Data, Decisions, and the Future of Finance
I’ve spent years working at the intersection of AI and finance, and I don’t just write about theory—I write about what works. Explore my books and take your expertise further.
Coming 2025
The AI-Powered Portfolio
From Factor Models to Deep Learning Strategies
Modern finance is shifting rapidly, and AI is no longer a future concept—it’s a core part of portfolio management today. This book explores the evolution of quantitative strategies, from traditional factor models to machine learning and deep learning applications. Covering everything from factor models to NLP-driven financial insights, it offers practical frameworks and real-world case studies for investors looking to integrate AI into their decision-making processes.
- The evolution of factor models and AI in finance
- Machine learning techniques for investment strategies
- Deep learning applications in forecasting and portfolio management
- Large language models for financial analysis
- Generative AI and multi-agent systems
- Synthetic data generation for stress testing portfolios
2024
Seeing the Elephant in Business Analytics
Why We Miss Critical Insights
This book provides a structured approach to business analytics, covering essential software tools, data preprocessing, predictive modeling, and risk optimization. Beyond technical skills, it uncovers the hidden challenges that lead to missed insights, such as cognitive biases, implementation hurdles, and big data complexities. Designed for business leaders, MBA students, and analytics professionals, it offers a roadmap to making analytics truly impactful.
- Data cleaning, predictive modeling, and optimization techniques
- Recognizing biases and hidden limitations in analytics
- AI-driven insights and real-world implementation challenges
- Scaling business analytics with big data infrastructure
- Storytelling with data for effective decision-making
- Balancing automation and human intuition in AI-driven analytics
