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A Bayesian dynamic model to test persistence in funds' performance

Author

Listed:
  • Emmanuel Mamatzakis

    (Department of Business and Management, University of Sussex, UK; Rimini Centre for Economic Analysis)

  • Mike Tsionas

    (Lancaster University Management School, UK; Athens University of Economics and Business, Greece)

Abstract

We provide a Bayesian panel model to take into account persistence in US funds' performance while we tackle the important problem of errors in variables. Our modelling departs from prior strong assumptions such as error terms across funds being independent. In fact, we provide a novel, general Bayesian model for (dynamic) panel data that is stable across different priors as reported from the mapping of the prior to the posterior of the Bayesian baseline model with the adoption of different priors. We demonstrate that our model detects previously undocumented striking variability in terms of performance and persistence across funds categories and over time, and in particular through the financial crisis. The reported stochastic volatility exhibits a rising trend as early as 2003-2004 and could act as an early warning of future crisis.

Suggested Citation

  • Emmanuel Mamatzakis & Mike Tsionas, 2018. "A Bayesian dynamic model to test persistence in funds' performance," Working Paper series 18-23, Rimini Centre for Economic Analysis.
  • Handle: RePEc:rim:rimwps:18-23
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    Keywords

    Bayesian panel model; time-varying stochastic heteroskedasticity; time-varying covariance; general autocorrelation; US mutual fund performance;
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