Algorithmic Trading

Algorithmic trading relies on automated strategies that identify profitable opportunities in the financial markets. These strategies, driven by mathematical models and historical data, allow traders to execute trades at high speeds with minimal human intervention. This article provides an overview of the most common trading algorithms and strategies, giving you a foundational understanding to start... read more

In algorithmic trading, data analysis is the foundation of any strategy. There are two primary approaches: technical analysis, which focuses on price movements and market patterns, and fundamental analysis, which evaluates an asset’s intrinsic value based on economic and financial data. Each has its place in the world of algo trading, and understanding how to... read more

Indicators are the foundation of many algorithmic trading strategies, providing insights into market trends, momentum, volume, and volatility. They help algorithmic systems identify optimal entry and exit points, assess risk, and maintain profitability in a structured manner. In this article, we’ll explore the main categories of indicators used in algo trading and provide a practical... read more

Moving averages (MAs) are among the most widely used indicators in algorithmic trading, helping to smooth price data and reveal underlying trends. By calculating the average price over a set period, MAs enable traders to identify trends and filter out market “noise.” In this article, we’ll discuss the different types of moving averages, explain how... read more

Momentum trading aims to capitalise on the strength or speed of a price movement, and the Relative Strength Index (RSI) is one of the most popular indicators for this purpose. Developed by J. Welles Wilder, RSI measures the speed and magnitude of price changes, identifying overbought and oversold conditions. In this article, we’ll dive into... read more

The Moving Average Convergence Divergence (MACD) is a popular indicator in algorithmic trading that combines trend-following and momentum analysis. By comparing two moving averages of different lengths, MACD helps identify shifts in momentum, signalling potential trend reversals. In this article, we’ll discuss the MACD’s components, how it’s calculated, and how to use it in trading... read more

Bollinger Bands are widely used in algorithmic trading to measure volatility and identify overbought or oversold conditions. Developed by John Bollinger, this indicator consists of three lines—a middle band (usually a simple moving average), an upper band, and a lower band. In this article, we’ll explore how Bollinger Bands are calculated, their significance in volatility... read more

The Stochastic Oscillator is a popular momentum indicator used in mean reversion trading strategies. Developed by George Lane, it measures the position of the current price relative to its range over a given period, helping to identify overbought and oversold conditions. This article explains how the Stochastic Oscillator works, how to calculate it, and how... read more

The Average True Range (ATR) is a widely used volatility indicator that helps traders measure market volatility. Unlike other indicators focused on price direction, ATR is purely about assessing price range, making it especially useful for managing risk. In this article, we’ll explain how ATR is calculated, its applications in risk management, and how to... read more