Finance

Algorithmic Trading

Algorithmic Trading

Algorithmic Trading is a cycle of executing orders using mechanized and pre-modified guidelines to represent factors such as price, time, and volume. It is an algorithm to solve problems. It is also called black-box trading, automated trading, or Algo-trading. It can generate profits at a speed and frequency that is not possible for a human trader. Leaving aside the profits algo-trading renders market liquidity, more systematic trading by ruling out the impact of human traders. Also, there are times where a single trader is unable to do a large volume of trading, and that’s where you need an intelligent algorithm to interfere.

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How does it work?

Algorithms are a particular set of specifically defined instructions programmed to execute a task or procedure. In algorithmic trading, complex formulas are used combined with maths models and human oversight for making a decision to buy or sell the financial instrument. The computer program includes a series of instructions or an algorithm and automatically executes the business when the order has been fulfilled. This will save you time by analyzing the markets and almost immediately perform your trades. It uses high-frequency trading technology, which altogether helps in making larger profits.

Example:
  • Suppose a trader wants to buy 50 shares of a stock when its 50-days moving average goes over 200 days moving average (An avg. of past data points that shows fluctuations in price) and wants to sell50 shares when the 50-days moving average goes below the 200-moving average.
  • Using two simple commands, a computer program will monitor the price and moving average and place the buy and sell order automatically. The trader no longer needs to sit and monitor those stocks.

Advantages:

  • Algorithmic trading is mostly used by institutional investors and big brokerage firms to cut down the costs of trading.
  • It helps in creating market liquidity.
  • It allows faster and easier execution of orders making it very attractive for exchanges.
  • Traders and investors can quickly book their profit even if the price changes are small.
  • Most firms apply this because it involves rapid buying and selling.
  • Using real-time and historical data trading strategies may also be backtested.

Disadvantages:

  • An advantage of speed order execution in an ordinary situation can be a disadvantage at times when several orders are being executed without human oversight.
  • Another disadvantage is that the market liquidity which is created can disappear very quickly.
  • It can also lead to an instant loss of market liquidity.
  • Research has shown that algorithmic trading was a reason for causing loss of liquidity in currency markets after the Swiss franc discontinued its Euro peg in 2015.

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Bottom Line:

Algorithmic trading plays an important role in major equity markets and has also become important in the finance industry. The implementation of this method requires some technical effort but a great knowledge of the market. A human trader can trade on his feelings and knowledge but an automated system does not have this possibility. And with increasing computational work it will be easy to study the huge amounts of data produced by the market. As the world is moving towards technological power, the future seems interesting.

 

Author – Priyanshu Ahuja

About the author – I’m a first-year student from City Premier College, Nagpur, pursuing BBA. My interest includes financial markets and investment domain.

 

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