Risk Parity and Beyond - From Asset Allocation to Risk Allocation Decisions

Deguest, Romain; Martellini, Lionel; Meucci, Attilio

doi:10.2139/ssrn.2355778

Cited by 28 publications

(17 citation statements)

References 23 publications

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“…As a proxy for the risk‐free rate of interest ( R f ) the literature reports the use of 1 month or 3 month maturity U.S. Treasury Bills (see e.g. Deguest, Martellini, & Meucci, 2013) or alternatively an exogenously given value (see e.g. Brennan, 1998 who considered R f = 5%).…”

Section: Empirical Analysismentioning

confidence: 99%

Are Smart Beta strategies suitable for hedge fund portfolios?

Hitaj

Zambruno

2016

Rev Financ Econ

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In the equity context different Smart Beta strategies (such as the equally weighted, global minimum variance, equal risk contribution and maximum diversified ratio) have been proposed as alternatives to the capweighted index. These new approaches have attracted the attention of equity managers as different empirical analyses demonstrate the superiority of these strategies with respect to cap-weighted and to strategies that consider only mean and variance. In this paper we focus our attention to hedge fund index portfolios and analyze if the results reported in the equity framework are still valid. We consider hedge fund index and equity portfolios, the approaches used for portfolio selection are the four 'Smart Beta' strategies, mean-variance and meanvariance-skewness. In the two latter approaches the Taylor approximation of a CARA expected utility function and the Polynomial Goal Programing (PGP) have been used. The obtained portfolios are analyzed in the in-sample as well as in the out-of-sample perspectives.

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Section: Empirical Analysismentioning

confidence: 99%

Are Smart Beta strategies suitable for hedge fund portfolios?

Hitaj

Zambruno

2016

Rev Financ Econ

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“…A specific example is naive diversification (or equal weight portfolio), in which the same amount of wealth is invested in each available asset. Examples of law of large numbers (and in particular, naive diversification) measures are the effective number of constituents (see Carli, Deguest, and Martellini, 2014;Deguest, Martellini, and Meucci, 2013) and Bouchaud, Potters, and Aguilar's (1997) class of measures, which includes the Shannon and Gini-Simpson indexes (Zhou, Cai, and Tong, 2013). Other examples of naive diversification measures can be found in the studies by Yu, Lee, and Chiou (2014) and Lhabitant (2017).…”

Section: Law Of Large Numbers Diversification Measuresmentioning

confidence: 99%

Coherent Diversification Measures in Portfolio Theory: An Axiomatic Foundation

Koumou

Dionne

2019

SSRN Journal

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We provide an axiomatic foundation for the measurement of correlation diversification measures in a one-period portfolio model. We propose a set of nine desirable axioms for this class of diversification measures. We name the measures satisfying these axioms coherent correlation diversification measures which we distinguish from coherent risk measures. We provide the decision theoretic foundations of our axioms by studying their compatibility with investors' preference for diversification in rank-dependent expected utility theory. We examine some of the most frequently used methods for measuring correlation diversification in terms of our axioms. Lastly, we explore whether our axioms have a representation function.

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“…However, once dimension has been reduced, it is decorrelation that makes the PCs appealing for factor-risk parity, which spreads the portfolio-return risk among a set of uncorrelated factors. Indeed, most existing papers on factor-risk parity rely on the PCs as factors; see Meucci (2009), Deguest et al (2013), andRoncalli and. However, there is no sound motivation behind this particular choice because any rotation of the PCs remains uncorrelated, and thus is as suitable for factor-risk parity as the PCs.…”

Section: Principal Component Analysismentioning

confidence: 99%

Optimal Portfolio Diversification via Independent Component Analysis

Lassance

DeMiguel

Vrins³

2018

SSRN Journal

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A natural approach to enhance portfolio diversification is to rely on factor-risk parity, which yields the portfolio whose risk is equally spread among a set of uncorrelated factors. The standard choice is to take the variance as risk measure, and the principal components (PCs) of asset returns as factors. Although PCs are unique and useful for dimension reduction, they are an arbitrary choice: any rotation of the PCs results in uncorrelated factors. This is problematic because we demonstrate that any portfolio is a factor-varianceparity portfolio for some rotation of the PCs. More importantly, choosing the PCs does not account for the higher moments of asset returns. To overcome these issues, we propose to use the independent components (ICs) as factors, which are the rotation of the PCs that are maximally independent, and care about higher moments of asset returns. We demonstrate that using the IC-variance-parity portfolio helps to reduce the return kurtosis. We also show how to exploit the near independence of the ICs to parsimoniously estimate the factor-risk-parity portfolio based on Value-at-Risk. Finally, we empirically demonstrate that portfolios based on ICs outperform those based on PCs, and several state-of-the-art benchmarks.

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Risk Parity and Beyond - From Asset Allocation to Risk Allocation Decisions

Cited by 28 publications

References 23 publications

Are Smart Beta strategies suitable for hedge fund portfolios?

Are Smart Beta strategies suitable for hedge fund portfolios?

Coherent Diversification Measures in Portfolio Theory: An Axiomatic Foundation

Optimal Portfolio Diversification via Independent Component Analysis

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