CHAPTER 1Preliminaries

The chapter begins with a review of two topics that will serve as the foundations of our asset allocation framework: expected utility and estimation error. Asset allocation is then defined as the process of maximizing expected utility while minimizing estimation error and its consequences—a simple yet powerful definition that will guide us through the rest of the book. The chapter concludes with an explicit definition of the modern yet tractable asset allocation framework that is recommended in this book: the maximization of a utility function with not one but three dimensions of client risk preferences while minimizing estimation error and its consequences by only investing in distinct assets and using statistically sound historical estimates as our forecasting foundation.

Key Takeaways:

  1. Individual investors look to maximize their future utility of wealth, not their future wealth.
  2. Mean-variance optimization is just an approximation to the full utility maximization problem we will tackle.
  3. Maximizing the full utility function allows for a transparent and precise mapping of client preferences to portfolios.
  4. A utility function with three risk preferences, accounting for both neoclassical and behavioral risk preferences, will be maximized in a returns-based framework.
  5. Estimation error and the associated sensitivity to asset allocation recommendations can't be avoided or removed via a holy grail solution.
  6. Estimation error will be managed by deploying non-parametric ...

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