Algorithmic trading, algo trading, automated trading, or black box trading is a technological advancement in the stock market. It is a programed process that runs on a computer, which follows a specific set of instructions (an algorithm) for placing a trade in order to generate profits at a speed and frequency that is impossible for a human trader. Algorithmic trading is gaining significant traction, which is useful for financial market and accepted by various countries such as the U.S., India, the U.K., and South Korea. Accuracy, exceptional speed and liquidity are the unique features of algorithmic trading, which will result in exponential growth of algorithmic trading market in the near future.

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Global algorithmic trading market is expected to witness significant growth during the forecast period (2018-2026). This is attributed to increasing adoption of cloud-based solutions, services, and cloud computing for algorithmic trading. Traders use the cloud services to check backtest, trading strategies, and run-time series analysis with executing trade. Traders choose cloud computing as it is capital intensive to build one’s own data centers for services such as data storage, backup and recovery, data management and networking traders. Therefore, it is easier to rent space over cloud rather than developing software/hardware infrastructure. According to Coherent Market Insights, the cloud computing market is expected to grow from US$ 58 billion in 2013, to US$ 191 billion by 2020, and professional cloud services market is expected to grow from US$ 15.36 billion in 2017, to US$ 41.59 billion by 2023. Hence, increasing adoption of cloud based services is expected to drive growth of the algorithmic trading market.

Growing demand for AI-based services in financial sector drives growth of the algorithmic trading market. In algorithmic trading, AI helps to adopt market conditions, learn from experiences, and accordingly make trade decisions. Trading houses such as Blackrock, Renaissance Technologies, Two Sigma, and others, are using AI for selecting stocks. According to Coherent Market Insights, in 2018, about 37% of the financial institutions in India invested in artificial intelligence-focused technologies and around 68 % plan to adopt it in the near future. Therefore, increasing adoption of AI in financial sector is expected to drive growth of the algorithmic trading market over the forecast period. Moreover, increasing adoption of non-equity trading algorithms by institutional asset managers is another factor driving growth of the algorithmic trading market.

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Moreover, owing to increasing disposable income has let to increasing trading activity. Henceforth, increasing disposable income is one of the driving factor of algorithmic trading market. According to IBEF (India Brand Equity Foundation), in 2018 total rural income is at around US$ 572 billion, is projected to reach US$ 1.8 trillion by year 2021. India’s rural per capita disposable income is estimated to increase at a CAGR of 4.4 per cent to US$ 631 by 2026