Clash of the Titans: Factor Portfolios versus Alternative Weighting Schemes

In this article, the authors (re) introduce mean–variance portfolio construction for factor portfolios. These models, first popular with quants in the 1990s, are being resurrected today in a different context for transparent factor portfolios. The authors then evaluate the merits of these mean–variance factor portfolios against alternative weighting schemes. They point out that alternative weighting schemes have arguably weak theoretical foundations, and their supporters rationalize them with a range of (very different) reasons, most of them dissatisfying in the view of the authors. They then show that alternative weighting schemes derive a large part of their outperformance from a handful of well-known factors. The authors argue that sensibly built factor portfolios deliver a similar or higher information ratio by explicitly harnessing the factors and doing so in an efficient risk- and transaction cost-aware way.

2006 ◽  
Vol 174 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Hong-Gang Xue ◽  
Cheng-Xian Xu ◽  
Zong-Xian Feng

2014 ◽  
Vol 543-547 ◽  
pp. 4339-4345
Author(s):  
Jiang Ping Zhu ◽  
Xi Kun Liang

A robust mean-variance portfolio selection model with transaction cost is presented for the case that both risky and risk-free assets exist in the market and expected returns of assets are uncertain and belong to a convex polyhedron. The model helps investors to identify such portfolios that expectations of investors are ensured even if the worst case in the expected returns of assets occurs. Analytical expression of the optimal portfolio determined by the proposed model is derived based on the Lagrange method for constrained optimization. Empirical analysis with three real stocks is performed to give the efficient frontier of portfolios.


2021 ◽  
Author(s):  
Raymond Kan ◽  
Xiaolu Wang ◽  
Guofu Zhou

We propose an optimal combining strategy to mitigate estimation risk for the popular mean-variance portfolio choice problem in the case without a risk-free asset. We find that our strategy performs well in general, and it can be applied to known estimated rules and the resulting new rules outperform the original ones. We further obtain the exact distribution of the out-of-sample returns and explicit expressions of the expected out-of-sample utilities of the combining strategy, providing not only a fast and accurate way of evaluating the performance, but also analytical insights into the portfolio construction. This paper was accepted by Tyler Shumway, finance.


2009 ◽  
Vol 12 (4) ◽  
pp. 91-115 ◽  
Author(s):  
Daniel Kuhn ◽  
Panos Parpas ◽  
Berç Rustem ◽  
Raquel Fonseca

2016 ◽  
Author(s):  
Masafumi Nakano ◽  
Akihiko Takahashi ◽  
Soichiro Takahashi

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ishak Alia ◽  
Farid Chighoub

Abstract This paper studies optimal time-consistent strategies for the mean-variance portfolio selection problem. Especially, we assume that the price processes of risky stocks are described by regime-switching SDEs. We consider a Markov-modulated state-dependent risk aversion and we formulate the problem in the game theoretic framework. Then, by solving a flow of forward-backward stochastic differential equations, an explicit representation as well as uniqueness results of an equilibrium solution are obtained.


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