Calendar Based Mean Reversion Risk and Digital Signal Processing
作者： C. Kenneth Jones
DOI: 10.2139/SSRN.1361886
关键词: Market risk 、 Actuarial science 、 Systematic risk 、 Long term risk 、 White noise 、 Noise (signal processing) 、 Total risk 、 Econometrics 、 Digital signal processing 、 Economics 、 Mean reversion
摘要: The nature of risk and long-term returns is not fully understood. There a need for measure at multiple horizons. Digital signal processing an additive noise model are used to test the white hypothesis total idiosyncratic individual firms two-month four-year periods. All have significant annual effect risk. January-like effects influence small firms. Large firm mid-cap influenced by Joseph (8-year) summer effects. reflects presidential results suggest that single period composed calendar non-calendar variances.
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