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Volume Indicators in Algorithmic Trading: OBV, VWAP, and MQL4 Examples

Volume indicators are essential tools in algorithmic trading, providing insights into the strength of price movements and trends. By analysing volume data, these indicators help confirm trends, spot potential reversals, and assess the conviction behind price moves. In this article, we’ll cover the On-Balance Volume (OBV) and Volume-Weighted Average Price (VWAP) indicators, explaining how they... read more

Multi-Indicator Strategies in Algorithmic Trading: Combining Indicators for Signal Optimisation

In algorithmic trading, combining multiple indicators can improve the accuracy and reliability of trading signals. While a single indicator may perform well in certain conditions, using multiple indicators can provide additional confirmation and filter out false signals. This article covers the essentials of multi-indicator strategies, how to combine indicators effectively, and the importance of signal... read more

Backtesting and Optimising Trading Algorithms: A Guide for Algorithmic Traders

Backtesting is a crucial step in algorithmic trading, allowing traders to evaluate a strategy’s effectiveness using historical data. By simulating how a strategy would have performed in the past, backtesting helps identify strengths, weaknesses, and potential improvements before risking capital in live markets. In this article, we’ll explore the basics of backtesting, common pitfalls to... read more

Machine Learning in Algorithmic Trading: Implementing Linear Regression in MQL4

Machine learning is increasingly shaping the landscape of algorithmic trading by allowing traders to analyse large amounts of data, uncover hidden patterns, and make more data-driven predictions. By leveraging machine learning models, trading strategies can be optimised for better accuracy and adaptability. This article explores the types of machine learning used in algorithmic trading, their... read more