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Article Dans Une Revue Financial Innovation Année : 2023

Stock profiling using time–frequency-varying systematic risk measure

Roman Mestre

Résumé

Abstract 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.

Dates et versions

hal-04058285 , version 1 (04-04-2023)

Identifiants

Citer

Roman Mestre. Stock profiling using time–frequency-varying systematic risk measure. Financial Innovation, 2023, 9 (1), pp.52. ⟨10.1186/s40854-023-00457-7⟩. ⟨hal-04058285⟩
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