Unlock the full power of modern portfolio theory, machine learning, and quantitative finance using two of the most accessible tools in your arsenal: Excel and Python.

This advanced guide is designed for serious investors, analysts, and finance professionals who want to go beyond basic models and learn how to engineer high-performance portfolios. Inside, you’ll find a deep dive into risk-adjusted strategies, multi-factor models, regime switching, Monte Carlo simulations, Black-Litterman adjustments, and more—anchored by code and practical Excel frameworks you can apply immediately.

Whether you're managing capital or building algorithms, this book offers you the tools to:

Construct robust portfolios with modern optimization techniques
Combine fundamental and technical factors in allocation decisions
Apply risk-parity, volatility targeting, and regime-based tilts
Leverage Python for backtesting and Excel for scenario analysis
Bridge academic theory with real-world portfolio management

With a dual emphasis on financial insight and hands-on execution, this book is ideal for those who want more than just theory—it’s for builders, quants, and future fund managers.

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