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Portfolio Selection with Irregular Time Grids: an example using an ICA-COGARCH(1, 1) approach

Author

Listed:
  • Francesco Bianchi

    (Independent
    University of Milan
    CREST Japan Science and Technology Agency)

  • Lorenzo Mercuri

    (University of Milan
    CREST Japan Science and Technology Agency)

  • Edit Rroji

    (University of Milano-Bicocca)

Abstract

In this paper we consider a portfolio selection problem defined for irregularly spaced observations. We use the Independent Component Analysis for the identification of the dependence structure and continuous-time GARCH models for the marginals. We discuss both estimation and simulation of market prices in a context where the time grid of price quotations differs across assets. We present an empirical analysis of the proposed approach using two high-frequency datasets that provides better out-of-sample results than competing portfolio strategies except for the case of severe market conditions with frequent rebalancements.

Suggested Citation

  • Francesco Bianchi & Lorenzo Mercuri & Edit Rroji, 2022. "Portfolio Selection with Irregular Time Grids: an example using an ICA-COGARCH(1, 1) approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(1), pages 57-85, March.
    • Handle: RePEc:kap:fmktpm:v:36:y:2022:i:1:d:10.1007_s11408-021-00387-3
    DOI: 10.1007/s11408-021-00387-3
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    References listed on IDEAS

    as
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    3. Stefano M. Iacus & Lorenzo Mercuri & Edit Rroji, 2018. "Discrete‐Time Approximation of a Cogarch(p,q) Model and its Estimation," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(5), pages 787-809, September.
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    6. Hitaj, Asmerilda & Mercuri, Lorenzo & Rroji, Edit, 2015. "Portfolio selection with independent component analysis," Finance Research Letters, Elsevier, vol. 15(C), pages 146-159.
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    More about this item

    Keywords

    Irregular grids; Independent Component Analysis; Continuous GARCH; Risk measures;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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