Algorithmic Trading

What is 'Algorithmic Trading'

Algorithmic trading, also referred to as algo trading and black box trading, is a trading system that utilizes advanced and complex mathematical models and formulas to make high-speed decisions and transactions in the financial markets. Algorithmic trading involves the use of fast computer programs and complex algorithms to create and determine trading strategies for optimal returns.

BREAKING DOWN 'Algorithmic Trading'

Some investment strategies and trading strategies like arbitrage, intermarket spreading, market making, and speculation may be enhanced through algorithmic trading. Electronic platforms can completely operate investment and trading strategies through algorithmic trading. As such, algorithms are able to execute trading instructions under particular conditions in price, volume, and timing. The use of algorithmic trading is most commonly used by large institutional investors due to the large amount of shares they purchase every day. Complex algorithms allow these investors to obtain the best possible price without significantly affecting the stock's price and increasing purchasing costs.

Popular strategies include arbitrage, trading before index fund rebalancing, mean reversion, and scalping.


Arbitrage is the difference of market prices between two different entities. Arbitrage is commonly practiced in global businesses. For example, companies are able to take advantage of cheaper supplies or labor from other countries. These companies are able to cut costs and increase profits. Arbitrage can also be utilized in trading S&P futures and the S&P 500 stocks. It is typical for S&P futures and S&P 500 stocks to develop price differences. When this occurs, the stocks traded on the NASDAQ and NYSE markets either lag behind or get ahead of the S&P futures, providing an opportunity for arbitrage. High-speed algorithmic trading can track these movements and profit from the price differences.

Trading Before Index Fund Rebalancing

Retirement savings like pension funds are mostly invested in mutual funds. The index funds of mutual funds are regularly adjusted to match the new prices of the fund's underlying assets. Before this happens, preprogrammed trading instructions are triggered by algorithmic trading-supported strategies, which can transfer profits from investors to algorithmic traders.

Mean Reversion

Mean reversion is mathematical method that computes the average of a security's temporary high and low prices. Algorithmic trading computes this average and the potential profit from the movement of the security's price as it either goes away from or goes toward the mean price.


Scalpers profit from trading the bid-ask spread as fast as possible numerous times a day. Price movements must be less than the security's spread. These movements happen within minutes or less, thus the need for quick decisions, which can be optimized by algorithmic trading formulas.

Other strategies optimized by algorithmic trading include transaction cost reduction and other strategies pertaining to dark pools.