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市場調查報告書

商品編碼

1532462

演算法交易市場規模 - 按組件（軟體、服務）、按部署模式（本地、基於雲端）、按交易類型（外匯、股票、交易所交易基金、債券、加密貨幣）、按行業垂直和預測, 2024 - 2032

Algorithmic Trading Market Size - By Component (Software, Services), By Deployment Mode (On-premises, Cloud-based), By Trading Type (Foreign Exchange, Equity, Exchange-traded Funds, Bonds, Cryptocurrencies), By Industry Verticals & Forecast, 2024 - 2032

出版日期: 2024年05月16日 | 出版商:

Global Market Insights Inc. | 英文 280 Pages | 商品交期: 2-3個工作天內

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簡介目錄

在領先金融公司 MampA 併購不斷增加的推動下，全球演算法交易市場 2024 年至 2032 年間複合年成長率將超過 13%。這些策略整合正在推動創新並擴大演算法交易解決方案的範圍。 MampA 活動使公司能夠整合先進技術、增強其交易平台並利用資料分析功能。這帶來了更複雜的演算法，可以即時分析大量市場資料、最佳化交易策略並提高執行效率。例如，2024 年 7 月，基於雲端的科技公司 Clear Street 公佈了收購專門從事加拿大和美國股票的演算法執行解決方案公司的計畫。 Clear Street 已達成協議，收購 Instinet 的 Fox River 演算法交易業務。

此外，收購使公司能夠進入新的市場和客戶群，從而擴大演算法交易在不同行業和地區的採用。合併後的實體增加了對演算法交易技術的投資，增強了競爭優勢和市場流動性。隨著金融機構持續進行策略併購，對尖端演算法交易解決方案的需求預計將上升，推動市場進一步成長，並提高交易業務的整體效率和獲利能力。

演算法交易行業的整體價值根據組件、部署模式、交易類型、行業垂直和區域進行分類。

2024 年至2032 年，服務領域的演算法交易市場收入將實現令人稱讚的複合年成長率。財產損失等風險變得至關重要。全面的商業汽車保險可針對財務損失和營運中斷提供保護，保護企業資產並確保連續性。商用車數量的增加和風險管理意識的增強導致對這些政策的需求增加。因此，商業汽車保險市場正在不斷擴大，以滿足各行業不斷變化的需求。

從 2024 年到 2032 年，交易所交易領域將顯著成長。隨著企業擴大貨車和皮卡車隊，他們需要全面的保險，以防範事故、竊盜和損壞等風險。日常營運對這些車輛的日益依賴凸顯了需要客製化保險解決方案來解決其特定風險。因此，商業汽車保險市場正在不斷擴大，以滿足使用貨車和皮卡的企業的多樣化需求。

亞太地區演算法交易市場從 2024 年到 2032 年將呈現顯著的複合年成長率。隨著公司越來越依賴商用車輛進行營運，這種類型的保險對於保護其資產變得至關重要。不斷增加的道路事故以及對全面風險管理解決方案的渴望進一步推動了對碰撞保險的需求。這一趨勢凸顯了其在維護車隊安全和營運連續性方面的重要性，從而推動了市場成長。

產業生態系統分析
供應商格局
- 演算法開發者
- 技術提供者
- 交易平台提供者
- 顧問公司
- 最終用戶
利潤率分析
技術與創新格局
專利分析
重要新聞和舉措
監管環境
衝擊力
- 成長動力
  - 交易策略中擴大採用自動化
  - 對更快執行和降低交易成本的需求
  - 擴大電子交易平台和交易所
  - 全球化帶來跨境貿易機會
- 產業陷阱與挑戰
  - 容易受到技術故障和系統故障的影響
  - 演算法交易策略缺乏透明度
成長潛力分析
波特的分析
PESTEL分析

第 4 章：競爭格局

介紹
公司市佔率分析
競爭定位矩陣
戰略展望矩陣

第 5 章：市場估計與預測：按組成部分 2021 - 2032 年

主要趨勢
軟體
- 演算法
- 交易平台
- 風險管理工具
服務
- 諮詢
- 執行
- 支援與維護

第 6 章：市場估計與預測：依部署模式，2021 - 2032 年

主要趨勢
本地
基於雲端

第 7 章：市場估計與預測：依交易類型，2021 - 2032

主要趨勢
外匯（Forex）
公平
交易所交易基金 (ETF)
債券
加密貨幣
其他

第 8 章：市場估計與預測：按產業垂直分類，2021 - 2032 年

主要趨勢
銀行與金融
經紀自營商
其他

第 9 章：市場估計與預測：按地區，2021 - 2032

主要趨勢
北美洲
- 美國
- 加拿大
歐洲
- 英國
- 德國
- 法國
- 義大利
- 西班牙
- 俄羅斯
- 歐洲其他地區
亞太地區
- 中國
- 印度
- 日本
- 韓國
- 澳新銀行
- 東南亞
- 亞太地區其他地區
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
- 拉丁美洲其他地區
MEA
- 阿拉伯聯合大公國
- 南非
- 沙烏地阿拉伯
- MEA 的其餘部分

第 10 章：公司簡介

AlgoTrader
Automated Trading SoftTech
Codebase Technologies
CQG
Deltix
InfoReach
Marquee by Goldman Sachs
MetaTrader
Nasdaq
Optiver
Pragmatic
QuantHouse
Raptor Trading Systems
Refinitiv (formerly Reuters)
Tethys
Tick Data
Trading Technologies
Virtu Financial
Wissolution

簡介目錄

Product Code: 9512

Global Algorithmic Trading Market will witness over 13% CAGR between 2024 and 2032, fueled by the rising mergers and acquisitions M&A among leading financial companies. These strategic consolidations are driving innovation and expanding the reach of algorithmic trading solutions. M&A activities enable firms to integrate advanced technologies, enhance their trading platforms, and leverage data analytics capabilities. This results in more sophisticated algorithms that can analyze vast amounts of market data in real time, optimize trading strategies, and improve execution efficiency. For instance, in July 2024, cloud-based technology firm Clear Street unveiled plans to acquire an algorithmic execution solutions company specializing in Canadian and US equities. Clear Street has reached an agreement to purchase Instinet's Fox River algorithmic trading business.

Additionally, acquisitions allow firms to access new markets and client bases, broadening the adoption of algorithmic trading across different sectors and geographies. The increased investment in algorithmic trading technology by merged entities fosters competitive advantages and market liquidity. As financial institutions continue to pursue strategic mergers and acquisitions, the demand for cutting-edge algorithmic trading solutions is expected to rise, driving further growth in the market and enhancing the overall efficiency and profitability of trading operations.

The overall Algorithmic Trading Industry value is classified based on the component, deployment mode, trading type, industry vertical, and region.

The algorithmic trading market revenue from the services segment will register a commendable CAGR from 2024 to 2032. As companies increasingly rely on fleets for transportation, delivery, and logistics, robust insurance solutions become crucial to manage risks such as accidents, theft, and property damage. Comprehensive commercial auto insurance offers protection against financial losses and operational disruptions, safeguarding business assets and ensuring continuity. The rising number of commercial vehicles and growing awareness of risk management contribute to the increased demand for these policies. Consequently, the commercial auto insurance market is expanding to meet the evolving needs of businesses across various sectors.

The exchange traded segment will witness appreciable growth from 2024 to 2032. These vehicles are crucial for various commercial activities, including logistics, delivery, and field services. As businesses expand their fleets of vans and pickups, they require comprehensive insurance coverage to protect against risks such as accidents, theft, and damage. The increasing reliance on these vehicles for daily operations highlights the need for tailored insurance solutions that address their specific risks. Consequently, the commercial auto insurance market is expanding to cater to the diverse needs of businesses utilizing vans and pickups.

Asia Pacific algorithmic trading market will exhibit a notable CAGR from 2024 to 2032. Collision coverage protects businesses by covering repair or replacement costs for vehicles damaged in accidents, regardless of fault. As companies increasingly depend on commercial vehicles for their operations, the need for this type of coverage becomes essential to safeguard their assets. Rising road incidents and the desire for comprehensive risk management solutions further drive the demand for collision coverage. This trend highlights its importance in maintaining fleet safety and operational continuity, fueling market growth.

Chapter 1 Methodology & Scope

1.1 Market scope & definition
1.2 Research design
- 1.2.1 Research approach
- 1.2.2 Data collection methods
1.3 Base estimates & calculations
- 1.3.1 Base year calculation
- 1.3.2 Key trends for market estimation
1.4 Forecast model
1.5 Primary research and validation
- 1.5.1 Primary sources
- 1.5.2 Data mining sources

Chapter 2 Executive Summary

2.1 Industry 360° synopsis, 2021 - 2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Supplier landscape
- 3.2.1 Algorithm developers
- 3.2.2 Technology providers
- 3.2.3 Trading platform providers
- 3.2.4 Consulting firms
- 3.2.5 End user
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Patent analysis
3.6 Key news & initiatives
3.7 Regulatory landscape
3.8 Impact forces
- 3.8.1 Growth drivers
  - 3.8.1.1 Increasing adoption of automation in trading strategies
  - 3.8.1.2 Demand for faster execution and reduced transaction costs
  - 3.8.1.3 Expansion of electronic trading platforms and exchanges
  - 3.8.1.4 Globalization leading to cross-border trading opportunities
- 3.8.2 Industry pitfalls & challenges
  - 3.8.2.1 Vulnerability to technological glitches and system failures
  - 3.8.2.2 Lack of transparency in algorithmic trading strategies
3.9 Growth potential analysis
3.10 Porter's analysis
3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component 2021 - 2032 ($ Bn)

5.1 Key trends
5.2 Software
- 5.2.1 Algorithm
- 5.2.2 Trading platform
- 5.2.3 Risk management tools
5.3 Services
- 5.3.1 Consulting
- 5.3.2 Implementation
- 5.3.3 Support & maintenance

Chapter 6 Market Estimates & Forecast, By Deployment Mode, 2021 - 2032 ($ Bn)

6.1 Key trends
6.2 On-premises
6.3 Cloud-based

Chapter 7 Market Estimates & Forecast, By Trading Type, 2021 - 2032 ($ Bn)

7.1 Key trends
7.2 Foreign exchange (Forex)
7.3 Equity
7.4 Exchange-traded funds (ETFs)
7.5 Bonds
7.6 Cryptocurrencies
7.7 Others

Chapter 8 Market Estimates & Forecast, By Industry Verticals, 2021 - 2032 ($ Bn)

8.1 Key trends
8.2 Banking & finance
8.3 Broker-dealers
8.4 Others

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2032 ($ Bn)

9.1 Key trends
9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
9.3 Europe
- 9.3.1 UK
- 9.3.2 Germany
- 9.3.3 France
- 9.3.4 Italy
- 9.3.5 Spain
- 9.3.6 Russia
- 9.3.7 Rest of Europe
9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 India
- 9.4.3 Japan
- 9.4.4 South Korea
- 9.4.5 ANZ
- 9.4.6 Southeast Asia
- 9.4.7 Rest of Asia Pacific
9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Argentina
- 9.5.4 Rest of Latin America
9.6 MEA
- 9.6.1 UAE
- 9.6.2 South Africa
- 9.6.3 Saudi Arabia
- 9.6.4 Rest of MEA