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1571511

アルゴリズム取引の世界市場の評価、コンポーネント別、方式別、機能別、タイプ別、エンドユーザー別、地域別、機会、予測（2017年～2031年）

Algorithmic Trading Market Assessment, By Component, By Mode, By Function, By Type, By End-user, By Region, Opportunities and Forecast, 2017-2031F
出版日: | 発行: Market Xcel - Markets and Data | ページ情報: 英文 246 Pages | 納期: 3～5営業日

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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=154.02円
アルゴリズム取引の世界市場の評価、コンポーネント別、方式別、機能別、タイプ別、エンドユーザー別、地域別、機会、予測（2017年～2031年）
出版日: 2024年10月18日
発行: Market Xcel - Markets and Data
ページ情報: 英文 246 Pages
納期: 3～5営業日
  • 全表示
  • 概要
  • 図表
  • 目次
概要

世界のアルゴリズム取引の市場規模は、2023年の157億6,000万米ドルから2031年に354億9,000万米ドルに達すると予測され、2024年～2031年の予測期間にCAGRで10.68%の成長が見込まれます。さまざまな要因によって、世界のアルゴリズム取引市場は劇的な成長を示しています。市場のボラティリティが高まったことで、トレーダーは値動きを利用できる迅速な約定と優れたリスク管理にアルゴリズムを利用せざるを得なくなっています。コンピューティングパワーとデータ処理能力の技術的進歩は、アルゴリズム取引戦略の効率性と有効性を高めるために改良されてきました。ビッグデータアナリティクスにより、トレーダーは膨大な量のデータをリアルタイムで処理できるようになり、より精巧な取引手法が生み出されています。

加えて、アルゴリズム取引にかかる取引コストの削減や人的ミスの減少により、アルゴリズム取引は魅力的な取引オプションとなっています。規制遵守は、高頻度取引戦略の採用の増加とともに、より優れた手段を求めています。開発された取引プラットフォームによって可能になった個人投資家の参加の増加は、AIと機械学習の流入とともに、ほとんどの人がアクセスできるようになっています。

アルゴリズム取引は、コンピューターアルゴリズムを採用し、金融市場内で売買の意思決定や注文を自動的に生成および実行します。膨大な量の市場データを分析しながら、非常に高速に取引を実行することで、これらのアルゴリズムは価格差を利用し、取引戦略の収益性を最大化することができます。近年では、機関投資家や小売業者の間で流行しており、取引コストや人的ミスを最小限に抑えながら効率性を高めています。2024年10月、Broker ATFXはMetaTrader 5プラットフォームの立ち上げに成功しました。これは、投資家に最高の取引環境を提供するという使命の発展における重要な一歩です。MetaTrader 5は、運用機能の改善と一般的なユーザーエクスペリエンスの向上を提供し、世界な金融市場での取引をさらに成功させるための革新的なソリューションを顧客に提供します。

当レポートでは、世界のアルゴリズム取引市場について調査分析し、市場規模と予測、市場力学、主要企業の情勢などを提供しています。

目次

第1章 プロジェクトの範囲と定義

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 顧客の声

  • 製品と市場情報
  • ブランド認知の方式
  • 購入決定において考慮される要素
    • ソフトウェア名
    • コンピュータープログラミング
    • 価格
    • 実行速度
    • 機能
    • 平均取引
    • プロモーションオファー、割引
  • カスタマーサポート
  • アルゴリズム取引の頻度
  • プライバシーと規制の考慮

第5章 世界のアルゴリズム取引市場の見通し（2017年～2031年）

  • 市場規模の分析と予測
    • 金額
  • 市場シェアの分析と予測
    • コンポーネント別
    • 方式別
    • 機能別
    • タイプ別
    • エンドユーザー別
    • 地域別
    • 市場シェア分析：企業別（金額）（上位5社とその他 - 2023年）
  • 市場マップ分析（2023年）
    • コンポーネント別
    • 方式別
    • 機能別
    • タイプ別
    • エンドユーザー別
    • 地域別

第6章 北米のアルゴリズム取引市場の見通し（2017年～2031年）

  • 市場規模の分析と予測
    • 金額
  • 市場シェアの分析と予測
    • コンポーネント別
    • 方式別
    • 機能別
    • タイプ別
    • エンドユーザー別
    • シェア：国別
  • 各国の市場の評価
    • 米国のアルゴリズム取引市場の見通し（2017年～2031年）
    • カナダ
    • メキシコ

第7章 欧州のアルゴリズム取引市場の見通し（2017年～2031年）

  • ドイツ
  • フランス
  • イタリア
  • 英国
  • ロシア
  • オランダ
  • スペイン
  • トルコ
  • ポーランド

第8章 アジア太平洋のアルゴリズム取引市場の見通し（2017年～2031年）

  • インド
  • 中国
  • 日本
  • オーストラリア
  • ベトナム
  • 韓国
  • インドネシア
  • フィリピン

第9章 南米のアルゴリズム取引市場の見通し（2017年～2031年）

  • ブラジル
  • アルゼンチン

第10章 中東・アフリカのアルゴリズム取引市場の見通し（2017年～2031年）

  • サウジアラビア
  • アラブ首長国連邦
  • 南アフリカ

第11章 需給分析

第12章 規制枠組みとコンプライアンス

  • インド証券取引委員会のガイドラインと政策
  • RBIのガイドラインと政策
  • 課税政策

第13章 バリューチェーン分析

第14章 ポーターのファイブフォース分析

第15章 PESTLE分析

第16章 ソフトウェアの価格分析

第17章 市場力学

  • 市場促進要因
  • 市場の課題

第18章 市場の動向と発展

第19章 ケーススタディ

第20章 競合情勢

  • マーケットリーダー上位5社の競合マトリクス
  • 上位5社のSWOT分析
  • 主要企業上位10社の情勢
    • Bloomberg Finance L.P.
    • London Stock Exchange Group PLC (Refinitiv)
    • ION Capital UK Limited (Fidessa)
    • Charles River Systems Inc.
    • Trading Technologies International Inc.
    • QuantConnect Corporation
    • Algo Trader AG
    • Interactive Brokers Group Inc.
    • Metaquotes Software Corporation
    • Jump Trading LLC

第21章 戦略的推奨

第22章 当社について、免責事項

図表

List of Tables

  • Table 1. Pricing Analysis of Products from Key Players
  • Table 2. Competition Matrix of Top 5 Market Leaders
  • Table 3. Mergers & Acquisitions/ Joint Ventures (If Applicable)
  • Table 4. About Us - Regions and Countries Where We Have Executed Client Projects

List of Figures

  • Figure 1. Global Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 2. Global Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 3. Global Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 4. Global Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 5. Global Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 6. Global Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 7. Global Algorithmic Trading Market Share (%), By Region, 2017-2031F
  • Figure 8. North America Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 9. North America Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 10. North America Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 11. North America Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 12. North America Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 13. North America Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 14. North America Algorithmic Trading Market Share (%), By Country, 2017-2031F
  • Figure 15. United States Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 16. United States Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 17. United States Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 18. United States Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 19. United States Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 20. United States Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 21. Canada Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 22. Canada Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 23. Canada Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 24. Canada Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 25. Canada Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 26. Canada Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 27. Mexico Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 28. Mexico Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 29. Mexico Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 30. Mexico Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 31. Mexico Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 32. Mexico Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 33. Europe Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 34. Europe Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 35. Europe Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 36. Europe Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 37. Europe Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 38. Europe Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 39. Europe Algorithmic Trading Market Share (%), By Country, 2017-2031F
  • Figure 40. Germany Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 41. Germany Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 42. Germany Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 43. Germany Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 44. Germany Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 45. Germany Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 46. France Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 47. France Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 48. France Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 49. France Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 50. France Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 51. France Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 52. Italy Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 53. Italy Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 54. Italy Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 55. Italy Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 56. Italy Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 57. Italy Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 58. United Kingdom Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 59. United Kingdom Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 60. United Kingdom Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 61. United Kingdom Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 62. United Kingdom Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 63. United Kingdom Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 64. Russia Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 65. Russia Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 66. Russia Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 67. Russia Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 68. Russia Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 69. Russia Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 70. Netherlands Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 71. Netherlands Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 72. Netherlands Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 73. Netherlands Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 74. Netherlands Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 75. Netherlands Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 76. Spain Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 77. Spain Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 78. Spain Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 79. Spain Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 80. Spain Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 81. Spain Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 82. Turkey Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 83. Turkey Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 84. Turkey Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 85. Turkey Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 86. Turkey Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 87. Turkey Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 88. Poland Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 89. Poland Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 90. Poland Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 91. Poland Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 92. Poland Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 93. Poland Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 94. South America Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 95. South America Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 96. South America Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 97. South America Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 98. South America Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 99. South America Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 100. South America Algorithmic Trading Market Share (%), By Country, 2017-2031F
  • Figure 101. Brazil Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 102. Brazil Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 103. Brazil Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 104. Brazil Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 105. Brazil Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 106. Brazil Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 107. Argentina Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 108. Argentina Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 109. Argentina Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 110. Argentina Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 111. Argentina Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 112. Argentina Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 113. Asia-Pacific Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 114. Asia-Pacific Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 115. Asia-Pacific Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 116. Asia-Pacific Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 117. Asia-Pacific Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 118. Asia-Pacific Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 119. Asia-Pacific Algorithmic Trading Market Share (%), By Country, 2017-2031F
  • Figure 120. India Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 121. India Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 122. India Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 123. India Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 124. India Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 125. India Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 126. China Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 127. China Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 128. China Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 129. China Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 130. China Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 131. China Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 132. Japan Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 133. Japan Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 134. Japan Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 135. Japan Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 136. Japan Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 137. Japan Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 138. Australia Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 139. Australia Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 140. Australia Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 141. Australia Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 142. Australia Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 143. Australia Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 144. Vietnam Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 145. Vietnam Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 146. Vietnam Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 147. Vietnam Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 148. Vietnam Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 149. Vietnam Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 150. South Korea Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 151. South Korea Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 152. South Korea Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 153. South Korea Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 154. South Korea Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 155. South Korea Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 156. Indonesia Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 157. Indonesia Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 158. Indonesia Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 159. Indonesia Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 160. Indonesia Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 161. Indonesia Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 162. Philippines Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 163. Philippines Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 164. Philippines Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 165. Philippines Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 166. Philippines Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 167. Philippines Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 168. Middle East & Africa Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 169. Middle East & Africa Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 170. Middle East & Africa Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 171. Middle East & Africa Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 172. Middle East & Africa Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 173. Middle East & Africa Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 174. Middle East & Africa Algorithmic Trading Market Share (%), By Country, 2017-2031F
  • Figure 175. Saudi Arabia Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 176. Saudi Arabia Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 177. Saudi Arabia Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 178. Saudi Arabia Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 179. Saudi Arabia Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 180. Saudi Arabia Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 181. UAE Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 182. UAE Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 183. UAE Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 184. UAE Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 185. UAE Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 186. UAE Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 187. South Africa Algorithmic Trading Market, By Value, In USD Billion, 2017-2031F
  • Figure 188. South Africa Algorithmic Trading Market Share (%), By Component, 2017-2031F
  • Figure 189. South Africa Algorithmic Trading Market Share (%), By Mode, 2017-2031F
  • Figure 190. South Africa Algorithmic Trading Market Share (%), By Function, 2017-2031F
  • Figure 191. South Africa Algorithmic Trading Market Share (%), By Type, 2017-2031F
  • Figure 192. South Africa Algorithmic Trading Market Share (%), By End-user, 2017-2031F
  • Figure 193. By Component Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 194. By Mode Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 195. By Function Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 196. By Type Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 197. By End-user Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 198. By Region Map-Market Size (USD Billion) & Growth Rate (%), 2023
目次
Product Code: MX12077

Global algorithmic trading market is projected to witness a CAGR of 10.68% during the forecast period 2024-2031, growing from USD 15.76 billion in 2023 to USD 35.49 billion in 2031. With the help of various factors, the global algorithmic trading market is experiencing dramatic growth. Increased market volatility forces traders to use algorithms for quicker executions and better risk management, where a trader can take advantage of price movements. Technological progress in computing power and data processing capabilities has been improved to enhance the efficiency and effectiveness of algorithmic trading strategies. Big data analytics enable traders to process huge amounts of data in real-time, thus creating more sophisticated trading techniques.

Additionally, less transaction cost and fewer human errors with algorithmic trading make it an attractive trading option. Regulatory compliance calls for better means, along with the increased adoption of high-frequency trading strategies. Increased participation of retail investors, which has been made possible by developed trading platforms, is accessible to most people, along with the infusion of artificial intelligence and machine learning.

Algorithmic trading employs computer algorithms, automatically generating and executing trading decisions and orders within the financial markets. By analyzing enormous amounts of market data while executing trades at highly increased speeds, these algorithms can take advantage of price differences and maximize the profitability of trading strategies. Lately, it has become trendy among institutional traders and retailers, increasing efficiency with minimal transaction costs and human error. In October 2024, Broker ATFX successfully launches the MetaTrader 5 platform. This is an important step in the development of its mission to provide investors with the best possible trading environment. MetaTrader 5 provides operational functionality improvement and increased general user experiences, offering innovative solutions for further successful trading in global financial markets to clients.

Growing Demand for Effective Algorithmic Trading Solutions to Boost Market Growth

The increasing need for effective algorithmic trading solutions is a major driver for the growth of the market. Traders and institutions seek alternatives to enhance their trading strategy, and hence, it is pivotal to have automation in executing precise trades. Algorithmic trading could include analyzing information about the market in real time, allowing traders to make swift decisions or take full advantage of fleeting opportunities. It leads to higher productivity, ruling out the possibility of human error, especially when dealing with a fast-moving market, reducing transaction costs. In October 2024, LIST, a subsidiary of ION Capital UK Limited, enhanced its FastTrade trading solution to provide customers with access to the direct equity trading mechanism of Cboe Europe. As a result, it became possible for LIST's customers to be connected directly to the largest available Dark and Periodic Auction Books of Cboe, along with their Lit Order Books. The upgrade brings sweep functionality that allows access to multiple Cboe order books using a single order so that users can maximize potential size and price improvement opportunities.

Also, with increased market volatility, algorithmic solutions have gained popularity among traders for optimal risk management and overall performance enhancement. Advanced technologies, such as AI and ML, have increased the demand as they support the development of sophisticated trading algorithms. Financial firms are thus investing heavily in these technologies in the pursuit of competitive advantages, a situation that is likely to propel growth in the algorithmic trading market.

Increasing Market Liquidity to Drive Market Growth

One of the main factors driving the growth of the algorithmic trading market is increased market liquidity. Market liquidity refers to the ease with which it is possible to buy and sell assets without affecting the level of market prices. Indeed, as algorithms percolate into markets, they increase market liquidity due to faster and more efficient transactions. With algorithms trading extremely fast, adding more institutional and retail participants is possible. Increasing liquidity attracts higher liquidity, benefitting traders with lower spreads and other transaction costs and stabilizing markets against extreme price changes. In April 2024, a capital markets technology platform provider headquartered in Chicago, Trading Technologies International Inc. (TT) announced the release of TT Splicer, a new TT Premium Order Type that brings industry-first functionality for synthetic multi-leg spread trading.

As more traders use algorithmic strategies, interconnectivity across global financial markets rises, and hence, overall liquidity increases. The birth of new financial instruments and asset classes works as an encouragement as algorithms easily switch to different trading environments. Per se, the whole synergy between algorithmic trading and market liquidity creates an ever-growing virtuous cycle that thrusts more players into adopting automated solutions so that it fosters a more dynamic and resilient trading landscape that will reward every participant in the market.

Stock Market Segment to Dominate the Global Algorithmic Trading Market Share

The high liquidity, diversified trading opportunities, and growing participation of institutional and retail investors make the stock market segment dominant in the algorithmic trading market. With advanced technologies being deployed in stock exchanges across the world, more transactions are taking place, including algorithmic trading in their list of services. The algorithms allow the processing of enormous quantities of data and the execution of trades at lightning-fast speeds, making them very effective in a highly volatile market with rapidly moving prices. This efficiency is enhancing trading strategies and slashing transaction costs, appealing to a wide spectrum of traders. In October 2024, Bloomberg Finance L.P., a financial software company, launched its fully customizable intraday quant pricing solution for Investment Research, the Open-High-Low-Close (OHLC) Bar product. The new product simplifies workflows in the quant arena, allowing customers to quickly build intraday pricing datasets, using either pre-set templates through Bloomberg or customizing fully-tailored pricing with their choice of trade condition codes.

Another factor that gives rise to algorithmic trading is the inflating usage of exchange-traded funds and new financial products. Investors look to optimize their portfolios and control the amount of risk involved, and the demand for algorithms making automated stock market trades is expected to rise. Altogether, when the stock market segment is put in the equation of technological advancements, market dynamics and the behavior of investors will be molding the force of algorithmic trading in the forecast years.

North America to Dominate the Algorithmic Trading Market Share

North America will lead the share of the global algorithmic trading market, driven by a strong financial infrastructure, technological innovation, and a high population of institutional investors. Some of the world's largest exchanges are located in this region, such as the National Association of Securities Dealers Automated Quotations (NASDAQ) and the New York Stock Exchange. Furthermore, the presence of leading fintech companies and investment firms creates an environment of competition, accelerating the development of sophisticated trading algorithms. Additionally, increased market volatility and high demand for much faster execution speeds impel traders in North America to have more algorithmic solutions to improve their strategies and reduce risks.

Also, various regulatory frames within the region continue to change in ways that support algorithmic trading practices. This is leading to an increase in the market. North America will continue to be a significant player within the global sphere of algorithmic trading, impelling trends and innovations across all regions. Institutional and retail investors are focused on exploiting their opportunities through technology. In July 2024, Trading Technologies International Inc. (TT), a Chicago-based provider of capital markets technology solutions, announced that it is offering its clients access to Abaxx Exchange, a global commodity futures exchange and clearinghouse located in Singapore.

With rapid economic growth, Asia-Pacific is emerging as the most rapidly growing market for algorithmic trading. Countries such as China, India, and Japan are seeing growing retail investors and hosting increasingly developed technological hubs. Algorithmic trading is, therefore, gaining prominence through advanced trading infrastructure and ideal regulatory support that saves firms from teething difficulties in using automated strategies for trading. Hence, Asia-Pacific will prove to be a more important hub for future algorithmic trading as a response to volatility exploitation and further implementation efficiency.

Future Market Scenario (2024 - 2031F)

Enhanced algorithms that include artificial intelligence and machine learning will further enhance increasingly sophisticated trading strategies and predictive analytics.

Algorithmic trading will bring tighter regulations in the trading style, which will change and stabilize the market to ensure fair trade.

Growing demand for customized trading algorithms used by the platforms will tailor the needs of traders in the forecast period.

Key Players Landscape and Outlook

The top market players in the algorithmic trading market are engaged with strategies to broaden their geographical footprint through region-specific and industry-specific solutions. By working together and buying local firms, they are establishing a regional stronghold and responding to the nuances of different markets. Innovations and new products are at the heart of their strategy, considering that these developments attract diverse groups of customers and improve revenue margins.

Companies look forward to effective marketing strategies to increase brand awareness, along with customer contact, while developing new solutions to maintain and gain higher market share. The growing global trade volume creates new opportunities for profitable business, and thus, market participants take it as an opportunity to grow in the global algorithmic trading market. In a quest to remain competitive, firms engage in strategic initiatives, such as mergers, acquisitions, and partnerships, that enable them to exploit synergies and upgrade their capabilities of offering cutting-edge trading technologies and solutions.

In October 2024, London-based trading automation software company ION Capital UK Limited announced that Instantia had selected ION Foreign Exchange for trade execution, trade management, risk management, and settlement services for its FX operations. By leveraging ION APIs, Instantia created customized user interfaces for clients and dealers, bringing fundamental differences in overall user experience.

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Voice of Customer

  • 4.1. Product and Market Intelligence
  • 4.2. Mode of Brand Awareness
  • 4.3. Factors Considered in Purchase Decisions
    • 4.3.1. Software Name
    • 4.3.2. Computer Programming
    • 4.3.3. Price
    • 4.3.4. Execution Speed
    • 4.3.5. Functions
    • 4.3.6. Average Trade
    • 4.3.7. Promotional Offers and Discounts
  • 4.4. Customer Support
  • 4.5. Frequency of Algorithmic Trading
  • 4.6. Consideration of Privacy and Regulations

5. Global Algorithmic Trading Market Outlook, 2017-2031F

  • 5.1. Market Size Analysis & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share Analysis & Forecast
    • 5.2.1. By Component
      • 5.2.1.1. Solution
        • 5.2.1.1.1. Platform
        • 5.2.1.1.2. Software Tools
      • 5.2.1.2. Services
    • 5.2.2. By Mode
      • 5.2.2.1. Cloud
      • 5.2.2.2. On-premises
    • 5.2.3. By Function
      • 5.2.3.1. Programming
      • 5.2.3.2. Debugging
      • 5.2.3.3. Data Extraction
      • 5.2.3.4. Back-testing and Optimization
      • 5.2.3.5. Risk Management
    • 5.2.4. By Type
      • 5.2.4.1. Stock Market
      • 5.2.4.2. Foreign Exchange Market
      • 5.2.4.3. Exchange-traded Funds
      • 5.2.4.4. Bonds
      • 5.2.4.5. Cryptocurrencies
      • 5.2.4.6. Others
    • 5.2.5. By End-user
      • 5.2.5.1. Short-term Traders
      • 5.2.5.2. Long-term Traders
      • 5.2.5.3. Retail Investors
      • 5.2.5.4. Institutional Investors
    • 5.2.6. By Region
      • 5.2.6.1. North America
      • 5.2.6.2. Europe
      • 5.2.6.3. Asia-Pacific
      • 5.2.6.4. South America
      • 5.2.6.5. Middle East and Africa
    • 5.2.7. By Company Market Share Analysis (Top 5 Companies and Others - By Value, 2023)
  • 5.3. Market Map Analysis, 2023
    • 5.3.1. By Component
    • 5.3.2. By Mode
    • 5.3.3. By Function
    • 5.3.4. By Type
    • 5.3.5. By End-user
    • 5.3.6. By Region

6. North America Algorithmic Trading Market Outlook, 2017-2031F*

  • 6.1. Market Size Analysis & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share Analysis & Forecast
    • 6.2.1. By Component
      • 6.2.1.1. Solution
        • 6.2.1.1.1. Platform
        • 6.2.1.1.2. Software Tools
      • 6.2.1.2. Services
    • 6.2.2. By Mode
      • 6.2.2.1. Cloud
      • 6.2.2.2. On-premises
    • 6.2.3. By Function
      • 6.2.3.1. Programming
      • 6.2.3.2. Debugging
      • 6.2.3.3. Data Extraction
      • 6.2.3.4. Back-testing and Optimization
      • 6.2.3.5. Risk Management
    • 6.2.4. By Type
      • 6.2.4.1. Stock Market
      • 6.2.4.2. Foreign Exchange Market
      • 6.2.4.3. Exchange-traded Funds
      • 6.2.4.4. Bonds
      • 6.2.4.5. Cryptocurrencies
      • 6.2.4.6. Others
    • 6.2.5. By End-user
      • 6.2.5.1. Short-term Traders
      • 6.2.5.2. Long-term Traders
      • 6.2.5.3. Retail Investors
      • 6.2.5.4. Institutional Investors
    • 6.2.6. By Country Share
      • 6.2.6.1. United States
      • 6.2.6.2. Canada
      • 6.2.6.3. Mexico
  • 6.3. Country Market Assessment
    • 6.3.1. United States Algorithmic Trading Market Outlook, 2017-2031F*
      • 6.3.1.1. Market Size Analysis & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share Analysis & Forecast
        • 6.3.1.2.1. By Component
          • 6.3.1.2.1.1. Solution
          • 6.3.1.2.1.1.1. Platform
          • 6.3.1.2.1.1.2. Software Tools
          • 6.3.1.2.1.2. Services
        • 6.3.1.2.2. By Mode
          • 6.3.1.2.2.1. Cloud
          • 6.3.1.2.2.2. On-premises
        • 6.3.1.2.3. By Function
          • 6.3.1.2.3.1. Programming
          • 6.3.1.2.3.2. Debugging
          • 6.3.1.2.3.3. Data Extraction
          • 6.3.1.2.3.4. Back-testing and Optimization
          • 6.3.1.2.3.5. Risk Management
        • 6.3.1.2.4. By Type
          • 6.3.1.2.4.1. Stock Market
          • 6.3.1.2.4.2. Foreign Exchange Market
          • 6.3.1.2.4.3. Exchange-traded Funds
          • 6.3.1.2.4.4. Bonds
          • 6.3.1.2.4.5. Cryptocurrencies
          • 6.3.1.2.4.6. Others
        • 6.3.1.2.5. By End-user
          • 6.3.1.2.5.1. Short-term Traders
          • 6.3.1.2.5.2. Long-term Traders
          • 6.3.1.2.5.3. Retail Investors
          • 6.3.1.2.5.4. Institutional Investors
    • 6.3.2. Canada
    • 6.3.3. Mexico

All segments will be provided for all regions and countries covered

7. Europe Algorithmic Trading Market Outlook, 2017-2031F

  • 7.1. Germany
  • 7.2. France
  • 7.3. Italy
  • 7.4. United Kingdom
  • 7.5. Russia
  • 7.6. Netherlands
  • 7.7. Spain
  • 7.8. Turkey
  • 7.9. Poland

8. Asia-Pacific Algorithmic Trading Market Outlook, 2017-2031F

  • 8.1. India
  • 8.2. China
  • 8.3. Japan
  • 8.4. Australia
  • 8.5. Vietnam
  • 8.6. South Korea
  • 8.7. Indonesia
  • 8.8. Philippines

9. South America Algorithmic Trading Market Outlook, 2017-2031F

  • 9.1. Brazil
  • 9.2. Argentina

10. Middle East and Africa Algorithmic Trading Market Outlook, 2017-2031F

  • 10.1. Saudi Arabia
  • 10.2. UAE
  • 10.3. South Africa

11. Demand Supply Analysis

12. Regulatory Framework and Compliance

  • 12.1. Securities & Exchange Board of India Guidelines and Policies
  • 12.2. RBI Guidelines and Policies
  • 12.3. Taxation Policies

13. Value Chain Analysis

14. Porter's Five Forces Analysis

15. PESTLE Analysis

16. Software Price Analysis

17. Market Dynamics

  • 17.1. Market Drivers
  • 17.2. Market Challenges

18. Market Trends and Developments

19. Case Studies

20. Competitive Landscape

  • 20.1. Competition Matrix of Top 5 Market Leaders
  • 20.2. SWOT Analysis for Top 5 Players
  • 20.3. Key Players Landscape for Top 10 Market Players
    • 20.3.1. Bloomberg Finance L.P.
      • 20.3.1.1. Company Details
      • 20.3.1.2. Key Management Personnel
      • 20.3.1.3. Products and Services
      • 20.3.1.4. Financials (As Reported)
      • 20.3.1.5. Key Market Focus and Geographical Presence
      • 20.3.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
    • 20.3.2. London Stock Exchange Group PLC (Refinitiv)
    • 20.3.3. ION Capital UK Limited (Fidessa)
    • 20.3.4. Charles River Systems Inc.
    • 20.3.5. Trading Technologies International Inc.
    • 20.3.6. QuantConnect Corporation
    • 20.3.7. Algo Trader AG
    • 20.3.8. Interactive Brokers Group Inc.
    • 20.3.9. Metaquotes Software Corporation
    • 20.3.10. Jump Trading LLC

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

21. Strategic Recommendations

22. About Us and Disclaimer