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1610728

アルゴリズム取引の市場規模、シェア、成長分析、コンポーネント別、展開別、取引タイプ別、トレーダータイプ別、地域別 - 産業予測、2024年~2031年

Algorithmic Trading Market Size, Share, Growth Analysis, By Component (Solution, Service), By Deployment, By Trading Types, By Type of Traders, By Region - Industry Forecast 2024-2031


出版日
発行
SkyQuest
ページ情報
英文 186 Pages
納期
3~5営業日
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=143.57円
アルゴリズム取引の市場規模、シェア、成長分析、コンポーネント別、展開別、取引タイプ別、トレーダータイプ別、地域別 - 産業予測、2024年~2031年
出版日: 2024年12月08日
発行: SkyQuest
ページ情報: 英文 186 Pages
納期: 3~5営業日
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  • 概要
  • 目次
概要

アルゴリズム取引の世界市場規模は、2022年に167億米ドルと評価され、2023年の186億4,000万米ドルから2031年には448億4,000万米ドルに成長し、予測期間中(2024年~2031年)のCAGRは11.6%で成長する見通しです。

アルゴリズム取引市場は、主に人工知能(AI)と機械学習(ML)の進歩によって大きな成長を遂げています。これらの技術により、トレーダーは膨大なデータセットを迅速に分析し、動向を見極め、従来の手法よりもはるかに効率的に予測を行うことができる高度なアルゴリズムを開発することができます。ミリ秒単位の迅速な注文処理を特徴とする高頻度取引(HFT)の台頭は、企業が微細な価格変動を利用できるようにすることで、市場の拡大をさらに後押ししています。さらに、ユーザーフレンドリーなプラットフォームや教育リソースが利用可能になったことで、個人投資家はアルゴリズム戦略を取引やポートフォリオ管理に取り入れることができるようになった。このようなテクノロジーの民主化は、金融市場への参入を促し、イノベーションと競争を促進します。企業は、進化する規制の枠組みに合わせてコンプライアンス・ソリューションへの投資を強化する可能性が高く、その結果、アルゴリズム取引セクターのさらなる成長が促進されます。

目次

イントロダクション

  • 調査の目的
  • 調査範囲
  • 定義

調査手法

  • 情報調達
  • 二次データと一次データの方法
  • 市場規模予測
  • 市場の前提条件と制限

エグゼクティブサマリー

  • 世界市場の見通し
  • 供給と需要の動向分析
  • セグメント別機会分析

市場力学と見通し

  • 市場概要
  • 市場規模
  • 市場力学
    • 促進要因と機会
    • 抑制要因と課題
  • ポーター分析と影響
    • 競争企業間の敵対関係
    • 代替品の脅威
    • 買い手の交渉力
    • 新規参入業者の脅威
    • 供給企業の交渉力

主な市場の考察

  • 重要成功要因
  • 競合の程度
  • 主な投資機会
  • 市場エコシステム
  • 市場の魅力指数(2023年)
  • PESTEL分析
  • マクロ経済指標
  • バリューチェーン分析
  • 価格分析
  • 技術の進歩
  • 規制情勢
  • 特許分析
  • ケーススタディ
  • 顧客と購買基準の分析

アルゴリズム取引の市場規模:コンポーネント別& CAGR(2024-2031)

  • 市場概要
  • ソリューション
    • プラットフォーム
    • ソフトウェアツール
  • サービス
    • プロフェッショナルサービス
    • マネージドサービス

アルゴリズム取引の市場規模:展開別& CAGR(2024-2031)

  • 市場概要
  • クラウド
  • オンプレミス

アルゴリズム取引の市場規模:取引タイプ別& CAGR(2024-2031)

  • 市場概要
  • 外国為替(FOREX)
  • 株式市場
  • 上場投資信託(ETF)
  • 債券
  • 暗号通貨
  • その他

アルゴリズム取引の市場規模:トレーダータイプ別& CAGR(2024-2031)

  • 市場概要
  • 機関投資家
  • 長期トレーダー
  • 短期トレーダー
  • 個人投資家

アルゴリズム取引の市場規模:組織規模別& CAGR(2024-2031)

  • 市場概要
  • 中小企業
  • 大企業

アルゴリズム取引の市場規模:地域別& CAGR(2024-2031)

  • 北米
    • 米国
    • カナダ
  • 欧州
    • 英国
    • ドイツ
    • スペイン
    • フランス
    • イタリア
    • その他欧州地域
  • アジア太平洋地域
    • 中国
    • インド
    • 日本
    • 韓国
    • その他アジア太平洋地域
  • ラテンアメリカ
    • ブラジル
    • その他ラテンアメリカ地域
  • 中東・アフリカ
    • GCC諸国
    • 南アフリカ
    • その他中東・アフリカ

競合情報

  • 上位5社の比較
  • 主要企業の市場ポジショニング(2023年)
  • 主な市場企業が採用した戦略
  • 市場の最近の動向
  • 企業の市場シェア分析(2023年)
  • 主要企業の企業プロファイル
    • 会社概要
    • 製品ポートフォリオ分析
    • セグメント別シェア分析
    • 収益の前年比比較(2021-2023)

主要企業プロファイル

  • Thomson Reuters
  • 63 Moons
  • Virtu Financial
  • MetaQuotes Software
  • Symphony
  • InfoReach
  • Argo SE
  • Kuberre Systems
  • Tata Consultancy Services
  • QuantCore Capital Management
  • iRageCapital
  • Automated Trading SoftTech
  • Tethys
  • uTrade
  • Vela
  • Algo Trader

結論と推奨事項

目次
Product Code: SQMIG45J2250

Global Algorithmic Trading Market size was valued at USD 16.70 billion in 2022 and is poised to grow from USD 18.64 billion in 2023 to USD 44.84 billion by 2031, growing at a CAGR of 11.6% during the forecast period (2024-2031).

The algorithmic trading market is experiencing significant growth, primarily fueled by advancements in artificial intelligence (AI) and machine learning (ML). These technologies enable traders to develop sophisticated algorithms capable of swiftly analyzing vast data sets, identifying trends, and generating predictions far more efficiently than traditional methods. The rise of high-frequency trading (HFT), characterized by the rapid processing of orders in milliseconds, further propels market expansion by allowing firms to exploit minute price fluctuations. Additionally, the availability of user-friendly platforms and educational resources empowers individual investors to incorporate algorithmic strategies into their trading and portfolio management. This democratization of technology fosters increased participation in financial markets, spurring innovation and competition. Organizations are likely to enhance investments in compliance solutions to align with evolving regulatory frameworks, consequently driving further growth in the algorithmic trading sector.

Top-down and bottom-up approaches were used to estimate and validate the size of the Global Algorithmic Trading market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.

Global Algorithmic Trading Market Segmental Analysis

Global Algorithmic Trading Market is segmented by Component, Deployment, Trading Types, Type of Traders, Organization Size, and Region. Based on Component, the market is segmented into Solution, and Service. Based on Deployment, the market is segmented into Cloud, and On-premise. Based on Trading Types, the market is segmented into Foreign Exchange (FOREX), Stock Markets, Exchange-Traded Fund (ETF), Bonds, Cryptocurrencies, and Others. Based on Type of Traders, the market is segmented into Institutional Investors, Long-Term Traders, Short-Term Traders, and Retail Investors. Based on Organization Size, the market is segmented into Small and Medium-Sized Enterprises, and Large Enterprises. Based on Region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.

Driver of the Global Algorithmic Trading Market

One of the primary catalysts for the growth of the global algorithmic trading market is the increasing volatility within financial markets. As market fluctuations intensify, traders seek efficient methods to capitalize on rapid price changes, and this is where algorithmic trading shines. The speed and precision of algorithms facilitate timely responses to market shifts, allowing traders to swiftly exploit potential profit opportunities. Consequently, algorithmic trading empowers market participants to not only stay well-informed but also to implement optimized strategies that enhance their trading performance. This dynamic landscape underscores the importance of algorithmic trading in navigating and thriving amidst market volatility.

Restraints in the Global Algorithmic Trading Market

The global algorithmic trading market faces significant constraints primarily due to stringent government regulations intended to stabilize the market and safeguard investors. These regulatory challenges can impose considerable complexities and costs, potentially stifling the development and implementation of algorithmic trading strategies. Moreover, heightened scrutiny and stricter oversight could curtail innovation and limit the operational flexibility of trading firms. As regulations become increasingly rigorous, they may create additional barriers that hinder market growth and discourage new entrants, ultimately impacting the overall evolution of the algorithmic trading landscape. Consequently, these regulatory impositions could impede the market's potential and adaptability.

Market Trends of the Global Algorithmic Trading Market

The global algorithmic trading market is witnessing a significant trend driven by the adoption of cloud computing, which offers traders scalable and flexible resources essential for executing complex algorithms and analyzing vast data sets efficiently. This transformative shift allows smaller trading firms to leverage cloud technology to enhance their trading capabilities, reducing the traditional barriers related to high capital investments in infrastructure. As a result, these firms are increasingly able to compete with larger institutions, enabling faster market responsiveness and the ability to capitalize on emerging opportunities. This democratization of trading technology is reshaping the competitive landscape, fostering innovation and agility in the trading ecosystem.

Table of Contents

Introduction

  • Objectives of the Study
  • Scope of the Report
  • Definitions

Research Methodology

  • Information Procurement
  • Secondary & Primary Data Methods
  • Market Size Estimation
  • Market Assumptions & Limitations

Executive Summary

  • Global Market Outlook
  • Supply & Demand Trend Analysis
  • Segmental Opportunity Analysis

Market Dynamics & Outlook

  • Market Overview
  • Market Size
  • Market Dynamics
    • Driver & Opportunities
    • Restraints & Challenges
  • Porters Analysis & Impact
    • Competitive rivalry
    • Threat of substitute
    • Bargaining power of buyers
    • Threat of new entrants
    • Bargaining power of suppliers

Key Market Insights

  • Key Success Factors
  • Degree of Competition
  • Top Investment Pockets
  • Market Ecosystem
  • Market Attractiveness Index, 2023
  • PESTEL Analysis
  • Macro-Economic Indicators
  • Value Chain Analysis
  • Pricing Analysis
  • Technological Advancement
  • Regulatory Landscape
  • Patent Analysis
  • Case Studies
  • Customer & Buying Criteria Analysis

Global Algorithmic Trading Market Size by Component & CAGR (2024-2031)

  • Market Overview
  • Solution
    • Platforms
    • Software Tools
  • Service
    • Professional Services
    • Managed Services

Global Algorithmic Trading Market Size by Deployment & CAGR (2024-2031)

  • Market Overview
  • Cloud
  • On-premises

Global Algorithmic Trading Market Size by Trading Types & CAGR (2024-2031)

  • Market Overview
  • Foreign Exchange (FOREX)
  • Stock Markets
  • Exchange-Traded Fund (ETF)
  • Bonds
  • Cryptocurrencies
  • Others

Global Algorithmic Trading Market Size by Type of Traders & CAGR (2024-2031)

  • Market Overview
  • Institutional Investors
  • Long-Term Traders
  • Short-Term Traders
  • Retail Investors

Global Algorithmic Trading Market Size by Organization Size & CAGR (2024-2031)

  • Market Overview
  • Small and Medium-Sized Enterprises
  • Large Enterprises

Global Algorithmic Trading Market Size & CAGR (2024-2031)

  • North America, (Component, Deployment, Trading Types, Type of Traders, Organization Size)
    • US
    • Canada
  • Europe, (Component, Deployment, Trading Types, Type of Traders, Organization Size)
    • UK
    • Germany
    • Spain
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific, (Component, Deployment, Trading Types, Type of Traders, Organization Size)
    • China
    • India
    • Japan
    • South Korea
    • Rest of Asia Pacific
  • Latin America, (Component, Deployment, Trading Types, Type of Traders, Organization Size)
    • Brazil
    • Rest of Latin America
  • Middle East & Africa, (Component, Deployment, Trading Types, Type of Traders, Organization Size)
    • GCC Countries
    • South Africa
    • Rest of Middle East & Africa

Competitive Intelligence

  • Top 5 Player Comparison
  • Market Positioning of Key Players, 2023
  • Strategies Adopted by Key Market Players
  • Recent Developments in the Market
  • Company Market Share Analysis, 2023
  • Company Profiles of All Key Players
    • Company Details
    • Product Portfolio Analysis
    • Company's Segmental Share Analysis
    • Revenue Y-O-Y Comparison (2021-2023)

Key Company Profiles

  • Thomson Reuters
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • 63 Moons
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Virtu Financial
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • MetaQuotes Software
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Symphony
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • InfoReach
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Argo SE
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Kuberre Systems
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Tata Consultancy Services
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • QuantCore Capital Management
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • iRageCapital
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Automated Trading SoftTech
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Tethys
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • uTrade
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Vela
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments
  • Algo Trader
    • Company Overview
    • Business Segment Overview
    • Financial Updates
    • Key Developments

Conclusion & Recommendation