Algorithmic Trading Market Overview
Algorithmic trading (also called automated trading 1, black-box trading, or algo-trading) is a trading strategy that uses computer programs or algorithms to execute trades. It involves the use of complex algorithms and data-driven strategies to make trading decisions, often taking advantage of small price differentials in the markets. An algorithmic trading program analyzes market data, such as price and volume, to determine when to buy or sell a particular financial instrument. It can also be used to manage risk and to execute trades at a high frequency. Algorithmic trading has grown significantly in popularity in recent years, particularly with the advent of high-speed trading and the increasing availability of market data.
The global Algorithmic Trading market Share is projected to grow at a CAGR of 13.1% from 2021 to 2030
The majority of financial services firms are increasing their AI and ML adoption in order to capitalize on data from digitally driven channels. Several companies in the insurance, banking, and asset management industries use it. This has resulted in the last decade’s emerging trend of the data-driven investments. This, in turn, increased demand for high-frequency trading, also known as algorithmic trading. Such AI-powered trading systems analyze huge amounts of data faster than humans. As a result, AI and algorithms in financial services are opportunistic for market growth in the forecast period, as they enable market innovation.
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Opportunities
Growing Adoption of Cloud-Based Services for Algorithmic Trading to offer Robust Opportunities
The growing adoption of cloud-based services, cloud computing, and cloud-based solutions for algorithmic trading will offer robust opportunities for the algorithmic trading market over the forecast period. Cloud services are used by traders for trading strategies, backtesting, and run-time series analysis while executing trades. Traders prefer cloud computing because building one’s own data centres for services like backup and recovery, data storage, trading networks, and data management is expensive. As a result, renting space via the cloud is more convenient than developing hardware or software infrastructure.
Restraints and Challenges
Insufficient Risk Valuation Capabilities to act as Market Restraint
The insufficient risk valuation capabilities and lack of observation may act as market restraints over the forecast period.
Algorithmic Trading Market Key Players
Key players profiled in the global algorithmic trading market report includes:
- Thomson Reuters (US)
- 63 moons (India)
- Virtu Financial (US)
- Software AG (Germany)
- MetaQuotes Software (Cyprus)
- Symphony Fintech (India)
- InfoReach (US)
- Argo SE (US)
- Kuberre Systems (US)
- Tata Consultancy Services (India)
- QuantCore Capital Management (China)
- iRageCapital (India)
- Automated Trading SoftTech (India)
- Tethys (US)
- Trading Technologies (US)
- uTrade (India)
- Vela (US)
- AlgoTrader (Switzerland).
Algorithmic Trading Market Segmentation
The global algorithmic trading market is bifurcated based on component, type, traders, deployment mode, and organization size.
By component, the solutions segment will lead the market over the forecast period.
By type, the ETF segment will dominate the market over the forecast period.
By traders, institutional investors will spearhead the market over the forecast period.
By deployment mode, the cloud segment will have the lions share in the market over the forecast period.
By organization size, the large enterprises will have the largest share in the market over the forecast period.
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Algorithmic Trading Market Regional Analysis
North America to Command Algorithmic Trading Market
In 2018, the North American market accounted for the majority of the global algorithm trading market, and it is expected to continue to lead the market all through the forecast timeframe. The market’s rise may be attributed to the high level of technical knowledge required to create the algorithm using Python, MATLAB, C++, Perl, and JAVA. North America heads the algorithmic trading market for a variety of reasons, including massive investments in trading technologies and increased government support for global trading. Furthermore, the region’s extensive presence of top algorithmic trading vendors propels market growth.
Rising investments in trading technologies especially blockchain, an increase in the presence of popular algorithmic trading companies, and increasing support from the government for global trading are expected to drive market growth during the forecast period. Because of technological advancements and increased use of algorithm trading amid various end-users like banks & financial institutions in the region, the North America algorithmic trading market contributed the largest market share in 2018. Furthermore, several North American algorithmic trading solution providers are working to integrate Artificial Intelligence & Machine Learning functionalities into their existing algorithmic trading platforms.
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In the United States, algorithmic trading accounts nearly for 60-73 percent of all stock trading. According to Select USA, the United States’ financial markets are the most liquid and largest in the world. Sentient Technologies, a hedge fund run by a US-based AI startup, created an algorithm which analyses huge data points for uncovering trading patterns & forecast trends. Sentient’s algorithms analyze trillions of the simulated trading scenarios for discovering and combining profitable trading patterns and to develop new techniques. This not only saves time and effort, but it also guarantees the top-most level of accuracy.
APAC to Have Admirable Growth in Algorithmic Trading Market
Due to heavy investments by the public and private sectors to improve trading technologies, Asia-Pacific is expected to have the highest growth rate during the forecast period, driving the need for algorithmic trading solutions for automating trading processes. Countries such as Japan, India, the Philippines, & Singapore have increased their use of algorithmic trading platforms, services, and software.
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