Algorithmic Trading Global Market Report 2022: Ukraine-Russia War Impact
The algorithmic trading includes revenues earned by entities by providing automated trading services, financial services, trade executions, system architecture management.
NEW YORK, Dec. 22, 2022 /PRNewswire/ --
Major players in the algorithmic trading market are 63 Moons Technologies Limited, MetaQuotes Software, AlgoTrader, Virtu Financial Inc, Tethys Technology Inc, Trading Technologies International Inc, Argo SE, Software AG, Vela Trading Systems LLC, uTrade Solutions, InfoReach Inc, Tata Consultancy Services, Symphony Fintech Solutions Pvt Ltd, Refinitiv, Thomson Reuters Corporation, iRageCapital Advisory Private Limited, Lightspeed Financial Services Group LLC, FlexTrade Systems Inc, and Citadel LLC.
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The global algorithmic trading market is expected to grow from $14.13 billion in 2021 to $15.93 billion in 2022 at a compound annual growth rate (CAGR) of 12.7%. The Russia-Ukraine war disrupted the chances of global economic recovery from the COVID-19 pandemic, at least in the short term. The war between these two countries has led to economic sanctions on multiple countries, surge in commodity prices, and supply chain disruptions, effecting many markets across the globe. The algorithmic trading market is expected to reach $24.79 billion in 2026 at a CAGR of 11.7%.
The algorithmic trading includes revenues earned by entities by providing automated trading services, financial services, trade executions, system architecture management. The market value includes the value of related goods sold by the service provider or included within the service offering.
Algorithmic trading is a technique that uses scripted computer codes and algorithms to open and close transactions under predefined rules that are programmed into a computer system. It reduces transaction costs and avoids significant price changes.
North America was the largest region in the algorithmic trading market in 2021.Asia Pacific is expected to be the fastest-growing region in the forecast period.
The regions covered in the algorithmic trading market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.
The market value is defined as the revenues that enterprises gain from goods and/or services sold within the specified market and geography through sales, grants, or donations in terms of currency (in USD ($) unless otherwise specified).
The revenues for a specified geography are consumption valuesâ€"that is, they are revenues generated by organisations in the specified geography within the specified market, irrespective of where they are produced. It does not include revenues from resales either further along the supply chain or as part of other products.
The main types of algorithmic trading are stock market, foreign exchange (forex), exchange-traded fund (ETF), bonds, cryptocurrencies, and others.A stock market refers to a location where buyers and sellers exchange public corporation equity shares.
The components involved are solutions and services that operate on programming, debugging, data extraction, back-testing and optimization, risk management functions. These are used by institutional investors, long-term traders, short-term traders, retail investors for equities, forex, commodities, funds, other applications.
The rising need for quick digital transformation is expected to propel the algorithmic trading market going forward.Digital transformation refers to the process of employing digital technology to build new business processes, cultures, and customer experiences or to adapt current ones to fit shifting company and market needs.
The quick digital transformation leads to an increasing number of trades that can boost algorithmic trading.For instance, according to articles published by Forbes, a US-based business magazine, in 2019 globally, 70% of businesses either already have a digital transformation strategy in place or are developing one.
Additionally, the year 2019 has seen a 40% increase in investment in technology related to digital transformation with businesses investing over $2 trillion in digital transformation. Therefore, the rising need for quick digital transformation is driving the algorithmic trading market.
Product innovations are a key trend gaining popularity in the algorithmic trading market.Major players are concentrating their efforts on creating innovative products to sustain their position in the algorithmic trading market.
For instance, in July 2021, Rain Technologies, Inc., a Canada-based technology company, launched RAIN TRADER. Rain Trader is a web-based platform that provides automated trading and algorithmic trading models. This platform gives individuals the opportunity to engage in hassle-free, fully automated algorithmic trading.
In March 2022, Trading Technologies International Inc., a US-based technology company specializing in professional trading software, infrastructure, and data solutions, acquired RCM-X for an undisclosed amount. Through this acquisition Trading Technologies increases its product portfolio in algorithmic execution strategies, trade analytics, and TCA (transaction cost analysis) services to improve customer experience. RCM-X is a US-based financial technology company that develops algorithmic execution strategies and quantitative trading products.
The countries covered in the algorithmic trading market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA.
The algorithmic trading market research report is one of a series of new reports that provides algorithmic trading market statistics, including algorithmic trading industry global market size, regional shares, competitors with algorithmic trading market share, detailed algorithmic trading market segments, market trends, and opportunities, and any further data you may need to thrive in the algorithmic trading industry. This algorithmic trading market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.
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