Articles
Self Optimizing Expert Advisors in MQL5 (Part 8): Multiple Strategy Analysis (3) — Weighted Voting Policy for MetaTrader 5
This article explores how determining the optimal number of strategies in an ensemble can be a complex task that is easier to solve through the use of the MetaTrader 5 genetic optimizer. The MQL5 Cloud is also employed as a key resource for accelerating backtesting and optimization. All in all, our
Self Optimizing Expert Advisors in MQL5 (Part 8): Multiple Strategy Analysis (2) for MetaTrader 5
Join us for our follow-up discussion, where we will merge our first two trading strategies into an ensemble trading strategy. We shall demonstrate the different schemes possible for combining multiple strategies and also how to exercise control over the parameter space, to ensure that effective
Reimagining Classic Strategies (Part 13): Taking Our Crossover Strategy to New Dimensions (Part 2) for MetaTrader 5
Join us in our discussion as we look for additional improvements to make to our moving-average cross over strategy to reduce the lag in our trading strategy to more reliable levels by leveraging our skills in data science. It is a well-studied fact that projecting your data to higher dimensions can
Build Self Optimizing Expert Advisors in MQL5 (Part 8): Multiple Strategy Analysis for MetaTrader 5
How best can we combine multiple strategies to create a powerful ensemble strategy? Join us in this discussion as we look to fit together three different strategies into our trading application. Traders often employ specialized strategies for opening and closing positions, and we want to know if our
Build Self Optimizing Expert Advisors in MQL5 (Part 7): Trading With Multiple Periods At Once for MetaTrader 5
In this series of articles, we have considered multiple different ways of identifying the best period to use our technical indicators with. Today, we shall demonstrate to the reader how they can instead perform the opposite logic, that is to say, instead of picking the single best period to use, we
Overcoming The Limitation of Machine Learning (Part 2): Lack of Reproducibility for MetaTrader 5
The article explores why trading results can differ significantly between brokers, even when using the same strategy and financial symbol, due to decentralized pricing and data discrepancies. The piece helps MQL5 developers understand why their products may receive mixed reviews on the MQL5
Overcoming The Limitation of Machine Learning (Part 1): Lack of Interoperable Metrics for MetaTrader 5
There is a powerful and pervasive force quietly corrupting the collective efforts of our community to build reliable trading strategies that employ AI in any shape or form. This article establishes that part of the problems we face, are rooted in blind adherence to "best practices". By furnishing
Reimagining Classic Strategies (Part 14): High Probability Setups for MetaTrader 5
High probability Setups are well known in our trading community, but regrettably they are not well-defined. In this article, we will aim to find an empirical and algorithmic way of defining exactly what is a high probability setup, identifying and exploiting them. By using Gradient Boosting Trees
Feature Engineering With Python And MQL5 (Part IV): Candlestick Pattern Recognition With UMAP Regression for MetaTrader 5
Dimension reduction techniques are widely used to improve the performance of machine learning models. Let us discuss a relatively new technique known as Uniform Manifold Approximation and Projection (UMAP). This new technique has been developed to explicitly overcome the limitations of legacy
Build Self Optimizing Expert Advisors in MQL5 (Part 6): Self Adapting Trading Rules (II) for MetaTrader 5
This article explores optimizing RSI levels and periods for better trading signals. We introduce methods to estimate optimal RSI values and automate period selection using grid search and statistical models. Finally, we implement the solution in MQL5 while leveraging Python for analysis. Our
Forum
Has The Withdrawal Format Changed Again?
Normally, there's an option specifying which VISA card you'd like to withdraw to, after linking the card to your account. I can't find the option any more, additionally, when I'm making the withdrawal it warns me I'm about to withdraw to a new card, without informing me which card I'm withdrawing
Plotting into the future.
I've been working with ONNX models and I want to draw my model's forecast on to the chart so that as time goes on I can visually see the difference between what the model was expecting and what actually happened. As trivial as that sounds, I'm having a headache trying to plot into the future. I've
Plotting Indicator Values Into The Future For Begginers
I asked before for help on plotting future values directly on the chart, and I received informative help. I'd like to ask now, how can I plot into the future for your indicators. For example, I've got this indicator, shown in Fig 1, and I'd like to plot my predictions of what the indicator's value
ALGLIB For Beginners
I'm keen on learning how to use ALGLIB. However, all the articles I have read so far were teaching too many things at once for me to confidently follow along. Like there's theory in there about SVM, Neural Networks , Grokking Market Memory (I don't even know what that means bro). It's too much for
Failing to read a CSV file
Hi guys. I'm trying to read in a csv file with 2 rows and 8 columns and I keep failing. I'm able to open the file, however I cannot yet access the content of the file. Here is my code. //+------------------------------------------------------------------+ //|
Backtesting Libraries in MQL5
Given OHLC price data and a trading strategy , we can evaluate how profitable the strategy is. We could run a historical back test in MQL5 or if you have the data in CSV format you could use a library in Python or R to backtest your strategy. But how is this being done under the hood? I want to
The Bible of Money Management
Greenings I'd like to talk about money management and I'm keen to gain new perspectives. I trade the daily chart. What I do is, I pull up the chart and I've built an EA that opens a position on the minimum lot size and then places a stop loss 1.5 x the ATR. From there I check the value of the stop
Automating EA Optimization
Can someone please help me understand how to Automatically optimize my EA to a selected chart using a Python Script and the MT5 module for Python. Everything I've learned so far either 1) Simply didn't work, 2) Didn't make use of the MT5 Python module 3) Required me to learn C++ and build a DLL but