PUBLISHER: Grand View Research | PRODUCT CODE: 1587803
PUBLISHER: Grand View Research | PRODUCT CODE: 1587803
The global algorithmic trading market size is expected to reach USD 42.99 billion by 2030, registering a CAGR of 12.9% from 2025 to 2030, according to a new report by Grand View Research, Inc. The growth can be attributed to the increasing demand for effective, reliable, fast order execution and reduced transaction costs. Algorithmic trading solutions are widely used to process orders using pre-programmed and automated trading instructions to account for variables such as timing, price, and volume.
Investors and algorithmic traders regularly use high-frequency trading technology, enabling their firms to carry out tens of thousands of trades per second. Moreover, algorithmic trading solutions are widely used by investors and algorithmic traders in a wide variety of conditions, including arbitrage, order execution, and trend trading strategies, among others. Furthermore, the increasing trading volumes put pressure on trading desks to efficiently improve execution performance. This, as a result, is expected to create demand for algorithmic trading solutions.
The increasing use of algorithmic trading platforms by brokerage houses and institutional investors to cut down on costs associated with trading is expected to propel market growth over the forecast period. Brokerage houses and institutional investors are using these platforms to trade large order sizes. Furthermore, businesses across the globe use these platforms to create liquidity.
The COVID-19 outbreak is anticipated to impact the market positively. The increasing shift towards algorithmic trading solutions for making trade decisions at a rapid pace by eliminating human errors is further expected to propel market growth. Moreover, the Reserve Bank of Australia stated that the impact of the COVID-19 pandemic had advanced the industry's shift toward electronic trading. These aforementioned factors are expected to propel market growth over the forecast period.