Principal Component Analysis of Time Variations in the Mean-Variance Efficient Frontier

7 Pages Posted: 12 Mar 2013

Date Written: March 11, 2013

Abstract

We explain the variability of the mean-variance efficient frontier over time with a statistical three factor model. For an asset universe consisting of 22 stocks listed in Switzerland, the model explains more than 99% of the time variations in the efficient frontier.

The three factors can be interpreted as level, slope and curvature effects. This result is similar to statistical factors that have been identified in the analysis of yield curve dynamics.

We also show that the first factor which explains about 95% of the variability in the efficient frontier is highly correlated with average stock returns. This can be interpreted as evidence that the efficient frontier is mainly driven by time-variation in returns. Risk, on the other hand, measured by both asset volatilities and asset correlations, seems to be a second-order effect.

Keywords: mean-variance, efficient frontier, PCA, Principal Component Analysis, dynamic time-varying return, volatility, risk

JEL Classification: C10, G11

Suggested Citation

Steiner, Andreas, Principal Component Analysis of Time Variations in the Mean-Variance Efficient Frontier (March 11, 2013). Available at SSRN: https://ssrn.com/abstract=2228666 or http://dx.doi.org/10.2139/ssrn.2228666

Andreas Steiner (Contact Author)

Andreas Steiner Consulting GmbH ( email )

Walderstrasse 43c
Hinwil, 8340
Switzerland

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