Algorithmic Trading Market Report: Sales and Revenue, Competitive Analysis, Growth, Including Top Companies by 2028 Algorithmic Trading Market Size
The algorithmic trading market size is quantitatively analyzed from 2020 to 2028 to highlight the financial competency of the industry.
PORTLAND, PORTLAND, OR, UNITED STATES, October 27, 2023 / EINPresswire.com / — According to the report published by Allied Market Research, the global algorithmic trading market garnered $12.14 billion in 2020, and is expected to garner $31.49 billion by 2028, manifesting a CAGR of 12.7% from 2021 to 2028.The report provides a detailed analysis of changing market dynamics, key segments, value chain, regional scenario, top investment pockets, and competitive landscape.
Algorithmic trading, often referred to as algo trading or automated trading, is a method of executing financial transactions using computer algorithms or predefined sets of rules.In this approach, computers are programmed to automatically buy or sell financial assets (such as stocks, bonds, options, or commodities) based on a specific set of criteria, without the need for direct human intervention.
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The global algorithmic trading market is experiencing growth driven by heightened demand for swift, dependable, and efficient order execution, bolstered by supportive government regulations and the imperative to lower transaction costs.Nevertheless, market expansion faces hindrances due to the absence of suitable risk assessment capabilities.On the flip side, the emergence of artificial intelligence and diverse financial algorithms, along with an upsurge in the desire for cloud-based solutions, offer promising prospects in the coming years.
The algorithmic trading market is being primarily driven by the increasing adoption of automation in financial markets, the demand for faster and more efficient trading strategies, advancements in technology, and the need for risk management and compliance in the trading process.
Market Trends:
1.Rise in Algorithmic Trading: Algorithmic trading has seen significant growth in recent years.It is estimated that the majority of trading in equity markets is now executed by algorithms.
2.
High-Frequency Trading (HFT): High-frequency trading remains a major segment of algorithmic trading.
HFT firms use advanced algorithms to execute a large number of trades in a very short period, often in milliseconds.
3.Quantitative Trading: Quantitative trading, which relies on mathematical models and statistical analysis, is a popular approach in algorithmic trading.These models can include factors like price, volume, and market sentiment.
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By type, the global algorithmic trading market share was dominated by the stock markets segment in 2020, and is expected to maintain its dominance in the upcoming years, due to increase in adoption of algorithmic trading solutions by investors to trade stocks as it operates through a computer program without a need for human interventions.However, the cryptocurrencies segment is expected to witness the highest growth, owing to rise in interest of trading professionals toward crypto-currency trading.
By component, the solution segment contributed to the highest share in 2020, accounting for nearly two-thirds of the total market share, and is expected to maintain its lead during the forecast period.
However, the services segment is projected to witness the highest CAGR of 13.8% from 2021 to 2028.
By region, North America held the highest share in 2020, contributing to more than two-fifths of the total market, and is expected to continue its dominance by 2028.However, Asia-Pacific is projected to witness the fastest CAGR of 15.3% during the forecast period.
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Some of the key algorithmic trading industry players profiled in the report include 63MOONS, Virtu Financial, Software AG, Refinitiv Ltd.MetaQuotes Software Corp.
Symphony Fintech Solutions Pvt Ltd.Argo SE, Tata Consultancy Services, Algo Trader AG, and Tethys.This study includes algorithmic trading market trends, algorithmic trading market analysis, and future estimations to determine the imminent investment pockets.
Covid-19 Scenario:
• Traders have been inclined to opt for algorithmic trading for reducing human errors and taking fast decisions during the times of uncertainty that arose due to the Covid-19 pandemic.
• Moreover, increase in popularity of high-frequency traders (HFT) has been experienced during the pandemic, which led to the growth of the algorithmic trading market.
• Novel algorithmic trading products have been launched to carry out better decision-making than before and cater to the rise in volumes of trading.
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