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Modelling Profitability of Private Equity: A Fractional Integration Approach

Author

Listed:
  • Guglielmo Maria Caporale
  • Luis A. Gil-Alana
  • Francisco Puertolas

Abstract

This paper analyses the stochastic behaviour of Private Equity returns (a measure of profitability) applying fractional integration methods to an extensive dataset including quarterly data spanning the last four decades for various geographical areas (US, Europe, Asia/Pacific, the Rest of the World and the Total) and investment types (Buyout & Growth Equity, Venture Capital, Fund of Funds & Secondary Funds, Infrastructure, Natural Resources, Real Estate, Subordinated Capital & Distressed as well as the aggregate category All Types). The results support the hypothesis of stationarity and mean reversion in all cases; however, there are differences in the degree of persistence across regions, the series for Europe being the closest to a short-memory process, while those for the US exhibit long memory, which implies that shocks have long-lived effects. Differences are also found in the results by asset class. The implications of these findings for private equity management, profit smoothing and return benchmarking are briefly discussed.

Suggested Citation

  • Guglielmo Maria Caporale & Luis A. Gil-Alana & Francisco Puertolas, 2022. "Modelling Profitability of Private Equity: A Fractional Integration Approach," CESifo Working Paper Series 9843, CESifo.
    • Handle: RePEc:ces:ceswps:_9843
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    References listed on IDEAS

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    More about this item

    Keywords

    private equity; profitability; fractional integration; long memory; mean reversion;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
    • Y10 - Miscellaneous Categories - - Data: Tables and Charts - - - Data: Tables and Charts

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