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Convex combinations of long memory estimates from different sampling rates

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  • Souza, Leonardo Rocha
  • Smith, Jeremy
  • Souza, Reinaldo Castro

Abstract

Convex combinations of long memory estimates using the same data observed at different sampling rates can decrease the standard deviation of the estimates, at the cost of inducing a slight bias. The convex combination of such estimates requires a preliminary correction for the bias observed at lower sampling rates, reported by Souza and Smith (2002). Through Monte Carlo simulations, we investigate the bias and the standard deviation of the combined estimates, as well as the root mean squared error (RMSE), which takes both into account. While comparing the results of standard methods and their combined versions, the latter achieve lower RMSE, for the two semi-parametric estimators under study (by about 30% on average for ARFIMA(0,d,0) series).

Suggested Citation

  • Souza, Leonardo Rocha & Smith, Jeremy & Souza, Reinaldo Castro, 2003. "Convex combinations of long memory estimates from different sampling rates," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 489, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    • Handle: RePEc:fgv:epgewp:489
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    References listed on IDEAS

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    8. Leonardo Rocha Souza, 2007. "Temporal Aggregation and Bandwidth selection in estimating long memory," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(5), pages 701-722, September.
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