Trader Must Win Project
Building up Sustainability with a remarkable Profitability
No ''Martingale w/o S/L''
No ''Full Grid Hedge''
No ''News Trading''
Choosing stable & sustainable Strategies
We have developed tens of forex trading systems during past 15 years, we observed and eliminated some of them which did not produce stable profit with a maximum drawdown of 20%.
We have chosen 6 systems which are the most stable ones that are compatible with each other to create an ultimate combination. We are running and optimizing new systems and keeping them ready to use at anytime.
Control for sustainability
There are safety criterias that are looking for a resilient and sustainable trading system. We monitor them 24/5 and if we observe untolerable faults on any of the systems, we delete it from the system instantly and add a new good-performing one when it is ready.
Notice: We are on your side and we are not obliged to keep on using a bad performing system. Running 6 different and independent systems helps us allocate such risks as well.
Analyzing and Filtering the Trades
We, first, do manual detections according to our experience of 15-year forex knowledge with 19 critical criterias. Secondly, we use our testing programs OuantAnalyzer and Arya.
We block the possible wrong trades with multiple examinations. We use Arya (It is an AI - Artificial Intelligence) that has a 'machine learning' module warning us for repeating market conditions that cause losses and prevents us doing the same mistakes again. It examines a trading order within 100 miliseconds (0,1 sec) before it is placed to the trading account.
24/7 Tech Safetiness
We handle all technical controls and add automated programs to our signal providing environment such as 'news autostop', 'automatic restarter' ,'autostop' .We define risk ratios and trade copier rules as default settings.
Notice: We are not changing the techical fundamentals of a trading system on the way, which -in fact- would mostly destroy it.
Step by Step Process
We get trading systems from genetic algorithm machines or we develop them inhouse.
Existing backtesting programs are useless because they are not tick-basis.But we get algo tradings with verified track records or our developed systems have real trading performances.
We test them with 19 strict criterias and find out which of them has no schemes, performing well and able to provide sustainability.
After the manual tests, we use a Quantitative Analytics program to expose irregularities and to trim the bad outputs in order to keep it sustainable.
At this step, we create the most compatible combination concerning the risk management rules along with the stable growth of earning.
New Sender Rules & add-ons
We define the publishing rules on sender ea side of the copier. We may change the S/L or omit signals for some pairs , setting news schedule to prevent sharp movements , adding heartbeat module etc.
Machine Learning Risk Management
We have ARYA -machine learning artificial intelligence program- to be added to our trading system to requestion a signal within 0.1 sec. before it is executed.
ARYA is not similar to backtesting or forward testing.
It is a 'self-learning machine program' that learns from past mistakes of each trading system and examines the economic environment that causes the 'loss' of a trade and remembers and warns/blocks if the similar condition occurs obviously for the next trades.
Setting up and running
Setting up the trade copier is very simple, you do not need to know any tech knowledge.It is a few clicking thing.
We monitor the system 24/7 and detect any situation that threatens ongoing sustainability or a remarkable performance fluctuation from one of the signal components.
Once we get the idea that one of feeder systems repeating malfunction or bad performance etc. and if it is impossible to fix it , we change it with another substitute system
Please do not forget:
We are on your side and we are not obliged to keep on using a bad performing system. Running 6 different and independent systems helps us allocate such risks as well.