Articles
Low-Frequency Quantitative Strategies in Metatrader 5: (Part 1) Setting Up An OLAP-Friendly Data Store for MetaTrader 5
The article outlines a practical data pipeline for quantitative analysis based on Parquet storage, Hive-style partitions, and DuckDB. It details migrating selected SQLite tables to Parquet, structuring market data by source, symbol, timeframe, and date, and querying it with SQL window functions. A
Statistical Arbitrage Through Cointegrated Stocks (Final): Data Analysis with Specialized Database for MetaTrader 5
The article shows how to pair SQLite (OLTP) with DuckDB (OLAP) for statistical arbitrage data processing. DuckDB’s columnar engine, ASOF JOIN, and array functions accelerate core tasks such as quote–trade alignment and RWEC, with measured speedups from 2x to 23x versus SQLite on larger inputs. You
Statistical Arbitrage Through Cointegrated Stocks (Part 10): Detecting Structural Breaks for MetaTrader 5
This article presents the Chow test for detecting structural breaks in pair relationships and the application of the Cumulative Sum of Squares - CUSUM - for structural breaks monitoring and early detection. The article uses the Nvidia/Intel partnership announcement and the US Gov foreign trade
Statistical Arbitrage Through Cointegrated Stocks (Part 9): Backtesting Portfolio Weights Updates for MetaTrader 5
This article describes the use of CSV files for backtesting portfolio weights updates in a mean-reversion-based strategy that uses statistical arbitrage through cointegrated stocks. It goes from feeding the database with the results of a Rolling Windows Eigenvector Comparison (RWEC) to comparing the
Statistical Arbitrage Through Cointegrated Stocks (Part 8): Rolling Windows Eigenvector Comparison for Portfolio Rebalancing for MetaTrader 5
This article proposes using Rolling Windows Eigenvector Comparison for early imbalance diagnostics and portfolio rebalancing in a mean-reversion statistical arbitrage strategy based on cointegrated stocks. It contrasts this technique with traditional In-Sample/Out-of-Sample ADF validation, showing
Statistical Arbitrage Through Cointegrated Stocks (Part 7): Scoring System 2 for MetaTrader 5
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
Statistical Arbitrage Through Cointegrated Stocks (Part 6): Scoring System for MetaTrader 5
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
Statistical Arbitrage Through Cointegrated Stocks (Part 5): Screening for MetaTrader 5
This article proposes an asset screening process for a statistical arbitrage trading strategy through cointegrated stocks. The system starts with the regular filtering by economic factors, like asset sector and industry, and finishes with a list of criteria for a scoring system. For each statistical
Statistical Arbitrage Through Cointegrated Stocks (Part 4): Real-time Model Updating for MetaTrader 5
This article describes a simple but comprehensive statistical arbitrage pipeline for trading a basket of cointegrated stocks. It includes a fully functional Python script for data download and storage; correlation, cointegration, and stationarity tests, along with a sample Metatrader 5 Service
Statistical Arbitrage Through Cointegrated Stocks (Part 3): Database Setup for MetaTrader 5
This article presents a sample MQL5 Service implementation for updating a newly created database used as source for data analysis and for trading a basket of cointegrated stocks. The rationale behind the database design is explained in detail and the data dictionary is documented for reference. MQL5