Basics of Algorithmic Trading

Algorithmic trading (also called automated trading, black-box trading, or algo-trading) uses a computer program that follows a defined set of instructions (an algorithm) to place a trade. The trade, in theory, can generate profits at a speed and frequency that is impossible for a human trader.

The defined sets of instructions are based on timing, price, quantity, or any mathematical model. Apart from profit opportunities for the trader, algo-trading renders markets more liquid and trading more systematic by ruling out the impact of human emotions on trading activities. 

Algorithmic Trading In Practice

Suppose a trader follows these simple trade criteria:

• Buy 50 shares of a stock when its 50-day moving average goes above the 200-day moving average. (A moving average is an average of past data points that smooths out day-to-day price fluctuations and thereby identifies trends.)
• Sell assets when its 50-day moving average goes below the 200-day moving average.

Using these two simple instructions, a computer program will automatically monitor the stock price (and the moving average indicators) and place the buy and sell orders when the defined conditions are met. The trader no longer needs to monitor live prices and graphs or put in the orders manually. The algorithmic trading system does this automatically by correctly identifying the trading opportunity. 

Benefits of Algorithmic Trading

Algo-trading provides the following benefits:

• Trades are executed at the best possible prices.
• Trade order placement is instant and accurate (there is a high chance of execution at the desired levels).
• Trades are timed correctly and instantly to avoid significant price changes.
• Reduced transaction costs.
• Simultaneous automated checks on multiple market conditions.
• Reduced risk of manual errors when placing trades.
• Algo-trading can be backtested using available historical and real-time datato see if it is a viable trading strategy.
• Reduced possibility of mistakes by human traders based on emotional and psychological factors.

Most algo-trading today is high-frequency trading (HFT), which attempts to capitalize on placing a large number of orders at rapid speeds across multiple markets and multiple decision parameters based on preprogrammed instructions. 

Algo-trading is used in many forms of trading and investment activities including:

• Mid- to long-term investors or buy-side firms—pension funds, mutual funds, insurance companies—use algo-trading to purchase stocks in large quantities when they do not want to influence stock prices with discrete, large-volume investments.
• Short-term traders and sell-side participants—market makers (such as brokerage houses),speculators, and arbitrageurs—benefit from automated trade execution; in addition, algo-trading aids in creating sufficient liquidity for sellers in the market.
• Systematic traders—trend followers, hedge funds, or pairs traders (a market-neutral trading strategy that matches a long position with a short position in a pair of highly correlated instruments such as two stocks, exchange-traded funds (ETFs) or currencies)—find it much more efficient to program their trading rules and let the program trade automatically.

Algorithmic trading provides a more systematic approach to active trading than methods based on trader intuition or instinct.

For more details read the original investopedia article here : https://www.investopedia.com/articles/active-trading/101014/basics-algorithmic-trading-concepts-and-examples.asp