Calendar Based Risk, Firm Size, and the Random Walk Hypothesis
作者： C. Kenneth Jones
DOI: 10.2139/SSRN.639683
关键词:
摘要: A model of risk with multiple independent unconditional calendar and non-calendar variance components is used to explain time-varying returns. Digital signals represent finite stock return series. The random walk hypothesis tested using digital signal processing methods. stochastic additive market noise measures total idiosyncratic risks signals. With monthly returns four year the white rejected small sample Large firms have four-year one-year risk. Mid-cap two-year six-month Small display January-like Unconditional based appears coincident anomalies.
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