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A Critical Review Of Kosowski, R., Naik, N. Y. and Teo, Y. (2007) ‘Do hedge funds deliver alpha? A Bayesian and bootstrap analysis’

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In this passage, Kosowski, Naik and Teo (2007) innovatively introduce Bayesian and bootstrap analysis into the study of hedge fund performances. With the assistance of those two statistical sophisticates, the authors’ deductions diminish luck and advocate persistence on an annual horizon. (Kosowski et al., 2007: 229) Their comprehensive arguments have truly challenged the traditional views on hedge funds’ performance in particular and on market efficiency in general. As the technical skills applied are as exciting as the implications arisen, this passage is worth reading in detail for either statistical inspirations or hedge fund insights.
The rest of this critical review provides a brief summary of the passage and arguments for its topic’s significance first. For the review, the main focus is on the passage’s contribution measured by relationship to literature, and efficiency in data adjustment and application of methodologies. Some limitations of their conclusions are pointed out by the end, which can also be notes for readers.
In a nutshell, this passage studies top hedge funds’ performances between 1990s and 2000s on their ability to generate risk-adjusted excessive returns before and after fees. For such ability, alpha t-statistics are calculated as indicators meanwhile returns, denoted alphas, are estimated using the seven-factor model initiated by Fung and Hsieh (2004) benchmarking systematic risks. The null hypothesis emphasizing sample variations can be rejected considering the low probability found in bootstrap approach yielding as extreme ramifications with luck only. (Kosowski et al., 2007: 238) Data biases are then controlled separately later for the robustness of that conclusion. That finding, together with Bayesian ...

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