Definition

Algorithmic trading is a method of trading where computers make decisions on what to buy and sell in the financial markets.

Description

The aim of algorithmic trading is to either make profits by buying lower and selling higher, or to reduce trading costs by buying or selling big blocks of financial products in an efficient way.

The computer decides what and how much to buy and sell based on certain rules. However, humans design these rules.

Algorithmic trading usually involves financial, programming and data science knowledge.

Algorithmic trading can be divided into 2 processes:

Step 1) Market Inefficiency Discovery

We look for something amiss in the markets that we can exploit. For example, if the same financial product is priced differently on 2 exchanges, there might be a discrepancy.

Step 2) Market Inefficiency Exploitation

We design a strategy to take advantage of the market inefficiency we discovered. This means to decide when to buy and sell, how much to buy and sell, and how to close the trade.

One version of algorithmic trading is high frequency trading (HFT). In HFT, computing and communication speed are vital. For instance, we need to fire a trade faster than a rival trading firm.

Low frequency trading does not require us to be fast. For instance, we can take our time to analyze millions of tweets before firing a trade.

In manual trading, humans know when and how much to buy and sell. This decision-making process usually involves qualitative work; such as reading companies’ annual reports.

Examples

• John creates a software to scrape a popular job-listing site for data. Whenever a company posts a lot more job openings than before, John’s software will buy that stock.
• Jane codes a system that tracks the prices of 100 retail stocks in America. She expects these stocks to move in a similar manner. Whenever a stock falls much more than the rest, Jane’s software will buy that stock and short the rest of the 99 stocks.
• Tom’s code tracks the prices of a cryptocurrency on 2 exchanges. Whenever a cryptocurrency is priced differently on one exchange compared to the other, his code will buy the under-priced product and short the overpriced one.

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