Algorithmic Trading: How Algorithms Came To Rule Our Investment World

Algorithmic trading is a system that uses very advanced mathematical models for making transaction decisions in the financial markets. The system attempts to determine the optimal time for an order to be placed that will cause the least amount of impact on a stock's price. Algorithmic trading is widely used by investment banks, pension funds, mutual funds, and other buy-side (investor-driven) institutional traders, to divide large trades into several smaller trades to manage market impact and risk. Sell side traders, such as market makers and some hedge funds, provide liquidity to the market, generating and executing orders automatically.

The main objective of algorithmic trading is not necessarily to maximize profits but rather to control execution costs and market risk.

Algorithms started as tools for institutional investors in the beginning of the 1990s. Decimalization, direct market access (DMA), 100% electronic exchanges, reduction of commissions and exchange fees, rebates, the creation of new markets aside from NYSE and NASDAQ and Reg NMS led to an explosion of algorithmic trading.

Algorithims Replacing Wall Street Analysts, Investors

Computerized algorithms are quickly replacing single-stock analysts and investors, leading to big changes in the way the stock market will value companies and increasing the chance that software glitches or hack attacks will jeopardize market stability. Algorithmic trading may be used in any investment strategy, including market making, inter-market spreading, arbitrage, or pure speculation.

A third of all European Union and United States stock trades in 2006 were driven by automatic programs, or algorithms. As of 2009, studies suggested High-Frequency Trading (HFT) firms accounted for 60-73% of all US equity trading volume, with that number falling to approximately 50% in 2012.

Technological forces - including HFT, an explosion in exchange-traded funds and the proliferation of free information via social media - are behind this shift.

The changes that started with high-frequency and algorithmic trading are just the first step to an entirely different process of determining stock prices. Computers and decimalization have chipped away at the ranks of human traders in the past decade. Now, smarter machines are taking aim at the very people who analyze a company's merits and who make buying and selling decisions based on that analysis.

These algorithms tend to see the market from a machine's point of view, which can be very different from a human's. Rather than focus on the behavior of individual stocks, for instance, many prop-trading algorithms look at the market as a vast weather system, with trends and movements that can be predicted and capitalized upon. These patterns may not be visible to humans, but computers, with their ability to analyze massive amounts of data at lightening speed, can sense them.

Boon for Individual Investors

For individual investors, trading with algorithms has been a boon. Today, they can buy and sell stocks much faster, cheaper, and easier than ever before. But from a systemic perspective, the stock market risks spinning out of control. Even if each individual algorithm makes perfect sense, collectively they obey an emergent logic - artificial intelligence. It is simply, alien, operating at the natural scale of silicon, not neurons and synapses. We may be able to slow it down, but we can never contain, control, of comprehend it. It's the machines' market now; we just trade in it.$

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