The Efficient Frontier and Monte Carlo Software, II

Let’s move on from yesterday’s blog on the Efficient Frontier, formulated half a century ago by Harry Markowitz, to the New Frontier postulated by investment advisor Richard Machaud.  Michaud is the author of Efficient Asset Management:A Practical Guide to Stock Portfolio Optimization and Asset Allocation (Oxford University Press, 2008), among other works, and now heads up New Frontier Advisors, an institutional research and investment advisory company.
Michaud’s New Frontier adds further sophistication to Markowitz’s ideas about optimizing investment diversification to balance risk and return by introducing resampling to the optimization process.  Resampling is a method from statistical analysis that compensates for possible error by analyzing a dataset from which a subset has been portioned off and replacing values in the initial analysis with randomly sampled values from the subset.  
More specifically about the New Frontier technique,  Michaud adds resampling capability to Monte Carlo simulation.  According to one commentator, this "allows managers to assign a greater range of probabilities to various outcomes.  The goal is to produce a more realistic portfolio based on a more realistic frontier."

New Frontier now markets proprietary Monte Carlo software with a built-in resampling function to its institutional clients, and my own in-house experts tell me that resampling functionality is available in some commercial Monte Carlo Excel software as well. 

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