Estimating the market risk premium for valuations: arithmetic or geometric mean or something in between?
نویسندگان
چکیده
Abstract It is well-known that using arithmetic averages of yearly return observations leads to downward biased discount rates estimations. Well-known corrections, however, lead upward results under the presence negative serial correlation. Using a simulation analysis, we first show specific variant Cooper estimator, labelled as C4 in this paper, robust estimations even both correlation and heteroscedasticity. We also among simple estimators, i.e. (AM) or geometric mean (GM) (MoM), one tends perform best unless there high degree In case so-called means rule would be better. Secondly, data from Jordà et al. (Q J Econ 134(3):1225–1298, 2019) find heteroscedasticity market risk premia widely spread phenomenon. Finally, use derive presumably least based on estimator. For majority countries these are somewhere between average. When comparing estimators each other empirical data, almost equally well, while clearly underperforms. Moreover, found some evidence MoM slightly outperforming AM local CAPM perspective, opposite true global perspective. This us cautious conclusion used by practitioners has rationale when for substantial
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ژورنال
عنوان ژورنال: Journal of Business Economics
سال: 2022
ISSN: ['1861-8928', '0044-2372']
DOI: https://doi.org/10.1007/s11573-022-01104-w