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Stock Return Serial Dependence and Out-of-Sample Portfolio Performance

Author

Listed:
  • Uppal, Raman
  • DeMiguel, Victor
  • Nogales, Francisco J.
Abstract
We study whether investors can exploit stock return serial dependence to improve out-of- sample portfolio performance. To do this, we first show that a vector-autoregressive (VAR) model estimated with ridge regression captures daily stock return serial dependence in a stable manner. Second, we characterize (analytically and empirically) expected returns of VAR-based arbitrage portfolios, and show that they compare favorably to those of existing arbitrage portfolios. Third, we evaluate the performance of VAR-based investment (positive-cost) portfolios. We show that, subject to a suitable norm constraint, these portfolios outperform the traditional (unconditional) portfolios for transaction costs below 10 basis points.

Suggested Citation

  • Uppal, Raman & DeMiguel, Victor & Nogales, Francisco J., 2013. "Stock Return Serial Dependence and Out-of-Sample Portfolio Performance," CEPR Discussion Papers 9456, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:9456
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    More about this item

    Keywords

    Out-of-sample performance; Portfolio choice; Serial dependence; Vector autoregression;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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