Least Squares Predictions and Mean-Variance Analysis
AbstractWe compare the Sharpe ratios of traders who combine one riskless and one risky asset following (i) buy and hold strategies; (ii) timing strategies with forecasts from simple; or (iii) multiple regressions; and (iv) passive allocations of (i) and (ii) with mean-variance optimizers. We show that (iv) implicitly uses the linear forecasting rule that maximizes the Sharpe ratio of managed portfolios, but the remaining rankings are unclear. We also suggest generalized method of moments (GMM) estimators to make (iv) operational and evaluate their significance with spanning tests. Finally, we characterize the equivalence between (iii) and (iv), and propose moment tests to assess it. Copyright 2005, Oxford University Press.
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Bibliographic InfoArticle provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.
Volume (Year): 3 (2005)
Issue (Month): 1 ()
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Other versions of this item:
- Sentana, E., 1997. "Least Squares Predictions and Mean-Variance Analysis," Papers 9711, Centro de Estudios Monetarios Y Financieros-.
- Enrique Sentana & Enrique Sentana, 1999. "Least Squares Predictions and Mean-Variance Analysis," FMG Discussion Papers dp312, Financial Markets Group.
- Sentana, Enrique, 1999. "Least Squares Predictions and Mean-Variance Analysis," CEPR Discussion Papers 2088, C.E.P.R. Discussion Papers.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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