Chapter 11Advances in Quantitative Equity Portfolio Management

The mean-variance portfolio optimization framework introduced in Chapter 8 suggested that quantitative investment management can be formulated as the question of determining an appropriate probability distribution of portfolio returns and engineering the optimal trade-off between risk and return as a function of individual risk preferences. More than 60 years after Harry Markowitz came up with the framework, the investment management community is divided over its adoption. Some portfolio managers reject the idea of quantitative portfolio management on principle. Others have given quantitative portfolio management a chance but have given up after growing frustrated with some of the significant shortcomings of the Markowitz framework, such as the sensitivity of portfolio allocation schemes to errors in the inputs to the problem and the limitations of portfolio variance as a measure of risk. A third group has faced the latter problems but has decided to invest in finding solutions that can correct for them because it believes that there is a benefit to the ability to quantify, measure, and allocate risks in an optimal way. Elements of advanced tools from multiple analytical fields—robust statistics, Bayesian methods, simulation, robust optimization—have been employed to address some of the issues with the mean-variance framework. For example, the framework has been expanded to include practical approaches for parameter ...

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