Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures

Jan Patrick Hartkopf and Laura Reh

Finance Research Letters, 2023, vol. 56, issue C

Abstract: We investigate the calibration of the smoothing parameter in an exponentially weighted moving average (EWMA) for realized covariance matrices. Whereas the popular risk metrics calibration of JPMorgan (Reuters, 1996) has been proven to be successful in applications based on daily or monthly return data, we demonstrate that the golden standard degree of smoothing is not transferable to applications with realized (co)variances which convey a substantially more informative signal. Moreover, we propose a simple data-driven heuristic for the calibration of λ and demonstrate in our empirical application its superiority over ad-hoc choices for λ in multivariate settings with regard to predictive accuracy.

Keywords: Exponentially weighted moving average; EWMA; RiskMetrics; Realized covariance; Prediction; Matrix-F distribution (search for similar items in EconPapers)
JEL-codes: C32 C51 C53 C58 G17 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323005019

DOI: 10.1016/j.frl.2023.104129

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