Data Mining with Markowitz Portfolio Optimization in Higher Dimensions

In the spirit of financial analytics, this is an applied statistical approach to the data mining of equities price trends in order to gain insight into selecting the most desireable portfolios on the basis of return, volatility, and intersecurity time series correlation. It expands the Markowitz Portfolio Theory approach, which depends upon a multivariate normal distribution of log returns, in finding optimal security portfolios to higher dimensions (N~p). Results are reported for hundreds of candidate securities using data adjustments followed by quadratic programming in the R language

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Year of publication:	2015
Authors:	Bennett, Mark
Publisher:	[2015]: [S.l.] : SSRN
Subject:	Portfolio-Management \| Portfolio selection \| Data Mining \| Data mining \| Theorie \| Theory \| Mathematische Optimierung \| Mathematical programming

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