Publicação
The effect of serial correlation in time-aggregation of annual sharpe ratios from monthly data
| Resumo: | The Sharpe ratio is one of the most widely used measures of risk-adjusted returns. It rests on the estimation of the mean and standard deviation of returns, which is subject to estimation errors. Moreover, it assumes identically and independently distributed returns, normality and no serial correlation, which are very restrictive assumptions in general. By using the Generalized Method of Moments approach to estimate these quantities, the assumptions may be relaxed and a more efficient estimator can be derived, by allowing serial correlation in returns. The purpose of this research is to show how serial correlation can affect the timeaggregation of Sharpe ratios, changing the ordering of a ranking of assets based on the ratio. |
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| Autores principais: | Alves, Pedro Miguel Carregueiro Jordão |
| Assunto: | serial correlation sharpe ratio time-aggregation risk-adjusted returns |
| Ano: | 2018 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | The Sharpe ratio is one of the most widely used measures of risk-adjusted returns. It rests on the estimation of the mean and standard deviation of returns, which is subject to estimation errors. Moreover, it assumes identically and independently distributed returns, normality and no serial correlation, which are very restrictive assumptions in general. By using the Generalized Method of Moments approach to estimate these quantities, the assumptions may be relaxed and a more efficient estimator can be derived, by allowing serial correlation in returns. The purpose of this research is to show how serial correlation can affect the timeaggregation of Sharpe ratios, changing the ordering of a ranking of assets based on the ratio. |
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