
Hardcoded prop-firm rules lock the sizer to one program. This article factors those rules into a PropFirmRuleSet and refactors PropFirmAccountState and the sizing modifiers to consume it, including dynamic versus fixed daily limits and the news-window profit-credit haircut. Parity against the original FundedNext behavior is validated on a simulated equity path, so you can retarget sizing by configuration instead of rewriting code.

We need a way to handle the graphical objects we create. The approach presented in the previous article works very well for certain scenarios. In this case, we will need something more complex, given the specific nature of the problem at hand. Therefore, we will not attempt to replace the ZOrder management mechanisms already present in MetaTrader 5, nor, of course, will we check which object is in the foreground or covered by another object. We are going to do something completely different. Here, I will show you what changes need to be made to the code in order to use part of what MetaTrader 5 already does for us.

This is an article that you, dear reader, should study carefully. That is due to the nature of the material presented here. Although we have tried to present the material as simply and informatively as possible, the information provided here can certainly seem quite complex to those who are just beginning to learn programming. Nevertheless, this is no reason to lose heart or ignore what is explained here, as this article will establish a link between two completely different, though closely related, topics.

This article shows how to build an interactive bar replay tool in MQL5 for MetaTrader 5 that reveals historical candles one by one without exposing future data. You will implement custom candles with DRAW COLOR CANDLES, an event-driven engine with OnChartEvent and OnTimer, a dashboard with Play/Pause, a draggable replay anchor, and Buy/Sell paper trading with SL/TP lines, while keeping the active bar in view to practice discretionary analysis and execution.

We introduce a persistent bookmark layer for the MetaTrader 5 History Navigator. Bookmarks capture a chart's symbol, timeframe, and historical position with a name and notes, write them to a CSV file, and reload them later without manual date entry. The implementation integrates bookmark management into the current navigation engine, enabling quick creation, selection, navigation, and deletion for efficient historical study.

In this turning-point article, we will begin to explore in greater depth the interaction between the applications we are developing to ensure full support for the replay/simulation system. Here we will analyze a problem that, on the one hand, is quite unpleasant, but on the other hand, is very interesting to explain and solve. The problem is this: how can we restore the take-profit and stop-loss lines after they have been deleted, and do so without using the terminal by performing the operation directly on the chart? At first glance, it seems simple. However, there are several obstacles that must be overcome.

In this article, we'll begin exploring a short series of concepts that are of immense importance to anyone who truly wants to learn how to program properly. Since this may seem very complicated at first—even though it is based on simple elements—we will go through the material step by step. So, let's start by figuring out what queues are.

How to purchase a trading robot from the MetaTrader Market and to install it?
A product from the MetaTrader Market can be purchased on the MQL5.com website or straight from the MetaTrader 4 and MetaTrader 5 trading platforms. Choose a desired product that suits your trading style, pay for it using your preferred payment method, and activate the product.
How to Test a Trading Robot Before Buying
Buying a trading robot on MQL5 Market has a distinct benefit over all other similar options - an automated system offered can be thoroughly tested directly in the MetaTrader 5 terminal. Before buying, an Expert Advisor can and should be carefully run in all unfavorable modes in the built-in Strategy Tester to get a complete grasp of the system.

The article examines the Hamiltonian Monte Carlo (HMC) algorithm — the gold standard for sampling from complex multivariate distributions. A full-featured implementation of HMC in MQL5 is presented, including adaptive mass matrix tuning, MAP estimation using the L-BFGS optimization method, and comprehensive diagnostics.

In the previous article, we considered how to implement a position indicator that allows you to close an open position directly from the chart by interacting with an object available on the chart. After completing and testing the first mechanism, we began making changes to ensure that take-profit and stop-loss levels could be removed for an open position. However, since the necessary changes required detailed explanations, in that same article I showed only the changes that needed to be made to the expert advisor; I still needed to show the changes that needed to be made to the position indicator.

We invite you to explore the innovative SCNN framework, which takes time series analysis to a new level by clearly separating data into long-term, seasonal, short-term, and residual components. This approach significantly improves forecasting accuracy by allowing the model to adapt to complex and changing market dynamics.

This article will explain a very simple and easy-to-understand mechanism whose purpose is to sort any array. In it, we will see that the result obtained does not always meet expectations, so the implementation itself will need to be adapted to achieve the desired results.

Fixed exits ignore state changes while a trade is open. We implement a discrete-time competing-risks model entirely in MQL5, estimate cause-specific hazards for take-profit and stop-loss via Newton–Raphson on a person-period dataset with time-varying features, and turn cumulative incidence into a bar-by-bar hold-or-close rule, then test it against fixed take-profit/stop-loss with identical entry logic.

This article presents a complete RL trading pipeline for XAUUSD: a supervised signal baseline with triple-barrier labels, PPO training, purged walk-forward validation with embargo, multi-seed checks, and contract-guarded deployment with normalization. It includes runnable code for data validation, features, environment, training, and broker‑based reconciliation. The live demo over 763 closed trades showed no statistically significant edge, and the methods highlight where information and costs, not architecture, set performance limits.

The Dandelion Optimizer (DO) turns the simple flight of a seed carried by the wind into a mathematical search strategy. The three phases — vortex rising, drift toward the center of the population, and landing along a Lévy-flight trajectory — form an elegant metaphor that yields interesting results in practice.

In this article, we'll start making some improvements to the position indicator so that we can interact with it and modify price lines or close a position directly through the position indicator. Before we move on to the implementation, there are a few things worth clarifying, especially for those who aren't familiar with this. The indicator cannot be used in any way to change anything on the trading server. This is because MetaTrader 5 has a security system in place that allows only Expert Advisors to modify orders and positions. No application other than an Expert Advisor can manipulate orders or positions.