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市場調查報告書
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2024025

人工智慧驅動的投資分析市場：預測（至2034年）－按策略、資料來源、功能、資產、最終使用者和地區分類的全球分析

AI-Driven Investment Analytics Market Forecasts to 2034 - Global Analysis By Strategy, Data Source, Function, Asset, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧驅動的投資分析市場預計將在 2026 年達到 3,759 億美元，並在預測期內以 26.6% 的複合年成長率成長，到 2034 年達到 24,801 億美元。

人工智慧驅動的投資分析利用人工智慧 (AI) 和機器學習技術來分析金融數據、預測市場趨勢並最佳化投資策略。這為投資組合經理、交易員和個人投資者提供可操作的洞察、風險評估和自動化決策工具。其主要應用包括演算法交易、情緒分析和預測建模。由於對數據驅動型投資解決方案和即時分析的需求不斷成長，以及人工智慧技術在財富管理、資產管理和避險基金營運中的應用日益廣泛，該市場正在不斷擴張。

演算法交易的普及

人工智慧模型即時處理大量資料集的能力正在改變決策流程。演算法交易還能減少人為偏見，進而實現更穩健的投資組合策略。股票、商品和外匯市場對預測分析日益成長的需求進一步推動了人工智慧的應用。機構投資者正在利用人工智慧最佳化交易執行並最大限度地降低交易成本。這些因素共同賦予了市場強勁的發展動能。

熟練的人工智慧分析師短缺

金融公司在招募精通量化金融和機器學習的專家方面面臨重重困難。這種人才短缺正在減緩交易部門採用人工智慧驅動平台的速度。高昂的培訓成本和陡峭的學習曲線也阻礙了中小企業採用人工智慧驅動平台。此外，對人工智慧輸出結果的誤解可能導致錯誤的投資決策。這些挑戰共同阻礙了人工智慧驅動的投資分析充分發揮其潛力。

與智慧投顧平台整合

智慧投顧正日益融入複雜的演算法，以根據客戶的風險承受能力和市場狀況最佳化投資組合。這種融合擴大了服務的可近性，使個人投資者也能受益於機構級的分析。金融科技公司與資產管理公司之間的合作正在加速該領域的創新。人工智慧驅動的洞察也提高了自動化諮詢服務的透明度和可靠性。隨著智慧投顧在全球的普及，與人工智慧分析的協同效應將開啟新的收入來源。

來自分析型新創公司的激烈競爭

敏捷型新創公司常常透過部署低成本、顛覆性的解決方案來挑戰老牌公司。快速的創新週期使得大型企業難以維持技術領先地位。在創業投資的支持下，新參與企業也瞄準了諸如ESG分析和另類數據等細分領域。這種競爭壓力會降低傳統供應商的利潤率和市場佔有率。如果缺乏持續創新，老牌公司將面臨在快速變化的環境中失去競爭力的風險。

新冠疫情的影響：

新冠疫情加速了金融服務領域的數位轉型，並提升了對人工智慧主導分析的需求。疫情期間的市場波動凸顯了即時洞察和自適應交易策略的重要性。在不確定性的背景下，金融機構紛紛轉向人工智慧工具進行風險管理和投資組合最佳化。然而，招募和培訓的中斷延緩了人工智慧相關人才的取得。同時，遠距辦公的普及也增加了對雲端分析平台的依賴。總而言之，新冠疫情起到了催化劑的作用，重塑了投資實踐，並進一步鞏固了人工智慧驅動型解決方案的重要性。

在預測期內，市場和交易資料區段預計將是規模最大的部分。

預計在預測期內，市場與交易資料區段將佔據最大的市場佔有率，因為機構投資者在處理高頻交易資料方面對人工智慧的依賴程度日益提高。即時分析能夠加快決策速度並改善執行策略。該板塊將受益於股票和衍生性商品預測建模需求的成長。與交易平台的整合提高了營運效率和透明度。此外，人工智慧主導的流動性和波動模式洞察能夠增強投資組合管理。

在預測期內，多元資產投資組合板塊預計將呈現最高的複合年成長率。

在預測期內，受多元化投資策略需求不斷成長的推動，多元資產投資組合領域預計將呈現最高的成長率。人工智慧驅動的分析技術使投資者能夠最佳化股票、債券、大宗商品和另類資產的資產配置。對環境、社會和治理（ESG）以及主題投資組合日益成長的興趣進一步推動了其應用。該領域受益於人工智慧在多個資產類別中平衡風險和回報的能力。機構投資者正在利用多元資產分析來增強其抵禦市場衝擊的能力。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其先進的金融基礎設施以及機構投資者對人工智慧的積極應用。美國在強勁的創業投資支持下，在演算法交易和金融科技創新領域處於主導地位。大型資產管理公司和避險基金正在將人工智慧驅動的分析融入其核心業務。有關數位投資平台的監管細則也提振了市場信心。此外，北美眾多領先的人工智慧技術供應商的存在進一步鞏固了其優勢。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於金融科技的快速發展和個人投資者參與度的不斷提高。中國、印度和新加坡等國家在交易和諮詢服務領域引領人工智慧的應用。智慧型手機普及率的提升和數位支付生態系統的擴展正在推動對智慧投顧平台的需求。該地區各國政府正積極透過科技主導的解決方案來促進普惠金融。此外，亞太地區龐大的投資者群體也為人工智慧分析提供了龐大的市場。

免費客製化服務：

訂閱本報告的用戶可享有以下免費自訂選項之一：

  • 公司簡介
    • 對其他公司（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域分類
    • 根據客戶興趣量身定做的主要國家/地區的市場估算、預測和複合年成長率（註：基於可行性檢查）
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 成長要素、挑戰與機遇
  • 競爭格局概述
  • 戰略考慮和建議

第2章：分析框架

  • 分析的目標和範圍
  • 相關人員分析
  • 分析的前提條件與限制
  • 分析方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 科技與創新趨勢
  • 新興市場和高成長市場
  • 監管和政策環境
  • 感染疾病的影響及恢復前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商議價能力
    • 買方的議價能力
    • 替代產品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧驅動型投資分析市場：依策略分類

  • 量化和演算法策略
  • 情感主導分析
  • 基於元素/智慧 Beta 分析
  • 智慧投顧分析
  • 主題 ESG 分析
  • 其他策略

第6章：全球人工智慧驅動型投資分析市場：依資料來源分類

  • 市場和交易數據
  • 替代資料（社群媒體、衛星資料、網路資料）
  • 財務報表及申報文件
  • 新聞媒體數據
  • 宏觀經濟數據
  • 其他數據來源

第7章：全球人工智慧驅動型投資分析市場：按功能分類

  • 阿爾法生成
  • 風險建模與管理
  • 投資組合最佳化
  • 價格預測
  • 交易執行最佳化
  • 其他功能

第8章：全球人工智慧驅動型投資分析市場：按資產類別分類

  • 庫存
  • 固定殖利率產品
  • 加密貨幣
  • 商品
  • 多資產組合
  • 其他資產

第9章：全球人工智慧驅動型投資分析市場：依最終用戶分類

  • 資產管理公司
  • 避險基金
  • 銀行和投資公司
  • 個人投資者
  • 金融科技平台
  • 其他最終用戶

第10章：全球人工智慧驅動型投資分析市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 其他地區（ROW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 產業加值網路與供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 企業合併（M&A）
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • BlackRock, Inc.
  • Bloomberg LP
  • FactSet Research Systems Inc.
  • MSCI Inc.
  • Refinitiv（LSEG）
  • AlphaSense Inc.
  • Kensho Technologies
  • Palantir Technologies Inc.
  • SAP SE
  • IBM Corporation
  • Oracle Corporation
  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services（AWS）
  • Yewno Inc.
  • Dataminr Inc.
  • Quandl（Nasdaq）
  • Sentieo
Product Code: SMRC35236

According to Stratistics MRC, the Global AI-Driven Investment Analytics Market is accounted for $375.9 billion in 2026 and is expected to reach $2,480.1 billion by 2034 growing at a CAGR of 26.6% during the forecast period. AI-Driven Investment Analytics uses artificial intelligence and machine learning to analyze financial data, predict market trends, and optimize investment strategies. It provides portfolio managers, traders, and retail investors with actionable insights, risk assessments, and automated decision-making tools. Applications include algorithmic trading, sentiment analysis, and predictive modeling. The market is expanding due to growing demand for data-driven investment solutions, real-time analytics, and increased adoption of AI technologies in wealth management, asset management, and hedge fund operations.

Market Dynamics:

Driver:

Growth in algorithmic trading adoption

The ability of AI models to process vast datasets in real time is transforming decision-making processes. Algorithmic trading also reduces human bias, enabling more consistent portfolio strategies. Rising demand for predictive analytics in equities, commodities, and forex markets further strengthens adoption. Institutional investors are leveraging AI to optimize execution and minimize transaction costs. Collectively, these factors are fueling strong momentum in the market.

Restraint:

Lack of skilled AI analysts

Financial firms struggle to recruit professionals with expertise in both quantitative finance and machine learning. This talent gap slows the deployment of AI-driven platforms across trading desks. High training costs and steep learning curves also discourage smaller firms from adoption. Additionally, misinterpretation of AI outputs can lead to flawed investment decisions. These challenges collectively hinder the full potential of AI-driven investment analytics.

Opportunity:

Integration with robo-advisory platforms

Robo-advisors are increasingly incorporating advanced algorithms to tailor portfolios based on client risk profiles and market conditions. This integration expands accessibility, allowing retail investors to benefit from institutional-grade analytics. Partnerships between fintech firms and asset managers are accelerating innovation in this space. AI-driven insights also improve transparency and trust in automated advisory services. As robo-advisory adoption grows globally, the synergy with AI analytics will unlock new revenue streams.

Threat:

Intense competition from analytics startups

Agile startups often introduce disruptive solutions at lower costs, challenging incumbents. Rapid innovation cycles make it difficult for larger firms to maintain technological leadership. Venture-backed entrants are also targeting niche segments such as ESG analytics and alternative data. This competitive pressure may erode margins and market share for traditional providers. Without continuous innovation, established firms risk losing relevance in a fast-evolving landscape.

Covid-19 Impact:

The Covid-19 pandemic accelerated digital transformation in financial services, boosting demand for AI-driven analytics. Market volatility during the crisis highlighted the need for real-time insights and adaptive trading strategies. Financial institutions turned to AI tools to manage risk and optimize portfolios amid uncertainty. However, disruptions in hiring and training slowed talent acquisition for AI roles. At the same time, remote work environments increased reliance on cloud-based analytics platforms. Overall, Covid-19 acted as a catalyst, reshaping investment practices and reinforcing the importance of AI-driven solutions.

The market & trading data segment is expected to be the largest during the forecast period

The market & trading data segment is expected to account for the largest market share during the forecast period as as institutions increasingly depend on AI to process high-frequency trading data. Real-time analytics enable faster decision-making and improved execution strategies. The segment benefits from rising demand for predictive modeling in equities and derivatives. Integration with trading platforms enhances operational efficiency and transparency. Moreover, AI-driven insights into liquidity and volatility patterns strengthen portfolio management.

The multi-asset portfolios segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the multi-asset portfolios segment is predicted to witness the highest growth rate due to increasing demand for diversified investment strategies. AI-driven analytics allow investors to optimize allocations across equities, bonds, commodities, and alternative assets. Rising interest in ESG and thematic portfolios further drives adoption. The segment benefits from AI's ability to balance risk and return across multiple asset classes. Institutional investors are leveraging multi-asset analytics to enhance resilience against market shocks.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share owing to advanced financial infrastructure and strong institutional adoption of AI. The U.S. leads in algorithmic trading and fintech innovation, supported by robust venture capital funding. Major asset managers and hedge funds are integrating AI-driven analytics into core operations. Regulatory clarity around digital investment platforms also fosters confidence. Additionally, North America hosts several leading AI technology providers, reinforcing its dominance.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR driven by rapid fintech expansion and growing retail investor participation. Countries such as China, India, and Singapore are spearheading AI adoption in trading and advisory services. Rising smartphone penetration and digital payment ecosystems are fueling demand for robo-advisory platforms. Governments in the region are actively promoting financial inclusion through technology-driven solutions. Moreover, Asia Pacific's large investor base provides a vast market for AI-driven analytics.

Key players in the market

Some of the key players in AI-Driven Investment Analytics Market include BlackRock, Inc., Bloomberg L.P., FactSet Research Systems Inc., MSCI Inc., Refinitiv (LSEG), AlphaSense Inc., Kensho Technologies, Palantir Technologies Inc., SAP SE, IBM Corporation, Oracle Corporation, Microsoft Corporation, Google LLC, Amazon Web Services (AWS), Yewno Inc., Dataminr Inc., Quandl and Sentieo.

Key Developments:

In March 2026, AlphaSense Launched "AI-Led Expert Calls," a revolutionary product that allows an AI Interviewer to conduct expert interviews on behalf of analysts. This autonomous agent scales early-stage discovery by generating structured transcripts and synthesis without requiring a live human moderator.

In February 2025, FactSet finalized the strategic acquisition of LiquidityBook, a leading provider of cloud-native buy-side and sell-side trading solutions. This acquisition allows FactSet to unify front-to-back office workflows, integrating execution management (EMS) directly with its AI-driven research and analytics suite.

Strategies Covered:

  • Quantitative & Algorithmic Strategies
  • Sentiment-Driven Analytics
  • Factor-Based & Smart Beta Analytics
  • Robo-Advisory Analytics
  • Thematic & ESG Analytics
  • Other Strategies

Data Sources Covered:

  • Market & Trading Data
  • Alternative Data (Social, Satellite, Web)
  • Financial Statements & Filings
  • News & Media Data
  • Macroeconomic Data
  • Other Data Sources

Functions Covered:

  • Alpha Generation
  • Risk Modeling & Management
  • Portfolio Optimization
  • Price Forecasting
  • Trade Execution Optimization
  • Other Functions

Assets Covered:

  • Equities
  • Fixed Income
  • Cryptocurrencies
  • Commodities
  • Multi-Asset Portfolios
  • Other Assets

End Users Covered:

  • Asset Management Firms
  • Hedge Funds
  • Banks & Investment Firms
  • Retail Investors
  • FinTech Platforms
  • Other End Users

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI-Driven Investment Analytics Market, By Strategy

  • 5.1 Quantitative & Algorithmic Strategies
  • 5.2 Sentiment-Driven Analytics
  • 5.3 Factor-Based & Smart Beta Analytics
  • 5.4 Robo-Advisory Analytics
  • 5.5 Thematic & ESG Analytics
  • 5.6 Other Strategies

6 Global AI-Driven Investment Analytics Market, By Data Source

  • 6.1 Market & Trading Data
  • 6.2 Alternative Data (Social, Satellite, Web)
  • 6.3 Financial Statements & Filings
  • 6.4 News & Media Data
  • 6.5 Macroeconomic Data
  • 6.6 Other Data Sources

7 Global AI-Driven Investment Analytics Market, By Function

  • 7.1 Alpha Generation
  • 7.2 Risk Modeling & Management
  • 7.3 Portfolio Optimization
  • 7.4 Price Forecasting
  • 7.5 Trade Execution Optimization
  • 7.6 Other Functions

8 Global AI-Driven Investment Analytics Market, By Asset

  • 8.1 Equities
  • 8.2 Fixed Income
  • 8.3 Cryptocurrencies
  • 8.4 Commodities
  • 8.5 Multi-Asset Portfolios
  • 8.6 Other Assets

9 Global AI-Driven Investment Analytics Market, By End User

  • 9.1 Asset Management Firms
  • 9.2 Hedge Funds
  • 9.3 Banks & Investment Firms
  • 9.4 Retail Investors
  • 9.5 FinTech Platforms
  • 9.6 Other End Users

10 Global AI-Driven Investment Analytics Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 BlackRock, Inc.
  • 13.2 Bloomberg L.P.
  • 13.3 FactSet Research Systems Inc.
  • 13.4 MSCI Inc.
  • 13.5 Refinitiv (LSEG)
  • 13.6 AlphaSense Inc.
  • 13.7 Kensho Technologies
  • 13.8 Palantir Technologies Inc.
  • 13.9 SAP SE
  • 13.10 IBM Corporation
  • 13.11 Oracle Corporation
  • 13.12 Microsoft Corporation
  • 13.13 Google LLC
  • 13.14 Amazon Web Services (AWS)
  • 13.15 Yewno Inc.
  • 13.16 Dataminr Inc.
  • 13.17 Quandl (Nasdaq)
  • 13.18 Sentieo

List of Tables

  • Table 1 Global AI-Driven Investment Analytics Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Driven Investment Analytics Market, By Strategy (2023-2034) ($MN)
  • Table 3 Global AI-Driven Investment Analytics Market, By Quantitative & Algorithmic Strategies (2023-2034) ($MN)
  • Table 4 Global AI-Driven Investment Analytics Market, By Sentiment-Driven Analytics (2023-2034) ($MN)
  • Table 5 Global AI-Driven Investment Analytics Market, By Factor-Based & Smart Beta Analytics (2023-2034) ($MN)
  • Table 6 Global AI-Driven Investment Analytics Market, By Robo-Advisory Analytics (2023-2034) ($MN)
  • Table 7 Global AI-Driven Investment Analytics Market, By Thematic & ESG Analytics (2023-2034) ($MN)
  • Table 8 Global AI-Driven Investment Analytics Market, By Other Strategies (2023-2034) ($MN)
  • Table 9 Global AI-Driven Investment Analytics Market, By Data Source (2023-2034) ($MN)
  • Table 10 Global AI-Driven Investment Analytics Market, By Market & Trading Data (2023-2034) ($MN)
  • Table 11 Global AI-Driven Investment Analytics Market, By Alternative Data (Social, Satellite, Web) (2023-2034) ($MN)
  • Table 12 Global AI-Driven Investment Analytics Market, By Financial Statements & Filings (2023-2034) ($MN)
  • Table 13 Global AI-Driven Investment Analytics Market, By News & Media Data (2023-2034) ($MN)
  • Table 14 Global AI-Driven Investment Analytics Market, By Macroeconomic Data (2023-2034) ($MN)
  • Table 15 Global AI-Driven Investment Analytics Market, By Other Data Sources (2023-2034) ($MN)
  • Table 16 Global AI-Driven Investment Analytics Market, By Function (2023-2034) ($MN)
  • Table 17 Global AI-Driven Investment Analytics Market, By Alpha Generation (2023-2034) ($MN)
  • Table 18 Global AI-Driven Investment Analytics Market, By Risk Modeling & Management (2023-2034) ($MN)
  • Table 19 Global AI-Driven Investment Analytics Market, By Portfolio Optimization (2023-2034) ($MN)
  • Table 20 Global AI-Driven Investment Analytics Market, By Price Forecasting (2023-2034) ($MN)
  • Table 21 Global AI-Driven Investment Analytics Market, By Trade Execution Optimization (2023-2034) ($MN)
  • Table 22 Global AI-Driven Investment Analytics Market, By Other Functions (2023-2034) ($MN)
  • Table 23 Global AI-Driven Investment Analytics Market, By Asset (2023-2034) ($MN)
  • Table 24 Global AI-Driven Investment Analytics Market, By Equities (2023-2034) ($MN)
  • Table 25 Global AI-Driven Investment Analytics Market, By Fixed Income (2023-2034) ($MN)
  • Table 26 Global AI-Driven Investment Analytics Market, By Cryptocurrencies (2023-2034) ($MN)
  • Table 27 Global AI-Driven Investment Analytics Market, By Commodities (2023-2034) ($MN)
  • Table 28 Global AI-Driven Investment Analytics Market, By Multi-Asset Portfolios (2023-2034) ($MN)
  • Table 29 Global AI-Driven Investment Analytics Market, By Other Assets (2023-2034) ($MN)
  • Table 30 Global AI-Driven Investment Analytics Market, By End User (2023-2034) ($MN)
  • Table 31 Global AI-Driven Investment Analytics Market, By Asset Management Firms (2023-2034) ($MN)
  • Table 32 Global AI-Driven Investment Analytics Market, By Hedge Funds (2023-2034) ($MN)
  • Table 33 Global AI-Driven Investment Analytics Market, By Banks & Investment Firms (2023-2034) ($MN)
  • Table 34 Global AI-Driven Investment Analytics Market, By Retail Investors (2023-2034) ($MN)
  • Table 35 Global AI-Driven Investment Analytics Market, By FinTech Platforms (2023-2034) ($MN)
  • Table 36 Global AI-Driven Investment Analytics Market, By Other End Users (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.