Jan 11 2019 at 18:16
566 комментариев
After waiting for long time finally we have started testing our machine learning algo in a small live account and made it available for public access. Though there is no 100% guarantee whether we will continue this account or not, but we are very much hopeful that if everything goes as per our calculations and testing, then we will continue with that live account. Since we are using high risk and hence, we have started in a small live account.

You can find the live account link in our profile. Anyone following this system might be also interested in that system. That is the modified version of this system.

Unlike this system where everything is hard coded and fixed inside the code and no learning involved, the other system involves machine learning and it automatically adopts to the markets irrespective of any kind of markets ranging markets, trending markets, volatile or flat markets etc. So we call that system as 'Final Holy Grail'.

Another reason for the name is that the system trades almost like a human professional trader or like a human brain and targets approximately 5% per day irrespective of any market conditions with a maximum equity protection of 50%. So it will continue to make around 200% per month until and unless an equity protection is hit. That particular month when the equity protection will be hit will make around 50% for that month which is not bad considering the trading style.

Though we are targeting 50% maximum drawdown still the system can be traded with a maximum drawdown of 40%,30%,.. as low as 5% of maximum drawdown and can still maintain the same trading pattern.

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