Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation
Richard O. Michaud
Harvard Business School Press, 1998 - Business & Economics - 152 pages
The failure of optimized portfolios to meet their practical investment goals has prompted many portfolio managers to abandon optimization techniques for simpler alternatives to maximize asset value. Yet, according to financial expert Richard Michaud, readily available methods exist to help practitioners reduce instability and enhance the value of optimization--tools that the investment community has largely ignored. In his succinct new book, Michaud argues that the problems lies with the conventional perception of optimization as a numerical computation; this view has severely restricted the typical manager's understanding of inherent limitations--and resulted in optimized portfolios that frequently fall short of their potential. If, instead, managers approach optimization as a statistical estimation, Michaud argues, they can resolve many of the serious limitations. Michaud identifies and explains five powerful techniques--improved estimation, application of benchmark priors, integration of active forecasts, tests for efficiency, and tests for portfolio weights--that portfolio managers can use to reduce errors, increase precision, and enhance the value of seemingly optimized portfolios. He illustrates the impact of each method with a simple asset allocation problem. With its important implications for investment practice, Efficient Asset Management's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud updates the practice of optimization for modern investment management.
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Classic MeanVariance Optimization
Mathematical Formulation of MeanVariance
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Efficient Asset Management: A Practical Guide to Stock Portfolio ...
Richard O. Michaud,Robert O. Michaud
No preview available - 2008
active return algorithm asset allocation asset management benchmark optimization benchmark-relative chapter computing confidence intervals confidence region constraints covariance estimation covariance matrix effi efficient frontier portfolios efficient portfolio mean equity portfolio optimization Euros Exhibit 4.1 expected return folio forecast return France fund geometric mean historic data implied returns index fund investment value investor James-Stein estimator Japan Jobson and Korkie Ledoit liability-relative limitations of MV linear regression long-term Markowitz maximum average return methods Michaud minimum variance mixed estimation Monte Carlo MV efficient frontier MV efficient portfolios MV optimization number of assets optimization inputs parameters portfo portfolio efficiency portfolio risk portfolio weights practical procedure quadratic programming rank-associated relative resampled efficient frontier resampled efficient portfolio return forecasts sample acceptance region sample covariance matrix sample mean Sharpe ratio sign-constrained significantly simulated efficient frontier Simultaneous Confidence Intervals standard deviation statistical inference statistically equivalent Stein estimators tion trading costs U.S. Bonds U.S. equities utility functions