Handbooks of Research Methods and Applications series
Edited by Adrian R. Bell, Chris Brooks and Marcel Prokopczuk
Chapter 2: Portfolio optimization: theory and practical implementation
In this chapter, I review the classical portfolio optimization problem and examine various applications of portfolio theory. I begin with pure portfolio theory where it is assumed that the means, variances and other parameters are known and there is a static one-period horizon. The analysis uses Arrow–Pratt risk aversion theory. The advantage of accurate means in static portfolio problems and, indeed, in all models, is stressed as is its relationship to the investor’s risk aversion. Then the stochastic programming approach to asset–liability management is discussed from a practitioner’s perspective. There it is assumed that there are scenarios on the asset parameters in the assets-only case and asset and liability parameters in asset–liability situations in multiple periods. Kelly and fractional Kelly investment strategies which maximize long-run wealth are discussed. This leads to a winning system for place and show betting. This is followed by a discussion of some great investors who have behaved as if they were using Kelly betting strategies.
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