Algorithmic trading or automated trading is a trading system that uses computers programmed to change orders, execute trades and make decisions autonomously based on signals from public/private market data and quantitative models. Algorithmic trading is widely used by investment banks, pension funds, mutual funds and other large institutional investors to divide large trades into several smaller trades to manage market impact and risk. Algorithmic trading incorporates advanced techniques such as artificial intelligence, machine learning, natural language processing, and neural networks. These sophisticated strategies allow algorithmic trading to identify trading opportunities and execute trades in fractions of a second, much faster than human traders.
The global Algorithmic Trading Market is estimated to be valued at US$ 2.18 Bn in 2023 and is expected to exhibit a CAGR of 5.5% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market key trends: Development of advanced analytic techniques such as artificial intelligence and machine learning is driving growth of the algorithmic trading market. AI and machine learning systems can analyze huge amounts of market data, recognize complex patterns of behavior and eliminate human biases and errors from the decision making process. These advanced technologies help algorithms execute trades based on real-time data which leads to higher returns. Moreover, AI and machine learning powered algorithms require less human supervision and can learn and improve decisions independently leading to cost savings. Growing adoption of AI and machine learning technologies is expected to accelerate growth of the global algorithmic trading market during the forecast period.
Segment Analysis
The global algorithmic trading market is dominated by the cloud-based segment which accounts for around 60% of the overall market share. This is because cloud-based algorithmic trading platforms offer numerous advantages to financial institutions like low upfront cost, scalability, flexibility and easy deployment. It also allows traders to access their trading algorithms from anywhere. Within the cloud segment, infrastructure as a service (IaaS) dominates over software as a service (SaaS) as it provides greater flexibility and control to customize the infrastructure.
Key Takeaways
The global Algorithmic Trading Market Growth is expected to witness high growth over the forecast period driven by rapid technological advancements in the FinTech industry. Factors such as increasing volumes of online transactions, growing digitalization of payment solutions, and proliferation of artificial intelligence and big data analytics are expected to spur the adoption of automated trading strategies. The global Algorithmic Trading Market is estimated to be valued at US$ 2.18 Bn in 2023 and is expected to exhibit a CAGR of 5.5% over the forecast period 2023 to 2030.
Regional analysis
North America currently leads the global algorithmic trading market with the United States accounting for the major share. This is attributed to strong presence of financial institutions that are early adopters of new technologies. Growing volumes of cross-border trades are also driving the implementation of algorithmic trading platforms in the region. The Asia Pacific region is expected to witness the highest growth over the next few years on account of rapid digitization of financial services in countries like China and India.
For more insights, read- https://www.ukwebwire.com/algorithmic-trading-market-trends-size-and-share-analysis/
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