Articles on data analysis and statistics in MQL5
Articles on mathematical models and laws of probability are interesting for many traders. Mathematics is the basis of technical indicators, and statistics is required to analyze trading results and develop strategies.
Read about the fuzzy logic, digital filters, market profile, Kohonen maps, neural gas and many other tools that can be used for trading.
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How to analyze the trades of the Signal selected in the chart
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.
Social Trading. Can a profitable signal be made even better?
Most subscribers choose a trade signal by the beauty of the balance curve and by the number of subscribers. This is why many today's providers care of beautiful statistics rather than of real signal quality, often playing with lot sizes and artificially reducing the balance curve to an ideal appearance. This paper deals with the reliability criteria and the methods a provider may use to enhance its signal quality. An exemplary analysis of a specific signal history is presented, as well as methods that would help a provider to make it more profitable and less risky.
Processing optimization results using the graphical interface
This is a continuation of the idea of processing and analysis of optimization results. This time, our purpose is to select the 100 best optimization results and display them in a GUI table. The user will be able to select a row in the optimization results table and receive a multi-symbol balance and drawdown graph on separate charts.
Visualizing trading strategy optimization in MetaTrader 5
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.
Money Management by Vince. Implementation as a module for MQL5 Wizard
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.
Controlled optimization: Simulated annealing
The Strategy Tester in the MetaTrader 5 trading platform provides only two optimization options: complete search of parameters and genetic algorithm. This article proposes a new method for optimizing trading strategies — Simulated annealing. The method's algorithm, its implementation and integration into any Expert Advisor are considered. The developed algorithm is tested on the Moving Average EA.
How to reduce trader's risks
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.
Risk Evaluation in the Sequence of Deals with One Asset. Continued
The article develops the ideas proposed in the previous part and considers them further. It describes the problems of yield distributions, plotting and studying statistical regularities.
Night trading during the Asian session: How to stay profitable
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.
Creating a new trading strategy using a technology of resolving entries into indicators
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.
Resolving entries into indicators
Different situations happen in trader’s life. Often, the history of successful trades allows us to restore a strategy, while looking at a loss history we try to develop and improve it. In both cases, we compare trades with known indicators. This article suggests methods of batch comparison of trades with a number of indicators.
Comparing different types of moving averages in trading
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.
Mini Market Emulator or Manual Strategy Tester
Mini Market Emulator is an indicator designed for partial emulation of work in the terminal. Presumably, it can be used to test "manual" strategies of market analysis and trading.
A New Approach to Interpreting Classic and Hidden Divergence
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.
Optimizing a strategy using balance graph and comparing results with "Balance + max Sharpe Ratio" criterion
In this article, we consider yet another custom trading strategy optimization criterion based on the balance graph analysis. The linear regression is calculated using the function from the ALGLIB library.
Risk Evaluation in the Sequence of Deals with One Asset
This article describes the use of methods of the theory of probability and mathematical statistics in the analysis of trading systems.
Deep Neural Networks (Part III). Sample selection and dimensionality reduction
This article is a continuation of the series of articles about deep neural networks. Here we will consider selecting samples (removing noise), reducing the dimensionality of input data and dividing the data set into the train/val/test sets during data preparation for training the neural network.
Deep Neural Networks (Part II). Working out and selecting predictors
The second article of the series about deep neural networks will consider the transformation and choice of predictors during the process of preparing data for training a model.
Custom Walk Forward optimization in MetaTrader 5
The article deals with the approaches enabling accurate simulation of walk forward optimization using the built-in tester and auxiliary libraries implemented in MQL.
Deep Neural Networks (Part I). Preparing Data
This series of articles continues exploring deep neural networks (DNN), which are used in many application areas including trading. Here new dimensions of this theme will be explored along with testing of new methods and ideas using practical experiments. The first article of the series is dedicated to preparing data for DNN.
How to conduct a qualitative analysis of trading signals and select the best of them
The article deals with evaluating the performance of Signals Providers. We offer several additional parameters highlighting signal trading results from a slightly different angle than in traditional approaches. The concepts of the proper management and perfect deal are described. We also dwell on the optimal selection using the obtained results and compiling the portfolio of multiple signal sources.
Naive Bayes classifier for signals of a set of indicators
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.
Sorting methods and their visualization using MQL5
The Graphic.mqh library has been designed to work with graphics in MQL5. The article provides an example of its practical application and explains the idea of sorting. The general concept of sorting is described here since each type of sorting already has at least one separate article, while some of sorting types are objects of detailed studies.
Forecasting market movements using the Bayesian classification and indicators based on Singular Spectrum Analysis
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.
DiNapoli trading system
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.
Analyzing Balance/Equity graphs by symbols and EAs' ORDER_MAGIC
With the introduction of hedging, MetaTrader 5 provides an excellent opportunity to trade several Expert Advisors on a single trading account simultaneously. When one strategy is profitable, while the second one is loss-making, the profit graph may hang around zero. In this case, it is useful to build the Balance and Equity graphs for each trading strategy separately.
Calculating the Hurst exponent
The article thoroughly explains the idea behind the Hurst exponent, as well as the meaning of its values and the calculation algorithm. A number of financial market segments are analyzed and the method of working with MetaTrader 5 products implementing the fractal analysis is described.
Visualize this! MQL5 graphics library similar to 'plot' of R language
When studying trading logic, visual representation in the form of graphs is of great importance. A number of programming languages popular among the scientific community (such as R and Python) feature the special 'plot' function used for visualization. It allows drawing lines, point distributions and histograms to visualize patterns. In MQL5, you can do the same using the CGraphics class.
Statistical distributions in the form of histograms without indicator buffers and arrays
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.
How to build and test a Binary Options strategy with the MetaTrader 4 Strategy Tester
Tutorial to build a Binary Options strategy an test it in Strategy-Tester of MetaTrader 4 with Binary-Options-Strategy-Tester utility from marketplace.
Statistical Distributions in MQL5 - taking the best of R and making it faster
The functions for working with the basic statistical distributions implemented in the R language are considered. Those include the Cauchy, Weibull, normal, log-normal, logistic, exponential, uniform, gamma distributions, the central and noncentral beta, chi-squared, Fisher's F-distribution, Student's t-distribution, as well as the discrete binomial and negative binomial distributions, geometric, hypergeometric and Poisson distributions. There are functions for calculating theoretical moments of distributions, which allow to evaluate the degree of conformity of the real distribution to the modeled one.
The Easy Way to Evaluate a Signal: Trading Activity, Drawdown/Load and MFE/MAE Distribution Charts
Subscribers often search for an appropriate signal by analyzing the total growth on the signal provider's account, which is not a bad idea. However, it is also important to analyze potential risks of a particular trading strategy. In this article we will show a simple and efficient way to evaluate a Trading Signal based on its performance values.
Portfolio trading in MetaTrader 4
The article reveals the portfolio trading principles and their application to Forex market. A few simple mathematical portfolio arrangement models are considered. The article contains examples of practical implementation of the portfolio trading in MetaTrader 4: portfolio indicator and Expert Advisor for semi-automated trading. The elements of trading strategies, as well as their advantages and pitfalls are described.
Self-optimization of EA: Evolutionary and genetic algorithms
This article covers the main principles set fourth in evolutionary algorithms, their variety and features. We will conduct an experiment with a simple Expert Advisor used as an example to show how our trading system benefits from optimization. We will consider software programs that implement genetic, evolutionary and other types of optimization, and provide examples of application when optimizing a predictor set and parameters of the trading system.
Self-organizing feature maps (Kohonen maps) - revisiting the subject
This article describes techniques of operating with Kohonen maps. The subject will be of interest to both market researchers with basic level of programing in MQL4 and MQL5 and experienced programmers that face difficulties with connecting Kohonen maps to their projects.
Applying fuzzy logic in trading by means of MQL4
The article deals with examples of applying fuzzy set theory in trading by means of MQL4. The use of FuzzyNet library for MQL4 in the development of an indicator and an Expert Advisor is described as well.
Deep neural network with Stacked RBM. Self-training, self-control
This article is a continuation of previous articles on deep neural network and predictor selection. Here we will cover features of a neural network initiated by Stacked RBM, and its implementation in the "darch" package.
Enhancing the StrategyTester to Optimize Indicators Solely on the Example of Flat and Trend Markets
It is essential to detect whether a market is flat or not for many strategies. Using the well known ADX we demonstrate how we can use the Strategy Tester not only to optimize this indicator for our specific purpose, but as well we can decide whether this indicator will meet our needs and get to know the average range of the flat and trend markets which might be quite important to determine stops and targets of the markets.
Evaluation and selection of variables for machine learning models
This article focuses on specifics of choice, preconditioning and evaluation of the input variables (predictors) for use in machine learning models. New approaches and opportunities of deep predictor analysis and their influence on possible overfitting of models will be considered. The overall result of using models largely depends on the result of this stage. We will analyze two packages offering new and original approaches to the selection of predictors.
An Introduction to Fuzzy Logic
Fuzzy logic expands our boundaries of mathematical logic and set theory. This article reveals the basic principles of fuzzy logic as well as describes two fuzzy inference systems using Mamdani-type and Sugeno-type models. The examples provided will describe implementation of fuzzy models based on these two systems using the FuzzyNet library for MQL5.