In this article, we will discuss the idea of creating a multicurrency monitor of trading signals and will develop a future application structure along with its prototype, as well as create its framework for further operation. The article presents a step-by-step creation of a flexible multicurrency application which will enable the generation of trading signals and which will assist traders in finding the desired signals.
In the previous two articles, we discussed the application of Merrill patterns to various data types. An application was developed to test the presented ideas. In this article, we will continue working with the Strategy Builder, to improve its efficiency and to implement new features and capabilities.
In the previous article, we considered application of Merrill patterns to various data, such as to a price value on a currency symbol chart and values of standard MetaTrader 5 indicators: ATR, WPR, CCI, RSI, among others. Now, let us try to create a strategy construction set based on Merrill patterns.
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.
The article provides a critical examination of regular divergence and efficiency of various indicators. In addition, it contains filtering options for an increased analysis accuracy and features description of non-standard solutions. As a result, we will create a new tool for solving the technical task.
Since its introduction, MetaTrader 5 provides multicurrency testing options. This possibility is often used by traders. However the function is not universal. The article presents several programs for drawing graphical objects on charts based on HTML and CSV trading history reports. Multicurrency trading can be analyzed in parallel, in several sub-windows, as well as in one window using the dynamic switching command.
Most of traders agree that the current market state analysis starts with the evaluation of higher chart timeframes. The analysis is performed downwards to lower timeframes until the one, at which deals are performed. This analysis method seems to be a mandatory part of professional approach for successful trading. In this article, we will discuss multi-timeframe indicators and their creation ways, as well as we will provide MQL5 code examples. In addition to the general evaluation of advantages and disadvantages, we will propose a new indicator approach using the MTF mode.
The purpose of this article is to create a custom tool, which would enable users to receive and use the entire array of information about patterns discussed earlier. We will create a library of pattern related functions which you will be able to use in your own indicators, trading panels, Expert Advisors, etc.
In the previous article, we analyzed 14 patterns selected from a large variety of existing candlestick formations. It is impossible to analyze all the patterns one by one, therefore another solution was found. The new system searches and tests new candlestick patterns based on known candlestick types.
In this article, we will consider popular candlestick patterns and will try to find out if they are still relevant and effective in today's markets. Candlestick analysis appeared more than 20 years ago and has since become quite popular. Many traders consider Japanese candlesticks the most convenient and easily understandable asset price visualization form.
Based on universal tools designed for working with Kohonen networks, we construct the system of analyzing and selecting the optimal EA parameters and consider forecasting time series. In Part I, we corrected and improved the publicly available neural network classes, having added necessary algorithms. Now, it is time to apply them to practice.
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 provides an overview of the terminal's capabilities for creating and working with custom symbols, offers options for simulating a trading history using custom symbols, trend and various chart patterns.
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.
The article deals with the algorithm of developing stock indicators based on real volumes using the CopyTicks() and CopyTicksRange() functions. Some subtle aspects of developing such indicators, as well as their operation in real time and in the strategy tester are also described.
When developing trading algorithms, we often encounter a problem: how to determine where a trend/flat begins and ends? In this article, we try to create a universal indicator, in which we try to combine signals for different types of strategies. We will try to simplify the process of obtaining trade signals in an expert as much as possible. An example of combining several indicators in one will be given.
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.
The trade Signals service develops in leaps and bounds. Trusting our funds to a signal provider, we would like to minimize the risk of losing our deposit. So how to puzzle out in this forest of trade signals? How to find the one that would produce profits? This paper proposes to create a tool for visually analyzing the history of trades on trade signals in a symbol chart.
The article demonstrates the development of the ZigZag indicator in accordance with one of the sample specifications described in the article "How to prepare Requirements Specification when ordering an indicator". The indicator is built by extreme values defined using an oscillator. There is an ability to use one of five oscillators: WPR, CCI, Chaikin, RSI or Stochastic Oscillator.
The ZUP indicator platform allows searching for multiple known patterns, parameters for which have already been set. These parameters can be edited to suit your requirements. You can also create new patterns using the ZUP graphical interfaces and save their parameters to a file. After that you can quickly check, whether these new patterns can be found on charts.
When making trading decisions, we often have to analyze charts on several timeframes. At the same time, these charts often contain graphical objects. Applying the same objects to all charts is inconvenient. In this article, I propose to automate cloning of objects to be displayed on charts.
Most often the first step in the development of a trading system is the creation of a technical indicator, which can identify favorable market behavior patterns. A professionally developed indicator can be ordered from the Freelance service. From this article you will learn how to create a proper Requirements Specification, which will help you to obtain the desired indicator faster.
The article deals with automatic construction of support/resistance lines using local tops and bottoms of price charts. The well-known ZigZag indicator is applied to define these extreme values.
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.
This article deals with seven types of moving averages (MA) and a trading strategy to work with them. We also test and compare various MAs at a single trading strategy and evaluate the efficiency of each moving average compared to others.
The article considers the classic method for divergence construction and provides an additional divergence interpretation method. A trading strategy was developed based on this new interpretation method. This strategy is also described in the article.
The article considers all kinds of divergence: simple, hidden, extended, triple, quadruple, convergence, as well as divergences of A, B and C classes. A universal indicator for their search and display on the chart is developed.
The article provides the analysis of the following patterns: Flag, Pennant, Wedge, Rectangle, Contracting Triangle, Expanding Triangle. In addition to analyzing their similarities and differences, we will create indicators for detecting these patterns on the chart, as well as a tester indicator for the fast evaluation of their effectiveness.
The article analyzes the application of the Bayes' formula for increasing the reliability of trading systems by means of using signals from multiple independent indicators. Theoretical calculations are verified with a simple universal EA, configured to work with arbitrary indicators.
The article considers the ideology and methodology of building a recommendatory system for time-efficient trading by combining the capabilities of forecasting with the singular spectrum analysis (SSA) and important machine learning method on the basis of Bayes' Theorem.
The article describes the Fibo levels-based trading system developed by Joe DiNapoli. The idea behind the system and the main concepts are explained, as well as a simple indicator is provided as an example for more clarity.
The article provides an example of how to implement an indicator for drawing support and resistance lines based on formalized conditions. In addition to having a ready-to-use indicator, you will see how simple the indicator creation process is. You will also learn how to formulate conditions for drawing any desired line by changing the indicator code.
In this article, I will tell you how to successfully trade by merging a very well-known strategy and a neural network. It will be about the Thomas DeMark's Sequential strategy with the use of an artificial intelligence system. Only the first part of the strategy will be applied, using the Setup and Intersection signals.
A time series is a dynamic system, in which values of a random variable are received continuously or at successive equally spaced points in time. Transition from 2D to 3D market analysis provides a new look at complex processes and research objects. The article describes visualization methods providing 3D representation of two-dimensional data.
Automation of trading strategies involving graphical patterns requires the ability to search for extreme points on the charts for further processing and interpretation. Existing tools do not always provide such an ability. The algorithms described in the article allow finding all extreme points on charts. The tools discussed here are equally efficient both during trends and flat movements. The obtained results are not strongly affected by a selected timeframe and are only defined by a specified scale.
The article discusses the possibility of plotting statistical distribution histograms of market conditions with the help of the graphical memory meaning no indicator buffers and arrays are applied. Sample histograms are described in details and the "hidden" functionality of MQL5 graphical objects is shown.
Scalping automatic systems are rightfully regarded the pinnacle of algorithmic trading, but at the same time their code is the most difficult to write. In this article we will show how to build strategies based on analysis of incoming ticks using the built-in debugging tools and visual testing. Developing rules for entry and exit often require years of manual trading. But with the help of MetaTrader 5, you can quickly test any such strategy on real history.
The article reveals how the "Rope" indicator is created based on "The Small Encyclopedia of Trader" by Erik L. Nayman. This indicator shows the direction of the trend using the calculated values of bulls and bears over a specified period of time. The article also contains principles of creating and calculating indicators along with the examples of codes. Other subjects covered include building an Expert Advisor based on the indicator, and the optimization of external parameters.
