市场调查报告书
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1137990

算法交易市场 - COVID-19 的增长、趋势、影响和预测(2022-2027 年)

Algorithmic Trading Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

出版日期: | 出版商: Mordor Intelligence Pvt Ltd | 英文 121 Pages | 商品交期: 2-3个工作天内

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  • 全貌
  • 简介
  • 目录
简介

算法交易市场预计在预测期间(2022-2027 年)以 10.5% 的复合年增长率增长。

传统上,交易者使用市场监控技术来了解他们的交易活动和投资组合。具有内置智能的应用程序(例如算法交易)可以根据用户指定的收益率和其他参数探索市场以寻找各种机会。

主要亮点

  • 由于有利的政府法规、对快速、可靠和高效订单执行的需求不断增加,对市场监控的需求增加以及交易成本降低,预计算法交易的需求将会增长。大型经纪公司和机构投资者正在使用算法交易来降低大宗交易的成本。此外,人工智能(AI)和金融服务算法的发展有望创造有吸引力的市场扩张机会。此外,对基于云的解决方案不断增长的需求也有望支持算法交易市场的增长。
  • 近年来,尤其是最近十年,金融科技工具得到大力发展,以增强金融行业的能力,算法交易席捲了资本市场,尤其是交易业务。数据科学工具、高速互联网和计算能力也正在向公众开放。在线交易平台和应用程序的激增使交易金融工具更容易获得。只需点击几下鼠标即可交易股票和货币。
  • 预计算法交易市场的增长将受到金融服务行业广泛采用 AI、ML 和大数据的重大影响。技术进步导致监管机构关註消费者如何与市场互动。世界上一些中央银行已经开始采用这种技术来促进算法交易。此外,算法交易可以在无需人工干预的情况下快速下单买卖,从而保持极高的市场流动性。算法在资产类别中的应用越来越多,尤其是跨资产自动化,是过去两年的趋势。
  • 根据 TRADE 的 2021 年算法交易调查,对冲基金越来越多地通过算法交易其大部分投资组合。对于多资产组合,对冲基金对此高度依赖更多供应商。算法提供商现在专注于多资产解决方案,以满足对冲基金的需求。研究表明,采用率最高的三种算法未得到充分实施——单一股票(53.14%)、VWAP(54.71%)和暗流动性寻求(72.94%)。此外,在 2021 年使用算法的主要原因是提高交易员生产力 (10.32%)、降低市场影响 (10.45%)、一致的执行性能 (1□□0.19%) 和易用性 (12.04%) 和低费用 (8.69%) )。此外,自动化和数位化的总量显着增加。此外,市场波动性的增加最大限度地增加了对算法交易服务和解决方案的需求。
  • 因此,由于需要快速数位化转型以适应动荡的市场条件、高交易量和远程工作环境,算法交易正在兴起。算法交易,因为在 COVID-19 流行期间,如果没有对更复杂的路由和电子算法的需求来协助交易者并提供流动性,地理分布的交易就无法有效运作。需求已经扩大。此外,大流行对算法交易部门的增长率产生了积极影响,因为算法交易的趋势已经增加,算法交易可以做出快速决策,同时最大限度地减少人为错误。

主要市场趋势

机构投资者有望持有大量股份

  • 机构和机构的账户由机构投资者管理,他们也代表他们买卖股票。机构投资者包括养老基金、共同基金家族、保险公司和交易所交易基金。机构投资者和大型经纪公司使用算法交易主要是为了节省交易成本。大订单可以从算法交易中受益匪浅。
  • 机构投资者每天都会在驱动股市的动盪交易市场中采用多种计算机辅助算法策略。这些策略使投资者能够降低交易成本并提高盈利能力。
  • 这些投资者必须处理高频数字,而这并不总是可以实现的。算法交易允许机构投资者将大笔资金分成更小的部分,并根据预定的时间框架和策略继续交易。例如,算法交易策略不是一次存入 100,000 股,而是每 15 秒推出 1,000 股,并在一段时间内或全天逐渐向研究市场注入适量的股票。
  • 由于高频交易者每天进行大量交易,因此需要由软件和人工智能驱动的自动交易主要是为了加速交易执行。因此,这项技术仅适用于机构投资者。此外,他们正在获得基于毫秒套利的价值来从中获利。其他机构投资者在试图从不时出现的各种小的市场价格差异中获利时,坚持套利交易策略并使用算法交易。
  • 机构投资者非常注重金钱,需要一个能让他们做出明智选择的系统。一些交易者在交易窗口打开的那一刻进行买卖,因此自动化流程可以显着减少过度交易。这种技术减少了人为错误的可能性。它是一种首选的投资选择,因为它可以立即响应营销情况。

北美有望主导市场

  • 预计北美将占所研究市场的最大份额。预测期内市场增长的主要驱动力是对交易技术(例如区块链)的投资增加、算法交易供应商的存在增加以及政府对国际贸易的支持不断增加。
  • 根据华尔街的数据,算法交易约占所有美国股票交易的 60-73%。据 Select USA 称,美国金融市场是世界上最大、流动性最强的市场。总部位于美国的人工智能公司 Sentient Technologies 构建了处理数百万个数据点的算法,以运行发现交易模式和预测趋势的对冲基金。
  • 现代技术正在迅速改变传统投资模式的格式,实现所有相关交易程序的自动化,为所有潜在投资者开发一个安全有效的生态系统。 2022 年 2 月,一群开发者建立了 Dex Finance 生态系统。通过自动化复杂的交易策略并鼓励投资者在协议内存款,Dex Finance 开发了一种几乎任何人都可以利用的低风险算法交易模型。
  • 在竞争激烈的金融市场中,企业提供低价以相互竞争。 2021 年 12 月,Stankevicius Group 将推出无需预付的量化金融算法交易服务,仅收取成功费用。该业务探索并创造了先进的金融服务,例如算法交易。 Stankevicius Quant Financial 的算法可以在牛市和熊市中同时交易大量货币对。它还允许专业交易者监控交易活动,如果出现意外错误或违约,管理员可以联繫并止损。
  • 由于当前平台的限制,许多交易者依赖提示和直觉,往往会因不利的市场走势而导致意外损失。为个人投资者提供算法交易和策略构建的提供商 Streak 宣布将在美国推出 Streak 应用程序来解决这个问题。该公司已为超过 300,000 名散户投资者提供服务,交易量超过 5 亿日元,不久将为其在美国的用户提供涵盖各种资产类别的广泛高级交易能力。这让用户可以开发新的交易思路和策略,快速抓住新的交易机会。 Streak 消除了算法交易的障碍,这些障碍要求交易者和投资者学习编程或购买昂贵、缓慢且不方便的遗留软件。

竞争格局

由于全球市场参与者众多,包括 Virtu Financial, Inc.、Algo Trader AG、MetaQuotes Software Corp. 和 Refinitiv Ltd.,全球算法交易行业适度分散。为了保持和扩大市场份额,主要参与者主要专注于创造创新的解决方案和成功的营销计划。

  • 2022 年 2 月 - Software AG 与美国最大的乡村生活方式零售商 Tractor Supply 合作,成功管理客户需求并改善购物体验。 Tractor Supply 利用 Software AG 的集成和 API 解决方案,使客户能够跨店内、移动和点击提货渠道连接体验。 Software AG 的解决方案通过整合从供应商到客户的供应链,提高了公司的卓越运营能力。
  • 2021 年 11 月 - Refinitiv 和 Pio-Tech 决定合作,为其在中东和非洲的银行客户提供智能、现代的解决方案,并带来许多独特的商业利益。宣布。这种伙伴关係的目的是提高所有银行业务中各种内部反洗钱 (AML) 业务的有效性。

其他特典

  • Excel 格式的市场预测 (ME) 表
  • 三个月的分析师支持

内容

第 1 章介绍

  • 研究假设和市场定义
  • 调查范围

第 2 章研究方法

第 3 章执行摘要

第 4 章市场洞察

  • 市场概览
  • 工业吸引力 - 波特五力分析
    • 新进入者的威胁
    • 买方/消费者议价能力
    • 供应商的议价能力
    • 替代品的威胁
    • 竞争公司之间的敌对关係
  • COVID-19 对市场的影响
  • 技术快照
    • 算法交易策略
      • 动量交易
      • 套利交易
      • 趋势和跟进
      • 基于执行的策略
      • 情绪分析
      • 指数基金再平衡
      • 基于数学模型的策略
      • 其他算法交易策略

第 5 章市场动态

  • 市场促进因素
    • 对快速、可靠和高效订单执行的需求不断增加
    • 由于交易成本降低,对市场监督的需求不断增加
  • 市场抑制因素
    • 暂时失去流动性

第 6 章市场细分

  • 按交易者类型
    • 机构投资者
    • 个人投资者
    • 长期交易者
    • 短线交易者
  • 按组件
    • 解决方案
      • 平台
      • 软件工具
    • 服务
  • 按部署
    • 云端
    • 本地
  • 按组织规模
    • 中小企业
    • 大企业
  • 按地区
    • 北美
    • 欧洲
    • 亚太地区
    • 拉丁美洲
    • 中东和非洲

第 7 章竞争格局

  • 公司简介
    • Thomson Reuters
    • Jump Trading LLC
    • Refinitiv Ltd
    • 63 Moons Technologies Limited
    • Virtu Financial Inc.
    • MetaQuotes Software Corp.
    • Symphony Fintech Solutions Pvt. Ltd
    • Info Reach Inc.
    • ARGO SE
    • IG Group
    • Kuberre Systems Inc.
    • Algo Trader AG

第 8 章投资分析

第 9 章市场机会和未来趋势

目录
Product Code: 66701

The Algorithmic Trading Market is anticipated to witness a CAGR of 10.5% throughout the forecast period (2022-2027). 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.

Key Highlights

  • 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 would 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 now 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. For advancing Algo trading, some of the global central banks began employing such technologies. 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 2021 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. To address the demand from hedge funds, algorithm providers are now emphasizing multi-asset solutions. 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 in 2021 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%). Also, there has 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 thus 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.

Key Market Trends

Institutional Investors Expected to Hold Major Share

  • 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 isn't 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 Expected to Dominate the Market

  • 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. An AI company, Sentient Technologies, based in the 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 in December 2021 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 with based on tips, gut feeling, as they are limited by current platforms and are often blind-sided 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 the US 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. Streak removes the obstacles to algo trading, which typically necessitates traders and investors to learn how to program or purchase costly, sluggish, and clunky legacy software.

Competitive Landscape

Due to the existence of 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. To maintain and grow their market share, key firms are mostly focusing on producing innovative solutions and successful marketing plans.

  • February 2022 - Software AG successfully partnered with the largest rural lifestyle retailer in the 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.
  • November 2021 - Refinitiv and Pio-Tech declared their collaboration in order to deliver smart, modern solutions with numerous unique business benefits to both firms' banking clients in the Middle East and Africa. The goal of this alliance is to increase the effectiveness of various internal anti-money laundering (AML) operations across all banking functions.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Threat of New Entrants
    • 4.2.2 Bargaining Power of Buyers/Consumers
    • 4.2.3 Bargaining Power of Suppliers
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Impact of COVID-19 on the Market
  • 4.4 Technology Snapshot
    • 4.4.1 Algorithmic Trading Strategies
      • 4.4.1.1 Momentum Trading
      • 4.4.1.2 Arbitrage Trading
      • 4.4.1.3 Trend Following
      • 4.4.1.4 Execution-based Strategies
      • 4.4.1.5 Sentiment Analysis
      • 4.4.1.6 Index-fund Rebalancing
      • 4.4.1.7 Mathematical Model-based Strategies
      • 4.4.1.8 Other Algorithmic Trading Strategies

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Rising Demand for Fast, Reliable, and Effective Order Execution
    • 5.1.2 Growing Demand for Market Surveillance Augmented by Reduced Transaction Costs
  • 5.2 Market Restraints
    • 5.2.1 Instant Loss of Liquidity

6 MARKET SEGMENTATION

  • 6.1 By Types of Traders
    • 6.1.1 Institutional Investors
    • 6.1.2 Retail Investors
    • 6.1.3 Long-term Traders
    • 6.1.4 Short-term Traders
  • 6.2 By Component
    • 6.2.1 Solutions
      • 6.2.1.1 Platforms
      • 6.2.1.2 Software Tools
    • 6.2.2 Services
  • 6.3 By Deployment
    • 6.3.1 On-cloud
    • 6.3.2 On-premise
  • 6.4 By Organization Size
    • 6.4.1 Small and Medium Enterprises
    • 6.4.2 Large Enterprises
  • 6.5 By Geography
    • 6.5.1 North America
    • 6.5.2 Europe
    • 6.5.3 Asia Pacific
    • 6.5.4 Latin America
    • 6.5.5 Middle-East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Thomson Reuters
    • 7.1.2 Jump Trading LLC
    • 7.1.3 Refinitiv Ltd
    • 7.1.4 63 Moons Technologies Limited
    • 7.1.5 Virtu Financial Inc.
    • 7.1.6 MetaQuotes Software Corp.
    • 7.1.7 Symphony Fintech Solutions Pvt. Ltd
    • 7.1.8 Info Reach Inc.
    • 7.1.9 ARGO SE
    • 7.1.10 IG Group
    • 7.1.11 Kuberre Systems Inc.
    • 7.1.12 Algo Trader AG

8 INVESTMENT ANALYSIS

9 MARKET OPPORTUNITIES AND FUTURE TRENDS