What is algorithmic trading?
Algorithmic trading is widely-used in financial market trading through automated platforms, mathematical tools, and computer programming. This system helps people in trading decision-making with complex formulas, mathematical models, and human insight.
The algorithm’s trading process uses automated trading instructions pre-programmed with variables such as pricing, timing, and volume. Usually, the technology used is high-frequency that can create massive works of trading every second. An algorithm is applicable in different situations like ordering, arbitrage, and strategizing.
What are the elements of algorithmic trading?
- Algorithms. Algorithms are instructions that make functions repetitively, solve problems, and facilitate data processing trend identification easily.
- Computer programs and automated buy and sell platforms. Automated platforms execute programmer-made algorithms and help in back-testing algorithms made by algo-traders or programmers before the execution.
- Technical analysis. Technical analysis studies and analyzes securities price movements. Examples of methods that help identify price trends are random oscillators, 150 and 200 moving average, and double exponential moving average. These can be made into algorithms and then transformed into computer programs deployed in the financial market for trading.
- Backtesting. Back-testing tests algorithms and verifies the anticipation of a trader. It tests the programmer’s strategy on historical market data and identifies the trader’s possible errors if used in market trading.
Emerging algorithmic tradings
Recently, DIY or do-it-yourself algorithmic trading is becoming more and more recognized by traders. For example, hedge funds like Quantopian are doing crowdsourcing to newbie programmers where the best one who creates the most profitable code wins an amount of money. Due to modern technology with high-speed internet and high-performing computers, this became easy and possible.
Another example that is becoming more widely-used is machine learning, where artificial intelligence helped computer programmers develop programs that can do self-improvement through deep learning. Algo-traders use deep learning to generate more profits.
Advantages and disadvantages of algorithmic trading
There are several advantages with the usage of algorithmic trading. These include fewer transaction costs, less human intervention, and fewer emotions and biases. It helps in identifying the perfect market timing and processing massive market offers quickly. Algorithmic trading happens swiftly with the best possible prices.
However, algorithm trading doesn’t come with advantages alone since it also has its downsides. Some of these are circuit breakers installed by regulatory authorities that limit the function of algo-traders, quick disappearance of liquidity, and execution speed without human intervention can impact live trading and settlements. Regulatory authorities can barely distinguish actual human trades and algo-trades, as a result, they raise the market participants when suspected algo-traders are present. Algo-traders can cause unwanted and unnecessary market volatility.
Limitations on algorithmic trading
The algorithm device is very complex and scientific. A traditional trader can have difficulty learning something very different from the conventional and use it in daily trading. Algorithm development involves predictive and quantitative models that need back-testing because they can cause massive losses for traditional traders. And, of course, subjectivity in decision-making in financial markets, but this is something that algorithmic trading cannot overrule since it does not involve human interaction.