4.5 Article

Stock profiling using time-frequency-varying systematic risk measure

期刊

FINANCIAL INNOVATION
卷 9, 期 1, 页码 -

出版社

SPRINGER
DOI: 10.1186/s40854-023-00457-7

关键词

Maximal overlap discrete wavelets transform; Time; Frequency-varying beta; Frequency rolling window; Risk-profile; Systematic risk

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This study proposes a wavelets approach to estimating time-frequency-varying betas in the capital asset pricing model (CAPM) framework. The dynamic of systematic risk across time and frequency is analyzed to investigate stock risk-profile robustness. We conclude that the standard CAPM assumes short-run investment. Then, investors should consider time-frequency CAPM to perform systematic risk analysis and portfolio allocation.
This study proposes a wavelets approach to estimating time-frequency-varying betas in the capital asset pricing model (CAPM) framework. The dynamic of systematic risk across time and frequency is analyzed to investigate stock risk-profile robustness. Furthermore, we emphasize the effect of an investor's investment horizon on the robustness of portfolio characteristics. We use a daily panel of French stocks from 2012 to 2022. Results show that varying systematic risk varies in time and frequency, and that its short and long-run evolutions differ. We observe differences in short and long dynamics, indicating that a stock's betas differently fluctuate to early announcements or signs of events. However, short-run and long-run betas exhibit similar dynamics during persistent shocks. Betas are more volatile during times of crisis, resulting in greater or lesser robustness of risk profiles. Significant differences exist in short-run and long-run risk profiles, implying a different asset allocation. We conclude that the standard CAPM assumes short-run investment. Then, investors should consider time-frequency CAPM to perform systematic risk analysis and portfolio allocation.

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