Add a new article
Timeseries in DoEasy library (part 46): Multi-period multi-symbol indicator buffers
Timeseries in DoEasy library (part 46): Multi-period multi-symbol indicator buffers
In this article, I am going to improve the classes of indicator buffer objects to work in the multi-symbol mode. This will pave the way for creating multi-symbol multi-period indicators in custom programs. I will add the missing functionality to the calculated buffer objects allowing us to create multi-symbol multi-period standard indicators.
Implementing the Janus factor in MQL5
Implementing the Janus factor in MQL5
Gary Anderson developed a method of market analysis based on a theory he dubbed the Janus Factor. The theory describes a set of indicators that can be used to reveal trends and assess market risk. In this article we will implement these tools in mql5.
Timeseries in DoEasy library (part 45): Multi-period indicator buffers
Timeseries in DoEasy library (part 45): Multi-period indicator buffers
In this article, I will start the improvement of the indicator buffer objects and collection class for working in multi-period and multi-symbol modes. I am going to consider the operation of buffer objects for receiving and displaying data from any timeframe on the current symbol chart.
Timeseries in DoEasy library (part 41): Sample multi-symbol multi-period indicator
Timeseries in DoEasy library (part 41): Sample multi-symbol multi-period indicator
In the article, we will consider a sample multi-symbol multi-period indicator using the timeseries classes of the DoEasy library displaying the chart of a selected currency pair on a selected timeframe as candles in a subwindow. I am going to modify the library classes a bit and create a separate file for storing enumerations for program inputs and selecting a compilation language.
Frequency domain representations of time series: The Power Spectrum
Frequency domain representations of time series: The Power Spectrum
In this article we discuss methods related to the analysis of timeseries in the frequency domain. Emphasizing the utility of examining the power spectra of time series when building predictive models. In this article we will discuss some of the useful perspectives to be gained by analyzing time series in the frequency domain using the discrete fourier transform (dft).
Measuring Indicator Information
Measuring Indicator Information
Machine learning has become a popular method for strategy development. Whilst there has been more emphasis on maximizing profitability and prediction accuracy , the importance of processing the data used to build predictive models has not received a lot of attention. In this article we consider using the concept of entropy to evaluate the appropriateness of indicators to be used in predictive model building as documented in the book Testing and Tuning Market Trading Systems by Timothy Masters.
Implementing an ARIMA training algorithm in MQL5
Implementing an ARIMA training algorithm in MQL5
In this article we will implement an algorithm that applies the Box and Jenkins Autoregressive Integrated Moving Average model by using Powells method of function minimization. Box and Jenkins stated that most time series could be modeled by one or both of two frameworks.
Canvas based indicators: Filling channels with transparency
Canvas based indicators: Filling channels with transparency
In this article I'll introduce a method for creating custom indicators whose drawings are made using the class CCanvas from standard library and see charts properties for coordinates conversion. I'll approach specially indicators which need to fill the area between two lines using transparency.
Population optimization algorithms: Harmony Search (HS)
Population optimization algorithms: Harmony Search (HS)
In the current article, I will study and test the most powerful optimization algorithm - harmonic search (HS) inspired by the process of finding the perfect sound harmony. So what algorithm is now the leader in our rating?
Dealing with Time (Part 2): The Functions
Dealing with Time (Part 2): The Functions
Determing the broker offset and GMT automatically. Instead of asking the support of your broker, from whom you will probably receive an insufficient answer (who would be willing to explain a missing hour), we simply look ourselves how they time their prices in the weeks of the time changes — but not cumbersome by hand, we let a program do it — why do we have a PC after all.
Population optimization algorithms: Gravitational Search Algorithm (GSA)
Population optimization algorithms: Gravitational Search Algorithm (GSA)
GSA is a population optimization algorithm inspired by inanimate nature. Thanks to Newton's law of gravity implemented in the algorithm, the high reliability of modeling the interaction of physical bodies allows us to observe the enchanting dance of planetary systems and galactic clusters. In this article, I will consider one of the most interesting and original optimization algorithms. The simulator of the space objects movement is provided as well.
Category Theory in MQL5 (Part 4): Spans, Experiments, and Compositions
Category Theory in MQL5 (Part 4): Spans, Experiments, and Compositions
Category Theory is a diverse and expanding branch of Mathematics which as of yet is relatively uncovered in the MQL5 community. These series of articles look to introduce and examine some of its concepts with the overall goal of establishing an open library that provides insight while hopefully furthering the use of this remarkable field in Traders' strategy development.
MQL5 Cookbook — Macroeconomic events database
MQL5 Cookbook — Macroeconomic events database
The article discusses the possibilities of handling databases based on the SQLite engine. The CDatabase class has been formed for convenience and efficient use of OOP principles. It is subsequently involved in the creation and management of the database of macroeconomic events. The article provides the examples of using multiple methods of the CDatabase class.
Population optimization algorithms: Fish School Search (FSS)
Population optimization algorithms: Fish School Search (FSS)
Fish School Search (FSS) is a new optimization algorithm inspired by the behavior of fish in a school, most of which (up to 80%) swim in an organized community of relatives. It has been proven that fish aggregations play an important role in the efficiency of foraging and protection from predators.
DoEasy. Controls (Part 29): ScrollBar auxiliary control
DoEasy. Controls (Part 29): ScrollBar auxiliary control
In this article, I will start developing the ScrollBar auxiliary control element and its derivative objects — vertical and horizontal scrollbars. A scrollbar is used to scroll the content of the form if it goes beyond the container. Scrollbars are usually located at the bottom and to the right of the form. The horizontal one at the bottom scrolls content left and right, while the vertical one scrolls up and down.
MQL5 Cookbook — Services
MQL5 Cookbook — Services
The article describes the versatile capabilities of services — MQL5 programs that do not require binding graphs. I will also highlight the differences of services from other MQL5 programs and emphasize the nuances of the developer's work with services. As examples, the reader is offered various tasks covering a wide range of functionality that can be implemented as a service.
Develop a Proof-of-Concept DLL with C++ multi-threading support for MetaTrader 5 on Linux
Develop a Proof-of-Concept DLL with C++ multi-threading support for MetaTrader 5 on Linux
We will begin the journey to explore the steps and workflow on how to base development for MetaTrader 5 platform solely on Linux system in which the final product works seamlessly on both Windows and Linux system. We will get to know Wine, and Mingw; both are the essential tools to make cross-platform development works. Especially Mingw for its threading implementations (POSIX, and Win32) that we need to consider in choosing which one to go with. We then build a proof-of-concept DLL and consume it in MQL5 code, finally compare the performance of both threading implementations. All for your foundation to expand further on your own. You should be comfortable building MT related tools on Linux after reading this article.
Population optimization algorithms: Grey Wolf Optimizer (GWO)
Population optimization algorithms: Grey Wolf Optimizer (GWO)
Let's consider one of the newest modern optimization algorithms - Grey Wolf Optimization. The original behavior on test functions makes this algorithm one of the most interesting among the ones considered earlier. This is one of the top algorithms for use in training neural networks, smooth functions with many variables.