What is Algorithmic Trading?
Algorithmic trading also referred to as Algo-trading is a variant of automated trading that basically involves the usage of automated platforms and advanced tools of maths and computer programming to drive trading transactions in the financial markets. The system utilizes a mathematical model or algorithm or standardized instruction set that facilitate placing of buying or sell signal in the financial markets and hence facilitate trade without the involvement of humans.
Components of Algorithmic Trading
The four components of algorithmic trading are discussed below:
#1 – An Algorithm
An algorithm can be defined as a set of instructions that performs certain repetitive functions. It can also be developed to cater to certain problem-solving situations. It helps in the easy facilitation of data processing and identification of trends.
#2 – Computer Program & Automated Trading Platforms
An automated trading platform provides a means to execute the algorithm developed by the programmers. It as a platform executes the computer programs developed by the programmers and algo-traders thereby facilitating buy and sell orders in the financial markets. These platforms also help in the backtesting of algorithms developed by the algo-traders or programmers as well before they can be deployed.
#3 – Technical Analysis
The technical analysis involves the study and analysis of the price movements of the listed securities in the financial markets. There are several methods such as 150-day moving average, 200-day moving average, double exponential moving average, random oscillators which helps in the identification of price trends for a particular security.
The methods of technical analysis can be developed as an algorithm and can, in turn, be transformed into a computer program that can then be deployed into the financial markets to automate the trading function.
#4 – Backtesting
The backtesting is the process of testing the algorithm and verify whether the strategy would deliver the results as anticipated by the trader. It involves testing of the strategy developed by the programmer on the historical market data. The backtesting lets the trader identify the pitfalls that could have emerged if the strategy were used with the live market trades.
Algorithmic Trading Examples
Below are examples of algorithmic trading.
Suppose a hedge fund has developed a quantitative model. They have developed a computer program that deploys the model into the financial market. The computer program assesses the market situation dynamically and thereby implement a hedging strategy in line with the market sentiments.
- Suppose a trader follows a trading criterion that it always purchases 100 shares whenever the price of the stock moves beyond and above the double exponential moving average.
- Simultaneously it places a sell order when the price of the stock goes below the double exponential moving average.
- The trader can hire a computer programmer who can understand the concept of the double exponential moving average.
- The programmer can develop a computer code that performs the above two instructions.
- The computer program can be made so dynamic that it can monitor the live prices of the financial markets and in turn trigger the above instructions.
- The computer program or the algorithm saves the time for the trader of going into the trading platforms, monitor prices and then place the trading orders.
Algorithmic Trading Examples – Practical Application
- The flash crash of 2010 can be regarded as an example of algorithm trading. In this crisis, there was the fast placement of sell orders for securities. There were also fast withdrawals of trade orders for securities and were high-frequency trades.
- The Regulatory authorities later placed circuit breakers to prevent such flash crash from happening again in the financial markets. They also prevented algo-trades to have direct access to the exchanges.
Advantages of Algorithmic Trading
The various different advantages related to algorithmic trading are as follows:
- The algo-trading helps in the lessening of transaction costs.
- The trades are placed into the system without the need for human intervention.
- They algo-trades are placed without any emotions or biases.
- The placement of algo-trades order happens instantly and at the best possible prices.
- It also helps in the perfect market timing.
- It helps in the processing of big orders in an efficient and faster manner.
Disadvantages of Algorithmic Trading
The various different disadvantages related to algorithmic trading are as follows:
- The regulatory authorities always install circuit breakers which limits the functionality of algo-trades.
- The liquidity provided by algo-traders can almost disappear in an instant or in a matter of seconds.
- The execution speed of algo-trades without the intervention of humans can adversely impact live trades and settlements which further limit the functionality of trading platforms and financial markets.
- It is hard for the regulatory authority to distinguish between a trade placed by a human and trade facilitated by an algorithm. Hence, they always increase the number of market participants when they suspect that the trades are executed through algorithm trades.
- The algo-trades if not monitored can trigger unnecessary volatility in the financial markets.
Limitations of Algorithmic Trading
The various limitations related to algorithmic trading are as follows:
- The devising of the algorithm can be very complex and difficult.
- Since the approach of devising an algorithm is scientific, it is difficult for a traditional trader to learn such an approach and apply such algorithms in their daily trades.
- The development of algorithms generally involves the development of predictive and quantitative models and if such models are not backtested, they can cause huge loss for the traditional traders who may employ them without backtesting.
- An algorithm cannot overrule and overplay subjective judgment which is present in the financial markets.
Some important points related to algorithmic trading are as follows:
- The algorithm trading employs the usage of computer programs.
- Before executing the algo-trades in the financial markets, it is always advised to perform back-testing of the automated strategy.
- The algorithm trading is employed by the high net worth individuals and institutional investors.
- Many institutional investors pay commissions to budding programmers for building a small piece of code that delivers the investors profitable returns.
Algorithm trading is a mechanism that facilitates buy and sell orders in the financial markets by using an algorithm which is executed by the means of computer programs. A definite criterion is developed in terms of programmable code and placed in the automated platforms to execute trades in the financial markets. The execution of algorithm trades is very fast and can cause a potential crash in the financial markets.
To monitor such trades, the regulatory authorities install circuit breakers at critical junctures. Hedge funds and institutional investors are the major users of the algorithm trading as it helps them a place and executes large trade orders very easily. They further help in devising trading strategies such as taking up long and short positions simultaneously to handle the lump sum amounts systematically and in a careful manner.
This has been a guide to algorithmic trading and its meaning. Here we discuss what is algorithmic trading along with the examples. we also discuss its limitations, advantages & disadvantages. You can learn more from the following articles –