Algorithm Trading : The Future Is Here!

Algorithm trading is dominating market volumes like never before and investors ought to understand what it means to their portfolio. Karan Bhojwani explains the basics of algorithm trading while highlighting the different algorithm strategies

Trading or investing in equity markets or any other markets is all about competing with the other market participants. The underlying objective is to have an edge over others. Algorithm trading is one such advantage or edge that seems to be influencing the fortunes of various tech-savvy market participants. However, there are many individual investors who are totally unaware of such a unique advantage. “I have been participating in equity markets for over two decades now. I am basically a long-term investor and I use my understanding of company fundamentals and financials for decision-making when it comes to identifying quality stocks and constructing a portfolio,” says company secretary and chartered accountant Sachin Chandanshiv.

“I have never felt any need for algorithm or any algorithm trading strategy so far. In fact, I do not know what is algorithm trading and I do not know how to use it. I am aware of its popularity and I do feel the need to understand it not because I want to indulge in algorithm trading but because it has started influencing the profitability of traders. I think it is of prime importance that I take a deeper look into the mechanics of algorithm trading. If I am comfortable I may use an algorithm in the future,” he adds. 

What is Algorithm Trading? It is said that almost 75% of the trades in the US equity markets are placed through machines and not by humans. They are placed by computer algorithm. In simple language, algorithm is a sequence of steps to achieve a goal. Algorithm trading is however a trading strategy which is automatic and executed using computers. Algorithm can make and execute thousands of trading decisions and that’s where the advantage over humans lies. Algorithm trading has become popular as an increasing number of traders search for an advantage and identify their core competence. The goal is to generate higher profits consistently using such an advantage over the other market participants.

Traders prefer algorithm by machines because the human brain cannot process the volumes of information needed to make trading decisions and place orders like a computer does. The unique advantage of algorithm trading is that it can process millions of pieces of data per second, make decisions in a few milliseconds and take autonomous actions. If that was not enough, one of the reasons why algorithm trading is popular is also because it can be applied across asset classes, be it foreign exchange, bonds, commodities or any other tradable asset class. According to several experts, it is not yet possible to digitize the instincts of a really good trader but algorithm trading is a far more superior way to beat the rest of the participants in the market. 

For and Against Algorithm Trading It is clear that algorithm trading provides unique advantages to a select few and that those participants using the system have an unfair advantage. This is the very reason why algorithm trading is viewed with suspicion by the regulators, at least in India. Even if algorithm trading is executed using machines, humans are still needed as creators of the algorithm. Algorithm has a lifecycle from research to implementation to testing to timing and is often believed to be a double-edged sword. If anything goes wrong with the algorithm, the cost of the error is huge. 

In case any company intends to engage in algorithm trading, it needs approval from the stock exchange. Algorithm trading has to pass a series of stringent tests and only then is it approved for trading. 

Types of Algorithm Trading

Algorithm trading basically can be classified into two broad categories:

Execution algorithm High frequency trading.

Execution Algorithm

Execution algorithm is considered to be an intelligent program used to slice up the large trades. Usually such large trades are sliced up in order to have minimal market impact and are placed on behalf of pension funds, mutual funds, etc. In execution algorithm, it is common to see large trades being executed over a period of time. Examples of execution algorithm trading are:

☛ Volume weighted average price
☛ Implementation shortfall
☛ Market participation algorithm.

High Frequency Trading While execution algorithm is all about minimising the market impact, high frequency trading is much more complex and self-learning. It can make decisions on what, when and how to trade while it executes trades on its own without any human inputs. High frequency trading is war-raging algorithm execution and is always found to be competing to find the best opportunities and execute them as fast as possible to generate higher profits consistently. In fact high-frequency trades thrive on speed. What differentiates high frequency trading from other trading strategies is the presence of low latency. Latency provides the strategy with unique advantage. Latency is the time difference between stimulus and response time taken for the following:

☛ Market data to be received
☛ Pattern to be identified
☛ Decision to be made
☛ Trades to be placed.

High frequency trading is all about the first-mover advantage and acting before the competitor does. Speed is one of the most important factors here. Those endowed with superior technology and resources can afford to get access to the market data quicker than the most market participants. Co-location becomes an important part of the infrastructure in case of high frequency trading strategies as access to market data is quicker and better in case of co-location. Some examples of high frequency trading include:
☛ Pair trading
☛ Index arbitrage
☛ Basket trading
☛ Spread trading
☛ Mean reversion
☛ Delta neutral strategies.

Market Projection According to the Global Algorithmic Trading Market : 2018-2022 report published by Research and Markets, the global algorithmic trading market size is projected to grow from USD 11.1 billion in 2019 to USD 18.8 million by 2024 expanding at a CAGR of 11.1 per cent.

"Successful investing is anticipating the anticipation of others

John Keynes, British economist.

According to Quantinsti that teaches algorithm trading, functionally, the following aspects are required to be managed:

 Order management
 Risk management
 Money and fund management
 Diversification of assets
 Portfolio management
 User management

Conclusion Algorithm trading is an inevitable evolution of the trading process. When compared to traditional trading, algorithm trading is much faster and accurate and can be carried out without human errors. It does look like algorithm trading is the future of trading and any serious trader who intends to trade profitably will have to learn algorithm trading going forward. This may be necessary not only to earn consistent profits but also to stay afloat in the ever-competitive trading space. Technology is the key factor when it comes to algorithm trading and traders will have to upgrade not only in terms of share market knowledge but also in terms of technological resources. Indian markets along with other emerging markets do provide good opportunity for algorithm traders as it has a smart order routing system and the markets are liquid. Also, Indian markets provide co-location facilities and have sophisticated technology at both the stock exchanges.