Artificial Intelligence for Asset Management and Investment A Strategic Perspective.

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Naqvi, Al
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2021.
Colección:Wiley Finance Ser.
Temas:
Artificial intelligence.
Asset allocation.
Financial services industry > Technological innovations.
Intelligence artificielle.
Affectation de l'actif.
Services financiers > Innovations.
artificial intelligence.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright
  • Contents
  • Preface
  • Acknowledgments
  • Chapter 1 AI in Investment Management
  • What about AI Suppliers?
  • Listening without Judging
  • Lessons from ALI
  • The Four Stages of AI in Investments
  • Stage 1: The Siloed Quant Era
  • Era 2: The Strategic Quant Era
  • Stage 3: The Organizational Chaos Era
  • Stage 4: The Modern Investment Firm
  • The Core Model of AIAI
  • Your Journey through This Book
  • How to Read and Apply this Book?
  • References
  • Chapter 2 AI and Business Strategy
  • Why Strategy? The Red Button
  • AI-a Revolution of its Own
  • Intelligence as a Competitive Advantage
  • Intelligence in Products
  • Intelligence in Production Platforms
  • Intelligence of an Interlinked Network of Systems
  • Intelligence as a Competitive Advantage and Various Strategy Schools
  • The Intelligence School
  • Intelligence and Actions
  • Actions
  • Automation
  • Intelligence Action Chain and Sequence
  • Enterprise Software
  • Data
  • Data Management Expertise
  • Partnering, Buying, and Building
  • Competitive Advantage
  • Business Capabilities
  • Chapter 3 Design
  • Who Is Responsible for Design?
  • Introduction to Design
  • AI as a Competitive Advantage
  • The Ten Elements of Design
  • 1. Design Your Business Model
  • 2. Set Goals for the Entire Firm
  • 3. Specify Objectives for Automation and Intelligence
  • 4. Design Work Task Frames Based on Human-Computer Interaction
  • 5. Perform a DTC (Do, Think, Create) Analysis
  • 6. Create a SADAL Framework
  • 7. Deploy a Feedback System and Define Performance Measures
  • 8. Determine the Business Case or Value
  • 9. Analyze Risks
  • 10. Develop a Governance Plan
  • Some Additional Ideas about Designing Intellectualization
  • Summary of the Design Process
  • References
  • Chapter 4 Data
  • Who Is Responsible for the Data Capability?
  • Data and Machine Learning
  • Raw Data
  • Structured vs. Unstructured Data
  • Data Used in Investments
  • Data Management Function for the AI Era
  • Step 1: Data Needs Assessment (DNA)
  • Step 2: Perform Strategic Data Planning
  • Step 3: Know the Sensors and Sources (Identify Gaps)
  • Step 4: Procure and Understand the Supply Base
  • Step 5: Understand the Data Type (Signals)
  • Step 6: Organize Data for Usability
  • Step 7: Architect Data
  • Step 8: Ensure Data Quality
  • Step 9: Data Storage and Warehousing
  • Step 10: Excel in Data Security and Privacy
  • Step 11: Implement Data for AI
  • Step 12: Provide Investment Specialization
  • About Legacy Data Management
  • References
  • Chapter 5 Model Development
  • Who Is Responsible?
  • High-Level Process
  • Models
  • The Power of Patterns
  • Techniques of Learning
  • What Is Machine Learning?
  • Scientific Process on Steroids
  • The Learning Machines
  • Algorithms
  • Supervised Learning
  • Supervised Learning Methods
  • Supervised: Classification
  • Classification: Decision Trees
  • Classification: Random Forest

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