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Advanced EA constructor for MetaTrader - botbrains.app
Advanced EA constructor for MetaTrader - botbrains.app
In this article, we demonstrate features of botbrains.app - a no-code platform for trading robots development. To create a trading robot you don't need to write any code - just drag and drop the necessary blocks onto the scheme, set their parameters, and establish connections between them.
Combinatorics and probability for trading (Part V): Curve analysis
Combinatorics and probability for trading (Part V): Curve analysis
In this article, I decided to conduct a study related to the possibility of reducing multiple states to double-state systems. The main purpose of the article is to analyze and to come to useful conclusions that may help in the further development of scalable trading algorithms based on the probability theory. Of course, this topic involves mathematics. However, given the experience of previous articles, I see that generalized information is more useful than details.
Combinatorics and probability for trading (Part IV): Bernoulli Logic
Combinatorics and probability for trading (Part IV): Bernoulli Logic
In this article, I decided to highlight the well-known Bernoulli scheme and to show how it can be used to describe trading-related data arrays. All this will then be used to create a self-adapting trading system. We will also look for a more generic algorithm, a special case of which is the Bernoulli formula, and will find an application for it.
MQL5 Cookbook: ОСО Orders
MQL5 Cookbook: ОСО Orders
Any trader's trading activity involves various mechanisms and interrelationships including relations among orders. This article suggests a solution of OCO orders processing. Standard library classes are extensively involved, as well as new data types are created herein.
How to Order an Expert Advisor and Obtain the Desired Result
How to Order an Expert Advisor and Obtain the Desired Result
How to write correctly the Requirement Specifications? What should and should not be expected from a programmer when ordering an Expert Advisor or an indicator? How to keep a dialog, what moments to pay special attention to? This article gives the answers to these, as well as to many other questions, which often don't seem obvious to many people.
How to Prepare MetaTrader 5 Quotes for Other Applications
How to Prepare MetaTrader 5 Quotes for Other Applications
The article describes the examples of creating directories, copying data, filing, working with the symbols in Market Watch or the common list, as well as the examples of handling errors, etc. All these elements can eventually be gathered in a single script for filing the data in a user-defined format.
Combinatorics and probability theory for trading (Part III): The first mathematical model
Combinatorics and probability theory for trading (Part III): The first mathematical model
A logical continuation of the earlier discussed topic would be the development of multifunctional mathematical models for trading tasks. In this article, I will describe the entire process related to the development of the first mathematical model describing fractals, from scratch. This model should become an important building block and be multifunctional and universal. It will build up our theoretical basis for further development of this idea.
Combinatorics and probability theory for trading (Part I): The basics
Combinatorics and probability theory for trading (Part I): The basics
In this series of article, we will try to find a practical application of probability theory to describe trading and pricing processes. In the first article, we will look into the basics of combinatorics and probability, and will analyze the first example of how to apply fractals in the framework of the probability theory.
Swaps (Part I): Locking and Synthetic Positions
Swaps (Part I): Locking and Synthetic Positions
In this article I will try to expand the classic concept of swap trading methods. I will explain why I have come to the conclusion that this concept deserves special attention and is absolutely recommended for study.
Developing a self-adapting algorithm (Part II): Improving efficiency
Developing a self-adapting algorithm (Part II): Improving efficiency
In this article, I will continue the development of the topic by improving the flexibility of the previously created algorithm. The algorithm became more stable with an increase in the number of candles in the analysis window or with an increase in the threshold percentage of the overweight of falling or growing candles. I had to make a compromise and set a larger sample size for analysis or a larger percentage of the prevailing candle excess.
Self-adapting algorithm (Part IV): Additional functionality and tests
Self-adapting algorithm (Part IV): Additional functionality and tests
I continue filling the algorithm with the minimum necessary functionality and testing the results. The profitability is quite low but the articles demonstrate the model of the fully automated profitable trading on completely different instruments traded on fundamentally different markets.
Self-adapting algorithm (Part III): Abandoning optimization
Self-adapting algorithm (Part III): Abandoning optimization
It is impossible to get a truly stable algorithm if we use optimization based on historical data to select parameters. A stable algorithm should be aware of what parameters are needed when working on any trading instrument at any time. It should not forecast or guess, it should know for sure.
Finding seasonal patterns in the forex market using the CatBoost algorithm
Finding seasonal patterns in the forex market using the CatBoost algorithm
The article considers the creation of machine learning models with time filters and discusses the effectiveness of this approach. The human factor can be eliminated now by simply instructing the model to trade at a certain hour of a certain day of the week. Pattern search can be provided by a separate algorithm.
Developing a self-adapting algorithm (Part I): Finding a basic pattern
Developing a self-adapting algorithm (Part I): Finding a basic pattern
In the upcoming series of articles, I will demonstrate the development of self-adapting algorithms considering most market factors, as well as show how to systematize these situations, describe them in logic and take them into account in your trading activity. I will start with a very simple algorithm that will gradually acquire theory and evolve into a very complex project.
Using spreadsheets to build trading strategies
Using spreadsheets to build trading strategies
The article describes the basic principles and methods that allow you to analyze any strategy using spreadsheets (Excel, Calc, Google). The obtained results are compared with MetaTrader 5 tester.
Gradient boosting in transductive and active machine learning
Gradient boosting in transductive and active machine learning
In this article, we will consider active machine learning methods utilizing real data, as well discuss their pros and cons. Perhaps you will find these methods useful and will include them in your arsenal of machine learning models. Transduction was introduced by Vladimir Vapnik, who is the co-inventor of the Support-Vector Machine (SVM).
A scientific approach to the development of trading algorithms
A scientific approach to the development of trading algorithms
The article considers the methodology for developing trading algorithms, in which a consistent scientific approach is used to analyze possible price patterns and to build trading algorithms based on these patterns. Development ideals are demonstrated using examples.
Practical application of neural networks in trading. Python (Part I)
Practical application of neural networks in trading. Python (Part I)
In this article, we will analyze the step-by-step implementation of a trading system based on the programming of deep neural networks in Python. This will be performed using the TensorFlow machine learning library developed by Google. We will also use the Keras library for describing neural networks.
Basic math behind Forex trading
Basic math behind Forex trading
The article aims to describe the main features of Forex trading as simply and quickly as possible, as well as share some basic ideas with beginners. It also attempts to answer the most tantalizing questions in the trading community along with showcasing the development of a simple indicator.
Custom symbols: Practical basics
Custom symbols: Practical basics
The article is devoted to the programmatic generation of custom symbols which are used to demonstrate some popular methods for displaying quotes. It describes a suggested variant of minimally invasive adaptation of Expert Advisors for trading a real symbol from a derived custom symbol chart. MQL source codes are attached to this article.
What is a trend and is the market structure based on trend or flat?
What is a trend and is the market structure based on trend or flat?
Traders often talk about trends and flats but very few of them really understand what a trend/flat really is and even fewer are able to clearly explain these concepts. Discussing these basic terms is often beset by a solid set of prejudices and misconceptions. However, if we want to make profit, we need to understand the mathematical and logical meaning of these concepts. In this article, I will take a closer look at the essence of trend and flat, as well as try to define whether the market structure is based on trend, flat or something else. I will also consider the most optimal strategies for making profit on trend and flat markets.
Using cryptography with external applications
Using cryptography with external applications
In this article, we consider encryption/decryption of objects in MetaTrader and in external applications. Our purpose is to determine the conditions under which the same results will be obtained with the same initial data.
How to Subscribe to Trading Signals
How to Subscribe to Trading Signals
The Signals service introduces social trading with MetaTrader 4 and MetaTrader 5. The Service is integrated into the trading platform, and allows anyone to easily copy trades of professional traders. Select any of the thousands of signal providers, subscribe in a few clicks and the provider's trades will be copied on your account.
Quick Manual Trading Toolkit: Basic Functionality
Quick Manual Trading Toolkit: Basic Functionality
Today, many traders switch to automated trading systems which can require additional setup or can be fully automated and ready to use. However, there is a considerable part of traders who prefer trading manually, in the old fashioned way. In this article, we will create toolkit for quick manual trading, using hotkeys, and for performing typical trading actions in one click.
Manual charting and trading toolkit (Part I). Preparation: structure description and helper class
Manual charting and trading toolkit (Part I). Preparation: structure description and helper class
This is the first article in a series, in which I am going to describe a toolkit which enables manual application of chart graphics by utilizing keyboard shortcuts. It is very convenient: you press one key and a trendline appears, you press another key — this will create a Fibonacci fan with the necessary parameters. It will also be possible to switch timeframes, to rearrange layers or to delete all objects from the chart.
Multicurrency monitoring of trading signals (Part 5): Composite signals
Multicurrency monitoring of trading signals (Part 5): Composite signals
In the fifth article related to the creation of a trading signal monitor, we will consider composite signals and will implement the necessary functionality. In earlier versions, we used simple signals, such as RSI, WPR and CCI, and we also introduced the possibility to use custom indicators.
An Example of Developing a Spread Strategy for Moscow Exchange Futures
An Example of Developing a Spread Strategy for Moscow Exchange Futures
The MetaTrader 5 platform allows developing and testing trading robots that simultaneously trade multiple financial instruments. The built-in Strategy Tester automatically downloads required tick history from the broker's server taking into account contract specifications, so the developer does not need to do anything manually. This makes it possible to easily and reliably reproduce trading environment conditions, including even millisecond intervals between the arrival of ticks on different symbols. In this article we will demonstrate the development and testing of a spread strategy on two Moscow Exchange futures.
Developing Pivot Mean Oscillator: a novel Indicator for the Cumulative Moving Average
Developing Pivot Mean Oscillator: a novel Indicator for the Cumulative Moving Average
This article presents Pivot Mean Oscillator (PMO), an implementation of the cumulative moving average (CMA) as a trading indicator for the MetaTrader platforms. In particular, we first introduce Pivot Mean (PM) as a normalization index for timeseries that computes the fraction between any data point and the CMA. We then build PMO as the difference between the moving averages applied to two PM signals. Some preliminary experiments carried out on the EURUSD symbol to test the efficacy of the proposed indicator are also reported, leaving ample space for further considerations and improvements.