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Calculating the Hurst exponent
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.
MetaTrader AppStore Results for Q3 2013
MetaTrader AppStore Results for Q3 2013
Another quarter of the year has passed and we have decided to sum up its results for MetaTrader AppStore - the largest store of trading robots and technical indicators for MetaTrader platforms. More than 500 developers have placed over 1 200 products in the Market by the end of the reported quarter.
Third Generation Neural Networks: Deep Networks
Third Generation Neural Networks: Deep Networks
This article is dedicated to a new and perspective direction in machine learning - deep learning or, to be precise, deep neural networks. This is a brief review of second generation neural networks, the architecture of their connections and main types, methods and rules of learning and their main disadvantages followed by the history of the third generation neural network development, their main types, peculiarities and training methods. Conducted are practical experiments on building and training a deep neural network initiated by the weights of a stacked autoencoder with real data. All the stages from selecting input data to metric derivation are discussed in detail. The last part of the article contains a software implementation of a deep neural network in an Expert Advisor with a built-in indicator based on MQL4/R.
Jeremy Scott - Successful MQL5 Market Seller
Jeremy Scott - Successful MQL5 Market Seller
Jeremy Scott who is better known under Johnnypasado nickname at MQL5.community became famous offering products in our MQL5 Market service. Jeremy has already made several thousands of dollars in the Market and that is not the limit. We decided to take a closer look at the future millionaire and receive some pieces of advice for MQL5 Market sellers.
Tips for Selecting a Trading Signal to Subscribe. Step-By-Step Guide
Tips for Selecting a Trading Signal to Subscribe. Step-By-Step Guide
This step-by-step guide is dedicated to the Signals service, examination of trading signals, a system approach to the search of a required signal which would satisfy criteria of profitability, risk, trading ambitions, working on various types of accounts and financial instruments.
MQL5 Market Results for Q1 2013
MQL5 Market Results for Q1 2013
Since its founding, the store of trading robots and technical indicators MQL5 Market has already attracted more than 250 developers who have published 580 products. The first quarter of 2013 has turned out to be quite successful for some MQL5 Market sellers who have managed to make handsome profit by selling their products.
Statistical Carry Trade Strategy
Statistical Carry Trade Strategy
An algorithm of statistical protection of open positive swap positions from unwanted price movements. This article features a variant of the carry trade protection strategy that allows to compensate for potential risk of the price movement in the direction opposite to that of the open position.
MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria
MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria
We continue the series of articles on MQL5 programming. This time we will see how to get results of each optimization pass right during the Expert Advisor parameter optimization. The implementation will be done so as to ensure that if the conditions specified in the external parameters are met, the corresponding pass values will be written to a file. In addition to test values, we will also save the parameters that brought about such results.
Calculation of Integral Characteristics of Indicator Emissions
Calculation of Integral Characteristics of Indicator Emissions
Indicator emissions are a little-studied area of market research. Primarily, this is due to the difficulty of analysis that is caused by the processing of very large arrays of time-varying data. Existing graphical analysis is too resource intensive and has therefore triggered the development of a parsimonious algorithm that uses time series of emissions. This article demonstrates how visual (intuitive image) analysis can be replaced with the study of integral characteristics of emissions. It can be of interest to both traders and developers of automated trading systems.
Universal Regression Model for Market Price Prediction
Universal Regression Model for Market Price Prediction
The market price is formed out of a stable balance between demand and supply which, in turn, depend on a variety of economic, political and psychological factors. Differences in nature as well as causes of influence of these factors make it difficult to directly consider all the components. This article sets forth an attempt to predict the market price on the basis of an elaborated regression model.
Controlling the Slope of Balance Curve During Work of an Expert Advisor
Controlling the Slope of Balance Curve During Work of an Expert Advisor
Finding rules for a trade system and programming them in an Expert Advisor is a half of the job. Somehow, you need to correct the operation of the Expert Advisor as it accumulates the results of trading. This article describes one of approaches, which allows improving performance of an Expert Advisor through creation of a feedback that measures slope of the balance curve.
Dialectic Search (DA)
Dialectic Search (DA)
The article introduces the dialectical algorithm (DA), a new global optimization method inspired by the philosophical concept of dialectics. The algorithm exploits a unique division of the population into speculative and practical thinkers. Testing shows impressive performance of up to 98% on low-dimensional problems and overall efficiency of 57.95%. The article explains these metrics and presents a detailed description of the algorithm and the results of experiments on different types of functions.
Price Action Analysis Toolkit Development (Part 46): Designing an Interactive Fibonacci Retracement EA with Smart Visualization in MQL5
Price Action Analysis Toolkit Development (Part 46): Designing an Interactive Fibonacci Retracement EA with Smart Visualization in MQL5
Fibonacci tools are among the most popular instruments used by technical analysts. In this article, we’ll build an Interactive Fibonacci EA that draws retracement and extension levels that react dynamically to price movement, delivering real‑time alerts, stylish lines, and a scrolling news‑style headline. Another key advantage of this EA is flexibility; you can manually type the high (A) and low (B) swing values directly on the chart, giving you exact control over the market range you want to analyze.
Royal Flush Optimization (RFO)
Royal Flush Optimization (RFO)
The original Royal Flush Optimization algorithm offers a new approach to solving optimization problems, replacing the classic binary coding of genetic algorithms with a sector-based approach inspired by poker principles. RFO demonstrates how simplifying basic principles can lead to an efficient and practical optimization method. The article presents a detailed analysis of the algorithm and test results.
Overcoming The Limitation of Machine Learning (Part 6): Effective Memory Cross Validation
Overcoming The Limitation of Machine Learning (Part 6): Effective Memory Cross Validation
In this discussion, we contrast the classical approach to time series cross-validation with modern alternatives that challenge its core assumptions. We expose key blind spots in the traditional method—especially its failure to account for evolving market conditions. To address these gaps, we introduce Effective Memory Cross-Validation (EMCV), a domain-aware approach that questions the long-held belief that more historical data always improves performance.
Statistical Arbitrage Through Cointegrated Stocks (Part 6): Scoring System
Statistical Arbitrage Through Cointegrated Stocks (Part 6): Scoring System
In this article, we propose a scoring system for mean-reversion strategies based on statistical arbitrage of cointegrated stocks. The article suggests criteria that go from liquidity and transaction costs to the number of cointegration ranks and time to mean-reversion, while taking into account the strategic criteria of data frequency (timeframe) and the lookback period for cointegration tests, which are evaluated before the score ranking properly. The files required for the reproduction of the backtest are provided, and their results are commented on as well.
Machine Learning Blueprint (Part 4): The Hidden Flaw in Your Financial ML Pipeline — Label Concurrency
Machine Learning Blueprint (Part 4): The Hidden Flaw in Your Financial ML Pipeline — Label Concurrency
Discover how to fix a critical flaw in financial machine learning that causes overfit models and poor live performance—label concurrency. When using the triple-barrier method, your training labels overlap in time, violating the core IID assumption of most ML algorithms. This article provides a hands-on solution through sample weighting. You will learn how to quantify temporal overlap between trading signals, calculate sample weights that reflect each observation's unique information, and implement these weights in scikit-learn to build more robust classifiers. Learning these essential techniques will make your trading models more robust, reliable and profitable.
Black-Scholes Greeks: Gamma and Delta
Black-Scholes Greeks: Gamma and Delta
Gamma and Delta measure how an option’s value reacts to changes in the underlying asset’s price. Delta represents the rate of change of the option’s price relative to the underlying, while Gamma measures how Delta itself changes as price moves. Together, they describe an option’s directional sensitivity and convexity—critical for dynamic hedging and volatility-based trading strategies.
Big Bang - Big Crunch (BBBC) algorithm
Big Bang - Big Crunch (BBBC) algorithm
The article presents the Big Bang - Big Crunch method, which has two key phases: cyclic generation of random points and their compression to the optimal solution. This approach combines exploration and refinement, allowing us to gradually find better solutions and open up new optimization opportunities.
From Novice to Expert: Revealing the Candlestick Shadows (Wicks)
From Novice to Expert: Revealing the Candlestick Shadows (Wicks)
In this discussion, we take a step forward to uncover the underlying price action hidden within candlestick wicks. By integrating a wick visualization feature into the Market Periods Synchronizer, we enhance the tool with greater analytical depth and interactivity. This upgraded system allows traders to visualize higher-timeframe price rejections directly on lower-timeframe charts, revealing detailed structures that were once concealed within the shadows.
Price Action Analysis Toolkit Development (Part 48): Multi-Timeframe Harmony Index with Weighted Bias Dashboard
Price Action Analysis Toolkit Development (Part 48): Multi-Timeframe Harmony Index with Weighted Bias Dashboard
This article introduces the “Multi-Timeframe Harmony Index”—an advanced Expert Advisor for MetaTrader 5 that calculates a weighted bias from multiple timeframes, smooths the readings using EMA, and displays the results in a clean chart panel dashboard. It includes customizable alerts and automatic buy/sell signal plotting when strong bias thresholds are crossed. Suitable for traders who use multi-timeframe analysis to align entries with overall market structure.
MetaTrader 5 Machine Learning Blueprint (Part 5): Sequential Bootstrapping—Debiasing Labels, Improving Returns
MetaTrader 5 Machine Learning Blueprint (Part 5): Sequential Bootstrapping—Debiasing Labels, Improving Returns
Sequential bootstrapping reshapes bootstrap sampling for financial machine learning by actively avoiding temporally overlapping labels, producing more independent training samples, sharper uncertainty estimates, and more robust trading models. This practical guide explains the intuition, shows the algorithm step‑by‑step, provides optimized code patterns for large datasets, and demonstrates measurable performance gains through simulations and real backtests.
Circle Search Algorithm (CSA)
Circle Search Algorithm (CSA)
The article presents a new metaheuristic optimization Circle Search Algorithm (CSA) based on the geometric properties of a circle. The algorithm uses the principle of moving points along tangents to find the optimal solution, combining the phases of global exploration and local exploitation.
Statistical Arbitrage Through Cointegrated Stocks (Part 7): Scoring System 2
Statistical Arbitrage Through Cointegrated Stocks (Part 7): Scoring System 2
This article describes two additional scoring criteria used for selection of baskets of stocks to be traded in mean-reversion strategies, more specifically, in cointegration based statistical arbitrage. It complements a previous article where liquidity and strength of the cointegration vectors were presented, along with the strategic criteria of timeframe and lookback period, by including the stability of the cointegration vectors and the time to mean reversion (half-time). The article includes the commented results of a backtest with the new filters applied and the files required for its reproduction are also provided.
From Novice to Expert: Forex Market Periods
From Novice to Expert: Forex Market Periods
Every market period has a beginning and an end, each closing with a price that defines its sentiment—much like any candlestick session. Understanding these reference points allows us to gauge the prevailing market mood, revealing whether bullish or bearish forces are in control. In this discussion, we take an important step forward by developing a new feature within the Market Periods Synchronizer—one that visualizes Forex market sessions to support more informed trading decisions. This tool can be especially powerful for identifying, in real time, which side—bulls or bears—dominates the session. Let’s explore this concept and uncover the insights it offers.
Reimagining Classic Strategies (Part 18): Searching For Candlestick Patterns
Reimagining Classic Strategies (Part 18): Searching For Candlestick Patterns
This article helps new community members search for and discover their own candlestick patterns. Describing these patterns can be daunting, as it requires manually searching and creatively identifying improvements. Here, we introduce the engulfing candlestick pattern and show how it can be enhanced for more profitable trading applications.
Self Optimizing Expert Advisors in MQL5 (Part 10): Matrix Factorization
Self Optimizing Expert Advisors in MQL5 (Part 10): Matrix Factorization
Factorization is a mathematical process used to gain insights into the attributes of data. When we apply factorization to large sets of market data — organized in rows and columns — we can uncover patterns and characteristics of the market. Factorization is a powerful tool, and this article will show how you can use it within the MetaTrader 5 terminal, through the MQL5 API, to gain more profound insights into your market data.
From Novice to Expert: Time Filtered Trading
From Novice to Expert: Time Filtered Trading
Just because ticks are constantly flowing in doesn’t mean every moment is an opportunity to trade. Today, we take an in-depth study into the art of timing—focusing on developing a time isolation algorithm to help traders identify and trade within their most favorable market windows. Cultivating this discipline allows retail traders to synchronize more closely with institutional timing, where precision and patience often define success. Join this discussion as we explore the science of timing and selective trading through the analytical capabilities of MQL5.
Price Action Analysis Toolkit Development (Part 51): Revolutionary Chart Search Technology for Candlestick Pattern Discovery
Price Action Analysis Toolkit Development (Part 51): Revolutionary Chart Search Technology for Candlestick Pattern Discovery
This article is intended for algorithmic traders, quantitative analysts, and MQL5 developers interested in enhancing their understanding of candlestick pattern recognition through practical implementation. It provides an in‑depth exploration of the CandlePatternSearch.mq5 Expert Advisor—a complete framework for detecting, visualizing, and monitoring classical candlestick formations in MetaTrader 5. Beyond a line‑by‑line review of the code, the article discusses architectural design, pattern detection logic, GUI integration, and alert mechanisms, illustrating how traditional price‑action analysis can be automated efficiently.
Market Positioning Codex for VGT with Kendall's Tau and Distance Correlation
Market Positioning Codex for VGT with Kendall's Tau and Distance Correlation
In this article, we look to explore how a complimentary indicator pairing can be used to analyze the recent 5-year history of Vanguard Information Technology Index Fund ETF. By considering two options of algorithms, Kendall’s Tau and Distance-Correlation, we look to select not just an ideal indicator pair for trading the VGT, but also suitable signal-pattern pairings of these two indicators.
Price Action Analysis Toolkit Development (Part 52): Master Market Structure with Multi-Timeframe Visual Analysis
Price Action Analysis Toolkit Development (Part 52): Master Market Structure with Multi-Timeframe Visual Analysis
This article presents the Multi‑Timeframe Visual Analyzer, an MQL5 Expert Advisor that reconstructs and overlays higher‑timeframe candles directly onto your active chart. It explains the implementation, key inputs, and practical outcomes, supported by an animated demo and chart examples showing instant toggling, multi‑timeframe confirmation, and configurable alerts. Read on to see how this tool can make chart analysis faster, clearer, and more efficient.