Global Algorithmic Trading Market: Growth, Trends, and Forecasts (2019-2024) – ResearchAndMarkets.com

DUBLIN–(BUSINESS WIRE)–The “Global Algorithmic Trading Market: Growth, Trends, and Forecasts (2019-2024)” report has been added to ResearchAndMarkets.com’s offering.

The global algorithmic trading market is expected to register a CAGR of 11% in the forecast period.

The application has built-in intelligence to search for the opportunities that exist in the market as per the yield and other criteria defined by the user.

Key Highlights

  • The major growth drivers include the rising demand for fast, reliable, and effective order execution, gradually reducing transactional costs. Institutional investors and big brokerage houses use algorithmic trading to cut down on costs associated with bulk trading.
  • Further, increasing government regulations and growing demand for market surveillance is aiding market growth. Traders keep track of their trading activities and investment portfolio by using market surveillance technology. Furthermore, the emergence of AI in the financial service sector is expected to be a major factor aiding in the growth of the algorithmic trading market.
  • However, the speed of order execution, an advantage in ordinary circumstances, can become a problem when several orders are executed simultaneously without human intervention. For instance, the flash crash of 2010 was majorly due to algorithmic trading.
  • Also, algorithmic trading creates a situation of the highly liquid market due to rapid buy and sell orders without any human intervention. It can also lead to an instant loss of liquidity. This is, however, expected to restrain market growth. For instance, algorithmic trading was a significant factor in causing a loss of liquidity in currency markets after the Swiss franc discontinued its Euro peg in 2015.

Major Market Trends

Cloud-based Algorithmic Trading Platforms Expected to Gain Maximum Traction

  • The cloud-based algorithmic trading platforms are expected to gain the maximum market traction in the forecast period. This is majorly due to the various benefits like cloud-based trading solutions help traders to gain maximum profits and effectively automate the trading process. Also, due to their benefits such as easy trade data maintenance, cost-effectiveness, scalability, and effective management.
  • Cloud computing is a model which uses networks of remote servers usually accessed over the internet, to store, manage, and process data. Cloud technology often achieves cost savings or improves business agility and responsiveness. Cloud-based trading removes all the complexities to provide an extraordinarily powerful environment to allow the traders to focus more on developing trading strategies that work.
  • Due to the convenience of the cloud, traders can use the cloud service to check new trading strategies, backtest and run-time series analysis along with executing trades. It also helps the traders to access real-time data and access the data anywhere at any time.
  • According to LogicMonitor’s survey, 41% of enterprise workloads will be run on public cloud platforms like Amazon AWS, Google Cloud Platform, IBM Cloud, Microsoft Azure, and others, by 2020. On-premise workloads are predicted to shrink from 37% today to 27% of all workloads by 2020. Financial Services has the highest percentage of server images deployed in private or public clouds, approaching nearly 100% versus a median adoption rate of 19%.

North America Expected to Dominate the Market

  • North America is expected to hold the largest market size in the global algorithmic trading market in terms of adopting and developing algorithmic trading. The rising investments in trading technologies such as blockchain, increasing presence of algorithmic trading vendors, and growing government support for global trading are the major factors expected to contribute to the market growth during the forecast period.
  • Also, due to the substantial technological advancements and considerable application of algorithm trading in various applications such as banks and financial institutions across the region is expected to stimulate market growth.
  • Algorithmic trading is responsible for around 60-73% of all U.S. equity trading. According to Select USA, financial markets in the U.S. are the largest and most liquid in the world. In 2017, finance and insurance represented 7.5% (or USD 1.45 trillion) of the U.S. gross domestic product.

Competitive Landscape

The global algorithmic trading market is moderately fragmented due to the presence of various market players across the globe. Key players are focusing on developing new solutions and create effective marketing strategies for market surveillance to maintain and increase their market share.

Industry Developments

  • April 2019 – Virtu Financial, Inc. and MarketAxess Holdings, Inc., two global leaders in electronic trading, partnered to provide institutions with enhanced trading tools and access to global exchange-traded funds (ETFs) and fixed income securities. The effort, which includes the distribution of Virtu’s streaming eNAV ETF fair value offering, is expected to launch in the third quarter.

Key Topics Covered

1 INTRODUCTION

1.1 Study Deliverables

1.2 Study Assumptions

1.3 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

4.1 Market Overview

4.2 Introduction to Market Drivers and Restraints

4.3 Market Drivers

4.3.1 Rising Demand for Fast, Reliable, and Effective Order Execution

4.3.2 Reduce Transaction Costs

4.3.3 Increasing Government Regulations

4.3.4 Growing Demand for Market Surveillance

4.4 Market Restraints

4.5 Industry Value Chain Analysis

4.6 Industry Attractiveness – Porter’s Five Force Analysis

4.6.1 Bargaining Power of Suppliers

4.6.2 Bargaining Power of Buyers/Consumers

4.6.3 Threat of New Entrants

4.6.4 Threat of Substitute Products

4.6.5 Intensity of Competitive Rivalry

4.7 Technology Snapshot

4.7.1 Algorithmic Trading Strategies

4.7.1.1 Momentum Trading

4.7.1.2 Arbitrage Trading

4.7.1.3 Trend Following

4.7.1.4 Execution-Based Strategies

4.7.1.5 Sentiment Analysis

4.7.1.6 Index-Fund Rebalancing

4.7.1.7 Mathematical Model-Based Strategies

4.7.1.8 Other Algorithmic Trading Strategies

5 MARKET SEGMENTATION

5.1 By Types of Traders

5.1.1 Institutional Investors

5.1.2 Retail Investors

5.1.3 Long-term Traders

5.1.4 Short-term Traders

5.2 By Component

5.2.1 Solutions

5.2.1.1 Platforms

5.2.1.2 Software Tools

5.2.2 Services

5.3 By Deployment

5.3.1 On-Cloud

5.3.2 On-Premise

5.4 By Organization Size

5.4.1 Small and Medium Enterprises

5.4.2 Large Enterprises

5.5 Geography

5.5.1 North America

5.5.2 Europe

5.5.3 Asia-Pacific

5.5.4 Latin America

5.5.5 Middle East & Africa

6 COMPETITIVE LANDSCAPE

6.1 Company Profiles

6.1.1 Software AG

6.1.2 Refinitiv

6.1.3 63 Moons Technologies Limited

6.1.4 Virtu Financial, Inc.

6.1.5 MetaQuotes Software Corp.

6.1.6 Symphony Fintech

6.1.7 Info Reach, Inc.

6.1.8 ARGO SE

6.1.9 Tata Consultancy Services Ltd.

6.1.10 Algo Trader

6.1.11 Kuberre Systems, Inc.

7 INVESTMENT ANALYSIS

8 MARKET OPPORTUNITIES AND FUTURE TRENDS

For more information about this report visit https://www.researchandmarkets.com/r/bqei34

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