Algorithmic Trading Market - Growth, Trends, Covid-19 Impact, and Forecasts (2023 - 2028)

Algorithmic Trading Market - Growth, Trends, Covid-19 Impact, and Forecasts (2023 - 2028)

The algorithmic trading market is anticipated to witness a CAGR of 10.5% during the forecast period. Traders have traditionally used market surveillance technology to keep track of their trading operations and investment portfolios. Applications with built-in intelligence, like algorithmic trading, can explore the market for various opportunities based on the yield and other parameters the user specifies.

• The need for the algorithmic trading industry is anticipated to be driven by favorable governmental rules, rising demand for quick, reliable, and efficient order execution, increasing demand for market surveillance, and declining transaction costs. Large brokerage firms and institutional investors use algorithmic trading to reduce the expenses of bulk trading. Additionally, it is anticipated that the development of artificial intelligence (AI) and financial service algorithms will create attractive market expansion opportunities. A rise in the demand for cloud-based solutions is also anticipated to support the growth of the algorithmic trading market.
• In recent years, especially in the last ten years, FinTech tools have been developed significantly to increase the capacity of the financial industry, and algorithmic trading has dominated the capital markets, particularly the trading business. The general public currently has access to data science tools, high-speed internet, and computing power. The proliferation of online trading platforms and apps has increased the accessibility of trading financial items. Trade stocks and currencies only take a few mouse clicks.
• The market growth for algorithmic trading is projected to be significantly influenced by the financial services industry's broad adoption of AI, ML, and big data. Technological improvements have caused regulators to pay attention to how consumers interact with the market. Some of the global central banks began employing such technologies for advancing Algo trading. Moreover, algorithmic trading can maintain exceptionally high market liquidity due to quick buy and sell orders placed without human interaction. The increased application of algorithms across asset classes, particularly cross-asset automation, has been a trend over the past two years.
• As per TRADE's January 2022 Algorithmic Trading Survey, hedge funds increasingly use algorithms to trade most of their portfolios. For a multi-asset portfolio, hedge funds highly depend on a more significant number of suppliers for this. Algorithm providers are emphasizing multi-asset solutions to address the demand from hedge funds. The survey found that implementation insufficiency - single stock (53.14%), VWAP (54.71%), and dark liquidity seeking (72.94%) were the three most employed types of algos. Furthermore, some of the primary reasons behind the utilization of the algos include increased trader productivity (10.32%), reduced market impact (10.45%), consistency of execution performance (10.19%), ease of use (12.04%), and low commission rates (8.69%). There has also been a noticeable rise in the overall amount of automation and electronification. Moreover, the market volatility increase has maximized the need for algorithmic trading services and solutions.
• Algorithmic trading has increased because of the volatile market circumstances, large trading volume, and need for quick digital transformation to deal with distant working environments. The necessity for algo trading expanded during the COVID-19 pandemic since there was no way for geographically diversified trading to function effectively without the requirement for more advanced routing and electronic algos to assist and offer liquidity for traders. Moreover, due to a growing tendency toward algorithmic trading to make quick decisions while minimizing human mistakes, the pandemic had a positive effect on the growth rate of the algorithmic trading sector.

• A group or institution's accounts are managed by institutional investors, who also buy and sell stocks on their behalf. Pension funds, mutual fund families, insurance companies, and exchange-traded funds are institutional investors. Institutional investors and large brokerage firms primarily use algorithmic trading to save trading costs. Large order sizes benefit significantly from algorithmic trading.
• Institutional investors employ several computer-driven algorithmic tactics daily in the volatile trading markets that power the stock market. These strategies allow investors to lower trade expenses and increase their profitability.
• These investors must execute high-frequency numbers, which is not always achievable. Institutional investors can divide a large sum of money into smaller portions and continue to trade according to predetermined time frames or strategies due to algorithmic trading. For instance, an algorithmic trading strategy may push 1,000 shares out every 15 seconds and progressively place modest quantities into the market studied throughout the period or the entire day rather than depositing 100,000 shares at once.
• Due to the massive volume of trades made by high-frequency traders daily, automated trading leveraging software and artificial intelligence is necessary, primarily to accelerate trade execution. Therefore, this technology may only be purchased by institutional investors. Moreover, they gain the benefit of value based on millisecond arbitrage to profit from it. Additionally, institutional-based investors use algorithmic trading by adhering to the arbitrage strategy when they want to benefit from various occasional tiny market price discrepancies.
• Institutional investors are very concerned about their capital. Thus, they require a system capable of making wise choices. Automation of processes reduces overtrading dramatically because some traders buy and sell at the first indication of a trade window opening. These techniques lessen the possibility of errors brought on by people. It responds to marketing conditions in a split second, making it a desired investment option.

• North America is anticipated to have the most significant market share in the market studied. The main drivers of market growth throughout the forecast period are the rising investments in trading technologies (such as blockchain), the growing presence of algorithmic trading suppliers, and the expanding government backing for international trading.
• According to Wall Street data, algorithmic trading accounts for around 60-73% of the overall US equity trading. As per Select USA, the US financial markets are the largest and most liquid globally. Sentient Technologies, an AI company based in United States, operates a hedge fund that built an algorithm processing millions of data points to find trading patterns and forecast trends.
• Modern technology is rapidly transforming the formats of conventional investment models by automating all associated trading procedures, enabling the development of a secure and effective ecosystem that will be accessible to all potential investors. In February 2022, a group of developers established the Dex Finance ecosystem. Dex Finance developed a low-risk algorithmic trading model that almost anyone can utilize by automating sophisticated trading tactics and encouraging investors to leave their deposits within the protocol.
• In order to compete with one another, businesses are offering low pricing in the highly competitive financial market. Stankevicius Group launched quant finance algorithmic trading services with no advance payments leading to success-based fees exclusively. The business has been researching and creating advanced financial services like algorithmic trading. The Stankevicius Quant Financial algorithm can trade numerous pairs simultaneously in bullish and bearish markets. Professional traders also monitor trading activities, and in case of unexpected mistakes or defaults, admin-side human contact is enabled to stop losses.
• Most traders trade based on tips and gut feeling, as they are limited by current platforms and are often blindsided by market movements against them that create unexpected losses. Streak, a supplier of algorithmic trading and strategy building for retail investors, announced the launch of its Streak application in United States to address this issue. It is anticipated that the company, which already serves more than 300,000 retail investors and has handled over half a billion in trading turnover, will soon give American users access to a broad range of advanced trading capabilities for various asset classes. This will enable them to develop new trading ideas and strategies and quickly seize new trading opportunities.

Due to numerous market participants worldwide, such as Virtu Financial Inc., Algo Trader AG, MetaQuotes Software Corp., and Refinitiv Ltd, the global algorithmic trading industry is moderately fragmented. Key firms primarily focus on producing innovative solutions and successful marketing plans to maintain and grow their market share.

In May 2022, PlatinX secured USD 5 million in funding to help bolster the success of its Algo Trading Software. PTX Algo, an AI-based Low Latency software developed by Plantix technology, a prop desk management and trading software development company, provides a one-stop solution for the virtual digital assets ecosystem.

In February 2022, Software AG partnered with the largest rural lifestyle retailer in United States, Tractor Supply, to manage customer demand and enhance the shopping experience. Tractor Supply utilizes Software AG's integration and APIs solution to allow its customers to connect experiences across the store, mobile, and click-and-collect channels. Software AG solutions improve its operational excellence by integrating the supply chain from supplier to customer.

• The market estimate (ME) sheet in Excel format
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