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Risk parity for Mixed Tempered Stable distributed sources of risk

Author

Listed:
  • Lorenzo Mercuri

    (University of Milan)

  • Edit Rroji

    (University of Trieste)

Abstract

In this paper we discuss a detailed methodology for dealing with Risk parity in a parametric context. In particular, we use the Independent Component Analysis for a linear decomposition of portfolio risk factors. Each Independent Component is modeled with the Mixed Tempered Stable distribution. Risk parity optimal portfolio weights are calculated for three risk measures: Volatility, modified Value At Risk and modified Expected Shortfall. Empirical analysis is discussed in terms of out-of-sample performance and portfolio diversification.

Suggested Citation

  • Lorenzo Mercuri & Edit Rroji, 2018. "Risk parity for Mixed Tempered Stable distributed sources of risk," Annals of Operations Research, Springer, vol. 260(1), pages 375-393, January.
    • Handle: RePEc:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-016-2394-y
    DOI: 10.1007/s10479-016-2394-y
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    Cited by:

    1. Asmerilda Hitaj & Lorenzo Mercuri & Edit Rroji, 2019. "Sensitivity analysis of Mixed Tempered Stable parameters with implications in portfolio optimization," Computational Management Science, Springer, vol. 16(1), pages 71-95, February.
    2. Michele Leonardo Bianchi & Asmerilda Hitaj & Gian Luca Tassinari, 2020. "Multivariate non-Gaussian models for financial applications," Papers 2005.06390, arXiv.org.

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