Yashar Seyyedin / Profil

Tron's black hole address receives burned TRX from transaction fees and protocol mechanisms. This used to be banks'.

Should not be a good idea to trade into new year anyway:

History has shown that the safe sectors of the economy consist of two groups: first, business owners who were owners from the beginning, not true entrepreneurs. Second, salaried workers and government contractors who are generally in their positions through family ties.
If you are a skilled worker and are not in the above two groups, you have very little chance. Don't try too much. Your effort has no effect on the outcome.

Today, both the Philly Fed and inflation data were bad enough for USD to fall, but this did not happen. Reading the news alone without knowing how much has been already priced seems difficult. Especially for those of us who are used to charts and spend less time studying macroeconomics and microeconomics. So how do we know?

In my opinion, a simple way is to monitor the price movements for a few months and analyze the reaction to the news. For example, the EUR/USD pair rose from the FOMC meeting in October into November/December. That was expected, while almost everyone knew that the rate was going to be cut, so further growth after the December meeting(last week) should not have been expected, while surprisingly the dollar fell slightly even afterwards. Now perhaps it is possible to understand why today's bad data (inflation and Philly Fed) practically did not lead to further decline in the dollar and the dollar is likely to grow in the coming days.

Updates on Existing Job işi için müşteriye geri bildirim bıraktı

Hey everyone! Check out this AI generated code I have done for detecting decoupling pairs... https://github.com/yasharseyyedin-a11y/FX_Correlations_Check
The script compares recent 1-day correlations against 10-day rolling correlations (longer-term baseline). When short-term correlations fade or reverse from the 10-day norm it signals mean reversion opportunities, choppy markets ending, or trend shifts. This "fading correlation" edge spots when pairs diverge temporarily, offering entries before they snap back.

I was hoping that implementing neural networks in MetaTrader would at least give me more options for evaluation. After all, our problem is maximizing profit, not maximizing an imaginary parameter... In the current situation, Python is definitely a better option for training.

AI is the best teacher, It is even saying when you should re-optimize!

One advantage of testing with normal strategies on MetaTrader is when you get a good result you have some idea to capture why it is performing good and reject problematic backtests. This will not work with ML-driven solutions... Everything is a blackbox. All you can do is trust it is splitting data correctly during cross validation and hopefully it is not ovefit. Am I right? Does anyone has an idea?

Something really annoying about academic approach to real world problems is "The academician does not even understand the problem..."
Here you see a LSTM approach to predicting price. It is like saying "OK... today price is 100USD so probably tomorrow will be around 100USD"
Absolutely useless for a trader.

A fundamental difference between the problems solved by AI and the problem of financial markets is that those problems were solved by humans in the past and now automation has been transferred to computers. Whereas the problem of trading is an unsolved problem... The fact that someone has a positive account does not in any way mean that they have solved the financial markets.

Five years ago, programming was a safe path and trading was a little dopamine. Today, trading is the only path.

Something I realized by intuition turned out to be correct. The more optimization parameters you have the more overfit risk you are exposed to, unless you have enough train data.
Although I am still on my word... when you cannot prove that the system applies to your chart, anything is overfit.

Update existing EA işi için müşteriye geri bildirim bıraktı

Considering markets have discrete structure it does not make sense to read it solely relying on continuous averages. We have to move to discrete ideas.

Here I am sharing the ups and down with my 20K challenge. Three months and a half passed and I am hardly at half point.

The success story of individuals and making money from prop firms is an exaggerated and unreliable story that has been promoted on social networks for many years. Many traders, through trial and error, endure successive failures in these challenges to access and earn money from funded accounts. This procedure is generally used by traders who do not have enough confidence in their trading systems.
In many cases, they may even make a profit, but this type of success is completely random. That is, a sequence of failures lead to a point where it is no longer possible to continue this game in the hope of winning. A successful trader may fail one out of every ten attempts he makes at challenges, but having one or two failures out of three attempts completely jeopardizes your success. A number of failures can easily bring you to a point of no return where you join the group of traders who are forced to leave the market before success.

In fact, we should accept the harsh truth that props hate profitable traders. Because they neither loose the challenge fee nor they make that much money that can bring a change for them which mostly rely on challenge sales. If you are concerned to go beyond trading personal capital you should think of another solution I guess.

I cannot edit or delete posts on my wall... Do you also have the same problem? Is there a maintenance going on?

That volume is showing something:

Here is my showcase project as a web developer.
You can check the github repo for source code: https://github.com/yasharseyyedin-a11y/messenger-project
Also there is illustration on upwork: https://www.upwork.com/freelancers/~0169759d56a4a0dc91?p=1994305529700442112


Messenger Project:

-- Developed a scalable, modular real-time messaging application using Django for the backend and Angular for the responsive frontend.

-- The system features secure JWT-based API authentication.

-- Integrates OAuth with Gmail API to enable automated email confirmation for new user registrations.

-- Implemented a comprehensive real-time notification system, supporting user interactions such as friend requests, acceptances, and rejections with immediate updates via WebSockets.

-- Messaging includes "seen" and "unseen" status indicators for improved user experience.

-- Secured WebSocket connections through custom middleware to ensure safe delivery of real-time data.

-- The frontend utilizes Angular with RxJS to manage asynchronous data streams efficiently, enabling smooth UI responsiveness across devices.

-- The project architecture emphasizes modularity and maintainability, allowing easy scaling and iterative enhancements to meet evolving user needs and application features.

In this chart you see several times the sellers tried to break below the latest low and every time they failed to reverse the trend... To avoid too soon entries one can wait for several of these pressure boxes...