Resumo:
The value added by an active investor is traditionally measured using alpha,
tracking error, and the information ratio. However, these measures do not characterize the
dynamic component of investor activity, nor do they consider the time horizons over which
weights are changed. In this paper, we propose a technique to measure the value of active
investment that captures both the static and dynamic contributions of an investment
process. This dynamic alpha is based on the decomposition of a portfolio’s expected return
into its frequency components using spectral analysis. The result is a static component that
measures the portion of a portfolio’s expected return resulting from passive investments
and security selection and a dynamic component that captures the manager’s timing ability
across a range of time horizons. Our framework can be universally applied to any portfolio
and is a useful method for comparing the forecast power of different investment processes.
Several analytical and empirical examples are provided to illustrate the practical relevance
of this decomposition.
Chaudhuri and Lo: Spectral Decomposition of Investment AlphaManagement Science, 2019, vol. 65, no. 9, pp. 4440–4450, © 2018 INFORMS
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