The Evolution of Algorithmic Trading: From Manual Markets to Data-Driven Strategies

The roots of algorithmic trading trace back to an era when financial markets operated entirely through human intervention. Traders shouted orders across crowded pits, chalkboards displayed fluctuating prices, and intuition guided decisions. Yet even in these early days, observable patterns in price behavior sparked the first attempts to formalize market analysis through mathematics.

Harry Markowitz revolutionized finance in the 1950s by introducing a scientific approach to portfolio construction. His framework demonstrated how statistical measures—volatility and covariance—could quantify the balance between risk and return. Though limited by the computational power of room-sized machines, this breakthrough shifted investment strategies from emotional judgments to data-driven logic. By the 1960s, primitive computer-assisted optimizers began emerging, planting the seeds for today's algorithmic dominance.