Articles on trading system automation in MQL5

In the first part, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. We created the COrder abstract object which is a base object for storing data on history orders and deals, as well as on market orders and positions. Now we will develop all the necessary objects for storing account history data in collections.

While analyzing a huge number of trading strategies, orders for development of applications for MetaTrader 5 and MetaTrader 4 terminals and various MetaTrader websites, I came to the conclusion that all this diversity is based mostly on the same elementary functions, actions and values appearing regularly in different programs. This resulted in DoEasy cross-platform library for easy and quick development of МetaТrader 5 and МetaТrader 4 applications.

In the article, we will apply Reinforcement learning to develop self-learning Expert Advisors. In the previous article, we considered the Random Decision Forest algorithm and wrote a simple self-learning EA based on Reinforcement learning. The main advantages of such an approach (trading algorithm development simplicity and high "training" speed) were outlined. Reinforcement learning (RL) is easily incorporated into any trading EA and speeds up its optimization.

In this article we will consider in detail the martingale system. We will review whether this system can be applied in trading and how to use it in order to minimize risks. The main disadvantage of this simple system is the probability of losing the entire deposit. This fact must be taken into account, if you decide to trade using the martingale technique.

The article considers applying the separate optimization method during various market conditions. Separate optimization means defining trading system's optimal parameters by optimizing for an uptrend and downtrend separately. To reduce the effect of false signals and improve profitability, the systems are made flexible, meaning they have some specific set of settings or input data, which is justified because the market behavior is constantly changing.

This is the last article within the series devoted to the Reversing trading strategy. Here we will try to solve the problem, which caused the testing results instability in previous articles. We will also develop and test our own algorithm for manual trading in any market using the reversing strategy.

In this article, we continue to dwell on reversing techniques. We will try to reduce the maximum balance drawdown till an acceptable level for the instruments considered earlier. We will see if the measures will reduce the profit. We will also check how the reversing method performs on other markets, including stock, commodity, index, ETF and agricultural markets. Attention, the article contains a lot of images!

This article is a follow-up to the previous one called "Reversal patterns: Testing the Double top/bottom pattern". Now we will have a look at another well-known reversal pattern called Head and Shoulders, compare the trading efficiency of the two patterns and make an attempt to combine them into a single trading system.

Traders often look for trend reversal points since the price has the greatest potential for movement at the very beginning of a newly formed trend. Consequently, various reversal patterns are considered in the technical analysis. The Double top/bottom is one of the most well-known and frequently used ones. The article proposes the method of the pattern programmatic detection. It also tests the pattern's profitability on history data.

The article dwells on gaps — significant differences between a close price of a previous timeframe and an open price of the next one, as well as on forecasting a daily bar direction. Applying the GetOpenFileName function by the system DLL is considered as well.

The article dwells on the development of an application for selecting the best optimization passes using several possible options. The application is able to sort out the optimization results by a variety of factors. Optimization passes are always written to a database, therefore you can always select new robot parameters without re-optimization. Besides, you are able to see all optimization passes on a single chart, calculate parametric VaR ratios and build the graph of the normal distribution of passes and trading results of a certain ratio set. Besides, the graphs of some calculated ratios are built dynamically beginning with the optimization start (or from a selected date to another selected date).

In this article, we will study the reverse martingale technique and will try to understand whether it is worth using, as well as whether it can help improve your trading strategy. We will create an Expert Advisor to operate on historic data and to check what indicators are best suitable for the reversing technique. We will also check whether it can be used without any indicator as an independent trading system. In addition, we will check if reversing can turn a loss-making trading system into a profitable one.

Efficiency of any trading robot depends on the correct selection of its parameters (optimization). However, parameters that are considered optimal for one time interval may not retain their effectiveness in another period of trading history. Besides, EAs showing profit during tests turn out to be loss-making in real time. The issue of continuous optimization comes to the fore here. When facing plenty of routine work, humans always look for ways to automate it. In this article, I propose a non-standard approach to solving this issue.

MetaTrader 5 is a multi-asset platform. Moreover, it supports different position management systems. Such opportunities provide significantly expanded options for the implementation and formalization of trading ideas. In this article, we discuss methods of handling and accounting of position properties in the hedging mode. The article features a derived class, as well as examples showing how to get and process the properties of a hedge position.

The article dwells on Elder-Ray trading system based on Bulls Power, Bears Power and Moving Average indicators (EMA — exponential averaging). This system was described by Alexander Elder in his book "Trading for a Living".

Members of the official MetaTrader Freelance service have completed more than 50,000 orders as at October 2018. This is the world's largest Freelance site for MQL programmers: more than a thousand developers, dozens of new orders daily and 7 languages localization.

There are numerous trading strategies out there. Some of them look for a trend, while others define ranges of price fluctuations to trade within them. Is it possible to combine these two approaches to increase profitability?

The article considers three methods which can be used to increase the classification quality of bagging ensembles, and their efficiency is estimated. The effects of optimization of the ELM neural network hyperparameters and postprocessing parameters are evaluated.

The largest store of ready-made applications for algo-trading now features 13,970 products. This includes 4,800 robots, 6,500 indicators, 2,400 utilities and other solutions. Almost half of the applications (6,000) are available for rent. Also, a quarter of the total number of products (3,800) can be downloaded for free.

Trading account monitoring provides a detailed report on all completed deals. All trading statistics are collected automatically and provided to you as easy-to-understand diagrams and graphs.

This article concludes the series devoted to trading currency pair baskets. Here we test the remaining pattern and discuss applying the entire method in real trading. Market entries and exits, searching for patterns and analyzing them, complex use of combined indicators are considered.

Are you trading using your own strategy? If your system rules can be formally described as software algorithms, it is better to entrust trading to an automated Expert Advisor. A robot does not need sleep or food and is not subject to human weaknesses. In this article, we show how to create Requirements Specification when ordering a trading robot in the Freelance service.

The article explores the advantages and disadvantages of trading in flat periods. The ten strategies created and tested within this article are based on the tracking of price movements inside a channel. Each strategy is provided with a filtering mechanism, which is aimed at avoiding false market entry signals.

This article presents a visual strategy builder. It is shown how any user can create trading robots and utilities without programming. Created Expert Advisors are fully functional and can be tested in the strategy tester, optimized in the cloud or executed live on real time charts.

Random Forest (RF) with the use of bagging is one of the most powerful machine learning methods, which is slightly inferior to gradient boosting. This article attempts to develop a self-learning trading system that makes decisions based on the experience gained from interaction with the market.

MQL programming language allows implementing the concept of modular development of trading strategies. The article shows an example of developing a multi-module Expert Advisor consisting of separately compiled file modules.

The article considers the possibility to apply Bayesian optimization to hyperparameters of deep neural networks, obtained by various training variants. The classification quality of a DNN with the optimal hyperparameters in different training variants is compared. Depth of effectiveness of the DNN optimal hyperparameters has been checked in forward tests. The possible directions for improving the classification quality have been determined.

The article implements an MQL application with a graphical interface for extended visualization of the optimization process. The graphical interface applies the last version of EasyAndFast library. Many users may ask why they need graphical interfaces in MQL applications. This article demonstrates one of multiple cases where they can be useful for traders.

The article is based on 'The Mathematics of Money Management' by Ralph Vince. It provides the description of empirical and parametric methods used for finding the optimal size of a trading lot. Also the article features implementation of trading modules for the MQL5 Wizard based on these methods.

In this article, we finish testing the patterns that can be detected when trading currency pair baskets. Here we present the results of testing the patterns tracking the movement of pair's currencies relative to each other.

Price trends form price channels that can be observed on financial symbol charts. The breakout of the current channel is one of the strong trend reversal signals. In this article, I suggest a way to automate the process of finding such signals and see if the channel breakout pattern can be used for creating a trading strategy.

Trading in financial markets is associated with a whole range of risks that should be taken into account in the algorithms of trading systems. Reducing such risks is the most important task to make a profit when trading.

The article deals with the concept of night trading, as well as trading strategies and their implementation in MQL5. We perform tests and make appropriate conclusions.

In this article, we continue to consider writing the code to trading systems described in a book by Linda B. Raschke and Laurence A. Connors “Street Smarts: High Probability Short-Term Trading Strategies”. This time we study Momentum Pinball system: there is described creation of two indicators, trade robot and signal block on it.

In this article we are going to analyze the NRTR indicator and create a trading system based on this indicator. We are going to develop a module of trading signals that can be used in creating strategies based on a combination of NRTR with additional trend confirmation indicators.

We continue testing the patterns and trying the methods described in the articles about trading currency pair baskets. Let's consider in practice, whether it is possible to use the patterns of the combined WPR graph crossing the moving average. If the answer is yes, we should consider the appropriate usage methods.

The article considers one of the variants for Expert Advisor practical realization to trade DiNapoli levels using MQL5 standard tools. Its performance is tested and conclusions are made.

The article suggests a technology helping everyone to create custom trading strategies by assembling an individual indicator set, as well as to develop custom market entry signals.

For successful trading, we almost always need indicators that can separate the main price movement from noise fluctuations. In this article, we consider one of the most promising digital filters, the Kalman filter. The article provides the description of how to draw and use the filter.

The article deals with the popular trading method - triangular arbitrage. Here we analyze the topic in as much detail as possible, consider the positive and negative aspects of the strategy and develop the ready-made Expert Advisor code.