Algorithmic Trading Market – Insights
Global algorithmic trading market was valued at US$ 10,346.6 Mn in 2018 and is expected to exhibit a CAGR of 10.7% over the forecast period to reach US$ 25,257.0 Mn in 2027.
Algorithmic trading, algo trading, automated trading, or black box trading is a technological advancement in the stock market. It is a programmed process that runs on a computer that follows a specific set of instructions (an algorithm) for placing a trade in order to generate profits at a speed and frequency that is impossible for human traders. Algorithmic trading is gaining significant traction which is useful for financial markets, and adopted in countries such as the U.S., India, the U.K., and South Korea. Accuracy, exceptional speed, and liquidity are unique features of algorithmic trading, which is expected to result in significant growth of the algorithmic trading market in the near future.
The global algorithmic trading market is expected to witness significant growth during the forecast period (2019-2027). This is attributed to increasing adoption of cloud-based solutions, services, and cloud computing for algorithmic trading. Traders use cloud services for backtesting, trading strategies, and run-time series analysis with executing trade. Traders choose cloud computing as it is capital intensive to build one’s own data centers for services such as data storage, backup and recovery, data management and trading networks. Therefore, it is easier to rent space over cloud rather than developing software or hardware infrastructure. According to Coherent Market Insights, the cloud computing market is expected to grow from US$ 58 billion in 2013 to US$ 191 billion by 2020, and the professional cloud services market is expected to grow from US$ 15.36 billion in 2017, to US$ 41.59 billion by 2023. Hence, increasing adoption of cloud-based services is expected to drive growth of the algorithmic trading market.
Growing demand for AI-based services in the financial sector is driving growth of the algorithmic trading market. In algorithmic trading, AI helps to adopt market conditions, learn from experiences and make trade decisions accordingly. Trading houses such as Blackrock, Renaissance Technologies, and Two Sigma among others use AI for selecting stocks. According to Coherent Market Insights, in 2018, about 37% of the financial institutions in India invested in artificial intelligence-focused technologies, and around 68% plan to adopt it in the near future. Therefore, increasing adoption of AI in the financial sector is expected to drive growth of the algorithmic trading market over the forecast period. Moreover, increasing adoption of non-equity trading algorithms by institutional asset managers is another factor driving growth of the algorithmic trading market.
Moreover, increasing disposable income has led to an increased trading activity which makes it an important factor driving the growth of the algorithmic trading market. According to India Brand Equity Foundation (IBEF), in 2018, India’s total rural income was around US$ 572 billion and is projected to reach US$ 1.8 trillion by the year 2021. India's rural per capita disposable income is estimated to increase at a CAGR of 4.4% to US$ 631 by 2020. Furthermore, according to DATA USA, in 2017, the U.S. population was 326 million with a median age of 38.1 and a median household income of US$ 60,336. Between 2016 and 2017, the U.S. population grew from 323 million to 326 million, which was an increase of 0.802%, and its median household income grew from US$ 57,617 to US$ 60,336 (a 4.72% increase).
Figure. Global Napping Pods Market Value (US$ Mn) Analysis and Forecast, by Application, 2017 & 2027
On the basis of application, the global algorithmic trading market is segmented into Equities, Forex, Commodities, Funds and Others. The equities segment accounted for the largest share in 2018, as is one of the leading asset classes for trading shares of companies in a secured, controlled, and managed environment. An equity market, also known as stock market or share market, is a market where shares of companies or entities are issued and traded, either through exchanges or through dealers or brokers. The place where the stocks in an equity market are traded is the 'Stock Exchange'. For instance, the equity shares in India are traded through two stock exchanges; National Stock Exchange of India (NSE) and Bombay Stock Exchange (BSE). In equity, algorithmic trading is used to execute a large market order by using automated pre-programmed trading instructions accounting for variables such as price, time, and volume. In equities, algorithmic trading is simply a way to minimize cost, market impact, as well as risk in execution of an order.
On the basis of region, algorithmic trading market is segmented into North America, Europe, Asia Pacific, Latin America, Middle East, and Africa. North America algorithmic trading market contributed the largest market share in 2018 owing to technological advancements and increasing application of algorithm trading among various end-users such as banks and financial institutions in the region. According to SelectUSA, financial markets in the U.S. are the largest and most liquid in the world. In 2017, the finance and insurance sector in the U.S. accounted for 7.5% (or US$ 1.45 trillion) of the country’s gross domestic product. In April 2018, BMO Capital Markets, the investment and corporate banking arm of BMO Financial Group, announced a multi-year strategic partnership with Clearpool Group, a provider of advanced electronic trading software. Under this agreement, Clearpool will provide BMO with a fully customizable algorithmic management system (AMS) infrastructure to execute Canada equities for BMO's institutional clients. Furthermore, several algorithmic trading solution providers in North America are focused on integrating Artificial Intelligence (AI) and Machine Learning (ML) functionalities with their existing algorithmic trading platforms. For instance, in May 2018, Bloomberg announced the launch of a new price forecasting application for investment professionals, which is powered by AI. The ‘Alpaca Forecast AI Prediction Matrix’ is an application (app), which provides short-term market price forecasts for major markets such as EUR/USD, AUD/JPY, USD/JPY, CME Nikkei 225 Futures Index, and US 10-year treasury bonds, using the Bloomberg’s Market Data Feed (B-PIPE). Such factors are expected to aid in growth of the algorithmic trading market in North America over the forecast period.
Moreover, in April 2016, the U.S. Securities and Exchange Commission (SEC) approved a rule proposed by the Financial Industry Regulatory Authority (FINRA) to reduce market manipulation that requires algorithmic trading developers to register as security traders.
Key Players in the Global Algorithmic Trading Market:
Some of the key players operating in the global algorithmic trading market include AlgoTrader GmbH, Trading Technologies International, Inc., Tethys Technology, Inc., Tower Research Capital LLC, Lime Brokerage LLC, InfoReach, Inc., FlexTrade Systems, Inc., Hudson River Trading LLC, Citadel LLC, and Virtu Financial.
Algorithmic trading, also termed as algo trading, is a method that uses computer programs and software to execute various trades with minimal human intervention. It has gained significant traction in the financial industry as it allows investment managers to be in full control of their trading process with reduced transactional costs. High frequency trading (HFT), which involves selling and buying of shares (mostly in thousands) in seconds, is one of the most popular methods in algo trading. The computer-programmed trading follows a defined set of rules for trading. The technology incorporates human as well as artificial intelligence, which enables higher accuracy and reliability among users.
Rising number of financial organizations and investors opting for automation of trading processes is one of the major factors driving adoption of algo trading in the market. For instance, in April 2018, SEBI announced plans to make algorithmic trading more accessible for investors. According to Coherent Market Insights, in 2018, in India, algorithmic trading gained popularity among institutional investors, investment banks, hedge funds, and accounted for 35-40% of the turnover on exchange from the aforementioned factors. Moreover, economies such as India, South Korea, and others, are focused on expanding their presence in the global market with a diverse portfolio of products. This is turn is expected to drive demand for algo trading process over the forecast period.
Key features of the study:
“*” marked represents similar segmentation in other categories in the respective section.
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